system

Abstract

We provide the system. [Solution] A means of providing personalized learning plans based on user characteristics and goals, and tracking progress. A method for managing users' time and improving work efficiency using the Pomodoro Technique, A means of providing users with customized reminders through visual or auditory means, A means of visualizing the user's completed tasks and progress, An automated feedback system that analyzes the user's task history and suggests the next action, A system that includes this.

Description

【Technical Field】 【0001】 The technology of the present disclosure relates to a system. 【Background Art】 【0002】 Patent Document 1 discloses a persona chatbot control method performed by at least one processor, the method including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, 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 Application Laid-Open No. 2022-180282 【Summary of the Invention】 【Problems to be Solved by the Invention】 【0004】 There is a problem that individuals with attention deficit or hyperactivity, or people lacking confidence in concentration or memory, cannot effectively perform task management in daily life, and as a result, feel stress and a lack of a sense of achievement. Existing notebooks and reminder apps cannot completely solve this problem, and more effective support tailored to individual needs is required. 【Means for Solving the Problems】 【0005】 This invention solves this problem by providing a means to offer a personalized learning plan based on the user's characteristics and goals, and to track its progress. Furthermore, by combining it with a time management method using the Pomodoro Technique, it improves the user's time management and work efficiency. By providing customized visual or audible reminders, users can complete important tasks without forgetting them. It also visualizes the user's task completion and progress, allowing them to feel a sense of accomplishment. In addition, it provides an automated feedback means that analyzes the user's task history and suggests the next action, promoting continuous improvement. Thus, this invention realizes a new task management system that is suitable for professional needs. 【0006】 "User" refers to an individual who uses this system, and includes, but is not limited to, people with attention deficit or hyperactivity traits. 【0007】 "Characteristics" refer to the user's behavioral and personality traits, and include elements used to personalize the services provided by the agent. 【0008】 A "goal" is a specific outcome or growth that the user wants to achieve, and it represents the ultimate target towards which the agent's support will be directed. 【0009】 A "personalized learning plan" refers to a plan that provides a learning schedule and content optimized for the individual user's characteristics and goals. 【0010】 "Means of tracking progress" refers to features that record and analyze users' activities and learning progress. 【0011】 The "Pomodoro Technique" is a time management method that involves repeating a cycle of 25 minutes of work followed by a 5-minute break to improve concentration. 【0012】 "Time management methods" refer to methods and tools for efficiently scheduling users' activities and effectively utilizing their time. 【0013】 A "reminder" refers to a visual or audio message used to notify a user of important tasks or schedules. 【0014】 "Task completion rate" refers to an indicator that shows the status of tasks that a user has in progress or has completed. 【0015】 "Means of visualizing progress" refers to functions that display completed tasks and related information using graphs, charts, etc. 【0016】 "Automated feedback mechanisms" refer to features that analyze users' past behavioral data and suggest improvements or next actions. 【0017】 "Task history" refers to a record of tasks that a user has entered or completed in the past. [Brief explanation of the drawing] 【0018】 [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7]It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined. 【Mode for Carrying Out the Invention】 【0019】 Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings. 【0020】 First, the language used in the following description will be explained. 【0021】 In the following embodiments, the signed processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Furthermore, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include CPU (Central Processing Unit), GPU (Graphics Processing Unit), GPGPU (General-Purpose computing on Graphics Processing Units), and APU (Accelerated Processing Unit). 【0022】 In the following embodiments, signed RAM (Random Access Memory) is a memory that temporarily stores information and is used as work memory by the processor. 【0023】 In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes. 【0024】 In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark). 【0025】 In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or." 【0026】 [First Embodiment] 【0027】 Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment. 【0028】 As shown in Figure 1, the 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. 【0029】 The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network). 【0030】 The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52. 【0031】 The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and 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. 【0032】 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 perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor. 【0033】 Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54. 【0034】 Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14. 【0035】 As shown in Figure 2, in the data processing device 12, a specific processing 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" related to the technology of this 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 according to the specific processing program 56 executed on the RAM 30. 【0036】 The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. 【0037】 In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48. 【0038】 Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal". 【0039】 The system according to the present invention realizes an AI agent that provides personalized learning plans and task management support to users, including individuals with attention deficit or hyperactivity. Its components and specific processes are shown below. 【0040】 First, the user accesses the system from their terminal and creates a user profile by entering user information. The server receives this input information and configures a database tailored to the user's characteristics and goals. This enables specialized support for individual users. 【0041】 Next, users can register their daily tasks through their device. The device sends this task information to the server, which then processes the received task information. This includes the automatic generation of schedules using the Pomodoro Technique, enabling users to manage their time efficiently. 【0042】 Furthermore, the system provides users with visual or audio reminders. The server creates and sends reminder information to the device according to a set schedule, ensuring users don't forget important tasks. This makes it easier for users to prioritize and manage their tasks. 【0043】 It also has a function to visualize user progress. The server collects data on tasks completed by the user and generates charts and graphs to visually display the progress. By sending this information to the terminal, users can easily check their level of achievement and maintain their motivation. 【0044】 In addition, the system provides automated feedback based on the user's activity history. The server analyzes past task history and suggests areas for improvement and actions to take next. This allows users to constantly review their work and strive for improvement. 【0045】 Through the mechanisms described above, this system strongly supports efficient task management and self-improvement for users with attention deficit or hyperactivity. This allows for flexible responses tailored to individual characteristics and effectively solves challenges in daily life. 【0046】 The following describes the processing flow. 【0047】 Step 1: 【0048】 The user accesses the system using their device and opens the initial setup screen. The user then enters information about their characteristics and goals. 【0049】 Step 2: 【0050】 The terminal sends the entered user information to the server. The server receives this information, saves it to a database, and creates a user profile. 【0051】 Step 3: 【0052】 Users register their daily tasks on their device screen. They enter necessary information such as task name, priority, deadline, and estimated time required. 【0053】 Step 4: 【0054】 The terminal sends registered task information to the server. Based on this, the server automatically generates a task schedule utilizing the Pomodoro Technique. 【0055】 Step 5: 【0056】 The server sends the generated schedule data to the terminal. The terminal visually displays the schedule to the user and shows a start button. 【0057】 Step 6: 【0058】 The user presses the start button on the device to begin the Pomodoro timer. The device starts a 25-minute work timer. 【0059】 Step 7: 【0060】 After the timer ends, the device will prompt the user to take a 5-minute break. After the break, the user can choose whether to start the next work session. 【0061】 Step 8: 【0062】 The server sends a reminder notification to the device based on a pre-set time. The device then notifies the user visually or audibly. 【0063】 Step 9: 【0064】 The server periodically compiles information on completed tasks by users. It creates charts and graphs to visualize progress. 【0065】 Step 10: 【0066】 The server sends the generated visual data to the terminal. The terminal then displays this to the user and prompts them to check the progress. 【0067】 Step 11: 【0068】 The server analyzes the user's task history and automatically generates feedback for the user regarding the next action and areas for improvement. The terminal then provides this feedback to the user. 【0069】 (Example 1) 【0070】 Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal." 【0071】 Many modern users face daily difficulties with time management. This includes users with attention deficit or hyperactivity, for whom specialized support is essential. Furthermore, these users need means to improve the efficiency of their daily lives through effective visualization of task prioritization and progress management. However, current systems fail to address individual needs and only offer general support, creating a strong demand for technologies that address the specific challenges of individual users. 【0072】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. 【0073】 In this invention, the server includes means for providing a personalized learning plan based on the user's characteristics and goals and tracking progress; means for improving the user's work efficiency using time management technology; and means for providing user-specific notifications visually or audibly. This enables flexible support tailored to the user's individual characteristics, facilitating efficient task management and promoting self-improvement. 【0074】 A "user" refers to an individual or group that uses the system for task management or time management. 【0075】 "Characteristics" refer to elements that indicate a user's individual personality, abilities, and behavioral patterns. 【0076】 A "goal" is a specific result or objective that a user sets with the aim of achieving it. 【0077】 "Time management techniques" refer to methods and techniques for efficiently allocating work time and break time. 【0078】 A "notification" is a message or signal that a system uses to inform a user of a reminder or a change in circumstances. 【0079】 "Progress status" refers to the extent to which a user has achieved their set tasks or goals. 【0080】 An "automatic response system" refers to a function that allows a system to provide appropriate feedback based on user input and circumstances. 【0081】 This invention provides a system that supports task management and time management tailored to the user's characteristics. The system is primarily based on the transmission and reception of information between a server, a terminal, and the user. 【0082】 Users enter basic information and set characteristics and goals using a terminal. This information is sent to the server. Based on this information, the server creates a user profile and generates personalized learning plans and task plans. The server is equipped with machine learning algorithms and database management software for advanced data processing and schedule generation. 【0083】 Users input their daily tasks from their device, and once this information is sent to the server, the server creates a schedule using the Pomodoro Technique. Based on this schedule, reminders are sent through the device at appropriate times. Visual notifications are provided through the device's user interface, while audio notifications are provided through an additional audio output device. 【0084】 The server also aggregates data on the user's completed tasks and generates charts and graphs to visualize progress. These are sent to the terminal, allowing the user to easily check their progress. Furthermore, the server analyzes the user's task history and uses an automated response function to suggest actions to take next and areas for improvement. 【0085】 For example, if a user sets the goal of "preparing for next week's project meeting," the server will generate a learning plan and task schedule based on this goal. Furthermore, by using the generative AI model and entering a prompt such as "create a personalized task management plan for a user with attention deficit or hyperactivity," the system will provide the user with the most suitable support plan. 【0086】 This system allows users to achieve flexible task management based on their own characteristics and goals, thereby improving efficiency in their daily lives. 【0087】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0088】 Step 1: 【0089】 Users input basic information, characteristics, and goals through their devices. This information is sent to the server. The server creates a user profile based on the received input data and constructs individual databases tailored to the user's characteristics and goals. This profile contains basic data for personalizing learning plans based on the user's needs. 【0090】 Step 2: 【0091】 Users input their daily tasks and events from their terminals. This information is sent to the server. The server uses this task information to automatically generate a schedule using the Pomodoro Technique. It performs data calculations that take into account the time required and deadlines of the entered tasks, and efficiently allocates work time and break time. The resulting schedule is then sent to the user's terminal. 【0092】 Step 3: 【0093】 The server creates reminders for the user based on the generated schedule. Reminder information is provided to the user in visual and audio formats. The device displays the reminder at the set time and issues an alert via the audio output device. Specifically, it displays a notification on the screen saying, "You have 10 minutes until your next task starts." 【0094】 Step 4: 【0095】 The server aggregates tasks completed by users and generates charts and graphs to visualize their progress. The server receives a list of completed tasks and their estimated time spent as input data. The server analyzes this data and creates graphs showing progress rates and results. These graphs are sent to the user's terminal, allowing them to easily check their own achievements. 【0096】 Step 5: 【0097】 The server analyzes the user's task history and generates feedback using an automated response function. Based on past task data, it performs data calculations to identify trends and areas for improvement, and suggests actions to take next. This feedback is displayed on the terminal, providing the user with specific advice such as, "We recommend adding 30 minutes to your next task." 【0098】 (Application Example 1) 【0099】 Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal." 【0100】 Individuals with attention deficit or hyperactivity often struggle with daily task management and the execution of learning plans, requiring improvements in time management and work efficiency. Furthermore, methods are needed to help users maintain sustained motivation through support within the home. Therefore, flexible responses tailored to individual characteristics and support methods utilizing home automation equipment are essential. 【0101】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. 