System

Abstract

To provide a diet program which can be continued pleasantly and naturally.SOLUTION: The system includes means for inputting basic attributes of a user, means for inputting behavior-related information such as a place of residence and a place of work, means for inputting a target value, means for transmitting the input information, means for storing the transmitted information in a database and creating a user profile, means for tracking a behavior pattern of the user, means for collating the tracked data with external data such as a day of the week and weather, means for analyzing the collated data, means for causing the user to input a mood and a schedule of the day, means for transmitting all the collected data to a server, means for analyzing the received data by the server and generating a diet plan suitable for the user, and means for proposing the generated diet plan to the user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Conventional diet programs do not adequately consider the lifestyle habits and mood of each individual user, so they tend to be unreasonable plans that are difficult to continue. Furthermore, they impose a heavy financial burden and tend to rely on specific exercise and dietary methods, which can lead to health risks. There is a need to improve this situation and provide diet programs that are fun and easy to continue. [Means for solving the problem]

[0005] This invention is a system that includes a means for inputting a user's basic attributes, behavior-related information such as place of residence and place of work, and target values, a means for tracking the user's behavioral patterns, a means for comparing the tracking data with external data, a means for inputting the user's mood and schedule for the day, a means for analyzing all collected data to generate an optimal diet plan, and a means for proposing the generated plan. This system provides a healthy and economical diet program that matches the user's lifestyle pattern and mood for the day, allowing the user to continue dieting in an enjoyable and effortless manner.

[0006] "Basic attributes" refers to information about an individual, such as the user's age, sex, build, and health information.

[0007] "Behavior-related information" refers to information related to the user's daily life and range of activities, such as the user's place of residence and place of work.

[0008] "Target value" refers to a numerical target regarding the body shape or health condition that the user wants to achieve.

[0009] "Tracking" refers to the process of collecting a user's movement history and exercise data and analyzing their behavioral patterns.

[0010] "External data" refers to external environmental data that affects user behavior, such as the day of the week and weather.

[0011] A "diet plan" refers to specific suggestions for exercise and meals that are generated based on the user's behavioral patterns and daily mood.

[0012] The "means of suggesting" refers to a means for presenting the generated diet plan to the user and providing specific guidelines for action.

[0013] "Means of analysis" refers to the process of analyzing the user's behavioral patterns and tendencies based on the collected data and generating an optimal diet plan. [Brief explanation of the drawings]

[0014] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0015] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

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

[0017] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0018] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0019] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0020] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0021] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0022] [First embodiment]

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

[0024] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0025] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0026] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0027] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0028] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0029] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

[0031] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0032] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0033] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0034] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0035] This invention relates to a "diet motivator" that provides the user with an optimal diet plan tailored to their lifestyle and mood on that day. Specifically, it is a system that takes into account the user's basic attributes and behavioral patterns to help them continue their diet economically and healthily.

[0036] 1. First-time user registration

[0037] When the server starts the system for the first time, the terminal prompts the user to enter basic attributes (age, sex, build, health information, etc.). The user enters age, sex, height, weight, medical history, etc. Next, the terminal prompts the user to enter their place of residence and place of work, and the user enters this information. Furthermore, the terminal prompts the user to enter target values ​​such as target weight and target body fat percentage, and the user enters the target values.

[0038] The terminal sends this input information to the server, and the server stores the received data in a database to create a user profile.

[0039] 2. Information gathering

[0040] To track a user's behavioral patterns, the device collects the user's GPS data, movement history, and exercise data (e.g., number of steps, calories burned) in real time. This data is periodically sent to a server, which then compares the received data with external data such as the day of the week and weather, and analyzes the user's behavioral patterns.

[0041] The terminal also prompts the user to input their mood and schedule for the day, as well as their planned exercise intensity, allowing the user to input their emotional state (e.g., fatigue, motivation), schedule for the day, and exercise plan.

[0042] 3. Proposal

[0043] The server generates a diet plan based on the data collected and analyzed to date, tailored to the user's behavioral patterns and daily mood. The plan creates a specific action plan that takes into account the balance of exercise, meals, and rest, and sends it to the device as suggested data. Specifically, it can suggest an exercise menu that suits the user's mood that day, as well as healthy and economical meal menus.

[0044] Specific examples

[0045] If a user inputs "It's raining today, so I don't want to go outside," the server will analyze the weather data and the user's behavioral patterns and suggest "yoga and stretching exercises that can be done indoors." The device will also display a recipe for a low-calorie yet nutritious "vegetable soup" based on ingredients in the user's refrigerator. In this way, users can continue their diet without any stress in their daily lives.

[0046] The system supports users in continuing a healthy and enjoyable diet through a consistent process from data collection to recommendations. It also helps users achieve their goals without straining themselves by providing specific advice that fits into their lifestyle while minimizing financial burden.

[0047] The processing flow will be explained below.

[0048] 1. First-time user registration

[0049] Step 1:

[0050] The device prompts the user to enter basic attributes (age, gender, build, health information, etc.).

[0051] Step 2:

[0052] The user inputs the age, sex, height, weight, medical history, etc. in order.

[0053] Step 3:

[0054] The terminal prompts the user to enter their place of residence and place of work.

[0055] Step 4:

[0056] The user enters their place of residence and place of work.

[0057] Step 5:

[0058] The terminal prompts the user to input target values ​​(target weight, target body fat percentage, etc.).

[0059] Step 6:

[0060] The user inputs a target value.

[0061] Step 7:

[0062] The terminal sends all entered information to the server.

[0063] Step 8:

[0064] The server stores the received data in a database and creates a user profile.

[0065] 2. Information gathering

[0066] Step 1:

[0067] The device collects the user's GPS data, movement history, and exercise data (e.g., number of steps taken, calories burned).

[0068] Step 2:

[0069] The terminal periodically transmits the collected data to the server.

[0070] Step 3:

[0071] The server compares the received data with external data such as the day of the week and weather.

[0072] Step 4:

[0073] The server analyzes the matched data and stores it in a statistical database.

[0074] Step 5:

[0075] The device prompts the user to input their mood, schedule, and exercise plans for the day.

[0076] Step 6:

[0077] The user inputs their emotional state (e.g., fatigue, motivation), their schedule for the day, and their exercise plan.

[0078] Step 7:

[0079] The terminal transmits the collected data and the user input data to the server.

[0080] Step 8:

[0081] The server analyzes the received data and models each user's behavioral patterns and tendencies.

[0082] 3. Proposal

[0083] Step 1:

[0084] Based on the data accumulated by the server, a diet plan is generated that is suited to the user's behavioral patterns and mood of the day.

[0085] Step 2:

[0086] The server creates a specific action plan, taking into account the balance of exercise, diet, and rest.

[0087] Step 3:

[0088] The server creates specific advice and suggestions (e.g., today's exercise menu, meal recipes) aimed at the user's goals.

[0089] Step 4:

[0090] The server transmits the created proposal data to the terminal.

[0091] Step 5:

[0092] The device displays healthy and economical lifestyle schedules and cooking menus to the user.

[0093] Step 6:

[0094] The user follows the proposed plan and carries out daily activities.

[0095] Example 1

[0096] 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."

[0097] Conventional diet support systems have difficulty providing individualized diet plans based on the user's lifestyle and mood. Furthermore, they are unable to efficiently analyze regularly collected data and provide feedback to users, making it difficult for them to continue dieting. Furthermore, they are inadequate in proposing economical and feasible meal plans.

[0098] 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.

[0099] In this invention, the server includes means for inputting a user's basic attributes, means for inputting behavior-related information such as place of residence and place of work, means for inputting target values, means for transmitting the input information, means for saving the transmitted information in a database and creating a user profile, means for tracking the user's behavioral patterns, means for comparing the tracked data with external data such as the day of the week and weather, means for analyzing the compared data, means for prompting the user to input their mood and schedule for the day, means for transmitting all the collected data to the server, means for the server to analyze the received data and generate a diet plan suitable for the user using a generative AI model, and means for generating prompts to suggest the generated diet plan to the user and displaying them on the user's terminal. This enables the server to propose an individual diet plan tailored to the user's lifestyle and mood, as well as economical meal menus, making it easier to continue dieting.

[0100] "Basic attributes" refers to information specific to an individual, such as the user's age, sex, height, weight, medical history, etc.

[0101] "Behavioral Information" refers to a user's place of residence and place of work, and related geographical and temporal information.

[0102] "Target value" refers to a specific numerical value that the user wishes to achieve, such as a target weight or body fat percentage.

[0103] A "user profile" refers to an individual information set that includes a user's basic attributes, behavior-related information, goal values, and the like.

[0104] "Behavioral patterns" refer to a user's daily movement history, exercise data, and related temporal and spatial trends.

[0105] "Tracking" refers to the collection and recording of user behavior and exercise data in real time.

[0106] "External data" refers to external information that influences a user's behavior and mood, such as the day of the week or the weather.

[0107] "Generative AI model" refers to an artificial intelligence model used to analyze user data and generate an optimal diet plan.

[0108] A "prompt sentence" refers to a guide message generated to prompt the user to take a specific action or make a choice.

[0109] A "diet plan" refers to specific guidelines for exercise and diet provided based on the user's basic attributes and behavioral patterns.

[0110] This invention relates to a "diet motivator" that provides an optimal diet plan according to the user's lifestyle and mood of the day. Specifically, it is a system that takes into account the user's basic attributes and behavior-related information to help them continue dieting economically and healthily.

[0111] First-time user registration

[0112] The terminal prompts the user to enter basic attributes. For this, a form is created using a front-end framework such as React or Vue.js, and the user is asked to enter information such as age, gender, height, weight, medical conditions, etc. When the user enters the information and presses the submit button, the entered information is sent to the server in JSON format.

[0113] The server saves the received data in a database and creates a user profile. Specifically, it receives POST requests using the Python Flask framework, converts them into a data frame using Pandas, and saves them in a MySQL database. Once the data is saved, the server returns a "Registration Complete" message to the terminal.

[0114] Information gathering

[0115] The device collects the user's GPS data, movement history, and exercise data in real time. Using external services such as the Google Fit API and Apple HealthKit, the device periodically collects data and stores it in a buffer. This data is then periodically (e.g., every hour) sent to a server.

[0116] The user inputs their mood and schedule for the day. The device prompts the user to input their mood, schedule, and exercise intensity for the day through a pop-up screen. Once the user enters this information, the data is sent to the server and recorded in MongoDB via the REST API of the Django framework.

[0117] Data analysis and plan generation

[0118] The server aggregates and organizes the collected data. Using Python, a cron job is run periodically to aggregate all the data stored in the database. Pandas and Numpy are used to analyze the data and identify user behavior patterns and trends. The OpenWeatherMap API is also used to obtain external weather data and compare it with this data.

[0119] The server generates a diet plan using the AI ​​model. Using TensorFlow and PyTorch, it inputs the user's behavioral patterns and mood data to generate an optimal exercise and meal plan. The generated plan is saved in JSON format and sent to the device.

[0120] proposal notification

[0121] The server sends the generated diet plan to the device. The device receives this data and displays a notification to the user. By implementing push notifications using React Native, the notification includes today's exercise menu and cooking recipes.

[0122] For example, if a user one day inputs "It's raining today, so I don't want to go outside," the server analyzes weather data and the user's behavioral patterns, and confirms from the weather API that today's weather is rainy. The server then suggests "yoga and stretches that can be done indoors," and the device notifies the user of this suggestion. The server also displays a recipe for "vegetable soup" based on the ingredients data in the user's refrigerator.

[0123] An example prompt is:

[0124] "I want to suggest today's exercise menu based on the user's current emotional state and weather data. The user has entered, 'It's raining today, so I don't want to go outside,' and there are tomatoes, cabbage, and carrots in the refrigerator. Given these conditions, what would be the optimal exercise menu and cooking recipe?"

[0125] This system can propose individual diet plans based on the user's behavioral patterns and moods, as well as economical meal menus, supporting users to continue their diet without straining themselves.

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

[0127] Step 1:

[0128] Entering Basic User Attributes

[0129] The terminal prompts the user to enter basic attributes such as age, sex, height, weight, and medical history. The user enters this information into the form and clicks the submit button. The entered data is sent from the terminal to the server in JSON format. Terminal input: Basic user attribute information Server output: JSON format data.

[0130] Step 2:

[0131] Entering user behavior-related information

[0132] The device prompts the user to enter activity-related information such as residence and workplace. The user enters this information and presses the submit button. The entered data is sent to the server in JSON format. Device input: User's residence and workplace information Server output: JSON format data.

[0133] Step 3:

[0134] Entering the target value

[0135] The terminal prompts the user to enter target values ​​such as target weight and target body fat percentage. The user enters this information and presses the submit button. The entered data is sent to the server in JSON format. Terminal input: User's target value Server output: JSON format data.

[0136] Step 4:

[0137] Data storage and user profile creation

[0138] The server saves all the data received in the previous steps in a database and creates a user profile. MySQL is used to save the user's basic attributes, behavior-related information, and goal values. Server input: User's basic attributes, behavior-related information, goal values ​​Server output: User profile created in the database.

[0139] Step 5:

[0140] Behavioral pattern tracking

[0141] The device collects the user's GPS data, movement history, and exercise data (number of steps, calories burned, etc.) in real time. The collected data is sent to the server at regular intervals. Device input: Exercise data collected in real time Server output: Data in JSON format.

[0142] Step 6:

[0143] Matching tracking data with external data

[0144] The server compares the received tracking data with external data such as the day of the week and weather. External data is obtained from sources such as the OpenWeatherMap API. Server input: Tracking data, day of the week, weather data. Server output: Matched data.

[0145] Step 7:

[0146] Input your mood and schedule

[0147] The device prompts the user to input their mood and schedule for the day. The data entered by the user is sent to the server and stored in MongoDB. Device input: User's mood, schedule Server output: Data in JSON format.

[0148] Step 8:

[0149] Data analysis

[0150] The server aggregates and analyzes all collected data. It uses Pandas and Numpy to analyze the data and understand behavioral patterns and moods of the day. Server input: All collected data. Server output: Analysis results.

[0151] Step 9:

[0152] Generate a diet plan

[0153] The server generates a diet plan using a generative AI model based on the analysis results. It uses TensorFlow and PyTorch to create the optimal exercise and meal plan for the user. Server input: Analysis results. Server output: Generated diet plan.

[0154] Step 10:

[0155] Diet plan notifications

[0156] The server sends the generated diet plan to the user's device. The device notifies the user of the received plan and suggests specific actions and cooking recipes. Specifically, a push notification is displayed using React Native. Server input: Generated diet plan Device output: Push notification.

[0157] As a specific example, if a user inputs "It's raining today and I don't want to go outside," the server will analyze weather data and the user's behavioral patterns to suggest yoga and stretching exercises that can be done indoors. The device will also display a recipe for a vegetable soup based on the ingredients in the user's refrigerator. An example of a prompt for the production version could be, "I would like to suggest today's exercise menu based on the user's current emotional state and weather data. The user inputs "It's raining today and I don't want to go outside," and there are tomatoes, cabbage, and carrots in the refrigerator. Please tell me the optimal exercise menu and cooking recipe based on these conditions."

[0158] (Application example 1)

[0159] 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."

[0160] In today's busy lifestyles, individual users need individually customized suggestions and support to maintain a healthy and economical diet. However, conventional diet systems have difficulty providing specific advice based on the user's mood and schedule that day, as well as real-time location information. In particular, brick-and-mortar stores require users to instantly receive appropriate diet information within the store. Therefore, there is a need for an effective diet motivator that reflects the user's individual circumstances in real time and can be utilized in brick-and-mortar stores.

[0161] 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.

[0162] In this invention, the server includes a means for inputting basic attributes of a user, a means for inputting behavior-related information such as place of residence and place of work, and a means for inputting target values. This makes it possible to provide appropriate diet information in real time through a display device worn by a user in a physical store. This allows users to receive personalized diet advice in real time within the store, allowing them to diet more effectively.

[0163] The "means for inputting basic user attributes" is a part of the system for inputting basic personal information such as the user's age, sex, height, and weight.

[0164] The "means for inputting behavior-related information" refers to a means for inputting information related to the user's behavior, such as the user's place of residence, place of work, and travel route.

[0165] The "means for inputting target values" is a means for inputting target values ​​for dieting, such as the user's target weight and target body fat percentage.

[0166] The "means for transmitting the input information" is a means for transmitting the basic attributes, behavior-related information, target values, etc. input by the user to the server.

[0167] The "means for storing in a database and creating a user profile" is the part of the system for storing the transmitted information in a database and creating an individual profile for the user based thereon.

[0168] The "means for tracking user behavior patterns" refers to a means for collecting user movement history and exercise data in real time and tracking the user's behavior patterns.

[0169] "Means for comparing with external data" refers to means for comparing collected data with external data such as the day of the week and weather, and analyzing the data.

[0170] The "means for analyzing data" is a means for analyzing the collated data and generating an optimal diet plan for the user.

[0171] The "means for inputting the mood and schedule of the day" is a means for the user to input the mood and schedule of the day.

[0172] The "means for transmitting all collected data to the server" refers to a means for transmitting all collected data to the server.

[0173] The "means for generating a diet plan" is a means for generating a diet plan suitable for the user based on the data received by the server.

[0174] The "means for proposing the generated diet plan to the user" is a means for presenting the generated diet plan to the user.

[0175] "Means for providing appropriate diet information in real time through a display device" refers to means for providing optimal diet information in real time through a display device worn by a user in a physical store.

[0176] This invention is a system that provides users with an optimal diet plan based on their basic attributes, behavior-related information, target values, etc. This system is composed of a server, a terminal, and a display device that the user wears in a physical store.

[0177] User Registration

[0178] When the terminal starts up the system for the first time, the user enters basic attributes such as name, age, sex, height, weight, and medical conditions. Next, the user enters their place of residence and place of work, as well as their target values ​​such as target weight and target body fat percentage. This information is sent from the terminal to the server and stored in a database to create a user profile.

[0179] Information gathering

[0180] The device collects real-time GPS data, movement history, and exercise data (step count, calories burned, etc.) to track the user's behavioral patterns. This data is then compared with external data such as weather data and the day of the week. The device also allows the user to input their mood, schedule, and planned exercise intensity for the day.

[0181] Plan Generation

[0182] Based on the collected and analyzed data, the server generates a diet plan suited to the user's behavioral patterns and mood for that day. The plan considers the balance of exercise, meals, and rest and is presented to the device as a specific action plan.

[0183] Application in physical stores

[0184] When users visit physical stores, especially supermarkets and fitness gyms, they can wear a head-mounted display to receive real-time diet information. For example, product information and recipes are displayed in supermarkets, and exercise methods are displayed in fitness gyms.

[0185] Hardware and software used

[0186] Hardware: Head-mounted display, GPS module

[0187] Software: Python program, GPS module library, RESTful API

[0188] Specific examples

[0189] If it's raining that day and the user types "I don't want to go outside today," the server will analyze the weather data and the user's behavioral patterns to suggest yoga and stretching exercises that can be done indoors. It will also display a recipe for a healthy "vegetable soup" based on the ingredients in the user's refrigerator.

[0190] Prompt Sentence Examples

[0191] Below are some examples of prompt sentences.

[0192] User Attribute Information:

[0193] Age: 28

[0194] Gender: Female

[0195] Height: 160 cm

[0196] Weight: 55 kg

[0197] Residence: Tokyo

[0198] Location: Shibuya

[0199] Target weight: 50 kg

[0200] Target body fat percentage: 20%

[0201] Current time: 2023-10-01T14:30:00

[0202] Current location: Latitude 35.6895, Longitude 139.6917

[0203] Use this information to generate the best diet plan for you.

[0204] In this way, the present invention supports the continuation of a healthy and economical diet by proposing a diet plan that matches the user's specific lifestyle and mood.

[0205] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0206] Step 1:

[0207] User enters basic attributes

[0208] The user uses a terminal to input basic attributes such as name, age, sex, height, weight, and medical conditions. The input information is sent to the server by the terminal. Input information: Name, age, sex, height, weight, medical conditions. Output information: Creates a user profile on the server.

[0209] Step 2:

[0210] The user inputs the behavior-related information and the goal value.

[0211] The user uses the terminal to input behavior-related information and goal values, such as place of residence, place of work, target weight, and target body fat percentage. This information is also sent from the terminal to the server and stored in the database. Input content: place of residence, place of work, target weight, target body fat percentage. Output content: user profile updated on the server.

[0212] Step 3:

[0213] Tracking user behavior patterns

[0214] The device collects GPS data, movement history, and exercise data (number of steps, calories burned, etc.) in real time. The collected data is periodically sent to the server. Input: GPS data, movement history, exercise data. Output: Behavioral pattern records on the server.

[0215] Step 4:

[0216] Compare with external data and analyze

[0217] The server compares the tracked data with external data such as the day of the week and weather, and analyzes the data. Input: Tracking data, day of the week, weather data. Output: Analysis results (behavioral pattern trends).

[0218] Step 5:

[0219] The user inputs their mood and schedule

[0220] The user uses the device to input the mood, planned exercise intensity, and schedule for the day. The input information is sent to the server. Input information: mood, planned exercise intensity, schedule. Output information: record of mood and schedule on the server.

[0221] Step 6:

[0222] Generate a diet plan

[0223] The server generates a diet plan suited to the user based on all the data received. Specifically, this includes the type of exercise and meal menu. Input: Basic attributes, behavioral patterns, mood and schedule. Output: Diet plan.

[0224] Step 7:

[0225] Suggest diet plans to users

[0226] The device notifies the user of the generated diet plan. In a physical store, the plan is displayed in real time on the head-mounted display worn by the user. Input: Diet plan. Output: The plan displayed on the user's head-mounted display.

[0227] Step 8:

[0228] Providing appropriate diet information in real time

[0229] When a user wears a head-mounted display in a physical store such as a supermarket or fitness gym, real-time diet information about products in the store and exercise methods is displayed. Input content: Location information and product information in the store. Output content: Diet information displayed on the head-mounted display.

[0230] 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.

[0231] This invention relates to a "diet motivator" that provides an optimal diet plan tailored to the user's lifestyle and mood on that day, and in particular, is a system that provides a more sophisticated and personalized diet plan by combining it with an emotion engine that recognizes the user's emotions.

[0232] 1. First-time user registration

[0233] When the server starts the system for the first time, the terminal prompts the user to enter basic attributes (age, sex, build, health information, etc.). The user enters age, sex, height, weight, medical history, etc. Next, the terminal prompts the user to enter their place of residence and place of work, and the user enters this information. Furthermore, the terminal prompts the user to enter target values ​​such as target weight and target body fat percentage, and the user enters the target values.

[0234] The terminal sends this input information to the server, and the server stores the received data in a database to create a user profile.

[0235] 2. Information gathering

[0236] To track a user's behavioral patterns, the device collects the user's GPS data, movement history, and exercise data (e.g., number of steps, calories burned) in real time. This data is periodically sent to a server, which then compares the received data with external data such as the day of the week and weather, and analyzes the user's behavioral patterns.

[0237] The device also prompts the user to input their mood, schedule, and planned exercise intensity for the day, allowing the user to input their emotional state (e.g., fatigue, motivation), schedule, and exercise plan for the day. The emotion engine recognizes the user's emotions in real time and sends the data to the server.

[0238] 3. Emotion Engine

[0239] The emotion engine analyzes the user's facial expressions, tone of voice, text input, etc. to recognize the user's emotions. Emotional data is analyzed in combination with the user's behavioral patterns and mood input for the day. For example, if the emotion engine recognizes that the user is tired, that data is sent to the server.

[0240] 4. Proposal

[0241] Based on the data collected and analyzed so far, the server generates a diet plan suited to the user's behavioral patterns, mood of the day, and emotional data. The generated plan creates a specific action plan that takes into account the balance of exercise, meals, and rest, and sends it to the device as suggested data. Specifically, it can suggest exercise menus that match the user's mood and emotions of the day, as well as healthy and economical cooking menus.

[0242] Specific examples

[0243] If a user inputs "I feel tired today" one day and the emotion engine recognizes the tiredness from the user's facial expression, the server will use that data to suggest "light stretching and relaxation exercises." The device will also display a recipe for "chicken and vegetable stew," which is effective in relieving fatigue, based on ingredients in the user's refrigerator. In this way, users can continue their diet without straining themselves in their daily lives.

[0244] This system supports users in continuing a healthy and enjoyable diet through a consistent process from data collection to recommendations. In addition, by combining it with an emotion engine, it provides specific advice based on the user's emotions, helping them achieve their goals without any stress.

[0245] The processing flow will be explained below.

[0246] 1. First-time user registration

[0247] Step 1:

[0248] The device prompts the user to enter basic attributes (age, gender, build, health information, etc.).

[0249] Step 2:

[0250] The user inputs the age, sex, height, weight, medical history, etc. in order.

[0251] Step 3:

[0252] The terminal prompts the user to enter their place of residence and place of work.

[0253] Step 4:

[0254] The user enters their place of residence and place of work.

[0255] Step 5:

[0256] The terminal prompts the user to input target values ​​(target weight, target body fat percentage, etc.).

[0257] Step 6:

[0258] The user inputs a target value.

[0259] Step 7:

[0260] The terminal sends all entered information to the server.

[0261] Step 8:

[0262] The server stores the received data in a database and creates a user profile.

[0263] 2. Information gathering

[0264] Step 1:

[0265] The device collects the user's GPS data, movement history, and exercise data (e.g., number of steps taken, calories burned).

[0266] Step 2:

[0267] The terminal periodically transmits the collected data to the server.

[0268] Step 3:

[0269] The server compares the received data with external data such as the day of the week and weather.

[0270] Step 4:

[0271] The server analyzes the matched data and stores it in a statistical database.

[0272] Step 5:

[0273] The device prompts the user to input their mood, schedule, and exercise plans for the day.

[0274] Step 6:

[0275] The user inputs their emotional state (e.g., fatigue, motivation), their schedule for the day, and their exercise plan.

[0276] Step 7:

[0277] The emotion engine analyzes the user's facial expressions, tone of voice, text input, etc. to recognize emotions.

[0278] Step 8:

[0279] The data collected by the device, user input data, and emotion data recognized by the emotion engine are sent to the server.

[0280] Step 9:

[0281] The server analyzes the received data and models each user's behavioral patterns and tendencies.

[0282] 3. Proposal

[0283] Step 1:

[0284] Based on the data accumulated by the server, a diet plan is generated that is suited to the user's behavioral patterns, mood of the day, and emotional data.

[0285] Step 2:

[0286] The server creates a specific action plan, taking into account the balance of exercise, diet, and rest.

[0287] Step 3:

[0288] The server creates specific advice and suggestions (e.g., today's exercise menu, meal recipes) aimed at the user's goals.

[0289] Step 4:

[0290] The server transmits the created proposal data to the terminal.

[0291] Step 5:

[0292] The device displays healthy and economical lifestyle schedules and cooking menus to the user.

[0293] Step 6:

[0294] The user follows the proposed plan and carries out daily activities.

[0295] Examples:

[0296] One day, if a user types "I feel tired today," and the emotion engine recognizes the user's tiredness from their facial expression, the device will send that data to the server. Based on that data, the server will suggest "light stretching and relaxation exercises." The device will also display a recipe for "chicken and vegetable stew," which is effective in relieving fatigue, based on ingredients in the user's refrigerator. In this way, users can continue their diet without straining themselves in their daily lives.

[0297] Example 2

[0298] 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."

[0299] While conventional diet support systems propose diet plans based on the user's basic attributes and behavioral data, they lack the ability to consider the user's emotional state or mood on that day. This can lead to problems such as users not receiving appropriate support on days when they are tired or unmotivated, making it difficult to continue their diet. Furthermore, because detailed planning tailored to individual users is not possible, general proposals are less effective for some users.

[0300] 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.

[0301] In this invention, the server includes means for inputting a user's basic attributes, means for inputting behavior-related information such as place of residence and place of work, means for inputting target values, means for transmitting the input information, means for saving the transmitted information in a database and creating a user profile, means for tracking the user's behavioral patterns, means for comparing the tracked data with external data such as the day of the week and weather, means for analyzing the compared data, means for prompting the user to input their mood and schedule for the day, an emotion engine for analyzing the user's emotional state, means for transmitting all the collected data and emotion data to the server, means for the server to analyze the received data and generate a diet plan suitable for the user, and means for proposing the generated diet plan to the user. This makes it possible to provide a more personalized and specific diet plan based on the user's emotional state and mood for the day.

[0302] "Basic attributes" refers to basic information about an individual, such as the user's age, sex, height, weight, medical history, etc.

[0303] "Behavior-related information" is information about the user's place of residence, place of work, and behavioral patterns related thereto.

[0304] "Goal value" refers to a specific health goal such as weight or body fat percentage that a user aims to achieve.

[0305] A "user profile" is an individual information set in a database that is created based on input information such as a user's basic attributes, behavior-related information, and goal values.

[0306] A "behavioral pattern" is a series of behavioral trends over a specific period of time, analyzed based on a user's GPS data, movement history, exercise data, etc.

[0307] "External data" is information about the external environment that affects the user's behavior, such as the day of the week and weather.

[0308] An "emotion engine" is a system that has the function of analyzing a user's facial expressions, tone of voice, text input, etc. to recognize their emotional state.

[0309] A "diet plan" is a specific action plan for exercise, meals, rest, etc. that is generated based on the user's behavioral patterns, basic attributes, target values, and emotional state.

[0310] This invention relates to a "diet motivator" that provides an optimal diet plan tailored to the user's lifestyle and mood on that day. In particular, this system provides a more refined and personalized diet plan by combining it with an emotion engine that recognizes the user's emotions.

[0311] The system of the present invention relies primarily on two hardware components: a server and a terminal.

[0312] 1. First-time user registration

[0313] When the terminal starts the system for the first time, it displays a screen prompting the user to enter basic attributes (age, sex, build, health information, etc.). The user enters information such as age, sex, height, weight, and medical history. The terminal then prompts the user to enter their place of residence and place of work, and the user enters that information. The terminal then prompts the user to enter target values ​​such as target weight and target body fat percentage, and the user enters those target values.

[0314] The device sends this input information to the server, which stores the received data in a database and creates a user profile.

[0315] 2. Information gathering

[0316] To track a user's behavioral patterns, the device collects the user's GPS data, movement history, and exercise data (e.g., number of steps, calories burned) in real time. This data is periodically sent to a server, which then compares the received data with external data such as the day of the week and weather, and analyzes the user's behavioral patterns.

[0317] The device also displays a screen prompting the user to input their mood, schedule, and planned exercise intensity for the day. The user can input their emotional state (e.g., fatigue, motivation), schedule, and exercise plan for the day. The emotion engine analyzes the user's facial expression, tone of voice, and text input to recognize their emotional state. The device sends the output of the emotion engine to the server.

[0318] 3. Proposal

[0319] Based on the data collected and analyzed so far, the server generates a diet plan suited to the user's behavioral patterns, mood of the day, and emotional data. The generated plan takes into account the balance of exercise, meals, and rest, and sends the proposed data to the device as a specific action plan. Specifically, it can suggest an exercise menu that matches the user's mood and emotions of the day, as well as a healthy and economical cooking menu.

[0320] Specific examples

[0321] For example, if a user inputs "I feel tired today" one day and the emotion engine recognizes the feeling of fatigue from the user's facial expression, the server will use that data to suggest "light stretching and relaxation exercises." The device will also display a recipe for "chicken and vegetable stew," which is effective in relieving fatigue, based on ingredients in the user's refrigerator. This allows users to continue their diet without straining themselves in their daily lives.

[0322] Prompt Sentence Examples

[0323] "The user enters 'I'm tired today,' and the emotion engine recognizes this state of fatigue. Based on this data, please suggest appropriate exercise and meal plans."

[0324] By inputting such prompt sentences into the generative AI model, the accuracy of the model can be confirmed and the quality of the system can be improved.

[0325] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0326] Step 1: First-time user registration

[0327] Input: User's basic attribute information (age, gender, height, weight, medical history, etc.)

[0328] Specific operation When the terminal starts the system for the first time, it displays a screen prompting the user to enter basic attributes. The user enters the information. The terminal temporarily stores this information.

[0329] Output: Basic attribute information is saved to the device.

[0330] Step 2: Enter your place of residence and work

[0331] Input: User's residence and work location information

[0332] Specific operation: The terminal displays a screen prompting the user to enter residence and workplace information. The user enters the information. The terminal temporarily stores this information.

[0333] Output: Residence and work location information is saved on the device

[0334] Step 3: Enter the target value

[0335] Input: User's goal values ​​such as goal weight and goal body fat percentage

[0336] Specific operation: The device displays a screen prompting the user to input the target value. The user inputs the target value. The device temporarily stores this information.

[0337] Output: The target value is saved to the terminal.

[0338] Step 4: Data submission and user profile creation

[0339] Input: Basic attribute information, residence and workplace information, target value

[0340] Specific operation: The device sends all input information to the server, which stores the received data in a database and creates a user profile.

[0341] Output: The user profile is saved in the database.

[0342] Step 5: Collecting and Sending Dynamic Data

[0343] Input: User's GPS data, movement history, exercise data (number of steps, calories burned, etc.)

[0344] Specific operation: The device uses sensors to collect the user's GPS data, movement history, and exercise data in real time, and transmits the collected data to a server at regular intervals.

[0345] Output: Collected data is sent to a server and stored for analysis.

[0346] Step 6: Analyze behavioral patterns

[0347] Input: Collected dynamic data, external data (day of the week, weather)

[0348] Specific operation: The server compares the collected dynamic data with external data such as the day of the week and weather, and analyzes behavioral patterns.

[0349] Output: Behavioral pattern analysis data

[0350] Step 7: Enter your mood and schedule

[0351] Input: User's mood, schedule for the day, planned exercise intensity

[0352] Specific operation: The device displays a screen prompting the user to input their mood, schedule, and planned exercise intensity. The user inputs this information. The device temporarily stores this information.

[0353] Output: Mood and schedule information is saved on the device

[0354] Step 8: Emotion Analysis with the Emotion Engine

[0355] Input: User facial expression data, tone of voice, text input

[0356] How it works: The emotion engine analyzes the user's facial expressions, tone of voice, and text input to recognize their emotional state, and the device sends the output to the server.

[0357] Output: Emotional state data is sent to the server

[0358] Step 9: Analyze the data and generate a diet plan

[0359] Input: behavioral pattern analysis data, mood and schedule information, emotional state data

[0360] Specific operation: Based on the data collected and analyzed up to now, the server generates a diet plan suited to the user's behavioral patterns, mood of the day, and emotional data.

[0361] Output: The generated diet plan

[0362] Step 10: Inform your diet plan

[0363] Input: Generated diet plan

[0364] Specific operations: The server sends the generated diet plan to the terminal, and the terminal notifies the user of the plan.

[0365] Output: The diet plan notified to the user

[0366] (Application example 2)

[0367] 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."

[0368] Conventional diet plan suggestion systems often make uniform suggestions without considering the user's emotions or mood of the day. This makes it difficult to provide appropriate suggestions that match the user's mental state or daily lifestyle, making it difficult to motivate them to continue dieting. Furthermore, to actually prepare the suggested meal menu, the user must procure ingredients and cook the food themselves, which is time-consuming and labor-intensive.

[0369] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for inputting a user's basic attributes; means for inputting behavior-related information such as a residence and workplace; means for inputting a target value; means for transmitting the input information; means for saving the transmitted information in a database and creating a user profile; means for tracking the user's behavioral patterns; means for comparing the tracked data with external data such as the day of the week and the weather; means for analyzing the compared data; means for prompting the user to input their mood and schedule for the day; means for transmitting all collected data to the server; means for the server to analyze the received data and generate a diet plan suitable for the user; means for proposing the generated diet plan to the user; means including an emotion engine for collecting and analyzing the user's emotional data; means for proposing a meal menu suitable for the user based on the emotional data; and means for providing the meal menu to the user via a food delivery system. This makes it possible to provide a personalized diet plan based on the user's emotions and mood for the day, and the suggested meal menu can be easily ordered, making it easier to continue dieting.

[0370] "Basic attributes of a user" refers to personal information such as the user's age, sex, build, and health information.

[0371] "Behavioral information" refers to information about a user's behavior, including their place of residence, place of work, and daily movements.

[0372] "Target value" refers to a specific numerical target such as weight or body fat percentage that the user aims to achieve.

[0373] "User profile" refers to a comprehensive database entry that includes a user's basic attributes, behavior-related information, goals, etc.

[0374] "Behavioral patterns" refer to specific behavioral tendencies and habits in a user's daily life.

[0375] "External data" refers to relevant information other than the user's own behavior, such as the day of the week and weather.

[0376] "Emotion engine" refers to a function that recognizes a user's emotions by analyzing their facial expressions, tone of voice, and text input.

[0377] A "diet plan" refers to a specific action plan proposed to a user that takes into account a balance of exercise, diet, rest, and other factors.

[0378] "Meal menu" refers to specific meal items suggested based on the user's emotions, mood, and health status.

[0379] A "food delivery system" refers to an online service that allows users to easily order suggested meal menus.

[0380] This invention builds a system that proposes optimal diet plans and meal menus based on the user's emotions and mood of the day, and then actually provides them through a food delivery service. This system is realized by using the following programs, hardware, and software.

[0381] The server includes a means for inputting basic user attributes, a means for inputting behavior-related information such as place of residence and place of work, a means for inputting target values, a means for transmitting the input information, and a means for storing the transmitted information in a database and creating a user profile, thereby enabling centralized management of basic user information.

[0382] The server also includes a means for tracking the user's behavioral patterns, a means for comparing the tracked data with external data such as the day of the week and weather, and a means for analyzing the compared data, thereby collecting and analyzing detailed data about the user's daily life.

[0383] Furthermore, the server includes a means for allowing the user to input the mood and schedule of the day, a means for transmitting all the collected data to the server, a means for the server to analyze the received data and generate a diet plan suitable for the user, and a means for proposing the generated diet plan to the user, thereby enabling personalized suggestions to be made to each individual user.

[0384] The server further includes means for including an emotion engine that collects and analyzes emotion data of the user, means for suggesting a meal menu suitable for the user based on the emotion data, and means for providing the meal menu to the user via a food delivery system, so that the user can easily order the suggested meal menu and actually receive the meal through the food delivery service.

[0385] For example, if a user inputs "I'm tired today," and the emotion engine recognizes the same, the server will suggest light meal options such as "chicken soup" or "vegetable salad." Users can easily check these options within the app and request delivery by simply pressing the order button.

[0386] An example of a prompt to input to a generative AI model is as follows:

[0387] "Please suggest a healthy menu when the user feels tired. User information: age, gender, physique, health information, goal value. Emotion: fatigue."

[0388] The hardware used includes a cloud server, and the software includes Flask (Python) and a database (e.g., SQLite or PostgreSQL).

[0389] In this way, personalized diet plans and meal menus that reflect the user's emotions and mood of the day can be proposed and actually provided through a food delivery system, which will encourage users to continue their diet and improve the quality of their daily lives.

[0390] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0391] Step 1:

[0392] When the server starts the system for the first time, the terminal prompts the user to enter basic attributes (age, gender, build, health information, etc.). The user enters this information into the terminal, and the terminal sends the received information to the server. The server stores the received data in a database and creates a user profile.

[0393] Step 2:

[0394] The device prompts the user to enter activity-related information such as their place of residence and place of work. The user enters this information into the device, which then transmits the information to the server. The server stores the received data in a database and updates the user profile.

[0395] Step 3:

[0396] The device prompts the user to input goals (e.g., target weight or target body fat percentage). The user inputs the goals, and the device sends the input data to the server. The server stores the received goal data in a database and integrates it into the user profile.

[0397] Step 4:

[0398] The device collects GPS data, movement history, and exercise data (e.g., number of steps, calories burned) in real time to track the user's behavior. This data is periodically sent to a server, which stores the received data in a database.

[0399] Step 5:

[0400] The server compares the tracked data with external data such as the day of the week and weather, and analyzes the matched data. This allows the user's behavioral patterns to be understood. The analysis results are stored in a database.

[0401] Step 6:

[0402] The device provides an interface for the user to input the user's mood and schedule for the day. The user inputs the information, and the device sends it to the server. The server analyzes the received data and integrates it into the user profile.

[0403] Step 7:

[0404] The server uses an emotion engine to recognize the user's emotions in real time from facial expressions, tone of voice, and text input, and the emotion data is stored in a database.

[0405] Step 8:

[0406] The server uses a generative AI model based on the data collected and analyzed to generate a diet plan suited to the user. This calculation uses prompt statements and inputs the user's emotions and behavioral data. The generated diet plan is saved in a database as a specific action plan.

[0407] Step 9:

[0408] The server transmits the generated diet plan to the user's terminal as proposal data, and the terminal displays the received proposal data to the user, allowing the user to confirm the plan.

[0409] Step 10:

[0410] The server proposes a meal menu suitable for the user based on the user's emotional data. This meal menu is provided to the user via the food delivery system and is generated using an emotion engine and a generative AI model. The user can check the proposed menu through their device and easily order.

[0411] 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.

[0412] 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.

[0413] 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.