【0102】 This invention includes a server that provides a personalized learning plan based on the user's characteristics and goals and tracks progress; a server that manages the user's time and improves work efficiency using the Pomodoro Technique; and a server that interacts with the user through home automation equipment and assists the user in managing tasks through voice and visual displays. This enables users with attention deficit or hyperactivity to effectively manage their tasks and solve everyday challenges with efficient support in a home environment. 【0103】 A "user" is an individual who utilizes this system, possesses characteristics such as inattention deficit or hyperactivity, and requires efficient task management and learning plan provision. 【0104】 "Household automated devices" are automated devices used in a home environment that interact with the user and assist with task management using visual and auditory means. 【0105】 A "personalized learning plan" is an educational plan individually optimized based on the user's characteristics and goals, and aims to enable users to learn effectively through progress tracking. 【0106】 The "Pomodoro Technique" is a time management method that improves the user's concentration and work efficiency by repeating a fixed work period and break period. 【0107】 "Audio and visual displays" refer to means of facilitating user interaction, including voice instructions and information presentation, as well as visual notifications and reminders. 【0108】 Task management is a process that supports users in planning and executing their daily activities and goal achievements, guiding them while considering efficiency and priorities. 【0109】 This invention provides a system to support personalized learning plans and task management based on user characteristics. Users interact with the system through a home automated device using an interface that utilizes voice and visual displays. 【0110】 The server generates personalized learning plans based on user information, supporting the achievement of individual goals. Specifically, it uses a database to analyze user characteristics and goals, and proposes optimal tasks and schedules. This allows users to effectively execute their learning plans and track their progress. 【0111】 Furthermore, the server utilizes the Pomodoro Technique to efficiently manage the user's work and rest periods, improving work efficiency. The terminal sends visual or audio reminders to the user to help them remember and complete important tasks. 【0112】 Home automation devices use voice recognition software to understand user instructions and provide appropriate feedback. For example, if a user says, "Set up a Pomodoro schedule for tomorrow's meeting," the home automation device sends the information to a server, which generates a schedule and sends it to the device. 【0113】 Furthermore, the server utilizes a generative AI model to analyze the user's behavioral history and provide feedback on the optimal next action to take. This allows users to continuously improve their task management skills. An example of an input prompt for the generative AI model is, "Please provide a detailed example of how to create a personalized learning plan specifically for a student with attention deficit using the Pomodoro Technique." 【0114】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0115】 Step 1: 【0116】 The user gives voice commands through a home automated device. These voice commands are first captured by the device and converted into text format using speech recognition software. The input is voice data, and the output is text data. 【0117】 Step 2: 【0118】 The device sends the converted text data to the server. The server uses this text data to verify the user profile and, referencing a database tailored to the user's characteristics and goals, creates a personalized learning plan or task schedule. The input is the user profile, and the output is a personalized learning plan or task schedule. 【0119】 Step 3: 【0120】 The server sends the generated personalized task schedule to the home automation device. The home automation device presents this schedule to the user visually or audibly and sets timely reminders. The input is the generated schedule data, and the output is the visual / audio reminders to the user. 【0121】 Step 4: 【0122】 When a user completes a task, they send that information back to the server via a home automated device. The server aggregates this completion information and visualizes the user's progress. The input is data on completed tasks, and the output is charts and graphs representing the progress. 【0123】 Step 5: 【0124】 The server uses a generative AI model to analyze user behavior history data. Based on this analysis, it generates optimal actions and feedback to be taken next, and notifies the user through home automated devices. The input is behavior history data, and the output is feedback including improvement suggestions. 【0125】 The above are the specific processing steps for implementing this invention. 【0126】 Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions. 【0127】 This invention combines an emotion engine with an AI agent that supports personalized learning plans and task management based on the user's characteristics and goals, thereby enabling support that also takes the user's emotional state into account. The specific configuration and processing are shown below. 【0128】 Users access the system from their devices and input information about their characteristics, goals, and current emotional state. This information is received by the server and recorded in a database as a user profile. Furthermore, the emotion engine analyzes the user's input and daily activities to estimate their emotional state. 【0129】 This emotion engine allows the server to generate personalized learning plans based on the user's emotions. For example, if a user is feeling stressed, it can suggest content that promotes relaxation or tasks that are easier to manage. Task schedules based on the Pomodoro Technique are also adjusted to take the user's emotional state into account. 【0130】 Reminder notifications are delivered based on information from the emotion engine, tailored to the user's state in terms of timing and content. For example, if the user is fatigued, reminders are scheduled flexibly, prioritizing only important tasks. 【0131】 User progress data is regularly compiled and visualized along with changes in emotions. This allows users to track their work efficiency and mental health over time. The server also uses this data for long-term analysis and provides feedback on the user's mental health. 【0132】 For example, if a user feels anxious about the progress of their learning plan, the server uses an emotion engine to identify the user's emotions and readjust the task priorities and schedules to reduce the user's burden and provide reassurance. 【0133】 With the above configuration, this system provides support that comprehensively considers the user's emotional state, enabling more effective learning and task management. 【0134】 The following describes the processing flow. 【0135】 Step 1: 【0136】 Users log into the system via their device and input information about their characteristics, goals, and current emotional state. This information is collected by the emotion engine for analysis. 【0137】 Step 2: 【0138】 The terminal sends input information to the server. The server receives this information and stores it in the database as a user profile. Additionally, the emotion engine analyzes the user's emotional state and updates the necessary data. 【0139】 Step 3: 【0140】 The server automatically generates a learning plan and task schedule tailored to the user based on the analysis results of the emotion engine. During this process, the workload of the tasks is adjusted according to the user's emotional state. 【0141】 Step 4: 【0142】 The server sends the generated learning plan and schedule to the device. The device then presents this to the user and notifies them that they are ready to begin. 【0143】 Step 5: 【0144】 Once the user begins working on the device, the emotion engine continuously monitors the user's input and actions and evaluates their emotional state. A Pomodoro timer is then activated on the device to support time management based on emotions. 【0145】 Step 6: 【0146】 The server generates a reminder optimized for timing and content based on the user's emotional state. The reminder information is sent to the device, which then presents it to the user. 【0147】 Step 7: 【0148】 The server periodically compiles user progress and visualizes it along with emotional fluctuations. This allows users to monitor their own progress and mental health status. 【0149】 Step 8: 【0150】 The server analyzes the user's long-term task history and sentiment data to generate feedback. This feedback is sent to the terminal and presented to the user, providing suggestions for the next steps and improvements. 【0151】 (Example 2) 【0152】 Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal." 【0153】 In today's world, it has become increasingly difficult for users to learn efficiently and effectively under various circumstances. In particular, the effectiveness of learning plans can be significantly reduced when influenced by the emotional state of individual learners, such as stress. Furthermore, flexible responses to emotional changes are required even in task management outside of learning. Therefore, individualized support that comprehensively considers the user's characteristics, goals, and emotional state is necessary, but conventional systems are not adequately able to address this, and a more flexible and effective solution is needed. 【0154】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. 【0155】 In this invention, the server includes means for providing an individualized educational plan based on the user's characteristics, goals, and emotional state; means for estimating the user's mental state using an emotion analysis engine and providing information based thereon; and means for optimizing the user's work efficiency by using time management technology. This enables personalized learning support and emotional care that meets the individual needs of the user. 【0156】 A "user" is an individual or group that utilizes the system, inputting their characteristics, goals, and emotional state into the system and receiving support based on that information. 【0157】 "Characteristics" refer to the individual attributes and tendencies of a user, and the factors that influence their learning style and how they respond. 【0158】 A "goal" is a specific objective or desired outcome that the user aims to achieve, and it serves as the basis for determining the direction of the plans and tasks provided by the system. 【0159】 "Emotional state" refers to information that indicates the type and intensity of emotions a user experiences at a particular point in time, and includes various psychological elements such as stress, fatigue, and anxiety. 【0160】 An "individualized learning plan" is a plan that proposes learning methods and schedules optimized for each individual based on the user's characteristics, goals, and emotional state. 【0161】 A "sentiment analysis engine" refers to a technology or algorithm that analyzes user input information and activity history to estimate the user's emotional state. 【0162】 "Time management techniques" refer to methods and technologies that optimize users' work schedules and support efficient time management. 【0163】 "Work efficiency" is an indicator that shows how effectively a user can complete a task within a set time. 【0164】 A "notification function" is a system feature that informs users of important tasks or events. 【0165】 A "reminder" refers to a message or alert that prompts a user to take action by notifying them of the progress of scheduled tasks or appointments. 【0166】 "Feedback" refers to information and evaluations provided to users to help them better understand their own actions and results. 【0167】 "Visualization" is the process of making it easier for users to understand the situation by visually displaying their progress and changes in emotions. 【0168】 This invention is initiated when a user accesses it through a device. The user inputs data about their characteristics, goals, and emotional state. This information is transmitted from various devices such as tablets, smartphones, or computers. The input data is sent to a central server via the internet. 【0169】 The server creates and records a user-specific profile in a database based on data received from the user. This profile is analyzed by an emotion analysis engine that uses natural language processing and machine learning techniques, known as a generative AI model. The emotion analysis engine estimates the user's specific emotional state (e.g., stress, anxiety, fatigue) and generates a personalized learning plan based on the results. 【0170】 One of the key elements of this system is time management technology. Specifically, the server incorporates techniques such as the Pomodoro Technique to provide users with an optimized work schedule. This allows users to allocate their time efficiently and concentrate on learning and tasks. 【0171】 The notification function is also an important feature of this system, allowing users to receive reminders at the appropriate time. Reminders are adjusted to be sent at the right moment, taking into account the user's current emotional state. 【0172】 Furthermore, the server provides a dashboard to visualize the user's progress and emotional changes. This dashboard serves as a tool for users to monitor their learning efficiency and mental well-being in real time. 【0173】 For example, if a user feels anxious while monitoring their learning plan progress, the server uses an emotion analysis engine to identify that emotion and dynamically readjusts the priority and schedule of corresponding tasks. This allows the user to learn with peace of mind without feeling overwhelmed. 【0174】 By inputting prompts like the following into the AI ​​model, you can obtain more specific countermeasures and plans: 【0175】 "Propose an appropriate learning plan for users with high stress levels." 【0176】 "Please create a task schedule that takes my current emotional state into consideration." 【0177】 "How can I visualize user progress and emotional changes?" 【0178】 In this way, this system addresses the diverse needs of users and realizes a better learning environment and efficient task management. 【0179】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0180】 Step 1: 【0181】 Users access the system using a terminal and input information about their characteristics, goals, and emotional state. This input is in text format and is obtained by users entering specific numbers or text into input fields on the application. The entered data is sent to the server immediately. 【0182】 Step 2: 【0183】 The server stores information received from users in a database. The database updates individual user profiles with the latest information, ensuring consistent user data management. Input is user information (traits, goals, emotional state), and output is the updated user profile data. 【0184】 Step 3: 【0185】 The server activates the sentiment analysis engine based on the received data. The sentiment analysis engine analyzes the user's emotional state using natural language processing and machine learning techniques. In this process, it analyzes the input text data and outputs an emotion score. Specifically, it generates a numerical emotion index based on a standard model used by the scoring algorithm. 【0186】 Step 4: 【0187】 The server generates a personalized learning plan optimized for the user based on the results of the emotion analysis engine. Here, the learning plan is adjusted according to the user's emotional state to reduce stress and improve concentration. The input is the emotion score and user goals, and the output is a personalized learning plan. This plan includes actions such as suggesting specific tasks and their order. 【0188】 Step 5: 【0189】 The server creates reminder schedules and adjusts them based on the user's emotional state. Specifically, it sets appropriate reminder timings for the user's situation and manages them adaptively to avoid excessive notifications. The inputs are emotional state and task priority, and the output is an optimized reminder schedule. 【0190】 Step 6: 【0191】 The server visualizes progress and emotional changes, generating a user-friendly dashboard. Here, graphs and charts are used to visualize data, allowing users to track their progress and mental health. Inputs are progress and emotional data, and output is the visual information displayed as a dashboard. 【0192】 Step 7: 【0193】 The server analyzes users' long-term data and provides feedback. This process involves trend analysis based on historical data, pointing out areas for improvement and successful practices to the user. The input is cumulative data, and the output is a feedback report. This facilitates self-improvement and adaptive learning for the user. 【0194】 (Application Example 2) 【0195】 Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal". 【0196】 In today's busy lifestyle, providing personalized task management and learning plans tailored to individual characteristics and emotional states is crucial. However, existing systems struggle to respond flexibly to users' emotions, limiting the effectiveness of life support through integration with machines. Therefore, the challenge lies in providing a system that enables appropriate support in response to users' emotions. 【0197】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. 【0198】 In this invention, the server includes means for providing a personalized learning plan based on the user's characteristics and goals and tracking progress; means for estimating the user's emotional state and adjusting the learning plan and task schedule accordingly; and means for coordinating with household appliances to provide the user with suggestions to promote relaxation. This enables flexible task management and life support that responds to the user's emotions. 【0199】 A "user" refers to an individual who uses a system or service. 【0200】 "Characteristics" refer to the individual characteristics of a user, such as their personality, behavioral patterns, and preferences. 【0201】 "Goals" refer to the specific results or objectives that users want to achieve. 【0202】 A "personalized learning plan" refers to a learning plan specifically designed to suit each user's individual characteristics and goals. 【0203】 "Progress" indicates the current status of achievement towards the goals set by the user. 【0204】 The "Pomodoro Technique" is a time management method that involves repeating a cycle of work followed by breaks to improve work efficiency. 【0205】 "Work efficiency" refers to a user's ability to achieve high results in a short amount of time on a given task. 【0206】 A "reminder" refers to a notification function that periodically informs users of necessary information. 【0207】 "Visualization" refers to clearly displaying a user's progress and task history using graphs, charts, and other visual aids. 【0208】 "Feedback" refers to suggesting further improvements or next actions based on the user's behavior and results. 【0209】 "Emotional state" refers to the user's current psychological or emotional state. 【0210】 "Household machinery and equipment" refers to devices such as robots and smart devices used within the home. 【0211】 "Relaxation" refers to a state or activity that allows users to reduce stress and refresh their mind and body. 【0212】 A system for implementing this invention consists of a user terminal, a server, and a household appliance. 【0213】 Users use their devices to input their characteristics, goals, and current emotional state. This information is sent to the server and recorded in the database as a user profile. 【0214】 Based on this profile, the server uses a generative AI model to create a personalized learning plan for each user. It also uses an emotion engine to estimate emotions from user input and behavior, and adjusts the plan and task schedule accordingly. In this process, it analyzes changes in emotion using Google Cloud AI's emotion recognition API. 【0215】 Furthermore, the server interacts with home appliances and makes suggestions to promote relaxation when the user needs it. For example, if the user is feeling tired, it might play music or adjust the room temperature to a comfortable level. Such home appliances include common robots and smart home devices. 【0216】 For example, if a user feels that they are behind schedule to meet their monthly target, the server can use the prompt message "How to reduce stress" to suggest appropriate relaxation methods from home-use devices and adjust the user's work environment accordingly. 【0217】 In this embodiment, the system provided by the server enables flexible task management and life support tailored to the user's emotions and characteristics. 【0218】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0219】 Step 1: 【0220】 The user uses a terminal to input their characteristics, goals, and current emotional state. The input data is sent to the server in real time. The terminal functions as the user's interface, securing the input data and communicating with the server. 【0221】 Step 2: 【0222】 The server analyzes the received user data and records the user profile in a database. Here, a database management system is used to structure and store the input data. As part of the user profile, characteristics, goals, and emotional states are explicitly stated. 【0223】 Step 3: 【0224】 The server uses a generative AI model to generate a personalized learning plan based on recorded user profiles. User characteristics and goals are used as input data, resulting in an optimal learning plan. The generated plan is customized for each user. 【0225】 Step 4: 【0226】 The server uses an emotion engine to estimate the user's emotional state. The user's recent behavior and entered emotions are used as input data, and the emotion engine analyzes the emotional state. The output is an adjusted plan based on the estimated emotion. 【0227】 Step 5: 【0228】 The server communicates with home appliances and makes suggestions when the user needs relaxation. Based on the analysis of the emotional state, a generative AI model uses prompts to select relaxation methods. This information is sent to home robots and smart devices to instruct them on specific actions. 【0229】 Step 6: 【0230】 Home appliances follow instructions from a server and execute suggestions for the user. Specific examples include playing music or adjusting room temperature and lighting. The system's state after operation is fed back to the server, allowing for optimization in future operations. 【0231】 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating 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. 【0232】 Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. 【0233】 In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14. 【0234】 [Second Embodiment] 【0235】 Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment. 【0236】 As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server. 【0237】 The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network). 【0238】 The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52. 【0239】 The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46. 【0240】 Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision). 【0241】 Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner. 【0242】 Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56. 【0243】 The specific processing program 56 is an example of a "program" relating to the technology of this 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. 【0244】 The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. 【0245】 In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48. 【0246】 Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. 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". 【0247】 The system according to the present invention realizes an AI agent that provides personalized learning plans and task management support to users, including individuals with attention deficit or hyperactivity. Its components and specific processes are shown below. 【0248】 First, the user accesses the system from their terminal and creates a user profile by entering user information. The server receives this input information and configures a database tailored to the user's characteristics and goals. This enables specialized support for individual users. 【0249】 Next, users can register their daily tasks through their device. The device sends this task information to the server, which then processes the received task information. This includes the automatic generation of schedules using the Pomodoro Technique, enabling users to manage their time efficiently. 【0250】 Furthermore, the system provides users with visual or audio reminders. The server creates and sends reminder information to the device according to a set schedule, ensuring users don't forget important tasks. This makes it easier for users to prioritize and manage their tasks. 【0251】 It also has a function to visualize user progress. The server collects data on tasks completed by the user and generates charts and graphs to visually display the progress. By sending this information to the terminal, users can easily check their level of achievement and maintain their motivation. 【0252】 In addition, the system provides automated feedback based on the user's activity history. The server analyzes past task history and suggests areas for improvement and actions to take next. This allows users to constantly review their work and strive for improvement. 【0253】 Through the mechanisms described above, this system strongly supports efficient task management and self-improvement for users with attention deficit or hyperactivity. This allows for flexible responses tailored to individual characteristics and effectively solves challenges in daily life. 【0254】 The following describes the processing flow. 【0255】 Step 1: 【0256】 The user accesses the system using their device and opens the initial setup screen. The user then enters information about their characteristics and goals. 【0257】 Step 2: 【0258】 The terminal sends the entered user information to the server. The server receives this information, saves it to a database, and creates a user profile. 【0259】 Step 3: 【0260】 Users register their daily tasks on their device screen. They enter necessary information such as task name, priority, deadline, and estimated time required. 【0261】 Step 4: 【0262】 The terminal sends registered task information to the server. Based on this, the server automatically generates a task schedule utilizing the Pomodoro Technique. 【0263】 Step 5: 【0264】 The server sends the generated schedule data to the terminal. The terminal visually displays the schedule to the user and shows a start button. 【0265】 Step 6: 【0266】 The user presses the start button on the device to begin the Pomodoro timer. The device starts a 25-minute work timer. 【0267】 Step 7: 【0268】 After the timer ends, the device will prompt the user to take a 5-minute break. After the break, the user can choose whether to start the next work session. 【0269】 Step 8: 【0270】 The server sends a reminder notification to the device based on a pre-set time. The device then notifies the user visually or audibly. 【0271】 Step 9: 【0272】 The server periodically compiles information on completed tasks by users. It creates charts and graphs to visualize progress. 【0273】 Step 10: 【0274】 The server sends the generated visual data to the terminal. The terminal then displays this to the user and prompts them to check the progress. 【0275】 Step 11: 【0276】 The server analyzes the user's task history and automatically generates feedback for the user regarding the next action and areas for improvement. The terminal then provides this feedback to the user. 【0277】 (Example 1) 【0278】 Next, we will describe Example 1. 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." 【0279】 Many modern users face daily difficulties with time management. This includes users with attention deficit or hyperactivity, for whom specialized support is essential. Furthermore, these users need means to improve the efficiency of their daily lives through effective visualization of task prioritization and progress management. However, current systems fail to address individual needs and only offer general support, creating a strong demand for technologies that address the specific challenges of individual users. 【0280】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. 【0281】 In this invention, the server includes means for providing an individualized learning plan based on user characteristics and goals and tracking progress, means for improving user work efficiency using time management techniques, and means for providing notifications tailored to the user visually or aurally. This enables flexible support according to the individual characteristics of the user, facilitating efficient task management and self-improvement. 【0282】 "User" refers to an individual or group that uses the system for task management and time management. 【0283】 "Characteristic" refers to an element indicating the individual personality, ability, and behavior pattern of the user. 【0284】 "Goal" refers to a specific result or objective set by the user with the aim of achievement. 【0285】 "Time management technique" refers to a method or technique for efficiently allocating working time and break time. 【0286】 "Notification" refers to a message or signal for the system to inform the user of a reminder or a change in the situation. 【0287】 "Progress status" refers to a state indicating the degree of achievement of the tasks and goals set by the user. 【0288】 "Automatic response device" refers to a function for the system to provide appropriate feedback based on user input and situation. 【0289】 This invention provides a system for assisting task management and time management according to user characteristics. The system is mainly configured based on the transmission and reception of information among the server, the terminal, and the user. 【0290】 Users enter basic information and set characteristics and goals using a terminal. This information is sent to the server. Based on this information, the server creates a user profile and generates personalized learning plans and task plans. The server is equipped with machine learning algorithms and database management software for advanced data processing and schedule generation. 【0291】 Users input their daily tasks from their device, and once this information is sent to the server, the server creates a schedule using the Pomodoro Technique. Based on this schedule, reminders are sent through the device at appropriate times. Visual notifications are provided through the device's user interface, while audio notifications are provided through an additional audio output device. 【0292】 The server also aggregates data on the user's completed tasks and generates charts and graphs to visualize progress. These are sent to the terminal, allowing the user to easily check their progress. Furthermore, the server analyzes the user's task history and uses an automated response function to suggest actions to take next and areas for improvement. 【0293】 For example, if a user sets the goal of "preparing for next week's project meeting," the server will generate a learning plan and task schedule based on this goal. Furthermore, by using the generative AI model and entering a prompt such as "create a personalized task management plan for a user with attention deficit or hyperactivity," the system will provide the user with the most suitable support plan. 【0294】 This system allows users to achieve flexible task management based on their own characteristics and goals, thereby improving efficiency in their daily lives. 【0295】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0296】 Step 1: 【0297】 Users input basic information, characteristics, and goals through their devices. This information is sent to the server. The server creates a user profile based on the received input data and constructs individual databases tailored to the user's characteristics and goals. This profile contains basic data for personalizing learning plans based on the user's needs. 【0298】 Step 2: 【0299】 Users input their daily tasks and events from their terminals. This information is sent to the server. The server uses this task information to automatically generate a schedule using the Pomodoro Technique. It performs data calculations that take into account the time required and deadlines of the entered tasks, and efficiently allocates work time and break time. The resulting schedule is then sent to the user's terminal. 【0300】 Step 3: 【0301】 The server creates reminders for the user based on the generated schedule. Reminder information is provided to the user in visual and audio formats. The device displays the reminder at the set time and issues an alert via the audio output device. Specifically, it displays a notification on the screen saying, "You have 10 minutes until your next task starts." 【0302】 Step 4: 【0303】 The server aggregates tasks completed by users and generates charts and graphs to visualize their progress. The server receives a list of completed tasks and their estimated time spent as input data. The server analyzes this data and creates graphs showing progress rates and results. These graphs are sent to the user's terminal, allowing them to easily check their own achievements. 