[0414] [Second embodiment]

[0415] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0416] 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.

[0417] 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).

[0418] 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.

[0419] 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.

[0420] 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).

[0421] 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.

[0422] 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.

[0423] 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.

[0424] 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.

[0425] 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.

[0426] 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."

[0427] This invention relates to a "diet motivator" that provides the user with an optimal diet plan tailored to their lifestyle and mood on that day. Specifically, it is a system that takes into account the user's basic attributes and behavioral patterns to help them continue their diet economically and healthily.

[0428] 1. First-time user registration

[0429] When the server starts the system for the first time, the terminal prompts the user to enter basic attributes (age, sex, build, health information, etc.). The user enters age, sex, height, weight, medical history, etc. Next, the terminal prompts the user to enter their place of residence and place of work, and the user enters this information. Furthermore, the terminal prompts the user to enter target values ​​such as target weight and target body fat percentage, and the user enters the target values.

[0430] The terminal sends this input information to the server, and the server stores the received data in a database to create a user profile.

[0431] 2. Information gathering

[0432] To track a user's behavioral patterns, the device collects the user's GPS data, movement history, and exercise data (e.g., number of steps, calories burned) in real time. This data is periodically sent to a server, which then compares the received data with external data such as the day of the week and weather, and analyzes the user's behavioral patterns.

[0433] The terminal also prompts the user to input their mood and schedule for the day, as well as their planned exercise intensity, allowing the user to input their emotional state (e.g., fatigue, motivation), schedule for the day, and exercise plan.

[0434] 3. Proposal

[0435] The server generates a diet plan based on the data collected and analyzed to date, tailored to the user's behavioral patterns and daily mood. The plan creates a specific action plan that takes into account the balance of exercise, meals, and rest, and sends it to the device as suggested data. Specifically, it can suggest an exercise menu that suits the user's mood that day, as well as healthy and economical meal menus.

[0436] Specific examples

[0437] If a user inputs "It's raining today, so I don't want to go outside," the server will analyze the weather data and the user's behavioral patterns and suggest "yoga and stretching exercises that can be done indoors." The device will also display a recipe for a low-calorie yet nutritious "vegetable soup" based on ingredients in the user's refrigerator. In this way, users can continue their diet without any stress in their daily lives.

[0438] The system supports users in continuing a healthy and enjoyable diet through a consistent process from data collection to recommendations. It also helps users achieve their goals without straining themselves by providing specific advice that fits into their lifestyle while minimizing financial burden.

[0439] The processing flow will be explained below.

[0440] 1. First-time user registration

[0441] Step 1:

[0442] The device prompts the user to enter basic attributes (age, gender, build, health information, etc.).

[0443] Step 2:

[0444] The user inputs the age, sex, height, weight, medical history, etc. in order.

[0445] Step 3:

[0446] The terminal prompts the user to enter their place of residence and place of work.

[0447] Step 4:

[0448] The user enters their place of residence and place of work.

[0449] Step 5:

[0450] The terminal prompts the user to input target values ​​(target weight, target body fat percentage, etc.).

[0451] Step 6:

[0452] The user inputs a target value.

[0453] Step 7:

[0454] The terminal sends all entered information to the server.

[0455] Step 8:

[0456] The server stores the received data in a database and creates a user profile.

[0457] 2. Information gathering

[0458] Step 1:

[0459] The device collects the user's GPS data, movement history, and exercise data (e.g., number of steps taken, calories burned).

[0460] Step 2:

[0461] The terminal periodically transmits the collected data to the server.

[0462] Step 3:

[0463] The server compares the received data with external data such as the day of the week and weather.

[0464] Step 4:

[0465] The server analyzes the matched data and stores it in a statistical database.

[0466] Step 5:

[0467] The device prompts the user to input their mood, schedule, and exercise plans for the day.

[0468] Step 6:

[0469] The user inputs their emotional state (e.g., fatigue, motivation), their schedule for the day, and their exercise plan.

[0470] Step 7:

[0471] The terminal transmits the collected data and the user input data to the server.

[0472] Step 8:

[0473] The server analyzes the received data and models each user's behavioral patterns and tendencies.

[0474] 3. Proposal

[0475] Step 1:

[0476] Based on the data accumulated by the server, a diet plan is generated that is suited to the user's behavioral patterns and mood of the day.

[0477] Step 2:

[0478] The server creates a specific action plan, taking into account the balance of exercise, diet, and rest.

[0479] Step 3:

[0480] The server creates specific advice and suggestions (e.g., today's exercise menu, meal recipes) aimed at the user's goals.

[0481] Step 4:

[0482] The server transmits the created proposal data to the terminal.

[0483] Step 5:

[0484] The device displays healthy and economical lifestyle schedules and cooking menus to the user.

[0485] Step 6:

[0486] The user follows the proposed plan and carries out daily activities.

[0487] Example 1

[0488] 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."

[0489] Conventional diet support systems have difficulty providing individualized diet plans based on the user's lifestyle and mood. Furthermore, they are unable to efficiently analyze regularly collected data and provide feedback to users, making it difficult for them to continue dieting. Furthermore, they are inadequate in proposing economical and feasible meal plans.

[0490] 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.

[0491] In this invention, the server includes means for inputting a user's basic attributes, means for inputting behavior-related information such as place of residence and place of work, means for inputting target values, means for transmitting the input information, means for saving the transmitted information in a database and creating a user profile, means for tracking the user's behavioral patterns, means for comparing the tracked data with external data such as the day of the week and weather, means for analyzing the compared data, means for prompting the user to input their mood and schedule for the day, means for transmitting all the collected data to the server, means for the server to analyze the received data and generate a diet plan suitable for the user using a generative AI model, and means for generating prompts to suggest the generated diet plan to the user and displaying them on the user's terminal. This enables the server to propose an individual diet plan tailored to the user's lifestyle and mood, as well as economical meal menus, making it easier to continue dieting.

[0492] "Basic attributes" refers to information specific to an individual, such as the user's age, sex, height, weight, medical history, etc.

[0493] "Behavioral Information" refers to a user's place of residence and place of work, and related geographical and temporal information.

[0494] "Target value" refers to a specific numerical value that the user wishes to achieve, such as a target weight or body fat percentage.

[0495] A "user profile" refers to an individual information set that includes a user's basic attributes, behavior-related information, goal values, and the like.

[0496] "Behavioral patterns" refer to a user's daily movement history, exercise data, and related temporal and spatial trends.

[0497] "Tracking" refers to the collection and recording of user behavior and exercise data in real time.

[0498] "External data" refers to external information that influences a user's behavior and mood, such as the day of the week or the weather.

[0499] "Generative AI model" refers to an artificial intelligence model used to analyze user data and generate an optimal diet plan.

[0500] A "prompt sentence" refers to a guide message generated to prompt the user to take a specific action or make a choice.

[0501] A "diet plan" refers to specific guidelines for exercise and diet provided based on the user's basic attributes and behavioral patterns.

[0502] This invention relates to a "diet motivator" that provides an optimal diet plan according to the user's lifestyle and mood of the day. Specifically, it is a system that takes into account the user's basic attributes and behavior-related information to help them continue dieting economically and healthily.

[0503] First-time user registration

[0504] The terminal prompts the user to enter basic attributes. For this, a form is created using a front-end framework such as React or Vue.js, and the user is asked to enter information such as age, gender, height, weight, medical conditions, etc. When the user enters the information and presses the submit button, the entered information is sent to the server in JSON format.

[0505] The server saves the received data in a database and creates a user profile. Specifically, it receives POST requests using the Python Flask framework, converts them into a data frame using Pandas, and saves them in a MySQL database. Once the data is saved, the server returns a "Registration Complete" message to the terminal.

[0506] Information gathering

[0507] The device collects the user's GPS data, movement history, and exercise data in real time. Using external services such as the Google Fit API and Apple HealthKit, the device periodically collects data and stores it in a buffer. This data is then periodically (e.g., every hour) sent to a server.

[0508] The user inputs their mood and schedule for the day. The device prompts the user to input their mood, schedule, and exercise intensity for the day through a pop-up screen. Once the user enters this information, the data is sent to the server and recorded in MongoDB via the REST API of the Django framework.

[0509] Data analysis and plan generation

[0510] The server aggregates and organizes the collected data. Using Python, a cron job is run periodically to aggregate all the data stored in the database. Pandas and Numpy are used to analyze the data and identify user behavior patterns and trends. The OpenWeatherMap API is also used to obtain external weather data and compare it with this data.

[0511] The server generates a diet plan using the AI ​​model. Using TensorFlow and PyTorch, it inputs the user's behavioral patterns and mood data to generate an optimal exercise and meal plan. The generated plan is saved in JSON format and sent to the device.

[0512] proposal notification

[0513] The server sends the generated diet plan to the device. The device receives this data and displays a notification to the user. By implementing push notifications using React Native, the notification includes today's exercise menu and cooking recipes.

[0514] For example, if a user one day inputs "It's raining today, so I don't want to go outside," the server analyzes weather data and the user's behavioral patterns, and confirms from the weather API that today's weather is rainy. The server then suggests "yoga and stretches that can be done indoors," and the device notifies the user of this suggestion. The server also displays a recipe for "vegetable soup" based on the ingredients data in the user's refrigerator.

[0515] An example prompt is:

[0516] "I want to suggest today's exercise menu based on the user's current emotional state and weather data. The user has entered, 'It's raining today, so I don't want to go outside,' and there are tomatoes, cabbage, and carrots in the refrigerator. Given these conditions, what would be the optimal exercise menu and cooking recipe?"

[0517] This system can propose individual diet plans based on the user's behavioral patterns and moods, as well as economical meal menus, supporting users to continue their diet without straining themselves.

[0518] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0519] Step 1:

[0520] Entering Basic User Attributes

[0521] The terminal prompts the user to enter basic attributes such as age, sex, height, weight, and medical history. The user enters this information into the form and clicks the submit button. The entered data is sent from the terminal to the server in JSON format. Terminal input: Basic user attribute information Server output: JSON format data.

[0522] Step 2:

[0523] Entering user behavior-related information

[0524] The device prompts the user to enter activity-related information such as residence and workplace. The user enters this information and presses the submit button. The entered data is sent to the server in JSON format. Device input: User's residence and workplace information Server output: JSON format data.

[0525] Step 3:

[0526] Entering the target value

[0527] The terminal prompts the user to enter target values ​​such as target weight and target body fat percentage. The user enters this information and presses the submit button. The entered data is sent to the server in JSON format. Terminal input: User's target value Server output: JSON format data.

[0528] Step 4:

[0529] Data storage and user profile creation

[0530] The server saves all the data received in the previous steps in a database and creates a user profile. MySQL is used to save the user's basic attributes, behavior-related information, and goal values. Server input: User's basic attributes, behavior-related information, goal values ​​Server output: User profile created in the database.

[0531] Step 5:

[0532] Behavioral pattern tracking

[0533] The device collects the user's GPS data, movement history, and exercise data (number of steps, calories burned, etc.) in real time. The collected data is sent to the server at regular intervals. Device input: Exercise data collected in real time Server output: Data in JSON format.

[0534] Step 6:

[0535] Matching tracking data with external data

[0536] The server compares the received tracking data with external data such as the day of the week and weather. External data is obtained from sources such as the OpenWeatherMap API. Server input: Tracking data, day of the week, weather data. Server output: Matched data.

[0537] Step 7:

[0538] Input your mood and schedule

[0539] The device prompts the user to input their mood and schedule for the day. The data entered by the user is sent to the server and stored in MongoDB. Device input: User's mood, schedule Server output: Data in JSON format.

[0540] Step 8:

[0541] Data analysis

[0542] The server aggregates and analyzes all collected data. It uses Pandas and Numpy to analyze the data and understand behavioral patterns and moods of the day. Server input: All collected data. Server output: Analysis results.

[0543] Step 9:

[0544] Generate a diet plan

[0545] The server generates a diet plan using a generative AI model based on the analysis results. It uses TensorFlow and PyTorch to create the optimal exercise and meal plan for the user. Server input: Analysis results. Server output: Generated diet plan.

[0546] Step 10:

[0547] Diet plan notifications

[0548] The server sends the generated diet plan to the user's device. The device notifies the user of the received plan and suggests specific actions and cooking recipes. Specifically, a push notification is displayed using React Native. Server input: Generated diet plan Device output: Push notification.

[0549] As a specific example, if a user inputs "It's raining today and I don't want to go outside," the server will analyze weather data and the user's behavioral patterns to suggest yoga and stretching exercises that can be done indoors. The device will also display a recipe for a vegetable soup based on the ingredients in the user's refrigerator. An example of a prompt for the production version could be, "I would like to suggest today's exercise menu based on the user's current emotional state and weather data. The user inputs "It's raining today and I don't want to go outside," and there are tomatoes, cabbage, and carrots in the refrigerator. Please tell me the optimal exercise menu and cooking recipe based on these conditions."

[0550] (Application example 1)

[0551] 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."

[0552] In today's busy lifestyles, individual users need individually customized suggestions and support to maintain a healthy and economical diet. However, conventional diet systems have difficulty providing specific advice based on the user's mood and schedule that day, as well as real-time location information. In particular, brick-and-mortar stores require users to instantly receive appropriate diet information within the store. Therefore, there is a need for an effective diet motivator that reflects the user's individual circumstances in real time and can be utilized in brick-and-mortar stores.

[0553] 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.

[0554] In this invention, the server includes a means for inputting basic attributes of a user, a means for inputting behavior-related information such as place of residence and place of work, and a means for inputting target values. This makes it possible to provide appropriate diet information in real time through a display device worn by a user in a physical store. This allows users to receive personalized diet advice in real time within the store, allowing them to diet more effectively.

[0555] The "means for inputting basic user attributes" is a part of the system for inputting basic personal information such as the user's age, sex, height, and weight.

[0556] The "means for inputting behavior-related information" refers to a means for inputting information related to the user's behavior, such as the user's place of residence, place of work, and travel route.

[0557] The "means for inputting target values" is a means for inputting target values ​​for dieting, such as the user's target weight and target body fat percentage.

[0558] The "means for transmitting the input information" is a means for transmitting the basic attributes, behavior-related information, target values, etc. input by the user to the server.

[0559] The "means for storing in a database and creating a user profile" is the part of the system for storing the transmitted information in a database and creating an individual profile for the user based thereon.

[0560] The "means for tracking user behavior patterns" refers to a means for collecting user movement history and exercise data in real time and tracking the user's behavior patterns.

[0561] "Means for comparing with external data" refers to means for comparing collected data with external data such as the day of the week and weather, and analyzing the data.

[0562] The "means for analyzing data" is a means for analyzing the collated data and generating an optimal diet plan for the user.

[0563] The "means for inputting the mood and schedule of the day" is a means for the user to input the mood and schedule of the day.

[0564] The "means for transmitting all collected data to the server" refers to a means for transmitting all collected data to the server.

[0565] The "means for generating a diet plan" is a means for generating a diet plan suitable for the user based on the data received by the server.

[0566] The "means for proposing the generated diet plan to the user" is a means for presenting the generated diet plan to the user.

[0567] "Means for providing appropriate diet information in real time through a display device" refers to means for providing optimal diet information in real time through a display device worn by a user in a physical store.

[0568] This invention is a system that provides users with an optimal diet plan based on their basic attributes, behavior-related information, target values, etc. This system is composed of a server, a terminal, and a display device that the user wears in a physical store.

[0569] User Registration

[0570] When the terminal starts up the system for the first time, the user enters basic attributes such as name, age, sex, height, weight, and medical conditions. Next, the user enters their place of residence and place of work, as well as their target values ​​such as target weight and target body fat percentage. This information is sent from the terminal to the server and stored in a database to create a user profile.

[0571] Information gathering

[0572] The device collects real-time GPS data, movement history, and exercise data (step count, calories burned, etc.) to track the user's behavioral patterns. This data is then compared with external data such as weather data and the day of the week. The device also allows the user to input their mood, schedule, and planned exercise intensity for the day.

[0573] Plan Generation

[0574] Based on the collected and analyzed data, the server generates a diet plan suited to the user's behavioral patterns and mood for that day. The plan considers the balance of exercise, meals, and rest and is presented to the device as a specific action plan.

[0575] Application in physical stores

[0576] When users visit physical stores, especially supermarkets and fitness gyms, they can wear a head-mounted display to receive real-time diet information. For example, product information and recipes are displayed in supermarkets, and exercise methods are displayed in fitness gyms.

[0577] Hardware and software used

[0578] Hardware: Head-mounted display, GPS module

[0579] Software: Python program, GPS module library, RESTful API

[0580] Specific examples

[0581] If it's raining that day and the user types "I don't want to go outside today," the server will analyze the weather data and the user's behavioral patterns to suggest yoga and stretching exercises that can be done indoors. It will also display a recipe for a healthy "vegetable soup" based on the ingredients in the user's refrigerator.

[0582] Prompt Sentence Examples

[0583] Below are some examples of prompt sentences.

[0584] User Attribute Information:

[0585] Age: 28

[0586] Gender: Female

[0587] Height: 160 cm

[0588] Weight: 55 kg

[0589] Residence: Tokyo

[0590] Location: Shibuya

[0591] Target weight: 50 kg

[0592] Target body fat percentage: 20%

[0593] Current time: 2023-10-01T14:30:00

[0594] Current location: Latitude 35.6895, Longitude 139.6917

[0595] Use this information to generate the best diet plan for you.

[0596] In this way, the present invention supports the continuation of a healthy and economical diet by proposing a diet plan that matches the user's specific lifestyle and mood.

[0597] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0598] Step 1:

[0599] User enters basic attributes

[0600] The user uses a terminal to input basic attributes such as name, age, sex, height, weight, and medical conditions. The input information is sent to the server by the terminal. Input information: Name, age, sex, height, weight, medical conditions. Output information: Creates a user profile on the server.

[0601] Step 2:

[0602] The user inputs the behavior-related information and the goal value.

[0603] The user uses the terminal to input behavior-related information and goal values, such as place of residence, place of work, target weight, and target body fat percentage. This information is also sent from the terminal to the server and stored in the database. Input content: place of residence, place of work, target weight, target body fat percentage. Output content: user profile updated on the server.

[0604] Step 3:

[0605] Tracking user behavior patterns

[0606] The device collects GPS data, movement history, and exercise data (number of steps, calories burned, etc.) in real time. The collected data is periodically sent to the server. Input: GPS data, movement history, exercise data. Output: Behavioral pattern records on the server.

[0607] Step 4:

[0608] Compare with external data and analyze

[0609] The server compares the tracked data with external data such as the day of the week and weather, and analyzes the data. Input: Tracking data, day of the week, weather data. Output: Analysis results (behavioral pattern trends).

[0610] Step 5:

[0611] The user inputs their mood and schedule

[0612] The user uses the device to input the mood, planned exercise intensity, and schedule for the day. The input information is sent to the server. Input information: mood, planned exercise intensity, schedule. Output information: record of mood and schedule on the server.

[0613] Step 6:

[0614] Generate a diet plan

[0615] The server generates a diet plan suited to the user based on all the data received. Specifically, this includes the type of exercise and meal menu. Input: Basic attributes, behavioral patterns, mood and schedule. Output: Diet plan.

[0616] Step 7:

[0617] Suggest diet plans to users

[0618] The device notifies the user of the generated diet plan. In a physical store, the plan is displayed in real time on the head-mounted display worn by the user. Input: Diet plan. Output: The plan displayed on the user's head-mounted display.

[0619] Step 8:

[0620] Providing appropriate diet information in real time

[0621] When a user wears a head-mounted display in a physical store such as a supermarket or fitness gym, real-time diet information about products in the store and exercise methods is displayed. Input content: Location information and product information in the store. Output content: Diet information displayed on the head-mounted display.

[0622] 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.

[0623] This invention relates to a "diet motivator" that provides an optimal diet plan tailored to the user's lifestyle and mood on that day, and in particular, is a system that provides a more sophisticated and personalized diet plan by combining it with an emotion engine that recognizes the user's emotions.

[0624] 1. First-time user registration

[0625] When the server starts the system for the first time, the terminal prompts the user to enter basic attributes (age, sex, build, health information, etc.). The user enters age, sex, height, weight, medical history, etc. Next, the terminal prompts the user to enter their place of residence and place of work, and the user enters this information. Furthermore, the terminal prompts the user to enter target values ​​such as target weight and target body fat percentage, and the user enters the target values.

[0626] The terminal sends this input information to the server, and the server stores the received data in a database to create a user profile.

[0627] 2. Information gathering

[0628] To track a user's behavioral patterns, the device collects the user's GPS data, movement history, and exercise data (e.g., number of steps, calories burned) in real time. This data is periodically sent to a server, which then compares the received data with external data such as the day of the week and weather, and analyzes the user's behavioral patterns.