【0304】 Step 5: 【0305】 The server analyzes the user's task history and uses an automatic response function to generate feedback. Based on past task data, it performs data calculations to identify trends and areas for improvement, and then proposes the actions to be taken next. This feedback is displayed on the terminal, providing the user with specific advice such as "It is recommended to add 30 minutes to the time for the next task." 【0306】 (Application Example 1) 【0307】 Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal". 【0308】 Individuals with attention deficit or hyperactivity have difficulty in daily task management and carrying out learning plans, and there is a need to improve time management and work efficiency. Also, through support within the family, there is a need for a method for the user to maintain motivation continuously. Therefore, flexible responses according to individual characteristics are possible, and support means utilizing household appliances are essential. 【0309】 The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means respectively. 【0310】 In this invention, the server includes means for providing a personalized learning plan based on the user's characteristics and goals and tracking progress, means for managing the user's time using the Pomodoro technique and improving work efficiency, and means for interacting with the user by household appliances and assisting the user's task management through voice and visual displays. Thereby, users with attention deficit or hyperactivity can effectively manage their own tasks, receive efficient support in the home environment, and solve the problems of daily life. 【0311】 A "user" is an individual who utilizes this system, possesses characteristics such as inattention deficit or hyperactivity, and requires efficient task management and learning plan provision. 【0312】 "Household automated devices" are automated devices used in a home environment that interact with the user and assist with task management using visual and auditory means. 【0313】 A "personalized learning plan" is an educational plan individually optimized based on the user's characteristics and goals, and aims to enable users to learn effectively through progress tracking. 【0314】 The "Pomodoro Technique" is a time management method that improves the user's concentration and work efficiency by repeating a fixed work period and break period. 【0315】 "Audio and visual displays" refer to means of facilitating user interaction, including voice instructions and information presentation, as well as visual notifications and reminders. 【0316】 Task management is a process that supports users in planning and executing their daily activities and goal achievements, guiding them while considering efficiency and priorities. 【0317】 This invention provides a system to support personalized learning plans and task management based on user characteristics. Users interact with the system through a home automated device using an interface that utilizes voice and visual displays. 【0318】 The server generates personalized learning plans based on user information, supporting the achievement of individual goals. Specifically, it uses a database to analyze user characteristics and goals, and proposes optimal tasks and schedules. This allows users to effectively execute their learning plans and track their progress. 【0319】 Furthermore, the server utilizes the Pomodoro Technique to efficiently manage the user's work and rest periods, improving work efficiency. The terminal sends visual or audio reminders to the user to help them remember and complete important tasks. 【0320】 Home automation devices use voice recognition software to understand user instructions and provide appropriate feedback. For example, if a user says, "Set up a Pomodoro schedule for tomorrow's meeting," the home automation device sends the information to a server, which generates a schedule and sends it to the device. 【0321】 Furthermore, the server utilizes a generative AI model to analyze the user's behavioral history and provide feedback on the optimal next action to take. This allows users to continuously improve their task management skills. An example of an input prompt for the generative AI model is, "Please provide a detailed example of how to create a personalized learning plan specifically for a student with attention deficit using the Pomodoro Technique." 【0322】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0323】 Step 1: 【0324】 The user gives voice commands through a home automated device. These voice commands are first captured by the device and converted into text format using speech recognition software. The input is voice data, and the output is text data. 【0325】 Step 2: 【0326】 The device sends the converted text data to the server. The server uses this text data to verify the user profile and, referencing a database tailored to the user's characteristics and goals, creates a personalized learning plan or task schedule. The input is the user profile, and the output is a personalized learning plan or task schedule. 【0327】 Step 3: 【0328】 The server sends the generated personalized task schedule to the home automation device. The home automation device presents this schedule to the user visually or audibly and sets timely reminders. The input is the generated schedule data, and the output is the visual / audio reminders to the user. 【0329】 Step 4: 【0330】 When a user completes a task, they send that information back to the server via a home automated device. The server aggregates this completion information and visualizes the user's progress. The input is data on completed tasks, and the output is charts and graphs representing the progress. 【0331】 Step 5: 【0332】 The server uses a generative AI model to analyze user behavior history data. Based on this analysis, it generates optimal actions and feedback to be taken next, and notifies the user through home automated devices. The input is behavior history data, and the output is feedback including improvement suggestions. 【0333】 The above are the specific processing steps for implementing this invention. 【0334】 Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions. 【0335】 This invention combines an emotion engine with an AI agent that supports personalized learning plans and task management based on the user's characteristics and goals, thereby enabling support that also takes the user's emotional state into account. The specific configuration and processing are shown below. 【0336】 Users access the system from their devices and input information about their characteristics, goals, and current emotional state. This information is received by the server and recorded in a database as a user profile. Furthermore, the emotion engine analyzes the user's input and daily activities to estimate their emotional state. 【0337】 This emotion engine allows the server to generate personalized learning plans based on the user's emotions. For example, if a user is feeling stressed, it can suggest content that promotes relaxation or tasks that are easier to manage. Task schedules based on the Pomodoro Technique are also adjusted to take the user's emotional state into account. 【0338】 Reminder notifications are delivered based on information from the emotion engine, tailored to the user's state in terms of timing and content. For example, if the user is fatigued, reminders are scheduled flexibly, prioritizing only important tasks. 【0339】 User progress data is regularly compiled and visualized along with changes in emotions. This allows users to track their work efficiency and mental health over time. The server also uses this data for long-term analysis and provides feedback on the user's mental health. 【0340】 For example, if a user feels anxious about the progress of their learning plan, the server uses an emotion engine to identify the user's emotions and readjust the task priorities and schedules to reduce the user's burden and provide reassurance. 【0341】 With the above configuration, this system provides support that comprehensively considers the user's emotional state, enabling more effective learning and task management. 【0342】 The following describes the processing flow. 【0343】 Step 1: 【0344】 Users log into the system via their device and input information about their characteristics, goals, and current emotional state. This information is collected by the emotion engine for analysis. 【0345】 Step 2: 【0346】 The terminal sends input information to the server. The server receives this information and stores it in the database as a user profile. Additionally, the emotion engine analyzes the user's emotional state and updates the necessary data. 【0347】 Step 3: 【0348】 The server automatically generates a learning plan and task schedule tailored to the user based on the analysis results of the emotion engine. During this process, the workload of the tasks is adjusted according to the user's emotional state. 【0349】 Step 4: 【0350】 The server sends the generated learning plan and schedule to the device. The device then presents this to the user and notifies them that they are ready to begin. 【0351】 Step 5: 【0352】 Once the user begins working on the device, the emotion engine continuously monitors the user's input and actions and evaluates their emotional state. A Pomodoro timer is then activated on the device to support time management based on emotions. 【0353】 Step 6: 【0354】 The server generates a reminder optimized for timing and content based on the user's emotional state. The reminder information is sent to the device, which then presents it to the user. 【0355】 Step 7: 【0356】 The server periodically compiles user progress and visualizes it along with emotional fluctuations. This allows users to monitor their own progress and mental health status. 【0357】 Step 8: 【0358】 The server analyzes the user's long-term task history and sentiment data to generate feedback. This feedback is sent to the terminal and presented to the user, providing suggestions for the next steps and improvements. 【0359】 (Example 2) 【0360】 Next, we will describe Example 2. 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". 【0361】 In today's world, it has become increasingly difficult for users to learn efficiently and effectively under various circumstances. In particular, the effectiveness of learning plans can be significantly reduced when influenced by the emotional state of individual learners, such as stress. Furthermore, flexible responses to emotional changes are required even in task management outside of learning. Therefore, individualized support that comprehensively considers the user's characteristics, goals, and emotional state is necessary, but conventional systems are not adequately able to address this, and a more flexible and effective solution is needed. 【0362】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. 【0363】 In this invention, the server includes means for providing an individualized educational plan based on the user's characteristics, goals, and emotional state; means for estimating the user's mental state using an emotion analysis engine and providing information based thereon; and means for optimizing the user's work efficiency by using time management technology. This enables personalized learning support and emotional care that meets the individual needs of the user. 【0364】 A "user" is an individual or group that utilizes the system, inputting their characteristics, goals, and emotional state into the system and receiving support based on that information. 【0365】 "Characteristics" refer to the individual attributes and tendencies of a user, and the factors that influence their learning style and how they respond. 【0366】 A "goal" is a specific objective or desired outcome that the user aims to achieve, and it serves as the basis for determining the direction of the plans and tasks provided by the system. 【0367】 "Emotional state" refers to information that indicates the type and intensity of emotions a user experiences at a particular point in time, and includes various psychological elements such as stress, fatigue, and anxiety. 【0368】 An "individualized learning plan" is a plan that proposes learning methods and schedules optimized for each individual based on the user's characteristics, goals, and emotional state. 【0369】 A "sentiment analysis engine" refers to a technology or algorithm that analyzes user input information and activity history to estimate the user's emotional state. 【0370】 "Time management techniques" refer to methods and technologies that optimize users' work schedules and support efficient time management. 【0371】 "Work efficiency" is an indicator that shows how effectively a user can complete a task within a set time. 【0372】 A "notification function" is a system feature that informs users of important tasks or events. 【0373】 A "reminder" refers to a message or alert that prompts a user to take action by notifying them of the progress of scheduled tasks or appointments. 【0374】 "Feedback" refers to information and evaluations provided to users to help them better understand their own actions and results. 【0375】 "Visualization" is the process of making it easier for users to understand the situation by visually displaying their progress and changes in emotions. 【0376】 This invention is initiated when a user accesses it through a device. The user inputs data about their characteristics, goals, and emotional state. This information is transmitted from various devices such as tablets, smartphones, or computers. The input data is sent to a central server via the internet. 【0377】 The server creates and records a user-specific profile in a database based on data received from the user. This profile is analyzed by an emotion analysis engine that uses natural language processing and machine learning techniques, known as a generative AI model. The emotion analysis engine estimates the user's specific emotional state (e.g., stress, anxiety, fatigue) and generates a personalized learning plan based on the results. 【0378】 One of the key elements of this system is time management technology. Specifically, the server incorporates techniques such as the Pomodoro Technique to provide users with an optimized work schedule. This allows users to allocate their time efficiently and concentrate on learning and tasks. 【0379】 The notification function is also an important feature of this system, allowing users to receive reminders at the appropriate time. Reminders are adjusted to be sent at the right moment, taking into account the user's current emotional state. 【0380】 Furthermore, the server provides a dashboard to visualize the user's progress and emotional changes. This dashboard serves as a tool for users to monitor their learning efficiency and mental well-being in real time. 【0381】 For example, if a user feels anxious while monitoring their learning plan progress, the server uses an emotion analysis engine to identify that emotion and dynamically readjusts the priority and schedule of corresponding tasks. This allows the user to learn with peace of mind without feeling overwhelmed. 【0382】 By inputting prompts like the following into the AI ​​model, you can obtain more specific countermeasures and plans: 【0383】 "Propose an appropriate learning plan for users with high stress levels." 【0384】 "Please create a task schedule that takes my current emotional state into consideration." 【0385】 "How can I visualize user progress and emotional changes?" 【0386】 In this way, this system addresses the diverse needs of users and realizes a better learning environment and efficient task management. 【0387】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0388】 Step 1: 【0389】 Users access the system using a terminal and input information about their characteristics, goals, and emotional state. This input is in text format and is obtained by users entering specific numbers or text into input fields on the application. The entered data is sent to the server immediately. 【0390】 Step 2: 【0391】 The server stores information received from users in a database. The database updates individual user profiles with the latest information, ensuring consistent user data management. Input is user information (traits, goals, emotional state), and output is the updated user profile data. 【0392】 Step 3: 【0393】 The server activates the sentiment analysis engine based on the received data. The sentiment analysis engine analyzes the user's emotional state using natural language processing and machine learning techniques. In this process, it analyzes the input text data and outputs an emotion score. Specifically, it generates a numerical emotion index based on a standard model used by the scoring algorithm. 