[0629] The device also prompts the user to input their mood, schedule, and planned exercise intensity for the day, allowing the user to input their emotional state (e.g., fatigue, motivation), schedule, and exercise plan for the day. The emotion engine recognizes the user's emotions in real time and sends the data to the server.

[0630] 3. Emotion Engine

[0631] The emotion engine analyzes the user's facial expressions, tone of voice, text input, etc. to recognize the user's emotions. Emotional data is analyzed in combination with the user's behavioral patterns and mood input for the day. For example, if the emotion engine recognizes that the user is tired, that data is sent to the server.

[0632] 4. Proposal

[0633] Based on the data collected and analyzed so far, the server generates a diet plan suited to the user's behavioral patterns, mood of the day, and emotional data. The generated plan creates a specific action plan that takes into account the balance of exercise, meals, and rest, and sends it to the device as suggested data. Specifically, it can suggest exercise menus that match the user's mood and emotions of the day, as well as healthy and economical cooking menus.

[0634] Specific examples

[0635] If a user inputs "I feel tired today" one day and the emotion engine recognizes the tiredness from the user's facial expression, the server will use that data to suggest "light stretching and relaxation exercises." The device will also display a recipe for "chicken and vegetable stew," which is effective in relieving fatigue, based on ingredients in the user's refrigerator. In this way, users can continue their diet without straining themselves in their daily lives.

[0636] This system supports users in continuing a healthy and enjoyable diet through a consistent process from data collection to recommendations. In addition, by combining it with an emotion engine, it provides specific advice based on the user's emotions, helping them achieve their goals without any stress.

[0637] The processing flow will be explained below.

[0638] 1. First-time user registration

[0639] Step 1:

[0640] The device prompts the user to enter basic attributes (age, gender, build, health information, etc.).

[0641] Step 2:

[0642] The user inputs the age, sex, height, weight, medical history, etc. in order.

[0643] Step 3:

[0644] The terminal prompts the user to enter their place of residence and place of work.

[0645] Step 4:

[0646] The user enters their place of residence and place of work.

[0647] Step 5:

[0648] The terminal prompts the user to input target values ​​(target weight, target body fat percentage, etc.).

[0649] Step 6:

[0650] The user inputs a target value.

[0651] Step 7:

[0652] The terminal sends all entered information to the server.

[0653] Step 8:

[0654] The server stores the received data in a database and creates a user profile.

[0655] 2. Information gathering

[0656] Step 1:

[0657] The device collects the user's GPS data, movement history, and exercise data (e.g., number of steps taken, calories burned).

[0658] Step 2:

[0659] The terminal periodically transmits the collected data to the server.

[0660] Step 3:

[0661] The server compares the received data with external data such as the day of the week and weather.

[0662] Step 4:

[0663] The server analyzes the matched data and stores it in a statistical database.

[0664] Step 5:

[0665] The device prompts the user to input their mood, schedule, and exercise plans for the day.

[0666] Step 6:

[0667] The user inputs their emotional state (e.g., fatigue, motivation), their schedule for the day, and their exercise plan.

[0668] Step 7:

[0669] The emotion engine analyzes the user's facial expressions, tone of voice, text input, etc. to recognize emotions.

[0670] Step 8:

[0671] The data collected by the device, user input data, and emotion data recognized by the emotion engine are sent to the server.

[0672] Step 9:

[0673] The server analyzes the received data and models each user's behavioral patterns and tendencies.

[0674] 3. Proposal

[0675] Step 1:

[0676] Based on the data accumulated by the server, a diet plan is generated that is suited to the user's behavioral patterns, mood of the day, and emotional data.

[0677] Step 2:

[0678] The server creates a specific action plan, taking into account the balance of exercise, diet, and rest.

[0679] Step 3:

[0680] The server creates specific advice and suggestions (e.g., today's exercise menu, meal recipes) aimed at the user's goals.

[0681] Step 4:

[0682] The server transmits the created proposal data to the terminal.

[0683] Step 5:

[0684] The device displays healthy and economical lifestyle schedules and cooking menus to the user.

[0685] Step 6:

[0686] The user follows the proposed plan and carries out daily activities.

[0687] Examples:

[0688] One day, if a user types "I feel tired today," and the emotion engine recognizes the user's tiredness from their facial expression, the device will send that data to the server. Based on that data, the server will suggest "light stretching and relaxation exercises." The device will also display a recipe for "chicken and vegetable stew," which is effective in relieving fatigue, based on ingredients in the user's refrigerator. In this way, users can continue their diet without straining themselves in their daily lives.

[0689] Example 2

[0690] 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."

[0691] While conventional diet support systems propose diet plans based on the user's basic attributes and behavioral data, they lack the ability to consider the user's emotional state or mood on that day. This can lead to problems such as users not receiving appropriate support on days when they are tired or unmotivated, making it difficult to continue their diet. Furthermore, because detailed planning tailored to individual users is not possible, general proposals are less effective for some users.

[0692] 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.

[0693] In this invention, the server includes means for inputting a user's basic attributes, means for inputting behavior-related information such as place of residence and place of work, means for inputting target values, means for transmitting the input information, means for saving the transmitted information in a database and creating a user profile, means for tracking the user's behavioral patterns, means for comparing the tracked data with external data such as the day of the week and weather, means for analyzing the compared data, means for prompting the user to input their mood and schedule for the day, an emotion engine for analyzing the user's emotional state, means for transmitting all the collected data and emotion data to the server, means for the server to analyze the received data and generate a diet plan suitable for the user, and means for proposing the generated diet plan to the user. This makes it possible to provide a more personalized and specific diet plan based on the user's emotional state and mood for the day.

[0694] "Basic attributes" refers to basic information about an individual, such as the user's age, sex, height, weight, medical history, etc.

[0695] "Behavior-related information" is information about the user's place of residence, place of work, and behavioral patterns related thereto.

[0696] "Goal value" refers to a specific health goal such as weight or body fat percentage that a user aims to achieve.

[0697] A "user profile" is an individual information set in a database that is created based on input information such as a user's basic attributes, behavior-related information, and goal values.

[0698] A "behavioral pattern" is a series of behavioral trends over a specific period of time, analyzed based on a user's GPS data, movement history, exercise data, etc.

[0699] "External data" is information about the external environment that affects the user's behavior, such as the day of the week and weather.

[0700] An "emotion engine" is a system that has the function of analyzing a user's facial expressions, tone of voice, text input, etc. to recognize their emotional state.

[0701] A "diet plan" is a specific action plan for exercise, meals, rest, etc. that is generated based on the user's behavioral patterns, basic attributes, target values, and emotional state.

[0702] This invention relates to a "diet motivator" that provides an optimal diet plan tailored to the user's lifestyle and mood on that day. In particular, this system provides a more refined and personalized diet plan by combining it with an emotion engine that recognizes the user's emotions.

[0703] The system of the present invention relies primarily on two hardware components: a server and a terminal.

[0704] 1. First-time user registration

[0705] When the terminal starts the system for the first time, it displays a screen prompting the user to enter basic attributes (age, sex, build, health information, etc.). The user enters information such as age, sex, height, weight, and medical history. The terminal then prompts the user to enter their place of residence and place of work, and the user enters that information. The terminal then prompts the user to enter target values ​​such as target weight and target body fat percentage, and the user enters those target values.

[0706] The device sends this input information to the server, which stores the received data in a database and creates a user profile.

[0707] 2. Information gathering

[0708] To track a user's behavioral patterns, the device collects the user's GPS data, movement history, and exercise data (e.g., number of steps, calories burned) in real time. This data is periodically sent to a server, which then compares the received data with external data such as the day of the week and weather, and analyzes the user's behavioral patterns.

[0709] The device also displays a screen prompting the user to input their mood, schedule, and planned exercise intensity for the day. The user can input their emotional state (e.g., fatigue, motivation), schedule, and exercise plan for the day. The emotion engine analyzes the user's facial expression, tone of voice, and text input to recognize their emotional state. The device sends the output of the emotion engine to the server.

[0710] 3. Proposal

[0711] Based on the data collected and analyzed so far, the server generates a diet plan suited to the user's behavioral patterns, mood of the day, and emotional data. The generated plan takes into account the balance of exercise, meals, and rest, and sends the proposed data to the device as a specific action plan. Specifically, it can suggest an exercise menu that matches the user's mood and emotions of the day, as well as a healthy and economical cooking menu.

[0712] Specific examples

[0713] For example, if a user inputs "I feel tired today" one day and the emotion engine recognizes the feeling of fatigue from the user's facial expression, the server will use that data to suggest "light stretching and relaxation exercises." The device will also display a recipe for "chicken and vegetable stew," which is effective in relieving fatigue, based on ingredients in the user's refrigerator. This allows users to continue their diet without straining themselves in their daily lives.

[0714] Prompt Sentence Examples

[0715] "The user enters 'I'm tired today,' and the emotion engine recognizes this state of fatigue. Based on this data, please suggest appropriate exercise and meal plans."

[0716] By inputting such prompt sentences into the generative AI model, the accuracy of the model can be confirmed and the quality of the system can be improved.

[0717] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0718] Step 1: First-time user registration

[0719] Input: User's basic attribute information (age, gender, height, weight, medical history, etc.)

[0720] Specific operation When the terminal starts the system for the first time, it displays a screen prompting the user to enter basic attributes. The user enters the information. The terminal temporarily stores this information.

[0721] Output: Basic attribute information is saved to the device.

[0722] Step 2: Enter your place of residence and work

[0723] Input: User's residence and work location information

[0724] Specific operation: The terminal displays a screen prompting the user to enter residence and workplace information. The user enters the information. The terminal temporarily stores this information.

[0725] Output: Residence and work location information is saved on the device

[0726] Step 3: Enter the target value

[0727] Input: User's goal values ​​such as goal weight and goal body fat percentage

[0728] Specific operation: The device displays a screen prompting the user to input the target value. The user inputs the target value. The device temporarily stores this information.

[0729] Output: The target value is saved to the terminal.

[0730] Step 4: Data submission and user profile creation

[0731] Input: Basic attribute information, residence and workplace information, target value

[0732] Specific operation: The device sends all input information to the server, which stores the received data in a database and creates a user profile.

[0733] Output: The user profile is saved in the database.

[0734] Step 5: Collecting and Sending Dynamic Data

[0735] Input: User's GPS data, movement history, exercise data (number of steps, calories burned, etc.)

[0736] Specific operation: The device uses sensors to collect the user's GPS data, movement history, and exercise data in real time, and transmits the collected data to a server at regular intervals.

[0737] Output: Collected data is sent to a server and stored for analysis.

[0738] Step 6: Analyze behavioral patterns

[0739] Input: Collected dynamic data, external data (day of the week, weather)

[0740] Specific operation: The server compares the collected dynamic data with external data such as the day of the week and weather, and analyzes behavioral patterns.

[0741] Output: Behavioral pattern analysis data

[0742] Step 7: Enter your mood and schedule

[0743] Input: User's mood, schedule for the day, planned exercise intensity

[0744] Specific operation: The device displays a screen prompting the user to input their mood, schedule, and planned exercise intensity. The user inputs this information. The device temporarily stores this information.

[0745] Output: Mood and schedule information is saved on the device

[0746] Step 8: Emotion Analysis with the Emotion Engine

[0747] Input: User facial expression data, tone of voice, text input

[0748] How it works: The emotion engine analyzes the user's facial expressions, tone of voice, and text input to recognize their emotional state, and the device sends the output to the server.

[0749] Output: Emotional state data is sent to the server

[0750] Step 9: Analyze the data and generate a diet plan

[0751] Input: behavioral pattern analysis data, mood and schedule information, emotional state data

[0752] Specific operation: Based on the data collected and analyzed up to now, the server generates a diet plan suited to the user's behavioral patterns, mood of the day, and emotional data.

[0753] Output: The generated diet plan

[0754] Step 10: Inform your diet plan

[0755] Input: Generated diet plan

[0756] Specific operations: The server sends the generated diet plan to the terminal, and the terminal notifies the user of the plan.

[0757] Output: The diet plan notified to the user

[0758] (Application example 2)

[0759] 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."

[0760] Conventional diet plan suggestion systems often make uniform suggestions without considering the user's emotions or mood of the day. This makes it difficult to provide appropriate suggestions that match the user's mental state or daily lifestyle, making it difficult to motivate them to continue dieting. Furthermore, to actually prepare the suggested meal menu, the user must procure ingredients and cook the food themselves, which is time-consuming and labor-intensive.

[0761] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for inputting a user's basic attributes; means for inputting behavior-related information such as a residence and workplace; means for inputting a target value; means for transmitting the input information; means for saving the transmitted information in a database and creating a user profile; means for tracking the user's behavioral patterns; means for comparing the tracked data with external data such as the day of the week and the weather; means for analyzing the compared data; means for prompting the user to input their mood and schedule for the day; means for transmitting all collected data to the server; means for the server to analyze the received data and generate a diet plan suitable for the user; means for proposing the generated diet plan to the user; means including an emotion engine for collecting and analyzing the user's emotional data; means for proposing a meal menu suitable for the user based on the emotional data; and means for providing the meal menu to the user via a food delivery system. This makes it possible to provide a personalized diet plan based on the user's emotions and mood for the day, and the suggested meal menu can be easily ordered, making it easier to continue dieting.

[0762] "Basic attributes of a user" refers to personal information such as the user's age, sex, build, and health information.

[0763] "Behavioral information" refers to information about a user's behavior, including their place of residence, place of work, and daily movements.

[0764] "Target value" refers to a specific numerical target such as weight or body fat percentage that the user aims to achieve.

[0765] "User profile" refers to a comprehensive database entry that includes a user's basic attributes, behavior-related information, goals, etc.

[0766] "Behavioral patterns" refer to specific behavioral tendencies and habits in a user's daily life.

[0767] "External data" refers to relevant information other than the user's own behavior, such as the day of the week and weather.

[0768] "Emotion engine" refers to a function that recognizes a user's emotions by analyzing their facial expressions, tone of voice, and text input.

[0769] A "diet plan" refers to a specific action plan proposed to a user that takes into account a balance of exercise, diet, rest, and other factors.

[0770] "Meal menu" refers to specific meal items suggested based on the user's emotions, mood, and health status.

[0771] A "food delivery system" refers to an online service that allows users to easily order suggested meal menus.

[0772] This invention builds a system that proposes optimal diet plans and meal menus based on the user's emotions and mood of the day, and then actually provides them through a food delivery service. This system is realized by using the following programs, hardware, and software.

[0773] The server includes a means for inputting basic user attributes, a means for inputting behavior-related information such as place of residence and place of work, a means for inputting target values, a means for transmitting the input information, and a means for storing the transmitted information in a database and creating a user profile, thereby enabling centralized management of basic user information.

[0774] The server also includes a means for tracking the user's behavioral patterns, a means for comparing the tracked data with external data such as the day of the week and weather, and a means for analyzing the compared data, thereby collecting and analyzing detailed data about the user's daily life.

[0775] Furthermore, the server includes a means for allowing the user to input the mood and schedule of the day, a means for transmitting all the collected data to the server, a means for the server to analyze the received data and generate a diet plan suitable for the user, and a means for proposing the generated diet plan to the user, thereby enabling personalized suggestions to be made to each individual user.

[0776] The server further includes means for including an emotion engine that collects and analyzes emotion data of the user, means for suggesting a meal menu suitable for the user based on the emotion data, and means for providing the meal menu to the user via a food delivery system, so that the user can easily order the suggested meal menu and actually receive the meal through the food delivery service.

[0777] For example, if a user inputs "I'm tired today," and the emotion engine recognizes the same, the server will suggest light meal options such as "chicken soup" or "vegetable salad." Users can easily check these options within the app and request delivery by simply pressing the order button.

[0778] An example of a prompt to input to a generative AI model is as follows:

[0779] "Please suggest a healthy menu when the user feels tired. User information: age, gender, physique, health information, goal value. Emotion: fatigue."

[0780] The hardware used includes a cloud server, and the software includes Flask (Python) and a database (e.g., SQLite or PostgreSQL).

[0781] In this way, personalized diet plans and meal menus that reflect the user's emotions and mood of the day can be proposed and actually provided through a food delivery system, which will encourage users to continue their diet and improve the quality of their daily lives.

[0782] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0783] Step 1:

[0784] When the server starts the system for the first time, the terminal prompts the user to enter basic attributes (age, gender, build, health information, etc.). The user enters this information into the terminal, and the terminal sends the received information to the server. The server stores the received data in a database and creates a user profile.

[0785] Step 2:

[0786] The device prompts the user to enter activity-related information such as their place of residence and place of work. The user enters this information into the device, which then transmits the information to the server. The server stores the received data in a database and updates the user profile.

[0787] Step 3:

[0788] The device prompts the user to input goals (e.g., target weight or target body fat percentage). The user inputs the goals, and the device sends the input data to the server. The server stores the received goal data in a database and integrates it into the user profile.

[0789] Step 4:

[0790] The device collects GPS data, movement history, and exercise data (e.g., number of steps, calories burned) in real time to track the user's behavior. This data is periodically sent to a server, which stores the received data in a database.

[0791] Step 5:

[0792] The server compares the tracked data with external data such as the day of the week and weather, and analyzes the matched data. This allows the user's behavioral patterns to be understood. The analysis results are stored in a database.

[0793] Step 6:

[0794] The device provides an interface for the user to input the user's mood and schedule for the day. The user inputs the information, and the device sends it to the server. The server analyzes the received data and integrates it into the user profile.

[0795] Step 7:

[0796] The server uses an emotion engine to recognize the user's emotions in real time from facial expressions, tone of voice, and text input, and the emotion data is stored in a database.

[0797] Step 8:

[0798] The server uses a generative AI model based on the data collected and analyzed to generate a diet plan suited to the user. This calculation uses prompt statements and inputs the user's emotions and behavioral data. The generated diet plan is saved in a database as a specific action plan.

[0799] Step 9:

[0800] The server transmits the generated diet plan to the user's terminal as proposal data, and the terminal displays the received proposal data to the user, allowing the user to confirm the plan.

[0801] Step 10:

[0802] The server proposes a meal menu suitable for the user based on the user's emotional data. This meal menu is provided to the user via the food delivery system and is generated using an emotion engine and a generative AI model. The user can check the proposed menu through their device and easily order.

[0803] 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.

[0804] 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.

[0805] 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.

[0806] [Third embodiment]

[0807] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0808] 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.

[0809] 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).

[0810] 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.

[0811] 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.

[0812] 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).

[0813] 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.

[0814] 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.

[0815] 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.

[0816] 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.

[0817] 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.

[0818] 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."

[0819] This invention relates to a "diet motivator" that provides the user with an optimal diet plan tailored to their lifestyle and mood on that day. Specifically, it is a system that takes into account the user's basic attributes and behavioral patterns to help them continue their diet economically and healthily.

[0820] 1. First-time user registration

[0821] When the server starts the system for the first time, the terminal prompts the user to enter basic attributes (age, sex, build, health information, etc.). The user enters age, sex, height, weight, medical history, etc. Next, the terminal prompts the user to enter their place of residence and place of work, and the user enters this information. Furthermore, the terminal prompts the user to enter target values ​​such as target weight and target body fat percentage, and the user enters the target values.

[0822] The terminal sends this input information to the server, and the server stores the received data in a database to create a user profile.

[0823] 2. Information gathering

[0824] To track a user's behavioral patterns, the device collects the user's GPS data, movement history, and exercise data (e.g., number of steps, calories burned) in real time. This data is periodically sent to a server, which then compares the received data with external data such as the day of the week and weather, and analyzes the user's behavioral patterns.

[0825] The terminal also prompts the user to input their mood and schedule for the day, as well as their planned exercise intensity, allowing the user to input their emotional state (e.g., fatigue, motivation), schedule for the day, and exercise plan.

[0826] 3. Proposal

[0827] The server generates a diet plan based on the data collected and analyzed to date, tailored to the user's behavioral patterns and daily mood. The plan creates a specific action plan that takes into account the balance of exercise, meals, and rest, and sends it to the device as suggested data. Specifically, it can suggest an exercise menu that suits the user's mood that day, as well as healthy and economical meal menus.

[0828] Specific examples

[0829] If a user inputs "It's raining today, so I don't want to go outside," the server will analyze the weather data and the user's behavioral patterns and suggest "yoga and stretching exercises that can be done indoors." The device will also display a recipe for a low-calorie yet nutritious "vegetable soup" based on ingredients in the user's refrigerator. In this way, users can continue their diet without any stress in their daily lives.