【0394】 Step 4: 【0395】 The server generates a personalized learning plan optimized for the user based on the results of the emotion analysis engine. Here, the learning plan is adjusted according to the user's emotional state to reduce stress and improve concentration. The input is the emotion score and user goals, and the output is a personalized learning plan. This plan includes actions such as suggesting specific tasks and their order. 【0396】 Step 5: 【0397】 The server creates reminder schedules and adjusts them based on the user's emotional state. Specifically, it sets appropriate reminder timings for the user's situation and manages them adaptively to avoid excessive notifications. The inputs are emotional state and task priority, and the output is an optimized reminder schedule. 【0398】 Step 6: 【0399】 The server visualizes progress and emotional changes, generating a user-friendly dashboard. Here, graphs and charts are used to visualize data, allowing users to track their progress and mental health. Inputs are progress and emotional data, and output is the visual information displayed as a dashboard. 【0400】 Step 7: 【0401】 The server analyzes users' long-term data and provides feedback. This process involves trend analysis based on historical data, pointing out areas for improvement and successful practices to the user. The input is cumulative data, and the output is a feedback report. This facilitates self-improvement and adaptive learning for the user. 【0402】 (Application Example 2) 【0403】 Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal." 【0404】 In today's busy lifestyle, providing personalized task management and learning plans tailored to individual characteristics and emotional states is crucial. However, existing systems struggle to respond flexibly to users' emotions, limiting the effectiveness of life support through integration with machines. Therefore, the challenge lies in providing a system that enables appropriate support in response to users' emotions. 【0405】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. 【0406】 In this invention, the server includes means for providing a personalized learning plan based on the user's characteristics and goals and tracking progress; means for estimating the user's emotional state and adjusting the learning plan and task schedule accordingly; and means for coordinating with household appliances to provide the user with suggestions to promote relaxation. This enables flexible task management and life support that responds to the user's emotions. 【0407】 A "user" refers to an individual who uses a system or service. 【0408】 "Characteristics" refer to the individual characteristics of a user, such as their personality, behavioral patterns, and preferences. 【0409】 "Goals" refer to the specific results or objectives that users want to achieve. 【0410】 A "personalized learning plan" refers to a learning plan specifically designed to suit each user's individual characteristics and goals. 【0411】 "Progress" indicates the current status of achievement towards the goals set by the user. 【0412】 The "Pomodoro Technique" is a time management method that involves repeating a cycle of work followed by breaks to improve work efficiency. 【0413】 "Work efficiency" refers to a user's ability to achieve high results in a short amount of time on a given task. 【0414】 A "reminder" refers to a notification function that periodically informs users of necessary information. 【0415】 "Visualization" refers to clearly displaying a user's progress and task history using graphs, charts, and other visual aids. 【0416】 "Feedback" refers to suggesting further improvements or next actions based on the user's behavior and results. 【0417】 "Emotional state" refers to the user's current psychological or emotional state. 【0418】 "Household machinery and equipment" refers to devices such as robots and smart devices used within the home. 【0419】 "Relaxation" refers to a state or activity that allows users to reduce stress and refresh their mind and body. 【0420】 A system for implementing this invention consists of a user terminal, a server, and a household appliance. 【0421】 Users use their devices to input their characteristics, goals, and current emotional state. This information is sent to the server and recorded in the database as a user profile. 【0422】 Based on this profile, the server uses a generative AI model to create a personalized learning plan for each user. It also uses an emotion engine to estimate emotions from user input and behavior, and adjusts the plan and task schedule accordingly. In this process, it analyzes changes in emotion using Google Cloud AI's emotion recognition API. 【0423】 Furthermore, the server interacts with home appliances and makes suggestions to promote relaxation when the user needs it. For example, if the user is feeling tired, it might play music or adjust the room temperature to a comfortable level. Such home appliances include common robots and smart home devices. 【0424】 For example, if a user feels that they are behind schedule to meet their monthly target, the server can use the prompt message "How to reduce stress" to suggest appropriate relaxation methods from home-use devices and adjust the user's work environment accordingly. 【0425】 In this embodiment, the system provided by the server enables flexible task management and life support tailored to the user's emotions and characteristics. 【0426】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0427】 Step 1: 【0428】 The user uses a terminal to input their characteristics, goals, and current emotional state. The input data is sent to the server in real time. The terminal functions as the user's interface, securing the input data and communicating with the server. 【0429】 Step 2: 【0430】 The server analyzes the received user data and records the user profile in a database. Here, a database management system is used to structure and store the input data. As part of the user profile, characteristics, goals, and emotional states are explicitly stated. 【0431】 Step 3: 【0432】 The server uses a generative AI model to generate a personalized learning plan based on recorded user profiles. User characteristics and goals are used as input data, resulting in an optimal learning plan. The generated plan is customized for each user. 【0433】 Step 4: 【0434】 The server uses an emotion engine to estimate the user's emotional state. The user's recent behavior and entered emotions are used as input data, and the emotion engine analyzes the emotional state. The output is an adjusted plan based on the estimated emotion. 【0435】 Step 5: 【0436】 The server communicates with home appliances and makes suggestions when the user needs relaxation. Based on the analysis of the emotional state, a generative AI model uses prompts to select relaxation methods. This information is sent to home robots and smart devices to instruct them on specific actions. 【0437】 Step 6: 【0438】 Home appliances follow instructions from a server and execute suggestions for the user. Specific examples include playing music or adjusting room temperature and lighting. The system's state after operation is fed back to the server, allowing for optimization in future operations. 【0439】 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data. 【0440】 Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. 【0441】 In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214. 【0442】 [Third Embodiment] 【0443】 Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment. 【0444】 As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server. 【0445】 The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network). 【0446】 The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52. 【0447】 The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46. 【0448】 Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision). 【0449】 Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner. 【0450】 Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56. 【0451】 The specific processing program 56 is an example of a "program" relating to the technology of this 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. 【0452】 The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. 【0453】 In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48. 【0454】 Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal". 【0455】 The system according to the present invention realizes an AI agent that provides personalized learning plans and task management support to users, including individuals with attention deficit or hyperactivity. Its components and specific processes are shown below. 【0456】 First, the user accesses the system from their terminal and creates a user profile by entering user information. The server receives this input information and configures a database tailored to the user's characteristics and goals. This enables specialized support for individual users. 【0457】 Next, users can register their daily tasks through their device. The device sends this task information to the server, which then processes the received task information. This includes the automatic generation of schedules using the Pomodoro Technique, enabling users to manage their time efficiently. 【0458】 Furthermore, the system provides users with visual or audio reminders. The server creates and sends reminder information to the device according to a set schedule, ensuring users don't forget important tasks. This makes it easier for users to prioritize and manage their tasks. 【0459】 It also has a function to visualize user progress. The server collects data on tasks completed by the user and generates charts and graphs to visually display the progress. By sending this information to the terminal, users can easily check their level of achievement and maintain their motivation. 【0460】 In addition, the system provides automated feedback based on the user's activity history. The server analyzes past task history and suggests areas for improvement and actions to take next. This allows users to constantly review their work and strive for improvement. 【0461】 Through the mechanisms described above, this system strongly supports efficient task management and self-improvement for users with attention deficit or hyperactivity. This allows for flexible responses tailored to individual characteristics and effectively solves challenges in daily life. 【0462】 The following describes the processing flow. 【0463】 Step 1: 【0464】 The user accesses the system using their device and opens the initial setup screen. The user then enters information about their characteristics and goals. 【0465】 Step 2: 【0466】 The terminal sends the entered user information to the server. The server receives this information, saves it to a database, and creates a user profile. 【0467】 Step 3: 【0468】 Users register their daily tasks on their device screen. They enter necessary information such as task name, priority, deadline, and estimated time required. 【0469】 Step 4: 【0470】 The terminal sends registered task information to the server. Based on this, the server automatically generates a task schedule utilizing the Pomodoro Technique. 【0471】 Step 5: 【0472】 The server sends the generated schedule data to the terminal. The terminal visually displays the schedule to the user and shows a start button. 【0473】 Step 6: 【0474】 The user presses the start button on the device to begin the Pomodoro timer. The device starts a 25-minute work timer. 【0475】 Step 7: 【0476】 After the timer ends, the device will prompt the user to take a 5-minute break. After the break, the user can choose whether to start the next work session. 【0477】 Step 8: 【0478】 The server sends a reminder notification to the device based on a pre-set time. The device then notifies the user visually or audibly. 【0479】 Step 9: 【0480】 The server periodically compiles information on completed tasks by users. It creates charts and graphs to visualize progress. 【0481】 Step 10: 【0482】 The server sends the generated visual data to the terminal. The terminal then displays this to the user and prompts them to check the progress. 【0483】 Step 11: 【0484】 The server analyzes the user's task history and automatically generates feedback for the user regarding the next action and areas for improvement. The terminal then provides this feedback to the user. 【0485】 (Example 1) 【0486】 Next, we will describe Example 1. 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." 【0487】 Many modern users face daily difficulties with time management. This includes users with attention deficit or hyperactivity, for whom specialized support is essential. Furthermore, these users need means to improve the efficiency of their daily lives through effective visualization of task prioritization and progress management. However, current systems fail to address individual needs and only offer general support, creating a strong demand for technologies that address the specific challenges of individual users. 【0488】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. 【0489】 In this invention, the server includes means for providing a personalized learning plan based on the user's characteristics and goals and tracking progress; means for improving the user's work efficiency using time management technology; and means for providing user-specific notifications visually or audibly. This enables flexible support tailored to the user's individual characteristics, facilitating efficient task management and promoting self-improvement. 【0490】 A "user" refers to an individual or group that uses the system for task management or time management. 【0491】 "Characteristics" refer to elements that indicate a user's individual personality, abilities, and behavioral patterns. 【0492】 A "goal" is a specific result or objective that a user sets with the aim of achieving it. 【0493】 "Time management techniques" refer to methods and techniques for efficiently allocating work time and break time. 【0494】 A "notification" is a message or signal that a system uses to inform a user of a reminder or a change in circumstances. 【0495】 "Progress status" refers to the extent to which a user has achieved their set tasks or goals. 【0496】 An "automatic response system" refers to a function that allows a system to provide appropriate feedback based on user input and circumstances. 【0497】 This invention provides a system that supports task management and time management tailored to the user's characteristics. The system is primarily based on the transmission and reception of information between a server, a terminal, and the user. 【0498】 Users enter basic information and set characteristics and goals using a terminal. This information is sent to the server. Based on this information, the server creates a user profile and generates personalized learning plans and task plans. The server is equipped with machine learning algorithms and database management software for advanced data processing and schedule generation. 【0499】 Users input their daily tasks from their device, and once this information is sent to the server, the server creates a schedule using the Pomodoro Technique. Based on this schedule, reminders are sent through the device at appropriate times. Visual notifications are provided through the device's user interface, while audio notifications are provided through an additional audio output device. 【0500】 The server also aggregates data on the user's completed tasks and generates charts and graphs to visualize progress. These are sent to the terminal, allowing the user to easily check their progress. Furthermore, the server analyzes the user's task history and uses an automated response function to suggest actions to take next and areas for improvement. 【0501】 For example, if a user sets the goal of "preparing for next week's project meeting," the server will generate a learning plan and task schedule based on this goal. Furthermore, by using the generative AI model and entering a prompt such as "create a personalized task management plan for a user with attention deficit or hyperactivity," the system will provide the user with the most suitable support plan. 【0502】 This system allows users to achieve flexible task management based on their own characteristics and goals, thereby improving efficiency in their daily lives. 【0503】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0504】 Step 1: 【0505】 Users input basic information, characteristics, and goals through their devices. This information is sent to the server. The server creates a user profile based on the received input data and constructs individual databases tailored to the user's characteristics and goals. This profile contains basic data for personalizing learning plans based on the user's needs. 【0506】 Step 2: 【0507】 Users input their daily tasks and events from their terminals. This information is sent to the server. The server uses this task information to automatically generate a schedule using the Pomodoro Technique. It performs data calculations that take into account the time required and deadlines of the entered tasks, and efficiently allocates work time and break time. The resulting schedule is then sent to the user's terminal. 【0508】 Step 3: 【0509】 The server creates reminders for the user based on the generated schedule. Reminder information is provided to the user in visual and audio formats. The device displays the reminder at the set time and issues an alert via the audio output device. Specifically, it displays a notification on the screen saying, "You have 10 minutes until your next task starts." 【0510】 Step 4: 【0511】 The server aggregates tasks completed by users and generates charts and graphs to visualize their progress. The server receives a list of completed tasks and their estimated time spent as input data. The server analyzes this data and creates graphs showing progress rates and results. These graphs are sent to the user's terminal, allowing them to easily check their own achievements. 【0512】 Step 5: 【0513】 The server analyzes the user's task history and generates feedback using an automated response function. Based on past task data, it performs data calculations to identify trends and areas for improvement, and suggests actions to take next. This feedback is displayed on the terminal, providing the user with specific advice such as, "We recommend adding 30 minutes to your next task." 【0514】 (Application Example 1) 【0515】 Next, we will explain Application Example 1. In the following explanation, 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." 【0516】 Individuals with attention deficit or hyperactivity often struggle with daily task management and the execution of learning plans, requiring improvements in time management and work efficiency. Furthermore, methods are needed to help users maintain sustained motivation through support within the home. Therefore, flexible responses tailored to individual characteristics and support methods utilizing home automation equipment are essential. 【0517】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. 【0518】 This invention includes a server that provides a personalized learning plan based on the user's characteristics and goals and tracks progress; a server that manages the user's time and improves work efficiency using the Pomodoro Technique; and a server that interacts with the user through home automation equipment and assists the user in managing tasks through voice and visual displays. This enables users with attention deficit or hyperactivity to effectively manage their tasks and solve everyday challenges with efficient support in a home environment. 【0519】 A "user" is an individual who utilizes this system, possesses characteristics such as inattention deficit or hyperactivity, and requires efficient task management and learning plan provision. 【0520】 "Household automated devices" are automated devices used in a home environment that interact with the user and assist with task management using visual and auditory means. 【0521】 A "personalized learning plan" is an educational plan individually optimized based on the user's characteristics and goals, and aims to enable users to learn effectively through progress tracking. 【0522】 The "Pomodoro Technique" is a time management method that improves the user's concentration and work efficiency by repeating a fixed work period and break period. 【0523】 "Audio and visual displays" refer to means of facilitating user interaction, including voice instructions and information presentation, as well as visual notifications and reminders. 【0524】 Task management is a process that supports users in planning and executing their daily activities and goal achievements, guiding them while considering efficiency and priorities. 【0525】 This invention provides a system to support personalized learning plans and task management based on user characteristics. Users interact with the system through a home automated device using an interface that utilizes voice and visual displays. 【0526】 The server generates personalized learning plans based on user information, supporting the achievement of individual goals. Specifically, it uses a database to analyze user characteristics and goals, and proposes optimal tasks and schedules. This allows users to effectively execute their learning plans and track their progress. 【0527】 Furthermore, the server utilizes the Pomodoro Technique to efficiently manage the user's work and rest periods, improving work efficiency. The terminal sends visual or audio reminders to the user to help them remember and complete important tasks. 【0528】 Home automation devices use voice recognition software to understand user instructions and provide appropriate feedback. For example, if a user says, "Set up a Pomodoro schedule for tomorrow's meeting," the home automation device sends the information to a server, which generates a schedule and sends it to the device. 【0529】 Furthermore, the server utilizes a generative AI model to analyze the user's behavioral history and provide feedback on the optimal next action to take. This allows users to continuously improve their task management skills. An example of an input prompt for the generative AI model is, "Please provide a detailed example of how to create a personalized learning plan specifically for a student with attention deficit using the Pomodoro Technique." 【0530】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0531】 Step 1: 【0532】 The user gives voice commands through a home automated device. These voice commands are first captured by the device and converted into text format using speech recognition software. The input is voice data, and the output is text data. 【0533】 Step 2: 【0534】 The device sends the converted text data to the server. The server uses this text data to verify the user profile and, referencing a database tailored to the user's characteristics and goals, creates a personalized learning plan or task schedule. The input is the user profile, and the output is a personalized learning plan or task schedule. 【0535】 Step 3: 【0536】 The server sends the generated personalized task schedule to the home automation device. The home automation device presents this schedule to the user visually or audibly and sets timely reminders. The input is the generated schedule data, and the output is the visual / audio reminders to the user. 【0537】 Step 4: 【0538】 When a user completes a task, they send that information back to the server via a home automated device. The server aggregates this completion information and visualizes the user's progress. The input is data on completed tasks, and the output is charts and graphs representing the progress. 【0539】 Step 5: 【0540】 The server uses a generative AI model to analyze user behavior history data. Based on this analysis, it generates optimal actions and feedback to be taken next, and notifies the user through home automated devices. The input is behavior history data, and the output is feedback including improvement suggestions. 【0541】 The above are the specific processing steps for implementing this invention. 【0542】 Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions. 【0543】 This invention combines an emotion engine with an AI agent that supports personalized learning plans and task management based on the user's characteristics and goals, thereby enabling support that also takes the user's emotional state into account. The specific configuration and processing are shown below. 【0544】 Users access the system from their devices and input information about their characteristics, goals, and current emotional state. This information is received by the server and recorded in a database as a user profile. Furthermore, the emotion engine analyzes the user's input and daily activities to estimate their emotional state. 【0545】 This emotion engine allows the server to generate personalized learning plans based on the user's emotions. For example, if a user is feeling stressed, it can suggest content that promotes relaxation or tasks that are easier to manage. Task schedules based on the Pomodoro Technique are also adjusted to take the user's emotional state into account. 【0546】 Reminder notifications are delivered based on information from the emotion engine, tailored to the user's state in terms of timing and content. For example, if the user is fatigued, reminders are scheduled flexibly, prioritizing only important tasks. 【0547】 User progress data is regularly compiled and visualized along with changes in emotions. This allows users to track their work efficiency and mental health over time. The server also uses this data for long-term analysis and provides feedback on the user's mental health. 【0548】 For example, if a user feels anxious about the progress of their learning plan, the server uses an emotion engine to identify the user's emotions and readjust the task priorities and schedules to reduce the user's burden and provide reassurance. 【0549】 With the above configuration, this system provides support that comprehensively considers the user's emotional state, enabling more effective learning and task management. 【0550】 The following describes the processing flow. 【0551】 Step 1: 【0552】 Users log into the system via their device and input information about their characteristics, goals, and current emotional state. This information is collected by the emotion engine for analysis. 【0553】 Step 2: 【0554】 The terminal sends input information to the server. The server receives this information and stores it in the database as a user profile. Additionally, the emotion engine analyzes the user's emotional state and updates the necessary data. 【0555】 Step 3: 【0556】 The server automatically generates a learning plan and task schedule tailored to the user based on the analysis results of the emotion engine. During this process, the workload of the tasks is adjusted according to the user's emotional state. 【0557】 Step 4: 【0558】 The server sends the generated learning plan and schedule to the device. The device then presents this to the user and notifies them that they are ready to begin. 【0559】 Step 5: 【0560】 Once the user begins working on the device, the emotion engine continuously monitors the user's input and actions and evaluates their emotional state. A Pomodoro timer is then activated on the device to support time management based on emotions. 【0561】 Step 6: 【0562】 The server generates a reminder optimized for timing and content based on the user's emotional state. The reminder information is sent to the device, which then presents it to the user. 【0563】 Step 7: 【0564】 The server periodically compiles user progress and visualizes it along with emotional fluctuations. This allows users to monitor their own progress and mental health status. 【0565】 Step 8: 【0566】 The server analyzes the user's long-term task history and sentiment data to generate feedback. This feedback is sent to the terminal and presented to the user, providing suggestions for the next steps and improvements. 【0567】 (Example 2) 【0568】 Next, we will describe Example 2. 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." 【0569】 In today's world, it has become increasingly difficult for users to learn efficiently and effectively under various circumstances. In particular, the effectiveness of learning plans can be significantly reduced when influenced by the emotional state of individual learners, such as stress. Furthermore, flexible responses to emotional changes are required even in task management outside of learning. Therefore, individualized support that comprehensively considers the user's characteristics, goals, and emotional state is necessary, but conventional systems are not adequately able to address this, and a more flexible and effective solution is needed. 【0570】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. 【0571】 In this invention, the server includes means for providing an individualized educational plan based on the user's characteristics, goals, and emotional state; means for estimating the user's mental state using an emotion analysis engine and providing information based thereon; and means for optimizing the user's work efficiency by using time management technology. This enables personalized learning support and emotional care that meets the individual needs of the user. 【0572】 A "user" is an individual or group that utilizes the system, inputting their characteristics, goals, and emotional state into the system and receiving support based on that information. 【0573】 "Characteristics" refer to the individual attributes and tendencies of a user, and the factors that influence their learning style and how they respond. 【0574】 A "goal" is a specific objective or desired outcome that the user aims to achieve, and it serves as the basis for determining the direction of the plans and tasks provided by the system. 【0575】 "Emotional state" refers to information that indicates the type and intensity of emotions a user experiences at a particular point in time, and includes various psychological elements such as stress, fatigue, and anxiety. 【0576】 An "individualized learning plan" is a plan that proposes learning methods and schedules optimized for each individual based on the user's characteristics, goals, and emotional state. 【0577】 A "sentiment analysis engine" refers to a technology or algorithm that analyzes user input information and activity history to estimate the user's emotional state. 【0578】 "Time management techniques" refer to methods and technologies that optimize users' work schedules and support efficient time management. 【0579】 "Work efficiency" is an indicator that shows how effectively a user can complete a task within a set time. 【0580】 A "notification function" is a system feature that informs users of important tasks or events. 【0581】 A "reminder" refers to a message or alert that prompts a user to take action by notifying them of the progress of scheduled tasks or appointments. 【0582】 "Feedback" refers to information and evaluations provided to users to help them better understand their own actions and results. 【0583】 "Visualization" is the process of making it easier for users to understand the situation by visually displaying their progress and changes in emotions. 【0584】 This invention is initiated when a user accesses it through a device. The user inputs data about their characteristics, goals, and emotional state. This information is transmitted from various devices such as tablets, smartphones, or computers. The input data is sent to a central server via the internet. 【0585】 The server creates and records a user-specific profile in a database based on data received from the user. This profile is analyzed by an emotion analysis engine that uses natural language processing and machine learning techniques, known as a generative AI model. The emotion analysis engine estimates the user's specific emotional state (e.g., stress, anxiety, fatigue) and generates a personalized learning plan based on the results. 【0586】 One of the key elements of this system is time management technology. Specifically, the server incorporates techniques such as the Pomodoro Technique to provide users with an optimized work schedule. This allows users to allocate their time efficiently and concentrate on learning and tasks. 【0587】 The notification function is also an important feature of this system, allowing users to receive reminders at the appropriate time. Reminders are adjusted to be sent at the right moment, taking into account the user's current emotional state. 【0588】 Furthermore, the server provides a dashboard to visualize the user's progress and emotional changes. This dashboard serves as a tool for users to monitor their learning efficiency and mental well-being in real time. 【0589】 For example, if a user feels anxious while monitoring their learning plan progress, the server uses an emotion analysis engine to identify that emotion and dynamically readjusts the priority and schedule of corresponding tasks. This allows the user to learn with peace of mind without feeling overwhelmed. 【0590】 By inputting prompts like the following into the AI ​​model, you can obtain more specific countermeasures and plans: 【0591】 "Propose an appropriate learning plan for users with high stress levels." 【0592】 "Please create a task schedule that takes my current emotional state into consideration." 【0593】 "How can I visualize user progress and emotional changes?" 【0594】 In this way, this system addresses the diverse needs of users and realizes a better learning environment and efficient task management. 