[0830] The system supports users in continuing a healthy and enjoyable diet through a consistent process from data collection to recommendations. It also helps users achieve their goals without straining themselves by providing specific advice that fits into their lifestyle while minimizing financial burden.

[0831] The processing flow will be explained below.

[0832] 1. First-time user registration

[0833] Step 1:

[0834] The device prompts the user to enter basic attributes (age, gender, build, health information, etc.).

[0835] Step 2:

[0836] The user inputs the age, sex, height, weight, medical history, etc. in order.

[0837] Step 3:

[0838] The terminal prompts the user to enter their place of residence and place of work.

[0839] Step 4:

[0840] The user enters their place of residence and place of work.

[0841] Step 5:

[0842] The terminal prompts the user to input target values ​​(target weight, target body fat percentage, etc.).

[0843] Step 6:

[0844] The user inputs a target value.

[0845] Step 7:

[0846] The terminal sends all entered information to the server.

[0847] Step 8:

[0848] The server stores the received data in a database and creates a user profile.

[0849] 2. Information gathering

[0850] Step 1:

[0851] The device collects the user's GPS data, movement history, and exercise data (e.g., number of steps taken, calories burned).

[0852] Step 2:

[0853] The terminal periodically transmits the collected data to the server.

[0854] Step 3:

[0855] The server compares the received data with external data such as the day of the week and weather.

[0856] Step 4:

[0857] The server analyzes the matched data and stores it in a statistical database.

[0858] Step 5:

[0859] The device prompts the user to input their mood, schedule, and exercise plans for the day.

[0860] Step 6:

[0861] The user inputs their emotional state (e.g., fatigue, motivation), their schedule for the day, and their exercise plan.

[0862] Step 7:

[0863] The terminal transmits the collected data and the user input data to the server.

[0864] Step 8:

[0865] The server analyzes the received data and models each user's behavioral patterns and tendencies.

[0866] 3. Proposal

[0867] Step 1:

[0868] Based on the data accumulated by the server, a diet plan is generated that is suited to the user's behavioral patterns and mood of the day.

[0869] Step 2:

[0870] The server creates a specific action plan, taking into account the balance of exercise, diet, and rest.

[0871] Step 3:

[0872] The server creates specific advice and suggestions (e.g., today's exercise menu, meal recipes) aimed at the user's goals.

[0873] Step 4:

[0874] The server transmits the created proposal data to the terminal.

[0875] Step 5:

[0876] The device displays healthy and economical lifestyle schedules and cooking menus to the user.

[0877] Step 6:

[0878] The user follows the proposed plan and carries out daily activities.

[0879] Example 1

[0880] 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."

[0881] Conventional diet support systems have difficulty providing individualized diet plans based on the user's lifestyle and mood. Furthermore, they are unable to efficiently analyze regularly collected data and provide feedback to users, making it difficult for them to continue dieting. Furthermore, they are inadequate in proposing economical and feasible meal plans.

[0882] 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.

[0883] In this invention, the server includes means for inputting a user's basic attributes, means for inputting behavior-related information such as place of residence and place of work, means for inputting target values, means for transmitting the input information, means for saving the transmitted information in a database and creating a user profile, means for tracking the user's behavioral patterns, means for comparing the tracked data with external data such as the day of the week and weather, means for analyzing the compared data, means for prompting the user to input their mood and schedule for the day, means for transmitting all the collected data to the server, means for the server to analyze the received data and generate a diet plan suitable for the user using a generative AI model, and means for generating prompts to suggest the generated diet plan to the user and displaying them on the user's terminal. This enables the server to propose an individual diet plan tailored to the user's lifestyle and mood, as well as economical meal menus, making it easier to continue dieting.

[0884] "Basic attributes" refers to information specific to an individual, such as the user's age, sex, height, weight, medical history, etc.

[0885] "Behavioral Information" refers to a user's place of residence and place of work, and related geographical and temporal information.

[0886] "Target value" refers to a specific numerical value that the user wishes to achieve, such as a target weight or body fat percentage.

[0887] A "user profile" refers to an individual information set that includes a user's basic attributes, behavior-related information, goal values, and the like.

[0888] "Behavioral patterns" refer to a user's daily movement history, exercise data, and related temporal and spatial trends.

[0889] "Tracking" refers to the collection and recording of user behavior and exercise data in real time.

[0890] "External data" refers to external information that influences a user's behavior and mood, such as the day of the week or the weather.

[0891] "Generative AI model" refers to an artificial intelligence model used to analyze user data and generate an optimal diet plan.

[0892] A "prompt sentence" refers to a guide message generated to prompt the user to take a specific action or make a choice.

[0893] A "diet plan" refers to specific guidelines for exercise and diet provided based on the user's basic attributes and behavioral patterns.

[0894] This invention relates to a "diet motivator" that provides an optimal diet plan according to the user's lifestyle and mood of the day. Specifically, it is a system that takes into account the user's basic attributes and behavior-related information to help them continue dieting economically and healthily.

[0895] First-time user registration

[0896] The terminal prompts the user to enter basic attributes. For this, a form is created using a front-end framework such as React or Vue.js, and the user is asked to enter information such as age, gender, height, weight, medical conditions, etc. When the user enters the information and presses the submit button, the entered information is sent to the server in JSON format.

[0897] The server saves the received data in a database and creates a user profile. Specifically, it receives POST requests using the Python Flask framework, converts them into a data frame using Pandas, and saves them in a MySQL database. Once the data is saved, the server returns a "Registration Complete" message to the terminal.

[0898] Information gathering

[0899] The device collects the user's GPS data, movement history, and exercise data in real time. Using external services such as the Google Fit API and Apple HealthKit, the device periodically collects data and stores it in a buffer. This data is then periodically (e.g., every hour) sent to a server.

[0900] The user inputs their mood and schedule for the day. The device prompts the user to input their mood, schedule, and exercise intensity for the day through a pop-up screen. Once the user enters this information, the data is sent to the server and recorded in MongoDB via the REST API of the Django framework.

[0901] Data analysis and plan generation

[0902] The server aggregates and organizes the collected data. Using Python, a cron job is run periodically to aggregate all the data stored in the database. Pandas and Numpy are used to analyze the data and identify user behavior patterns and trends. The OpenWeatherMap API is also used to obtain external weather data and compare it with this data.

[0903] The server generates a diet plan using the AI ​​model. Using TensorFlow and PyTorch, it inputs the user's behavioral patterns and mood data to generate an optimal exercise and meal plan. The generated plan is saved in JSON format and sent to the device.

[0904] proposal notification

[0905] The server sends the generated diet plan to the device. The device receives this data and displays a notification to the user. By implementing push notifications using React Native, the notification includes today's exercise menu and cooking recipes.

[0906] For example, if a user one day inputs "It's raining today, so I don't want to go outside," the server analyzes weather data and the user's behavioral patterns, and confirms from the weather API that today's weather is rainy. The server then suggests "yoga and stretches that can be done indoors," and the device notifies the user of this suggestion. The server also displays a recipe for "vegetable soup" based on the ingredients data in the user's refrigerator.

[0907] An example prompt is:

[0908] "I want to suggest today's exercise menu based on the user's current emotional state and weather data. The user has entered, 'It's raining today, so I don't want to go outside,' and there are tomatoes, cabbage, and carrots in the refrigerator. Given these conditions, what would be the optimal exercise menu and cooking recipe?"

[0909] This system can propose individual diet plans based on the user's behavioral patterns and moods, as well as economical meal menus, supporting users to continue their diet without straining themselves.

[0910] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0911] Step 1:

[0912] Entering Basic User Attributes

[0913] The terminal prompts the user to enter basic attributes such as age, sex, height, weight, and medical history. The user enters this information into the form and clicks the submit button. The entered data is sent from the terminal to the server in JSON format. Terminal input: Basic user attribute information Server output: JSON format data.

[0914] Step 2:

[0915] Entering user behavior-related information

[0916] The device prompts the user to enter activity-related information such as residence and workplace. The user enters this information and presses the submit button. The entered data is sent to the server in JSON format. Device input: User's residence and workplace information Server output: JSON format data.

[0917] Step 3:

[0918] Entering the target value

[0919] The terminal prompts the user to enter target values ​​such as target weight and target body fat percentage. The user enters this information and presses the submit button. The entered data is sent to the server in JSON format. Terminal input: User's target value Server output: JSON format data.

[0920] Step 4:

[0921] Data storage and user profile creation

[0922] The server saves all the data received in the previous steps in a database and creates a user profile. MySQL is used to save the user's basic attributes, behavior-related information, and goal values. Server input: User's basic attributes, behavior-related information, goal values ​​Server output: User profile created in the database.

[0923] Step 5:

[0924] Behavioral pattern tracking

[0925] The device collects the user's GPS data, movement history, and exercise data (number of steps, calories burned, etc.) in real time. The collected data is sent to the server at regular intervals. Device input: Exercise data collected in real time Server output: Data in JSON format.

[0926] Step 6:

[0927] Matching tracking data with external data

[0928] The server compares the received tracking data with external data such as the day of the week and weather. External data is obtained from sources such as the OpenWeatherMap API. Server input: Tracking data, day of the week, weather data. Server output: Matched data.

[0929] Step 7:

[0930] Input your mood and schedule

[0931] The device prompts the user to input their mood and schedule for the day. The data entered by the user is sent to the server and stored in MongoDB. Device input: User's mood, schedule Server output: Data in JSON format.

[0932] Step 8:

[0933] Data analysis

[0934] The server aggregates and analyzes all collected data. It uses Pandas and Numpy to analyze the data and understand behavioral patterns and moods of the day. Server input: All collected data. Server output: Analysis results.

[0935] Step 9:

[0936] Generate a diet plan

[0937] The server generates a diet plan using a generative AI model based on the analysis results. It uses TensorFlow and PyTorch to create the optimal exercise and meal plan for the user. Server input: Analysis results. Server output: Generated diet plan.

[0938] Step 10:

[0939] Diet plan notifications

[0940] The server sends the generated diet plan to the user's device. The device notifies the user of the received plan and suggests specific actions and cooking recipes. Specifically, a push notification is displayed using React Native. Server input: Generated diet plan Device output: Push notification.

[0941] As a specific example, if a user inputs "It's raining today and I don't want to go outside," the server will analyze weather data and the user's behavioral patterns to suggest yoga and stretching exercises that can be done indoors. The device will also display a recipe for a vegetable soup based on the ingredients in the user's refrigerator. An example of a prompt for the production version could be, "I would like to suggest today's exercise menu based on the user's current emotional state and weather data. The user inputs "It's raining today and I don't want to go outside," and there are tomatoes, cabbage, and carrots in the refrigerator. Please tell me the optimal exercise menu and cooking recipe based on these conditions."

[0942] (Application example 1)

[0943] 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."

[0944] In today's busy lifestyles, individual users need individually customized suggestions and support to maintain a healthy and economical diet. However, conventional diet systems have difficulty providing specific advice based on the user's mood and schedule that day, as well as real-time location information. In particular, brick-and-mortar stores require users to instantly receive appropriate diet information within the store. Therefore, there is a need for an effective diet motivator that reflects the user's individual circumstances in real time and can be utilized in brick-and-mortar stores.

[0945] 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.

[0946] In this invention, the server includes a means for inputting basic attributes of a user, a means for inputting behavior-related information such as place of residence and place of work, and a means for inputting target values. This makes it possible to provide appropriate diet information in real time through a display device worn by a user in a physical store. This allows users to receive personalized diet advice in real time within the store, allowing them to diet more effectively.

[0947] The "means for inputting basic user attributes" is a part of the system for inputting basic personal information such as the user's age, sex, height, and weight.

[0948] The "means for inputting behavior-related information" refers to a means for inputting information related to the user's behavior, such as the user's place of residence, place of work, and travel route.

[0949] The "means for inputting target values" is a means for inputting target values ​​for dieting, such as the user's target weight and target body fat percentage.

[0950] The "means for transmitting the input information" is a means for transmitting the basic attributes, behavior-related information, target values, etc. input by the user to the server.

[0951] The "means for storing in a database and creating a user profile" is the part of the system for storing the transmitted information in a database and creating an individual profile for the user based thereon.

[0952] The "means for tracking user behavior patterns" refers to a means for collecting user movement history and exercise data in real time and tracking the user's behavior patterns.

[0953] "Means for comparing with external data" refers to means for comparing collected data with external data such as the day of the week and weather, and analyzing the data.

[0954] The "means for analyzing data" is a means for analyzing the collated data and generating an optimal diet plan for the user.

[0955] The "means for inputting the mood and schedule of the day" is a means for the user to input the mood and schedule of the day.

[0956] The "means for transmitting all collected data to the server" refers to a means for transmitting all collected data to the server.

[0957] The "means for generating a diet plan" is a means for generating a diet plan suitable for the user based on the data received by the server.

[0958] The "means for proposing the generated diet plan to the user" is a means for presenting the generated diet plan to the user.

[0959] "Means for providing appropriate diet information in real time through a display device" refers to means for providing optimal diet information in real time through a display device worn by a user in a physical store.

[0960] This invention is a system that provides users with an optimal diet plan based on their basic attributes, behavior-related information, target values, etc. This system is composed of a server, a terminal, and a display device that the user wears in a physical store.

[0961] User Registration

[0962] When the terminal starts up the system for the first time, the user enters basic attributes such as name, age, sex, height, weight, and medical conditions. Next, the user enters their place of residence and place of work, as well as their target values ​​such as target weight and target body fat percentage. This information is sent from the terminal to the server and stored in a database to create a user profile.

[0963] Information gathering

[0964] The device collects real-time GPS data, movement history, and exercise data (step count, calories burned, etc.) to track the user's behavioral patterns. This data is then compared with external data such as weather data and the day of the week. The device also allows the user to input their mood, schedule, and planned exercise intensity for the day.

[0965] Plan Generation

[0966] Based on the collected and analyzed data, the server generates a diet plan suited to the user's behavioral patterns and mood for that day. The plan considers the balance of exercise, meals, and rest and is presented to the device as a specific action plan.

[0967] Application in physical stores

[0968] When users visit physical stores, especially supermarkets and fitness gyms, they can wear a head-mounted display to receive real-time diet information. For example, product information and recipes are displayed in supermarkets, and exercise methods are displayed in fitness gyms.

[0969] Hardware and software used

[0970] Hardware: Head-mounted display, GPS module

[0971] Software: Python program, GPS module library, RESTful API

[0972] Specific examples

[0973] If it's raining that day and the user types "I don't want to go outside today," the server will analyze the weather data and the user's behavioral patterns to suggest yoga and stretching exercises that can be done indoors. It will also display a recipe for a healthy "vegetable soup" based on the ingredients in the user's refrigerator.

[0974] Prompt Sentence Examples

[0975] Below are some examples of prompt sentences.

[0976] User Attribute Information:

[0977] Age: 28

[0978] Gender: Female

[0979] Height: 160 cm

[0980] Weight: 55 kg

[0981] Residence: Tokyo

[0982] Location: Shibuya

[0983] Target weight: 50 kg

[0984] Target body fat percentage: 20%

[0985] Current time: 2023-10-01T14:30:00

[0986] Current location: Latitude 35.6895, Longitude 139.6917

[0987] Use this information to generate the best diet plan for you.

[0988] In this way, the present invention supports the continuation of a healthy and economical diet by proposing a diet plan that matches the user's specific lifestyle and mood.

[0989] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0990] Step 1:

[0991] User enters basic attributes

[0992] The user uses a terminal to input basic attributes such as name, age, sex, height, weight, and medical conditions. The input information is sent to the server by the terminal. Input information: Name, age, sex, height, weight, medical conditions. Output information: Creates a user profile on the server.

[0993] Step 2:

[0994] The user inputs the behavior-related information and the goal value.

[0995] The user uses the terminal to input behavior-related information and goal values, such as place of residence, place of work, target weight, and target body fat percentage. This information is also sent from the terminal to the server and stored in the database. Input content: place of residence, place of work, target weight, target body fat percentage. Output content: user profile updated on the server.

[0996] Step 3:

[0997] Tracking user behavior patterns

[0998] The device collects GPS data, movement history, and exercise data (number of steps, calories burned, etc.) in real time. The collected data is periodically sent to the server. Input: GPS data, movement history, exercise data. Output: Behavioral pattern records on the server.

[0999] Step 4:

[1000] Compare with external data and analyze

[1001] The server compares the tracked data with external data such as the day of the week and weather, and analyzes the data. Input: Tracking data, day of the week, weather data. Output: Analysis results (behavioral pattern trends).

[1002] Step 5:

[1003] The user inputs their mood and schedule

[1004] The user uses the device to input the mood, planned exercise intensity, and schedule for the day. The input information is sent to the server. Input information: mood, planned exercise intensity, schedule. Output information: record of mood and schedule on the server.

[1005] Step 6:

[1006] Generate a diet plan

[1007] The server generates a diet plan suited to the user based on all the data received. Specifically, this includes the type of exercise and meal menu. Input: Basic attributes, behavioral patterns, mood and schedule. Output: Diet plan.

[1008] Step 7:

[1009] Suggest diet plans to users

[1010] The device notifies the user of the generated diet plan. In a physical store, the plan is displayed in real time on the head-mounted display worn by the user. Input: Diet plan. Output: The plan displayed on the user's head-mounted display.

[1011] Step 8:

[1012] Providing appropriate diet information in real time

[1013] When a user wears a head-mounted display in a physical store such as a supermarket or fitness gym, real-time diet information about products in the store and exercise methods is displayed. Input content: Location information and product information in the store. Output content: Diet information displayed on the head-mounted display.

[1014] 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.

[1015] This invention relates to a "diet motivator" that provides an optimal diet plan tailored to the user's lifestyle and mood on that day, and in particular, is a system that provides a more sophisticated and personalized diet plan by combining it with an emotion engine that recognizes the user's emotions.

[1016] 1. First-time user registration

[1017] When the server starts the system for the first time, the terminal prompts the user to enter basic attributes (age, sex, build, health information, etc.). The user enters age, sex, height, weight, medical history, etc. Next, the terminal prompts the user to enter their place of residence and place of work, and the user enters this information. Furthermore, the terminal prompts the user to enter target values ​​such as target weight and target body fat percentage, and the user enters the target values.

[1018] The terminal sends this input information to the server, and the server stores the received data in a database to create a user profile.

[1019] 2. Information gathering

[1020] To track a user's behavioral patterns, the device collects the user's GPS data, movement history, and exercise data (e.g., number of steps, calories burned) in real time. This data is periodically sent to a server, which then compares the received data with external data such as the day of the week and weather, and analyzes the user's behavioral patterns.

[1021] The device also prompts the user to input their mood, schedule, and planned exercise intensity for the day, allowing the user to input their emotional state (e.g., fatigue, motivation), schedule, and exercise plan for the day. The emotion engine recognizes the user's emotions in real time and sends the data to the server.

[1022] 3. Emotion Engine

[1023] The emotion engine analyzes the user's facial expressions, tone of voice, text input, etc. to recognize the user's emotions. Emotional data is analyzed in combination with the user's behavioral patterns and mood input for the day. For example, if the emotion engine recognizes that the user is tired, that data is sent to the server.

[1024] 4. Proposal

[1025] Based on the data collected and analyzed so far, the server generates a diet plan suited to the user's behavioral patterns, mood of the day, and emotional data. The generated plan creates a specific action plan that takes into account the balance of exercise, meals, and rest, and sends it to the device as suggested data. Specifically, it can suggest exercise menus that match the user's mood and emotions of the day, as well as healthy and economical cooking menus.

[1026] Specific examples

[1027] If a user inputs "I feel tired today" one day and the emotion engine recognizes the tiredness from the user's facial expression, the server will use that data to suggest "light stretching and relaxation exercises." The device will also display a recipe for "chicken and vegetable stew," which is effective in relieving fatigue, based on ingredients in the user's refrigerator. In this way, users can continue their diet without straining themselves in their daily lives.

[1028] This system supports users in continuing a healthy and enjoyable diet through a consistent process from data collection to recommendations. In addition, by combining it with an emotion engine, it provides specific advice based on the user's emotions, helping them achieve their goals without any stress.

[1029] The processing flow will be explained below.

[1030] 1. First-time user registration

[1031] Step 1:

[1032] The device prompts the user to enter basic attributes (age, gender, build, health information, etc.).

[1033] Step 2:

[1034] The user inputs the age, sex, height, weight, medical history, etc. in order.

[1035] Step 3:

[1036] The terminal prompts the user to enter their place of residence and place of work.

[1037] Step 4:

[1038] The user enters their place of residence and place of work.

[1039] Step 5:

[1040] The terminal prompts the user to input target values ​​(target weight, target body fat percentage, etc.).

[1041] Step 6:

[1042] The user inputs a target value.

[1043] Step 7:

[1044] The terminal sends all entered information to the server.

[1045] Step 8:

[1046] The server stores the received data in a database and creates a user profile.

[1047] 2. Information gathering

[1048] Step 1:

[1049] The device collects the user's GPS data, movement history, and exercise data (e.g., number of steps taken, calories burned).

[1050] Step 2:

[1051] The terminal periodically transmits the collected data to the server.

[1052] Step 3:

[1053] The server compares the received data with external data such as the day of the week and weather.

[1054] Step 4:

[1055] The server analyzes the matched data and stores it in a statistical database.

[1056] Step 5:

[1057] The device prompts the user to input their mood, schedule, and exercise plans for the day.

[1058] Step 6:

[1059] The user inputs their emotional state (e.g., fatigue, motivation), their schedule for the day, and their exercise plan.

[1060] Step 7:

[1061] The emotion engine analyzes the user's facial expressions, tone of voice, text input, etc. to recognize emotions.

[1062] Step 8:

[1063] The data collected by the device, user input data, and emotion data recognized by the emotion engine are sent to the server.

[1064] Step 9:

[1065] The server analyzes the received data and models each user's behavioral patterns and tendencies.

[1066] 3. Proposal

[1067] Step 1:

[1068] Based on the data accumulated by the server, a diet plan is generated that is suited to the user's behavioral patterns, mood of the day, and emotional data.

[1069] Step 2:

[1070] The server creates a specific action plan, taking into account the balance of exercise, diet, and rest.

[1071] Step 3:

[1072] The server creates specific advice and suggestions (e.g., today's exercise menu, meal recipes) aimed at the user's goals.

[1073] Step 4:

[1074] The server transmits the created proposal data to the terminal.

[1075] Step 5:

[1076] The device displays healthy and economical lifestyle schedules and cooking menus to the user.

[1077] Step 6:

[1078] The user follows the proposed plan and carries out daily activities.

[1079] Examples:

[1080] One day, if a user types "I feel tired today," and the emotion engine recognizes the user's tiredness from their facial expression, the device will send that data to the server. Based on that data, the server will suggest "light stretching and relaxation exercises." The device will also display a recipe for "chicken and vegetable stew," which is effective in relieving fatigue, based on ingredients in the user's refrigerator. In this way, users can continue their diet without straining themselves in their daily lives.

[1081] Example 2

[1082] 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."

[1083] While conventional diet support systems propose diet plans based on the user's basic attributes and behavioral data, they lack the ability to consider the user's emotional state or mood on that day. This can lead to problems such as users not receiving appropriate support on days when they are tired or unmotivated, making it difficult to continue their diet. Furthermore, because detailed planning tailored to individual users is not possible, general proposals are less effective for some users.

[1084] 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.

[1085] In this invention, the server includes means for inputting a user's basic attributes, means for inputting behavior-related information such as place of residence and place of work, means for inputting target values, means for transmitting the input information, means for saving the transmitted information in a database and creating a user profile, means for tracking the user's behavioral patterns, means for comparing the tracked data with external data such as the day of the week and weather, means for analyzing the compared data, means for prompting the user to input their mood and schedule for the day, an emotion engine for analyzing the user's emotional state, means for transmitting all the collected data and emotion data to the server, means for the server to analyze the received data and generate a diet plan suitable for the user, and means for proposing the generated diet plan to the user. This makes it possible to provide a more personalized and specific diet plan based on the user's emotional state and mood for the day.

[1086] "Basic attributes" refers to basic information about an individual, such as the user's age, sex, height, weight, medical history, etc.

[1087] "Behavior-related information" is information about the user's place of residence, place of work, and behavioral patterns related thereto.

[1088] "Goal value" refers to a specific health goal such as weight or body fat percentage that a user aims to achieve.

[1089] A "user profile" is an individual information set in a database that is created based on input information such as a user's basic attributes, behavior-related information, and goal values.

[1090] A "behavioral pattern" is a series of behavioral trends over a specific period of time, analyzed based on a user's GPS data, movement history, exercise data, etc.

[1091] "External data" is information about the external environment that affects the user's behavior, such as the day of the week and weather.

[1092] An "emotion engine" is a system that has the function of analyzing a user's facial expressions, tone of voice, text input, etc. to recognize their emotional state.

[1093] A "diet plan" is a specific action plan for exercise, meals, rest, etc. that is generated based on the user's behavioral patterns, basic attributes, target values, and emotional state.

[1094] This invention relates to a "diet motivator" that provides an optimal diet plan tailored to the user's lifestyle and mood on that day. In particular, this system provides a more refined and personalized diet plan by combining it with an emotion engine that recognizes the user's emotions.

[1095] The system of the present invention relies primarily on two hardware components: a server and a terminal.

[1096] 1. First-time user registration

[1097] When the terminal starts the system for the first time, it displays a screen prompting the user to enter basic attributes (age, sex, build, health information, etc.). The user enters information such as age, sex, height, weight, and medical history. The terminal then prompts the user to enter their place of residence and place of work, and the user enters that information. The terminal then prompts the user to enter target values ​​such as target weight and target body fat percentage, and the user enters those target values.

[1098] The device sends this input information to the server, which stores the received data in a database and creates a user profile.

[1099] 2. Information gathering

[1100] To track a user's behavioral patterns, the device collects the user's GPS data, movement history, and exercise data (e.g., number of steps, calories burned) in real time. This data is periodically sent to a server, which then compares the received data with external data such as the day of the week and weather, and analyzes the user's behavioral patterns.

[1101] The device also displays a screen prompting the user to input their mood, schedule, and planned exercise intensity for the day. The user can input their emotional state (e.g., fatigue, motivation), schedule, and exercise plan for the day. The emotion engine analyzes the user's facial expression, tone of voice, and text input to recognize their emotional state. The device sends the output of the emotion engine to the server.

[1102] 3. Proposal

[1103] Based on the data collected and analyzed so far, the server generates a diet plan suited to the user's behavioral patterns, mood of the day, and emotional data. The generated plan takes into account the balance of exercise, meals, and rest, and sends the proposed data to the device as a specific action plan. Specifically, it can suggest an exercise menu that matches the user's mood and emotions of the day, as well as a healthy and economical cooking menu.

[1104] Specific examples

[1105] For example, if a user inputs "I feel tired today" one day and the emotion engine recognizes the feeling of fatigue from the user's facial expression, the server will use that data to suggest "light stretching and relaxation exercises." The device will also display a recipe for "chicken and vegetable stew," which is effective in relieving fatigue, based on ingredients in the user's refrigerator. This allows users to continue their diet without straining themselves in their daily lives.

[1106] Prompt Sentence Examples

[1107] "The user enters 'I'm tired today,' and the emotion engine recognizes this state of fatigue. Based on this data, please suggest appropriate exercise and meal plans."

[1108] By inputting such prompt sentences into the generative AI model, the accuracy of the model can be confirmed and the quality of the system can be improved.

[1109] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1110] Step 1: First-time user registration

[1111] Input: User's basic attribute information (age, gender, height, weight, medical history, etc.)

[1112] Specific operation When the terminal starts the system for the first time, it displays a screen prompting the user to enter basic attributes. The user enters the information. The terminal temporarily stores this information.

[1113] Output: Basic attribute information is saved to the device.

[1114] Step 2: Enter your place of residence and work

[1115] Input: User's residence and work location information

[1116] Specific operation: The terminal displays a screen prompting the user to enter residence and workplace information. The user enters the information. The terminal temporarily stores this information.

[1117] Output: Residence and work location information is saved on the device

[1118] Step 3: Enter the target value

[1119] Input: User's goal values ​​such as goal weight and goal body fat percentage

[1120] Specific operation: The device displays a screen prompting the user to input the target value. The user inputs the target value. The device temporarily stores this information.

[1121] Output: The target value is saved to the terminal.

[1122] Step 4: Data submission and user profile creation

[1123] Input: Basic attribute information, residence and workplace information, target value

[1124] Specific operation: The device sends all input information to the server, which stores the received data in a database and creates a user profile.

[1125] Output: The user profile is saved in the database.

[1126] Step 5: Collecting and Sending Dynamic Data

[1127] Input: User's GPS data, movement history, exercise data (number of steps, calories burned, etc.)

[1128] Specific operation: The device uses sensors to collect the user's GPS data, movement history, and exercise data in real time, and transmits the collected data to a server at regular intervals.

[1129] Output: Collected data is sent to a server and stored for analysis.

[1130] Step 6: Analyze behavioral patterns

[1131] Input: Collected dynamic data, external data (day of the week, weather)

[1132] Specific operation: The server compares the collected dynamic data with external data such as the day of the week and weather, and analyzes behavioral patterns.

[1133] Output: Behavioral pattern analysis data

[1134] Step 7: Enter your mood and schedule

[1135] Input: User's mood, schedule for the day, planned exercise intensity

[1136] Specific operation: The device displays a screen prompting the user to input their mood, schedule, and planned exercise intensity. The user inputs this information. The device temporarily stores this information.

[1137] Output: Mood and schedule information is saved on the device

[1138] Step 8: Emotion Analysis with the Emotion Engine

[1139] Input: User facial expression data, tone of voice, text input

[1140] How it works: The emotion engine analyzes the user's facial expressions, tone of voice, and text input to recognize their emotional state, and the device sends the output to the server.

[1141] Output: Emotional state data is sent to the server

[1142] Step 9: Analyze the data and generate a diet plan

[1143] Input: behavioral pattern analysis data, mood and schedule information, emotional state data

[1144] Specific operation: Based on the data collected and analyzed up to now, the server generates a diet plan suited to the user's behavioral patterns, mood of the day, and emotional data.

[1145] Output: The generated diet plan

[1146] Step 10: Inform your diet plan

[1147] Input: Generated diet plan

[1148] Specific operations: The server sends the generated diet plan to the terminal, and the terminal notifies the user of the plan.

[1149] Output: The diet plan notified to the user

[1150] (Application example 2)

[1151] 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."

[1152] Conventional diet plan suggestion systems often make uniform suggestions without considering the user's emotions or mood of the day. This makes it difficult to provide appropriate suggestions that match the user's mental state or daily lifestyle, making it difficult to motivate them to continue dieting. Furthermore, to actually prepare the suggested meal menu, the user must procure ingredients and cook the food themselves, which is time-consuming and labor-intensive.

[1153] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for inputting a user's basic attributes; means for inputting behavior-related information such as a residence and workplace; means for inputting a target value; means for transmitting the input information; means for saving the transmitted information in a database and creating a user profile; means for tracking the user's behavioral patterns; means for comparing the tracked data with external data such as the day of the week and the weather; means for analyzing the compared data; means for prompting the user to input their mood and schedule for the day; means for transmitting all collected data to the server; means for the server to analyze the received data and generate a diet plan suitable for the user; means for proposing the generated diet plan to the user; means including an emotion engine for collecting and analyzing the user's emotional data; means for proposing a meal menu suitable for the user based on the emotional data; and means for providing the meal menu to the user via a food delivery system. This makes it possible to provide a personalized diet plan based on the user's emotions and mood for the day, and the suggested meal menu can be easily ordered, making it easier to continue dieting.

[1154] "Basic attributes of a user" refers to personal information such as the user's age, sex, build, and health information.

[1155] "Behavioral information" refers to information about a user's behavior, including their place of residence, place of work, and daily movements.

[1156] "Target value" refers to a specific numerical target such as weight or body fat percentage that the user aims to achieve.

[1157] "User profile" refers to a comprehensive database entry that includes a user's basic attributes, behavior-related information, goals, etc.

[1158] "Behavioral patterns" refer to specific behavioral tendencies and habits in a user's daily life.

[1159] "External data" refers to relevant information other than the user's own behavior, such as the day of the week and weather.

[1160] "Emotion engine" refers to a function that recognizes a user's emotions by analyzing their facial expressions, tone of voice, and text input.

[1161] A "diet plan" refers to a specific action plan proposed to a user that takes into account a balance of exercise, diet, rest, and other factors.

[1162] "Meal menu" refers to specific meal items suggested based on the user's emotions, mood, and health status.

[1163] A "food delivery system" refers to an online service that allows users to easily order suggested meal menus.

[1164] This invention builds a system that proposes optimal diet plans and meal menus based on the user's emotions and mood of the day, and then actually provides them through a food delivery service. This system is realized by using the following programs, hardware, and software.

[1165] The server includes a means for inputting basic user attributes, a means for inputting behavior-related information such as place of residence and place of work, a means for inputting target values, a means for transmitting the input information, and a means for storing the transmitted information in a database and creating a user profile, thereby enabling centralized management of basic user information.

[1166] The server also includes a means for tracking the user's behavioral patterns, a means for comparing the tracked data with external data such as the day of the week and weather, and a means for analyzing the compared data, thereby collecting and analyzing detailed data about the user's daily life.

[1167] Furthermore, the server includes a means for allowing the user to input the mood and schedule of the day, a means for transmitting all the collected data to the server, a means for the server to analyze the received data and generate a diet plan suitable for the user, and a means for proposing the generated diet plan to the user, thereby enabling personalized suggestions to be made to each individual user.

[1168] The server further includes means for including an emotion engine that collects and analyzes emotion data of the user, means for suggesting a meal menu suitable for the user based on the emotion data, and means for providing the meal menu to the user via a food delivery system, so that the user can easily order the suggested meal menu and actually receive the meal through the food delivery service.

[1169] For example, if a user inputs "I'm tired today," and the emotion engine recognizes the same, the server will suggest light meal options such as "chicken soup" or "vegetable salad." Users can easily check these options within the app and request delivery by simply pressing the order button.

[1170] An example of a prompt to input to a generative AI model is as follows:

[1171] "Please suggest a healthy menu when the user feels tired. User information: age, gender, physique, health information, goal value. Emotion: fatigue."

[1172] The hardware used includes a cloud server, and the software includes Flask (Python) and a database (e.g., SQLite or PostgreSQL).

[1173] In this way, personalized diet plans and meal menus that reflect the user's emotions and mood of the day can be proposed and actually provided through a food delivery system, which will encourage users to continue their diet and improve the quality of their daily lives.

[1174] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1175] Step 1:

[1176] When the server starts the system for the first time, the terminal prompts the user to enter basic attributes (age, gender, build, health information, etc.). The user enters this information into the terminal, and the terminal sends the received information to the server. The server stores the received data in a database and creates a user profile.

[1177] Step 2:

[1178] The device prompts the user to enter activity-related information such as their place of residence and place of work. The user enters this information into the device, which then transmits the information to the server. The server stores the received data in a database and updates the user profile.

[1179] Step 3:

[1180] The device prompts the user to input goals (e.g., target weight or target body fat percentage). The user inputs the goals, and the device sends the input data to the server. The server stores the received goal data in a database and integrates it into the user profile.

[1181] Step 4:

[1182] The device collects GPS data, movement history, and exercise data (e.g., number of steps, calories burned) in real time to track the user's behavior. This data is periodically sent to a server, which stores the received data in a database.

[1183] Step 5:

[1184] The server compares the tracked data with external data such as the day of the week and weather, and analyzes the matched data. This allows the user's behavioral patterns to be understood. The analysis results are stored in a database.

[1185] Step 6:

[1186] The device provides an interface for the user to input the user's mood and schedule for the day. The user inputs the information, and the device sends it to the server. The server analyzes the received data and integrates it into the user profile.

[1187] Step 7:

[1188] The server uses an emotion engine to recognize the user's emotions in real time from facial expressions, tone of voice, and text input, and the emotion data is stored in a database.

[1189] Step 8:

[1190] The server uses a generative AI model based on the data collected and analyzed to generate a diet plan suited to the user. This calculation uses prompt statements and inputs the user's emotions and behavioral data. The generated diet plan is saved in a database as a specific action plan.

[1191] Step 9:

[1192] The server transmits the generated diet plan to the user's terminal as proposal data, and the terminal displays the received proposal data to the user, allowing the user to confirm the plan.

[1193] Step 10:

[1194] The server proposes a meal menu suitable for the user based on the user's emotional data. This meal menu is provided to the user via the food delivery system and is generated using an emotion engine and a generative AI model. The user can check the proposed menu through their device and easily order.

[1195] 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.

[1196] 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.

[1197] 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.

[1198] [Fourth embodiment]

[1199] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1200] 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.

[1201] 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).

[1202] 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.

[1203] 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.

[1204] 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).

[1205] 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.

[1206] 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.

[1207] 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.

[1208] 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.

[1209] 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.

[1210] 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.

[1211] 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."

[1212] This invention relates to a "diet motivator" that provides the user with an optimal diet plan tailored to their lifestyle and mood on that day. Specifically, it is a system that takes into account the user's basic attributes and behavioral patterns to help them continue their diet economically and healthily.

[1213] 1. First-time user registration

[1214] When the server starts the system for the first time, the terminal prompts the user to enter basic attributes (age, sex, build, health information, etc.). The user enters age, sex, height, weight, medical history, etc. Next, the terminal prompts the user to enter their place of residence and place of work, and the user enters this information. Furthermore, the terminal prompts the user to enter target values ​​such as target weight and target body fat percentage, and the user enters the target values.

[1215] The terminal sends this input information to the server, and the server stores the received data in a database to create a user profile.

[1216] 2. Information gathering

[1217] To track a user's behavioral patterns, the device collects the user's GPS data, movement history, and exercise data (e.g., number of steps, calories burned) in real time. This data is periodically sent to a server, which then compares the received data with external data such as the day of the week and weather, and analyzes the user's behavioral patterns.

[1218] The terminal also prompts the user to input their mood and schedule for the day, as well as their planned exercise intensity, allowing the user to input their emotional state (e.g., fatigue, motivation), schedule for the day, and exercise plan.

[1219] 3. Proposal

[1220] The server generates a diet plan based on the data collected and analyzed to date, tailored to the user's behavioral patterns and daily mood. The plan creates a specific action plan that takes into account the balance of exercise, meals, and rest, and sends it to the device as suggested data. Specifically, it can suggest an exercise menu that suits the user's mood that day, as well as healthy and economical meal menus.

[1221] Specific examples

[1222] If a user inputs "It's raining today, so I don't want to go outside," the server will analyze the weather data and the user's behavioral patterns and suggest "yoga and stretching exercises that can be done indoors." The device will also display a recipe for a low-calorie yet nutritious "vegetable soup" based on ingredients in the user's refrigerator. In this way, users can continue their diet without any stress in their daily lives.

[1223] The system supports users in continuing a healthy and enjoyable diet through a consistent process from data collection to recommendations. It also helps users achieve their goals without straining themselves by providing specific advice that fits into their lifestyle while minimizing financial burden.

[1224] The processing flow will be explained below.

[1225] 1. First-time user registration

[1226] Step 1:

[1227] The device prompts the user to enter basic attributes (age, gender, build, health information, etc.).

[1228] Step 2:

[1229] The user inputs the age, sex, height, weight, medical history, etc. in order.

[1230] Step 3:

[1231] The terminal prompts the user to enter their place of residence and place of work.

[1232] Step 4:

[1233] The user enters their place of residence and place of work.

[1234] Step 5:

[1235] The terminal prompts the user to input target values ​​(target weight, target body fat percentage, etc.).

[1236] Step 6:

[1237] The user inputs a target value.

[1238] Step 7:

[1239] The terminal sends all entered information to the server.

[1240] Step 8:

[1241] The server stores the received data in a database and creates a user profile.

[1242] 2. Information gathering

[1243] Step 1:

[1244] The device collects the user's GPS data, movement history, and exercise data (e.g., number of steps taken, calories burned).

[1245] Step 2:

[1246] The terminal periodically transmits the collected data to the server.

[1247] Step 3:

[1248] The server compares the received data with external data such as the day of the week and weather.

[1249] Step 4:

[1250] The server analyzes the matched data and stores it in a statistical database.

[1251] Step 5:

[1252] The device prompts the user to input their mood, schedule, and exercise plans for the day.

[1253] Step 6:

[1254] The user inputs their emotional state (e.g., fatigue, motivation), their schedule for the day, and their exercise plan.

[1255] Step 7:

[1256] The terminal transmits the collected data and the user input data to the server.

[1257] Step 8:

[1258] The server analyzes the received data and models each user's behavioral patterns and tendencies.

[1259] 3. Proposal

[1260] Step 1:

[1261] Based on the data accumulated by the server, a diet plan is generated that is suited to the user's behavioral patterns and mood of the day.

[1262] Step 2:

[1263] The server creates a specific action plan, taking into account the balance of exercise, diet, and rest.

[1264] Step 3:

[1265] The server creates specific advice and suggestions (e.g., today's exercise menu, meal recipes) aimed at the user's goals.

[1266] Step 4:

[1267] The server transmits the created proposal data to the terminal.