【0595】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0596】 Step 1: 【0597】 Users access the system using a terminal and input information about their characteristics, goals, and emotional state. This input is in text format and is obtained by users entering specific numbers or text into input fields on the application. The entered data is sent to the server immediately. 【0598】 Step 2: 【0599】 The server stores information received from users in a database. The database updates individual user profiles with the latest information, ensuring consistent user data management. Input is user information (traits, goals, emotional state), and output is the updated user profile data. 【0600】 Step 3: 【0601】 The server activates the sentiment analysis engine based on the received data. The sentiment analysis engine analyzes the user's emotional state using natural language processing and machine learning techniques. In this process, it analyzes the input text data and outputs an emotion score. Specifically, it generates a numerical emotion index based on a standard model used by the scoring algorithm. 【0602】 Step 4: 【0603】 The server generates a personalized learning plan optimized for the user based on the results of the emotion analysis engine. Here, the learning plan is adjusted according to the user's emotional state to reduce stress and improve concentration. The input is the emotion score and user goals, and the output is a personalized learning plan. This plan includes actions such as suggesting specific tasks and their order. 【0604】 Step 5: 【0605】 The server creates reminder schedules and adjusts them based on the user's emotional state. Specifically, it sets appropriate reminder timings for the user's situation and manages them adaptively to avoid excessive notifications. The inputs are emotional state and task priority, and the output is an optimized reminder schedule. 【0606】 Step 6: 【0607】 The server visualizes progress and emotional changes, generating a user-friendly dashboard. Here, graphs and charts are used to visualize data, allowing users to track their progress and mental health. Inputs are progress and emotional data, and output is the visual information displayed as a dashboard. 【0608】 Step 7: 【0609】 The server analyzes users' long-term data and provides feedback. This process involves trend analysis based on historical data, pointing out areas for improvement and successful practices to the user. The input is cumulative data, and the output is a feedback report. This facilitates self-improvement and adaptive learning for the user. 【0610】 (Application Example 2) 【0611】 Next, we will explain Application Example 2. In the following explanation, 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." 【0612】 In today's busy lifestyle, providing personalized task management and learning plans tailored to individual characteristics and emotional states is crucial. However, existing systems struggle to respond flexibly to users' emotions, limiting the effectiveness of life support through integration with machines. Therefore, the challenge lies in providing a system that enables appropriate support in response to users' emotions. 【0613】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. 【0614】 In this invention, the server includes means for providing a personalized learning plan based on the user's characteristics and goals and tracking progress; means for estimating the user's emotional state and adjusting the learning plan and task schedule accordingly; and means for coordinating with household appliances to provide the user with suggestions to promote relaxation. This enables flexible task management and life support that responds to the user's emotions. 【0615】 A "user" refers to an individual who uses a system or service. 【0616】 "Characteristics" refer to the individual characteristics of a user, such as their personality, behavioral patterns, and preferences. 【0617】 "Goals" refer to the specific results or objectives that users want to achieve. 【0618】 A "personalized learning plan" refers to a learning plan specifically designed to suit each user's individual characteristics and goals. 【0619】 "Progress" indicates the current status of achievement towards the goals set by the user. 【0620】 The "Pomodoro Technique" is a time management method that involves repeating a cycle of work followed by breaks to improve work efficiency. 【0621】 "Work efficiency" refers to a user's ability to achieve high results in a short amount of time on a given task. 【0622】 A "reminder" refers to a notification function that periodically informs users of necessary information. 【0623】 "Visualization" refers to clearly displaying a user's progress and task history using graphs, charts, and other visual aids. 【0624】 "Feedback" refers to suggesting further improvements or next actions based on the user's behavior and results. 【0625】 "Emotional state" refers to the user's current psychological or emotional state. 【0626】 "Household machinery and equipment" refers to devices such as robots and smart devices used within the home. 【0627】 "Relaxation" refers to a state or activity that allows users to reduce stress and refresh their mind and body. 【0628】 A system for implementing this invention consists of a user terminal, a server, and a household appliance. 【0629】 Users use their devices to input their characteristics, goals, and current emotional state. This information is sent to the server and recorded in the database as a user profile. 【0630】 Based on this profile, the server uses a generative AI model to create a personalized learning plan for each user. It also uses an emotion engine to estimate emotions from user input and behavior, and adjusts the plan and task schedule accordingly. In this process, it analyzes changes in emotion using Google Cloud AI's emotion recognition API. 【0631】 Furthermore, the server interacts with home appliances and makes suggestions to promote relaxation when the user needs it. For example, if the user is feeling tired, it might play music or adjust the room temperature to a comfortable level. Such home appliances include common robots and smart home devices. 【0632】 For example, if a user feels that they are behind schedule to meet their monthly target, the server can use the prompt message "How to reduce stress" to suggest appropriate relaxation methods from home-use devices and adjust the user's work environment accordingly. 【0633】 In this embodiment, the system provided by the server enables flexible task management and life support tailored to the user's emotions and characteristics. 【0634】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0635】 Step 1: 【0636】 The user uses a terminal to input their characteristics, goals, and current emotional state. The input data is sent to the server in real time. The terminal functions as the user's interface, securing the input data and communicating with the server. 【0637】 Step 2: 【0638】 The server analyzes the received user data and records the user profile in a database. Here, a database management system is used to structure and store the input data. As part of the user profile, characteristics, goals, and emotional states are explicitly stated. 【0639】 Step 3: 【0640】 The server uses a generative AI model to generate a personalized learning plan based on recorded user profiles. User characteristics and goals are used as input data, resulting in an optimal learning plan. The generated plan is customized for each user. 【0641】 Step 4: 【0642】 The server uses an emotion engine to estimate the user's emotional state. The user's recent behavior and entered emotions are used as input data, and the emotion engine analyzes the emotional state. The output is an adjusted plan based on the estimated emotion. 【0643】 Step 5: 【0644】 The server communicates with home appliances and makes suggestions when the user needs relaxation. Based on the analysis of the emotional state, a generative AI model uses prompts to select relaxation methods. This information is sent to home robots and smart devices to instruct them on specific actions. 【0645】 Step 6: 【0646】 Home appliances follow instructions from a server and execute suggestions for the user. Specific examples include playing music or adjusting room temperature and lighting. The system's state after operation is fed back to the server, allowing for optimization in future operations. 【0647】 The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data. 【0648】 Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. 【0649】 In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314. 【0650】 [Fourth Embodiment] 【0651】 Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment. 【0652】 As shown in Figure 7, the 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. 【0653】 The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network). 【0654】 The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52. 【0655】 The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46. 【0656】 Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision). 【0657】 Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner. 【0658】 The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive 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 robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes. 【0659】 Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56. 【0660】 The specific processing program 56 is an example of a "program" relating to the technology of this 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. 【0661】 The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. 【0662】 In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48. 【0663】 Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0664】 The system according to the present invention realizes an AI agent that provides personalized learning plans and task management support to users, including individuals with attention deficit or hyperactivity. Its components and specific processes are shown below. 【0665】 First, the user accesses the system from their terminal and creates a user profile by entering user information. The server receives this input information and configures a database tailored to the user's characteristics and goals. This enables specialized support for individual users. 【0666】 Next, users can register their daily tasks through their device. The device sends this task information to the server, which then processes the received task information. This includes the automatic generation of schedules using the Pomodoro Technique, enabling users to manage their time efficiently. 【0667】 Furthermore, the system provides users with visual or audio reminders. The server creates and sends reminder information to the device according to a set schedule, ensuring users don't forget important tasks. This makes it easier for users to prioritize and manage their tasks. 【0668】 It also has a function to visualize user progress. The server collects data on tasks completed by the user and generates charts and graphs to visually display the progress. By sending this information to the terminal, users can easily check their level of achievement and maintain their motivation. 【0669】 In addition, the system provides automated feedback based on the user's activity history. The server analyzes past task history and suggests areas for improvement and actions to take next. This allows users to constantly review their work and strive for improvement. 【0670】 Through the mechanisms described above, this system strongly supports efficient task management and self-improvement for users with attention deficit or hyperactivity. This allows for flexible responses tailored to individual characteristics and effectively solves challenges in daily life. 【0671】 The following describes the processing flow. 【0672】 Step 1: 【0673】 The user accesses the system using their device and opens the initial setup screen. The user then enters information about their characteristics and goals. 【0674】 Step 2: 【0675】 The terminal sends the entered user information to the server. The server receives this information, saves it to a database, and creates a user profile. 【0676】 Step 3: 【0677】 Users register their daily tasks on their device screen. They enter necessary information such as task name, priority, deadline, and estimated time required. 【0678】 Step 4: 【0679】 The terminal sends registered task information to the server. Based on this, the server automatically generates a task schedule utilizing the Pomodoro Technique. 【0680】 Step 5: 【0681】 The server sends the generated schedule data to the terminal. The terminal visually displays the schedule to the user and shows a start button. 【0682】 Step 6: 【0683】 The user presses the start button on the device to begin the Pomodoro timer. The device starts a 25-minute work timer. 【0684】 Step 7: 【0685】 After the timer ends, the device will prompt the user to take a 5-minute break. After the break, the user can choose whether to start the next work session. 【0686】 Step 8: 【0687】 The server sends a reminder notification to the device based on a pre-set time. The device then notifies the user visually or audibly. 【0688】 Step 9: 【0689】 The server periodically compiles information on completed tasks by users. It creates charts and graphs to visualize progress. 【0690】 Step 10: 【0691】 The server sends the generated visual data to the terminal. The terminal then displays this to the user and prompts them to check the progress. 【0692】 Step 11: 【0693】 The server analyzes the user's task history and automatically generates feedback for the user regarding the next action and areas for improvement. The terminal then provides this feedback to the user. 【0694】 (Example 1) 【0695】 Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0696】 Many modern users face daily difficulties with time management. This includes users with attention deficit or hyperactivity, for whom specialized support is essential. Furthermore, these users need means to improve the efficiency of their daily lives through effective visualization of task prioritization and progress management. However, current systems fail to address individual needs and only offer general support, creating a strong demand for technologies that address the specific challenges of individual users. 【0697】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. 【0698】 In this invention, the server includes means for providing a personalized learning plan based on the user's characteristics and goals and tracking progress; means for improving the user's work efficiency using time management technology; and means for providing user-specific notifications visually or audibly. This enables flexible support tailored to the user's individual characteristics, facilitating efficient task management and promoting self-improvement. 【0699】 A "user" refers to an individual or group that uses the system for task management or time management. 【0700】 "Characteristics" refer to elements that indicate a user's individual personality, abilities, and behavioral patterns. 【0701】 A "goal" is a specific result or objective that a user sets with the aim of achieving it. 【0702】 "Time management techniques" refer to methods and techniques for efficiently allocating work time and break time. 【0703】 A "notification" is a message or signal that a system uses to inform a user of a reminder or a change in circumstances. 【0704】 "Progress status" refers to the extent to which a user has achieved their set tasks or goals. 【0705】 An "automatic response system" refers to a function that allows a system to provide appropriate feedback based on user input and circumstances. 【0706】 This invention provides a system that supports task management and time management tailored to the user's characteristics. The system is primarily based on the transmission and reception of information between a server, a terminal, and the user. 【0707】 Users enter basic information and set characteristics and goals using a terminal. This information is sent to the server. Based on this information, the server creates a user profile and generates personalized learning plans and task plans. The server is equipped with machine learning algorithms and database management software for advanced data processing and schedule generation. 【0708】 Users input their daily tasks from their device, and once this information is sent to the server, the server creates a schedule using the Pomodoro Technique. Based on this schedule, reminders are sent through the device at appropriate times. Visual notifications are provided through the device's user interface, while audio notifications are provided through an additional audio output device. 