[1268] Step 5:

[1269] The device displays healthy and economical lifestyle schedules and cooking menus to the user.

[1270] Step 6:

[1271] The user follows the proposed plan and carries out daily activities.

[1272] Example 1

[1273] 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."

[1274] Conventional diet support systems have difficulty providing individualized diet plans based on the user's lifestyle and mood. Furthermore, they are unable to efficiently analyze regularly collected data and provide feedback to users, making it difficult for them to continue dieting. Furthermore, they are inadequate in proposing economical and feasible meal plans.

[1275] 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.

[1276] In this invention, the server includes means for inputting a user's basic attributes, means for inputting behavior-related information such as place of residence and place of work, means for inputting target values, means for transmitting the input information, means for saving the transmitted information in a database and creating a user profile, means for tracking the user's behavioral patterns, means for comparing the tracked data with external data such as the day of the week and weather, means for analyzing the compared data, means for prompting the user to input their mood and schedule for the day, means for transmitting all the collected data to the server, means for the server to analyze the received data and generate a diet plan suitable for the user using a generative AI model, and means for generating prompts to suggest the generated diet plan to the user and displaying them on the user's terminal. This enables the server to propose an individual diet plan tailored to the user's lifestyle and mood, as well as economical meal menus, making it easier to continue dieting.

[1277] "Basic attributes" refers to information specific to an individual, such as the user's age, sex, height, weight, medical history, etc.

[1278] "Behavioral Information" refers to a user's place of residence and place of work, and related geographical and temporal information.

[1279] "Target value" refers to a specific numerical value that the user wishes to achieve, such as a target weight or body fat percentage.

[1280] A "user profile" refers to an individual information set that includes a user's basic attributes, behavior-related information, goal values, and the like.

[1281] "Behavioral patterns" refer to a user's daily movement history, exercise data, and related temporal and spatial trends.

[1282] "Tracking" refers to the collection and recording of user behavior and exercise data in real time.

[1283] "External data" refers to external information that influences a user's behavior and mood, such as the day of the week or the weather.

[1284] "Generative AI model" refers to an artificial intelligence model used to analyze user data and generate an optimal diet plan.

[1285] A "prompt sentence" refers to a guide message generated to prompt the user to take a specific action or make a choice.

[1286] A "diet plan" refers to specific guidelines for exercise and diet provided based on the user's basic attributes and behavioral patterns.

[1287] This invention relates to a "diet motivator" that provides an optimal diet plan according to the user's lifestyle and mood of the day. Specifically, it is a system that takes into account the user's basic attributes and behavior-related information to help them continue dieting economically and healthily.

[1288] First-time user registration

[1289] The terminal prompts the user to enter basic attributes. For this, a form is created using a front-end framework such as React or Vue.js, and the user is asked to enter information such as age, gender, height, weight, medical conditions, etc. When the user enters the information and presses the submit button, the entered information is sent to the server in JSON format.

[1290] The server saves the received data in a database and creates a user profile. Specifically, it receives POST requests using the Python Flask framework, converts them into a data frame using Pandas, and saves them in a MySQL database. Once the data is saved, the server returns a "Registration Complete" message to the terminal.

[1291] Information gathering

[1292] The device collects the user's GPS data, movement history, and exercise data in real time. Using external services such as the Google Fit API and Apple HealthKit, the device periodically collects data and stores it in a buffer. This data is then periodically (e.g., every hour) sent to a server.

[1293] The user inputs their mood and schedule for the day. The device prompts the user to input their mood, schedule, and exercise intensity for the day through a pop-up screen. Once the user enters this information, the data is sent to the server and recorded in MongoDB via the REST API of the Django framework.

[1294] Data analysis and plan generation

[1295] The server aggregates and organizes the collected data. Using Python, a cron job is run periodically to aggregate all the data stored in the database. Pandas and Numpy are used to analyze the data and identify user behavior patterns and trends. The OpenWeatherMap API is also used to obtain external weather data and compare it with this data.

[1296] The server generates a diet plan using the AI ​​model. Using TensorFlow and PyTorch, it inputs the user's behavioral patterns and mood data to generate an optimal exercise and meal plan. The generated plan is saved in JSON format and sent to the device.

[1297] proposal notification

[1298] The server sends the generated diet plan to the device. The device receives this data and displays a notification to the user. By implementing push notifications using React Native, the notification includes today's exercise menu and cooking recipes.

[1299] For example, if a user one day inputs "It's raining today, so I don't want to go outside," the server analyzes weather data and the user's behavioral patterns, and confirms from the weather API that today's weather is rainy. The server then suggests "yoga and stretches that can be done indoors," and the device notifies the user of this suggestion. The server also displays a recipe for "vegetable soup" based on the ingredients data in the user's refrigerator.

[1300] An example prompt is:

[1301] "I want to suggest today's exercise menu based on the user's current emotional state and weather data. The user has entered, 'It's raining today, so I don't want to go outside,' and there are tomatoes, cabbage, and carrots in the refrigerator. Given these conditions, what would be the optimal exercise menu and cooking recipe?"

[1302] This system can propose individual diet plans based on the user's behavioral patterns and moods, as well as economical meal menus, supporting users to continue their diet without straining themselves.

[1303] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1304] Step 1:

[1305] Entering Basic User Attributes

[1306] The terminal prompts the user to enter basic attributes such as age, sex, height, weight, and medical history. The user enters this information into the form and clicks the submit button. The entered data is sent from the terminal to the server in JSON format. Terminal input: Basic user attribute information Server output: JSON format data.

[1307] Step 2:

[1308] Entering user behavior-related information

[1309] The device prompts the user to enter activity-related information such as residence and workplace. The user enters this information and presses the submit button. The entered data is sent to the server in JSON format. Device input: User's residence and workplace information Server output: JSON format data.

[1310] Step 3:

[1311] Entering the target value

[1312] The terminal prompts the user to enter target values ​​such as target weight and target body fat percentage. The user enters this information and presses the submit button. The entered data is sent to the server in JSON format. Terminal input: User's target value Server output: JSON format data.

[1313] Step 4:

[1314] Data storage and user profile creation

[1315] The server saves all the data received in the previous steps in a database and creates a user profile. MySQL is used to save the user's basic attributes, behavior-related information, and goal values. Server input: User's basic attributes, behavior-related information, goal values ​​Server output: User profile created in the database.

[1316] Step 5:

[1317] Behavioral pattern tracking

[1318] The device collects the user's GPS data, movement history, and exercise data (number of steps, calories burned, etc.) in real time. The collected data is sent to the server at regular intervals. Device input: Exercise data collected in real time Server output: Data in JSON format.

[1319] Step 6:

[1320] Matching tracking data with external data

[1321] The server compares the received tracking data with external data such as the day of the week and weather. External data is obtained from sources such as the OpenWeatherMap API. Server input: Tracking data, day of the week, weather data. Server output: Matched data.

[1322] Step 7:

[1323] Input your mood and schedule

[1324] The device prompts the user to input their mood and schedule for the day. The data entered by the user is sent to the server and stored in MongoDB. Device input: User's mood, schedule Server output: Data in JSON format.

[1325] Step 8:

[1326] Data analysis

[1327] The server aggregates and analyzes all collected data. It uses Pandas and Numpy to analyze the data and understand behavioral patterns and moods of the day. Server input: All collected data. Server output: Analysis results.

[1328] Step 9:

[1329] Generate a diet plan

[1330] The server generates a diet plan using a generative AI model based on the analysis results. It uses TensorFlow and PyTorch to create the optimal exercise and meal plan for the user. Server input: Analysis results. Server output: Generated diet plan.

[1331] Step 10:

[1332] Diet plan notifications

[1333] The server sends the generated diet plan to the user's device. The device notifies the user of the received plan and suggests specific actions and cooking recipes. Specifically, a push notification is displayed using React Native. Server input: Generated diet plan Device output: Push notification.

[1334] As a specific example, if a user inputs "It's raining today and I don't want to go outside," the server will analyze weather data and the user's behavioral patterns to suggest yoga and stretching exercises that can be done indoors. The device will also display a recipe for a vegetable soup based on the ingredients in the user's refrigerator. An example of a prompt for the production version could be, "I would like to suggest today's exercise menu based on the user's current emotional state and weather data. The user inputs "It's raining today and I don't want to go outside," and there are tomatoes, cabbage, and carrots in the refrigerator. Please tell me the optimal exercise menu and cooking recipe based on these conditions."

[1335] (Application example 1)

[1336] 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."

[1337] In today's busy lifestyles, individual users need individually customized suggestions and support to maintain a healthy and economical diet. However, conventional diet systems have difficulty providing specific advice based on the user's mood and schedule that day, as well as real-time location information. In particular, brick-and-mortar stores require users to instantly receive appropriate diet information within the store. Therefore, there is a need for an effective diet motivator that reflects the user's individual circumstances in real time and can be utilized in brick-and-mortar stores.

[1338] 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.

[1339] In this invention, the server includes a means for inputting basic attributes of a user, a means for inputting behavior-related information such as place of residence and place of work, and a means for inputting target values. This makes it possible to provide appropriate diet information in real time through a display device worn by a user in a physical store. This allows users to receive personalized diet advice in real time within the store, allowing them to diet more effectively.

[1340] The "means for inputting basic user attributes" is a part of the system for inputting basic personal information such as the user's age, sex, height, and weight.

[1341] The "means for inputting behavior-related information" refers to a means for inputting information related to the user's behavior, such as the user's place of residence, place of work, and travel route.

[1342] The "means for inputting target values" is a means for inputting target values ​​for dieting, such as the user's target weight and target body fat percentage.

[1343] The "means for transmitting the input information" is a means for transmitting the basic attributes, behavior-related information, target values, etc. input by the user to the server.

[1344] The "means for storing in a database and creating a user profile" is the part of the system for storing the transmitted information in a database and creating an individual profile for the user based thereon.

[1345] The "means for tracking user behavior patterns" refers to a means for collecting user movement history and exercise data in real time and tracking the user's behavior patterns.

[1346] "Means for comparing with external data" refers to means for comparing collected data with external data such as the day of the week and weather, and analyzing the data.

[1347] The "means for analyzing data" is a means for analyzing the collated data and generating an optimal diet plan for the user.

[1348] The "means for inputting the mood and schedule of the day" is a means for the user to input the mood and schedule of the day.

[1349] The "means for transmitting all collected data to the server" refers to a means for transmitting all collected data to the server.

[1350] The "means for generating a diet plan" is a means for generating a diet plan suitable for the user based on the data received by the server.

[1351] The "means for proposing the generated diet plan to the user" is a means for presenting the generated diet plan to the user.

[1352] "Means for providing appropriate diet information in real time through a display device" refers to means for providing optimal diet information in real time through a display device worn by a user in a physical store.

[1353] This invention is a system that provides users with an optimal diet plan based on their basic attributes, behavior-related information, target values, etc. This system is composed of a server, a terminal, and a display device that the user wears in a physical store.

[1354] User Registration

[1355] When the terminal starts up the system for the first time, the user enters basic attributes such as name, age, sex, height, weight, and medical conditions. Next, the user enters their place of residence and place of work, as well as their target values ​​such as target weight and target body fat percentage. This information is sent from the terminal to the server and stored in a database to create a user profile.

[1356] Information gathering

[1357] The device collects real-time GPS data, movement history, and exercise data (step count, calories burned, etc.) to track the user's behavioral patterns. This data is then compared with external data such as weather data and the day of the week. The device also allows the user to input their mood, schedule, and planned exercise intensity for the day.

[1358] Plan Generation

[1359] Based on the collected and analyzed data, the server generates a diet plan suited to the user's behavioral patterns and mood for that day. The plan considers the balance of exercise, meals, and rest and is presented to the device as a specific action plan.

[1360] Application in physical stores

[1361] When users visit physical stores, especially supermarkets and fitness gyms, they can wear a head-mounted display to receive real-time diet information. For example, product information and recipes are displayed in supermarkets, and exercise methods are displayed in fitness gyms.

[1362] Hardware and software used

[1363] Hardware: Head-mounted display, GPS module

[1364] Software: Python program, GPS module library, RESTful API

[1365] Specific examples

[1366] If it's raining that day and the user types "I don't want to go outside today," the server will analyze the weather data and the user's behavioral patterns to suggest yoga and stretching exercises that can be done indoors. It will also display a recipe for a healthy "vegetable soup" based on the ingredients in the user's refrigerator.

[1367] Prompt Sentence Examples

[1368] Below are some examples of prompt sentences.

[1369] User Attribute Information:

[1370] Age: 28

[1371] Gender: Female

[1372] Height: 160 cm

[1373] Weight: 55 kg

[1374] Residence: Tokyo

[1375] Location: Shibuya

[1376] Target weight: 50 kg

[1377] Target body fat percentage: 20%

[1378] Current time: 2023-10-01T14:30:00

[1379] Current location: Latitude 35.6895, Longitude 139.6917

[1380] Use this information to generate the best diet plan for you.

[1381] In this way, the present invention supports the continuation of a healthy and economical diet by proposing a diet plan that matches the user's specific lifestyle and mood.

[1382] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1383] Step 1:

[1384] User enters basic attributes

[1385] The user uses a terminal to input basic attributes such as name, age, sex, height, weight, and medical conditions. The input information is sent to the server by the terminal. Input information: Name, age, sex, height, weight, medical conditions. Output information: Creates a user profile on the server.

[1386] Step 2:

[1387] The user inputs the behavior-related information and the goal value.

[1388] The user uses the terminal to input behavior-related information and goal values, such as place of residence, place of work, target weight, and target body fat percentage. This information is also sent from the terminal to the server and stored in the database. Input content: place of residence, place of work, target weight, target body fat percentage. Output content: user profile updated on the server.

[1389] Step 3:

[1390] Tracking user behavior patterns

[1391] The device collects GPS data, movement history, and exercise data (number of steps, calories burned, etc.) in real time. The collected data is periodically sent to the server. Input: GPS data, movement history, exercise data. Output: Behavioral pattern records on the server.

[1392] Step 4:

[1393] Compare with external data and analyze

[1394] The server compares the tracked data with external data such as the day of the week and weather, and analyzes the data. Input: Tracking data, day of the week, weather data. Output: Analysis results (behavioral pattern trends).

[1395] Step 5:

[1396] The user inputs their mood and schedule

[1397] The user uses the device to input the mood, planned exercise intensity, and schedule for the day. The input information is sent to the server. Input information: mood, planned exercise intensity, schedule. Output information: record of mood and schedule on the server.

[1398] Step 6:

[1399] Generate a diet plan

[1400] The server generates a diet plan suited to the user based on all the data received. Specifically, this includes the type of exercise and meal menu. Input: Basic attributes, behavioral patterns, mood and schedule. Output: Diet plan.

[1401] Step 7:

[1402] Suggest diet plans to users

[1403] The device notifies the user of the generated diet plan. In a physical store, the plan is displayed in real time on the head-mounted display worn by the user. Input: Diet plan. Output: The plan displayed on the user's head-mounted display.

[1404] Step 8:

[1405] Providing appropriate diet information in real time

[1406] When a user wears a head-mounted display in a physical store such as a supermarket or fitness gym, real-time diet information about products in the store and exercise methods is displayed. Input content: Location information and product information in the store. Output content: Diet information displayed on the head-mounted display.

[1407] 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.

[1408] This invention relates to a "diet motivator" that provides an optimal diet plan tailored to the user's lifestyle and mood on that day, and in particular, is a system that provides a more sophisticated and personalized diet plan by combining it with an emotion engine that recognizes the user's emotions.

[1409] 1. First-time user registration

[1410] When the server starts the system for the first time, the terminal prompts the user to enter basic attributes (age, sex, build, health information, etc.). The user enters age, sex, height, weight, medical history, etc. Next, the terminal prompts the user to enter their place of residence and place of work, and the user enters this information. Furthermore, the terminal prompts the user to enter target values ​​such as target weight and target body fat percentage, and the user enters the target values.

[1411] The terminal sends this input information to the server, and the server stores the received data in a database to create a user profile.

[1412] 2. Information gathering

[1413] To track a user's behavioral patterns, the device collects the user's GPS data, movement history, and exercise data (e.g., number of steps, calories burned) in real time. This data is periodically sent to a server, which then compares the received data with external data such as the day of the week and weather, and analyzes the user's behavioral patterns.

[1414] The device also prompts the user to input their mood, schedule, and planned exercise intensity for the day, allowing the user to input their emotional state (e.g., fatigue, motivation), schedule, and exercise plan for the day. The emotion engine recognizes the user's emotions in real time and sends the data to the server.

[1415] 3. Emotion Engine

[1416] The emotion engine analyzes the user's facial expressions, tone of voice, text input, etc. to recognize the user's emotions. Emotional data is analyzed in combination with the user's behavioral patterns and mood input for the day. For example, if the emotion engine recognizes that the user is tired, that data is sent to the server.

[1417] 4. Proposal

[1418] Based on the data collected and analyzed so far, the server generates a diet plan suited to the user's behavioral patterns, mood of the day, and emotional data. The generated plan creates a specific action plan that takes into account the balance of exercise, meals, and rest, and sends it to the device as suggested data. Specifically, it can suggest exercise menus that match the user's mood and emotions of the day, as well as healthy and economical cooking menus.

[1419] Specific examples

[1420] If a user inputs "I feel tired today" one day and the emotion engine recognizes the tiredness from the user's facial expression, the server will use that data to suggest "light stretching and relaxation exercises." The device will also display a recipe for "chicken and vegetable stew," which is effective in relieving fatigue, based on ingredients in the user's refrigerator. In this way, users can continue their diet without straining themselves in their daily lives.

[1421] This system supports users in continuing a healthy and enjoyable diet through a consistent process from data collection to recommendations. In addition, by combining it with an emotion engine, it provides specific advice based on the user's emotions, helping them achieve their goals without any stress.

[1422] The processing flow will be explained below.

[1423] 1. First-time user registration

[1424] Step 1:

[1425] The device prompts the user to enter basic attributes (age, gender, build, health information, etc.).

[1426] Step 2:

[1427] The user inputs the age, sex, height, weight, medical history, etc. in order.

[1428] Step 3:

[1429] The terminal prompts the user to enter their place of residence and place of work.

[1430] Step 4:

[1431] The user enters their place of residence and place of work.

[1432] Step 5:

[1433] The terminal prompts the user to input target values ​​(target weight, target body fat percentage, etc.).

[1434] Step 6:

[1435] The user inputs a target value.

[1436] Step 7:

[1437] The terminal sends all entered information to the server.

[1438] Step 8:

[1439] The server stores the received data in a database and creates a user profile.

[1440] 2. Information gathering

[1441] Step 1:

[1442] The device collects the user's GPS data, movement history, and exercise data (e.g., number of steps taken, calories burned).

[1443] Step 2:

[1444] The terminal periodically transmits the collected data to the server.

[1445] Step 3:

[1446] The server compares the received data with external data such as the day of the week and weather.

[1447] Step 4:

[1448] The server analyzes the matched data and stores it in a statistical database.

[1449] Step 5:

[1450] The device prompts the user to input their mood, schedule, and exercise plans for the day.

[1451] Step 6:

[1452] The user inputs their emotional state (e.g., fatigue, motivation), their schedule for the day, and their exercise plan.

[1453] Step 7:

[1454] The emotion engine analyzes the user's facial expressions, tone of voice, text input, etc. to recognize emotions.

[1455] Step 8:

[1456] The data collected by the device, user input data, and emotion data recognized by the emotion engine are sent to the server.

[1457] Step 9:

[1458] The server analyzes the received data and models each user's behavioral patterns and tendencies.

[1459] 3. Proposal

[1460] Step 1:

[1461] Based on the data accumulated by the server, a diet plan is generated that is suited to the user's behavioral patterns, mood of the day, and emotional data.

[1462] Step 2:

[1463] The server creates a specific action plan, taking into account the balance of exercise, diet, and rest.

[1464] Step 3:

[1465] The server creates specific advice and suggestions (e.g., today's exercise menu, meal recipes) aimed at the user's goals.

[1466] Step 4:

[1467] The server transmits the created proposal data to the terminal.

[1468] Step 5:

[1469] The device displays healthy and economical lifestyle schedules and cooking menus to the user.

[1470] Step 6:

[1471] The user follows the proposed plan and carries out daily activities.

[1472] Examples:

[1473] One day, if a user types "I feel tired today," and the emotion engine recognizes the user's tiredness from their facial expression, the device will send that data to the server. Based on that data, the server will suggest "light stretching and relaxation exercises." The device will also display a recipe for "chicken and vegetable stew," which is effective in relieving fatigue, based on ingredients in the user's refrigerator. In this way, users can continue their diet without straining themselves in their daily lives.

[1474] Example 2

[1475] 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."

[1476] While conventional diet support systems propose diet plans based on the user's basic attributes and behavioral data, they lack the ability to consider the user's emotional state or mood on that day. This can lead to problems such as users not receiving appropriate support on days when they are tired or unmotivated, making it difficult to continue their diet. Furthermore, because detailed planning tailored to individual users is not possible, general proposals are less effective for some users.

[1477] 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.

[1478] In this invention, the server includes means for inputting a user's basic attributes, means for inputting behavior-related information such as place of residence and place of work, means for inputting target values, means for transmitting the input information, means for saving the transmitted information in a database and creating a user profile, means for tracking the user's behavioral patterns, means for comparing the tracked data with external data such as the day of the week and weather, means for analyzing the compared data, means for prompting the user to input their mood and schedule for the day, an emotion engine for analyzing the user's emotional state, means for transmitting all the collected data and emotion data to the server, means for the server to analyze the received data and generate a diet plan suitable for the user, and means for proposing the generated diet plan to the user. This makes it possible to provide a more personalized and specific diet plan based on the user's emotional state and mood for the day.

[1479] "Basic attributes" refers to basic information about an individual, such as the user's age, sex, height, weight, medical history, etc.

[1480] "Behavior-related information" is information about the user's place of residence, place of work, and behavioral patterns related thereto.

[1481] "Goal value" refers to a specific health goal such as weight or body fat percentage that a user aims to achieve.

[1482] A "user profile" is an individual information set in a database that is created based on input information such as a user's basic attributes, behavior-related information, and goal values.

[1483] A "behavioral pattern" is a series of behavioral trends over a specific period of time, analyzed based on a user's GPS data, movement history, exercise data, etc.

[1484] "External data" is information about the external environment that affects the user's behavior, such as the day of the week and weather.

[1485] An "emotion engine" is a system that has the function of analyzing a user's facial expressions, tone of voice, text input, etc. to recognize their emotional state.

[1486] A "diet plan" is a specific action plan for exercise, meals, rest, etc. that is generated based on the user's behavioral patterns, basic attributes, target values, and emotional state.

[1487] This invention relates to a "diet motivator" that provides an optimal diet plan tailored to the user's lifestyle and mood on that day. In particular, this system provides a more refined and personalized diet plan by combining it with an emotion engine that recognizes the user's emotions.

[1488] The system of the present invention relies primarily on two hardware components: a server and a terminal.

[1489] 1. First-time user registration

[1490] When the terminal starts the system for the first time, it displays a screen prompting the user to enter basic attributes (age, sex, build, health information, etc.). The user enters information such as age, sex, height, weight, and medical history. The terminal then prompts the user to enter their place of residence and place of work, and the user enters that information. The terminal then prompts the user to enter target values ​​such as target weight and target body fat percentage, and the user enters those target values.

[1491] The device sends this input information to the server, which stores the received data in a database and creates a user profile.

[1492] 2. Information gathering

[1493] To track a user's behavioral patterns, the device collects the user's GPS data, movement history, and exercise data (e.g., number of steps, calories burned) in real time. This data is periodically sent to a server, which then compares the received data with external data such as the day of the week and weather, and analyzes the user's behavioral patterns.

[1494] The device also displays a screen prompting the user to input their mood, schedule, and planned exercise intensity for the day. The user can input their emotional state (e.g., fatigue, motivation), schedule, and exercise plan for the day. The emotion engine analyzes the user's facial expression, tone of voice, and text input to recognize their emotional state. The device sends the output of the emotion engine to the server.

[1495] 3. Proposal

[1496] Based on the data collected and analyzed so far, the server generates a diet plan suited to the user's behavioral patterns, mood of the day, and emotional data. The generated plan takes into account the balance of exercise, meals, and rest, and sends the proposed data to the device as a specific action plan. Specifically, it can suggest an exercise menu that matches the user's mood and emotions of the day, as well as a healthy and economical cooking menu.

[1497] Specific examples

[1498] For example, if a user inputs "I feel tired today" one day and the emotion engine recognizes the feeling of fatigue from the user's facial expression, the server will use that data to suggest "light stretching and relaxation exercises." The device will also display a recipe for "chicken and vegetable stew," which is effective in relieving fatigue, based on ingredients in the user's refrigerator. This allows users to continue their diet without straining themselves in their daily lives.

[1499] Prompt Sentence Examples

[1500] "The user enters 'I'm tired today,' and the emotion engine recognizes this state of fatigue. Based on this data, please suggest appropriate exercise and meal plans."

[1501] By inputting such prompt sentences into the generative AI model, the accuracy of the model can be confirmed and the quality of the system can be improved.

[1502] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1503] Step 1: First-time user registration

[1504] Input: User's basic attribute information (age, gender, height, weight, medical history, etc.)

[1505] Specific operation When the terminal starts the system for the first time, it displays a screen prompting the user to enter basic attributes. The user enters the information. The terminal temporarily stores this information.

[1506] Output: Basic attribute information is saved to the device.

[1507] Step 2: Enter your place of residence and work

[1508] Input: User's residence and work location information

[1509] Specific operation: The terminal displays a screen prompting the user to enter residence and workplace information. The user enters the information. The terminal temporarily stores this information.

[1510] Output: Residence and work location information is saved on the device

[1511] Step 3: Enter the target value

[1512] Input: User's goal values ​​such as goal weight and goal body fat percentage

[1513] Specific operation: The device displays a screen prompting the user to input the target value. The user inputs the target value. The device temporarily stores this information.

[1514] Output: The target value is saved to the terminal.

[1515] Step 4: Data submission and user profile creation

[1516] Input: Basic attribute information, residence and workplace information, target value

[1517] Specific operation: The device sends all input information to the server, which stores the received data in a database and creates a user profile.

[1518] Output: The user profile is saved in the database.

[1519] Step 5: Collecting and Sending Dynamic Data

[1520] Input: User's GPS data, movement history, exercise data (number of steps, calories burned, etc.)

[1521] Specific operation: The device uses sensors to collect the user's GPS data, movement history, and exercise data in real time, and transmits the collected data to a server at regular intervals.

[1522] Output: Collected data is sent to a server and stored for analysis.

[1523] Step 6: Analyze behavioral patterns

[1524] Input: Collected dynamic data, external data (day of the week, weather)

[1525] Specific operation: The server compares the collected dynamic data with external data such as the day of the week and weather, and analyzes behavioral patterns.

[1526] Output: Behavioral pattern analysis data

[1527] Step 7: Enter your mood and schedule

[1528] Input: User's mood, schedule for the day, planned exercise intensity

[1529] Specific operation: The device displays a screen prompting the user to input their mood, schedule, and planned exercise intensity. The user inputs this information. The device temporarily stores this information.

[1530] Output: Mood and schedule information is saved on the device

[1531] Step 8: Emotion Analysis with the Emotion Engine

[1532] Input: User facial expression data, tone of voice, text input

[1533] How it works: The emotion engine analyzes the user's facial expressions, tone of voice, and text input to recognize their emotional state, and the device sends the output to the server.

[1534] Output: Emotional state data is sent to the server

[1535] Step 9: Analyze the data and generate a diet plan

[1536] Input: behavioral pattern analysis data, mood and schedule information, emotional state data

[1537] Specific operation: Based on the data collected and analyzed up to now, the server generates a diet plan suited to the user's behavioral patterns, mood of the day, and emotional data.

[1538] Output: The generated diet plan

[1539] Step 10: Inform your diet plan

[1540] Input: Generated diet plan

[1541] Specific operations: The server sends the generated diet plan to the terminal, and the terminal notifies the user of the plan.

[1542] Output: The diet plan notified to the user

[1543] (Application example 2)

[1544] 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."

[1545] Conventional diet plan suggestion systems often make uniform suggestions without considering the user's emotions or mood of the day. This makes it difficult to provide appropriate suggestions that match the user's mental state or daily lifestyle, making it difficult to motivate them to continue dieting. Furthermore, to actually prepare the suggested meal menu, the user must procure ingredients and cook the food themselves, which is time-consuming and labor-intensive.

[1546] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for inputting a user's basic attributes; means for inputting behavior-related information such as a residence and workplace; means for inputting a target value; means for transmitting the input information; means for saving the transmitted information in a database and creating a user profile; means for tracking the user's behavioral patterns; means for comparing the tracked data with external data such as the day of the week and the weather; means for analyzing the compared data; means for prompting the user to input their mood and schedule for the day; means for transmitting all collected data to the server; means for the server to analyze the received data and generate a diet plan suitable for the user; means for proposing the generated diet plan to the user; means including an emotion engine for collecting and analyzing the user's emotional data; means for proposing a meal menu suitable for the user based on the emotional data; and means for providing the meal menu to the user via a food delivery system. This makes it possible to provide a personalized diet plan based on the user's emotions and mood for the day, and the suggested meal menu can be easily ordered, making it easier to continue dieting.

[1547] "Basic attributes of a user" refers to personal information such as the user's age, sex, build, and health information.

[1548] "Behavioral information" refers to information about a user's behavior, including their place of residence, place of work, and daily movements.

[1549] "Target value" refers to a specific numerical target such as weight or body fat percentage that the user aims to achieve.

[1550] "User profile" refers to a comprehensive database entry that includes a user's basic attributes, behavior-related information, goals, etc.

[1551] "Behavioral patterns" refer to specific behavioral tendencies and habits in a user's daily life.

[1552] "External data" refers to relevant information other than the user's own behavior, such as the day of the week and weather.

[1553] "Emotion engine" refers to a function that recognizes a user's emotions by analyzing their facial expressions, tone of voice, and text input.

[1554] A "diet plan" refers to a specific action plan proposed to a user that takes into account a balance of exercise, diet, rest, and other factors.

[1555] "Meal menu" refers to specific meal items suggested based on the user's emotions, mood, and health status.

[1556] A "food delivery system" refers to an online service that allows users to easily order suggested meal menus.

[1557] This invention builds a system that proposes optimal diet plans and meal menus based on the user's emotions and mood of the day, and then actually provides them through a food delivery service. This system is realized by using the following programs, hardware, and software.

[1558] The server includes a means for inputting basic user attributes, a means for inputting behavior-related information such as place of residence and place of work, a means for inputting target values, a means for transmitting the input information, and a means for storing the transmitted information in a database and creating a user profile, thereby enabling centralized management of basic user information.

[1559] The server also includes a means for tracking the user's behavioral patterns, a means for comparing the tracked data with external data such as the day of the week and weather, and a means for analyzing the compared data, thereby collecting and analyzing detailed data about the user's daily life.

[1560] Furthermore, the server includes a means for allowing the user to input the mood and schedule of the day, a means for transmitting all the collected data to the server, a means for the server to analyze the received data and generate a diet plan suitable for the user, and a means for proposing the generated diet plan to the user, thereby enabling personalized suggestions to be made to each individual user.

[1561] The server further includes means for including an emotion engine that collects and analyzes emotion data of the user, means for suggesting a meal menu suitable for the user based on the emotion data, and means for providing the meal menu to the user via a food delivery system, so that the user can easily order the suggested meal menu and actually receive the meal through the food delivery service.

[1562] For example, if a user inputs "I'm tired today," and the emotion engine recognizes the same, the server will suggest light meal options such as "chicken soup" or "vegetable salad." Users can easily check these options within the app and request delivery by simply pressing the order button.

[1563] An example of a prompt to input to a generative AI model is as follows:

[1564] "Please suggest a healthy menu when the user feels tired. User information: age, gender, physique, health information, goal value. Emotion: fatigue."

[1565] The hardware used includes a cloud server, and the software includes Flask (Python) and a database (e.g., SQLite or PostgreSQL).

[1566] In this way, personalized diet plans and meal menus that reflect the user's emotions and mood of the day can be proposed and actually provided through a food delivery system, which will encourage users to continue their diet and improve the quality of their daily lives.

[1567] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1568] Step 1:

[1569] When the server starts the system for the first time, the terminal prompts the user to enter basic attributes (age, gender, build, health information, etc.). The user enters this information into the terminal, and the terminal sends the received information to the server. The server stores the received data in a database and creates a user profile.

[1570] Step 2:

[1571] The device prompts the user to enter activity-related information such as their place of residence and place of work. The user enters this information into the device, which then transmits the information to the server. The server stores the received data in a database and updates the user profile.

[1572] Step 3:

[1573] The device prompts the user to input goals (e.g., target weight or target body fat percentage). The user inputs the goals, and the device sends the input data to the server. The server stores the received goal data in a database and integrates it into the user profile.

[1574] Step 4:

[1575] The device collects GPS data, movement history, and exercise data (e.g., number of steps, calories burned) in real time to track the user's behavior. This data is periodically sent to a server, which stores the received data in a database.

[1576] Step 5:

[1577] The server compares the tracked data with external data such as the day of the week and weather, and analyzes the matched data. This allows the user's behavioral patterns to be understood. The analysis results are stored in a database.

[1578] Step 6:

[1579] The device provides an interface for the user to input the user's mood and schedule for the day. The user inputs the information, and the device sends it to the server. The server analyzes the received data and integrates it into the user profile.

[1580] Step 7:

[1581] The server uses an emotion engine to recognize the user's emotions in real time from facial expressions, tone of voice, and text input, and the emotion data is stored in a database.

[1582] Step 8:

[1583] The server uses a generative AI model based on the data collected and analyzed to generate a diet plan suited to the user. This calculation uses prompt statements and inputs the user's emotions and behavioral data. The generated diet plan is saved in a database as a specific action plan.

[1584] Step 9:

[1585] The server transmits the generated diet plan to the user's terminal as proposal data, and the terminal displays the received proposal data to the user, allowing the user to confirm the plan.

[1586] Step 10:

[1587] The server proposes a meal menu suitable for the user based on the user's emotional data. This meal menu is provided to the user via the food delivery system and is generated using an emotion engine and a generative AI model. The user can check the proposed menu through their device and easily order.

[1588] 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.

[1589] 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.

[1590] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1591] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1592] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1593] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1594] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1595] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1596] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1597] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1598] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1599] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1600] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1601] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1602] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1603] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1604] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1605] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1606] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1607] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1608] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1609] The following is further disclosed regarding the above embodiment.

[1610] (Claim 1)

[1611] a means for inputting basic attributes of a user;

[1612] a means for inputting activity-related information such as place of residence and place of work;

[1613] a means for inputting a target value;

[1614] means for transmitting the input information;

[1615] means for storing the transmitted information in a database and creating a user profile;

[1616] a means for tracking user behavior patterns;

[1617] A means of matching tracked data with external data such as day of the week or weather;

[1618] means for analyzing the collated data;

[1619] A means for allowing a user to input their mood and schedule for the day;

[1620] means for transmitting all of the collected data to a server;

[1621] A means for the server to analyze the received data and generate a diet plan suitable for the user;

[1622] means for proposing the generated diet plan to a user;

[1623] A system including:

[1624] (Claim 2)

[1625] 2. The system according to claim 1, further comprising means for suggesting healthy and economical cooking menus to the user based on the user's behavioral patterns.

[1626] (Claim 3)

[1627] 2. The system according to claim 1, further comprising means for suggesting an exercise plan according to the user's mood and schedule for that day.

[1628] "Example 1"

[1629] (Claim 1)

[1630] a means for inputting basic attributes of a user;

[1631] a means for inputting activity-related information such as place of residence and place of work;

[1632] a means for inputting a target value;

[1633] means for transmitting the input information;

[1634] means for storing the transmitted information in a database and creating a user profile;

[1635] a means for tracking user behavior patterns;

[1636] A means of matching tracked data with external data such as day of the week or weather;

[1637] means for analyzing the collated data;

[1638] A means for allowing a user to input their mood and schedule for the day;

[1639] means for transmitting all of the collected data to a server;

[1640] A means for the server to analyze the received data and generate a diet plan suitable for the user using a generative AI model;

[1641] means for generating a prompt message for proposing the generated diet plan to a user and displaying the prompt message on a user terminal;

[1642] A system including:

[1643] (Claim 2)

[1644] 2. The system according to claim 1, further comprising means for suggesting healthy and economical cooking menus to the user based on the user's behavioral patterns.

[1645] (Claim 3)

[1646] 2. The system according to claim 1, further comprising means for suggesting an exercise plan according to the user's mood and schedule for that day.

[1647] "Application Example 1"

[1648] (Claim 1)

[1649] a means for inputting basic attributes of a user;

[1650] a means for inputting activity-related information such as place of residence and place of work;

[1651] a means for inputting a target value;

[1652] means for transmitting the input information;

[1653] means for storing the transmitted information in a database and creating a user profile;

[1654] a means for tracking user behavior patterns;

[1655] A means of matching tracked data with external data such as day of the week or weather;

[1656] means for analyzing the collated data;

[1657] A means for allowing a user to input their mood and schedule for the day;

[1658] means for transmitting all of the collected data to a server;

[1659] A means for the server to analyze the received data and generate a diet plan suitable for the user;

[1660] means for proposing the generated diet plan to a user;

[1661] A means for providing appropriate diet information in real time through a display device worn by a user in a physical store;

[1662] A system including:

[1663] (Claim 2)

[1664] 2. The system according to claim 1, further comprising means for suggesting healthy and economical cooking menus to the user based on the user's behavioral patterns.

[1665] (Claim 3)

[1666] 2. The system according to claim 1, further comprising means for suggesting an exercise plan according to the user's mood and schedule for that day.

[1667] "Example 2: Combining Emotion Engines"

[1668] (Claim 1)

[1669] a means for inputting basic attributes of a user;

[1670] a means for inputting activity-related information such as place of residence and place of work;

[1671] a means for inputting a target value;

[1672] means for transmitting the input information;

[1673] means for storing the transmitted information in a database and creating a user profile;

[1674] a means for tracking user behavior patterns;

[1675] A means of matching tracked data with external data such as day of the week or weather;

[1676] means for analyzing the collated data;

[1677] A means for allowing a user to input their mood and schedule for the day;

[1678] an emotion engine that analyzes the user's emotional state;

[1679] means for transmitting all collected data and emotion data to a server;

[1680] A means for the server to analyze the received data and generate a diet plan suitable for the user;

[1681] means for proposing the generated diet plan to a user;

[1682] A system including:

[1683] (Claim 2)

[1684] 2. The system according to claim 1, further comprising means for suggesting healthy and economical cooking menus to the user based on the user's behavioral patterns.

[1685] (Claim 3)

[1686] 2. The system according to claim 1, further comprising means for suggesting an exercise plan according to the user's mood and schedule for that day.

[1687] (Claim 4)

[1688] 10. The system according to claim 1, further comprising means for proposing a specific action plan according to the user's emotional state based on the data obtained from the emotion engine.

[1689] "Application example 2 when combining emotion engines"

[1690] (Claim 1)

[1691] a means for inputting basic attributes of a user;

[1692] a means for inputting activity-related information such as place of residence and place of work;

[1693] a means for inputting a target value;

[1694] means for transmitting the input information;

[1695] means for storing the transmitted information in a database and creating a user profile;

[1696] a means for tracking user behavior patterns;

[1697] A means of matching tracked data with external data such as day of the week or weather;

[1698] means for analyzing the collated data;

[1699] A means for allowing a user to input their mood and schedule for the day;

[1700] means for transmitting all of the collected data to a server;

[1701] A means for the server to analyze the received data and generate a diet plan suitable for the user;

[1702] means for proposing the generated diet plan to a user;

[1703] means including an emotion engine for collecting and analyzing user emotion data;

[1704] means for proposing a meal menu suitable for the user based on the emotion data;

[1705] means for providing the meal menu to a user via a food delivery system;

[1706] A system including:

[1707] (Claim 2)

[1708] 2. The system according to claim 1, further comprising means for suggesting healthy and economical cooking menus to the user based on the user's behavioral patterns.

[1709] (Claim 3)

[1710] 2. The system according to claim 1, further comprising means for suggesting an exercise plan according to the user's mood and schedule for that day. [Explanation of symbols]

[1711] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a means for inputting basic attributes of a user; a means for inputting activity-related information such as place of residence and place of work; a means for inputting a target value; means for transmitting the input information; means for storing the transmitted information in a database and creating a user profile; a means for tracking user behavior patterns; A means of matching tracked data with external data such as day of the week or weather; means for analyzing the collated data; A means for allowing a user to input their mood and schedule for the day; means for transmitting all of the collected data to a server; A means for the server to analyze the received data and generate a diet plan suitable for the user; means for proposing the generated diet plan to a user; A system including:

2. The system according to claim 1, further comprising means for suggesting healthy and economical cooking menus to the user based on the user's behavioral patterns.

3. The system according to claim 1, further comprising means for suggesting an exercise plan according to the user's mood and schedule for that day.

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