【0709】 The server also aggregates data on the user's completed tasks and generates charts and graphs to visualize progress. These are sent to the terminal, allowing the user to easily check their progress. Furthermore, the server analyzes the user's task history and uses an automated response function to suggest actions to take next and areas for improvement. 【0710】 For example, if a user sets the goal of "preparing for next week's project meeting," the server will generate a learning plan and task schedule based on this goal. Furthermore, by using the generative AI model and entering a prompt such as "create a personalized task management plan for a user with attention deficit or hyperactivity," the system will provide the user with the most suitable support plan. 【0711】 This system allows users to achieve flexible task management based on their own characteristics and goals, thereby improving efficiency in their daily lives. 【0712】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0713】 Step 1: 【0714】 Users input basic information, characteristics, and goals through their devices. This information is sent to the server. The server creates a user profile based on the received input data and constructs individual databases tailored to the user's characteristics and goals. This profile contains basic data for personalizing learning plans based on the user's needs. 【0715】 Step 2: 【0716】 Users input their daily tasks and events from their terminals. This information is sent to the server. The server uses this task information to automatically generate a schedule using the Pomodoro Technique. It performs data calculations that take into account the time required and deadlines of the entered tasks, and efficiently allocates work time and break time. The resulting schedule is then sent to the user's terminal. 【0717】 Step 3: 【0718】 The server creates reminders for the user based on the generated schedule. Reminder information is provided to the user in visual and audio formats. The device displays the reminder at the set time and issues an alert via the audio output device. Specifically, it displays a notification on the screen saying, "You have 10 minutes until your next task starts." 【0719】 Step 4: 【0720】 The server aggregates tasks completed by users and generates charts and graphs to visualize their progress. The server receives a list of completed tasks and their estimated time spent as input data. The server analyzes this data and creates graphs showing progress rates and results. These graphs are sent to the user's terminal, allowing them to easily check their own achievements. 【0721】 Step 5: 【0722】 The server analyzes the user's task history and generates feedback using an automated response function. Based on past task data, it performs data calculations to identify trends and areas for improvement, and suggests actions to take next. This feedback is displayed on the terminal, providing the user with specific advice such as, "We recommend adding 30 minutes to your next task." 【0723】 (Application Example 1) 【0724】 Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0725】 Individuals with attention deficit or hyperactivity often struggle with daily task management and the execution of learning plans, requiring improvements in time management and work efficiency. Furthermore, methods are needed to help users maintain sustained motivation through support within the home. Therefore, flexible responses tailored to individual characteristics and support methods utilizing home automation equipment are essential. 【0726】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. 【0727】 This invention includes a server that provides a personalized learning plan based on the user's characteristics and goals and tracks progress; a server that manages the user's time and improves work efficiency using the Pomodoro Technique; and a server that interacts with the user through home automation equipment and assists the user in managing tasks through voice and visual displays. This enables users with attention deficit or hyperactivity to effectively manage their tasks and solve everyday challenges with efficient support in a home environment. 【0728】 A "user" is an individual who utilizes this system, possesses characteristics such as inattention deficit or hyperactivity, and requires efficient task management and learning plan provision. 【0729】 "Household automated devices" are automated devices used in a home environment that interact with the user and assist with task management using visual and auditory means. 【0730】 A "personalized learning plan" is an educational plan individually optimized based on the user's characteristics and goals, and aims to enable users to learn effectively through progress tracking. 【0731】 The "Pomodoro Technique" is a time management method that improves the user's concentration and work efficiency by repeating a fixed work period and break period. 【0732】 "Audio and visual displays" refer to means of facilitating user interaction, including voice instructions and information presentation, as well as visual notifications and reminders. 【0733】 Task management is a process that supports users in planning and executing their daily activities and goal achievements, guiding them while considering efficiency and priorities. 【0734】 This invention provides a system to support personalized learning plans and task management based on user characteristics. Users interact with the system through a home automated device using an interface that utilizes voice and visual displays. 【0735】 The server generates personalized learning plans based on user information, supporting the achievement of individual goals. Specifically, it uses a database to analyze user characteristics and goals, and proposes optimal tasks and schedules. This allows users to effectively execute their learning plans and track their progress. 【0736】 Furthermore, the server utilizes the Pomodoro Technique to efficiently manage the user's work and rest periods, improving work efficiency. The terminal sends visual or audio reminders to the user to help them remember and complete important tasks. 【0737】 Home automation devices use voice recognition software to understand user instructions and provide appropriate feedback. For example, if a user says, "Set up a Pomodoro schedule for tomorrow's meeting," the home automation device sends the information to a server, which generates a schedule and sends it to the device. 【0738】 Furthermore, the server utilizes a generative AI model to analyze the user's behavioral history and provide feedback on the optimal next action to take. This allows users to continuously improve their task management skills. An example of an input prompt for the generative AI model is, "Please provide a detailed example of how to create a personalized learning plan specifically for a student with attention deficit using the Pomodoro Technique." 【0739】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0740】 Step 1: 【0741】 The user gives voice commands through a home automated device. These voice commands are first captured by the device and converted into text format using speech recognition software. The input is voice data, and the output is text data. 【0742】 Step 2: 【0743】 The device sends the converted text data to the server. The server uses this text data to verify the user profile and, referencing a database tailored to the user's characteristics and goals, creates a personalized learning plan or task schedule. The input is the user profile, and the output is a personalized learning plan or task schedule. 【0744】 Step 3: 【0745】 The server sends the generated personalized task schedule to the home automation device. The home automation device presents this schedule to the user visually or audibly and sets timely reminders. The input is the generated schedule data, and the output is the visual / audio reminders to the user. 【0746】 Step 4: 【0747】 When a user completes a task, they send that information back to the server via a home automated device. The server aggregates this completion information and visualizes the user's progress. The input is data on completed tasks, and the output is charts and graphs representing the progress. 【0748】 Step 5: 【0749】 The server uses a generative AI model to analyze user behavior history data. Based on this analysis, it generates optimal actions and feedback to be taken next, and notifies the user through home automated devices. The input is behavior history data, and the output is feedback including improvement suggestions. 【0750】 The above are the specific processing steps for implementing this invention. 【0751】 Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions. 【0752】 This invention combines an emotion engine with an AI agent that supports personalized learning plans and task management based on the user's characteristics and goals, thereby enabling support that also takes the user's emotional state into account. The specific configuration and processing are shown below. 【0753】 Users access the system from their devices and input information about their characteristics, goals, and current emotional state. This information is received by the server and recorded in a database as a user profile. Furthermore, the emotion engine analyzes the user's input and daily activities to estimate their emotional state. 【0754】 This emotion engine allows the server to generate personalized learning plans based on the user's emotions. For example, if a user is feeling stressed, it can suggest content that promotes relaxation or tasks that are easier to manage. Task schedules based on the Pomodoro Technique are also adjusted to take the user's emotional state into account. 【0755】 Reminder notifications are delivered based on information from the emotion engine, tailored to the user's state in terms of timing and content. For example, if the user is fatigued, reminders are scheduled flexibly, prioritizing only important tasks. 【0756】 User progress data is regularly compiled and visualized along with changes in emotions. This allows users to track their work efficiency and mental health over time. The server also uses this data for long-term analysis and provides feedback on the user's mental health. 【0757】 For example, if a user feels anxious about the progress of their learning plan, the server uses an emotion engine to identify the user's emotions and readjust the task priorities and schedules to reduce the user's burden and provide reassurance. 【0758】 With the above configuration, this system provides support that comprehensively considers the user's emotional state, enabling more effective learning and task management. 【0759】 The following describes the processing flow. 【0760】 Step 1: 【0761】 Users log into the system via their device and input information about their characteristics, goals, and current emotional state. This information is collected by the emotion engine for analysis. 【0762】 Step 2: 【0763】 The terminal sends input information to the server. The server receives this information and stores it in the database as a user profile. Additionally, the emotion engine analyzes the user's emotional state and updates the necessary data. 【0764】 Step 3: 【0765】 The server automatically generates a learning plan and task schedule tailored to the user based on the analysis results of the emotion engine. During this process, the workload of the tasks is adjusted according to the user's emotional state. 【0766】 Step 4: 【0767】 The server sends the generated learning plan and schedule to the device. The device then presents this to the user and notifies them that they are ready to begin. 【0768】 Step 5: 【0769】 Once the user begins working on the device, the emotion engine continuously monitors the user's input and actions and evaluates their emotional state. A Pomodoro timer is then activated on the device to support time management based on emotions. 【0770】 Step 6: 【0771】 The server generates a reminder optimized for timing and content based on the user's emotional state. The reminder information is sent to the device, which then presents it to the user. 【0772】 Step 7: 【0773】 The server periodically compiles user progress and visualizes it along with emotional fluctuations. This allows users to monitor their own progress and mental health status. 【0774】 Step 8: 【0775】 The server analyzes the user's long-term task history and sentiment data to generate feedback. This feedback is sent to the terminal and presented to the user, providing suggestions for the next steps and improvements. 【0776】 (Example 2) 【0777】 Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0778】 In today's world, it has become increasingly difficult for users to learn efficiently and effectively under various circumstances. In particular, the effectiveness of learning plans can be significantly reduced when influenced by the emotional state of individual learners, such as stress. Furthermore, flexible responses to emotional changes are required even in task management outside of learning. Therefore, individualized support that comprehensively considers the user's characteristics, goals, and emotional state is necessary, but conventional systems are not adequately able to address this, and a more flexible and effective solution is needed. 【0779】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. 【0780】 In this invention, the server includes means for providing an individualized educational plan based on the user's characteristics, goals, and emotional state; means for estimating the user's mental state using an emotion analysis engine and providing information based thereon; and means for optimizing the user's work efficiency by using time management technology. This enables personalized learning support and emotional care that meets the individual needs of the user. 【0781】 A "user" is an individual or group that utilizes the system, inputting their characteristics, goals, and emotional state into the system and receiving support based on that information. 【0782】 "Characteristics" refer to the individual attributes and tendencies of a user, and the factors that influence their learning style and how they respond. 【0783】 A "goal" is a specific objective or desired outcome that the user aims to achieve, and it serves as the basis for determining the direction of the plans and tasks provided by the system. 【0784】 "Emotional state" refers to information that indicates the type and intensity of emotions a user experiences at a particular point in time, and includes various psychological elements such as stress, fatigue, and anxiety. 【0785】 An "individualized learning plan" is a plan that proposes learning methods and schedules optimized for each individual based on the user's characteristics, goals, and emotional state. 【0786】 A "sentiment analysis engine" refers to a technology or algorithm that analyzes user input information and activity history to estimate the user's emotional state. 【0787】 "Time management techniques" refer to methods and technologies that optimize users' work schedules and support efficient time management. 【0788】 "Work efficiency" is an indicator that shows how effectively a user can complete a task within a set time. 【0789】 A "notification function" is a system feature that informs users of important tasks or events. 【0790】 A "reminder" refers to a message or alert that prompts a user to take action by notifying them of the progress of scheduled tasks or appointments. 【0791】 "Feedback" refers to information and evaluations provided to users to help them better understand their own actions and results. 【0792】 "Visualization" is the process of making it easier for users to understand the situation by visually displaying their progress and changes in emotions. 【0793】 This invention is initiated when a user accesses it through a device. The user inputs data about their characteristics, goals, and emotional state. This information is transmitted from various devices such as tablets, smartphones, or computers. The input data is sent to a central server via the internet. 【0794】 The server creates and records a user-specific profile in a database based on data received from the user. This profile is analyzed by an emotion analysis engine that uses natural language processing and machine learning techniques, known as a generative AI model. The emotion analysis engine estimates the user's specific emotional state (e.g., stress, anxiety, fatigue) and generates a personalized learning plan based on the results. 【0795】 One of the key elements of this system is time management technology. Specifically, the server incorporates techniques such as the Pomodoro Technique to provide users with an optimized work schedule. This allows users to allocate their time efficiently and concentrate on learning and tasks. 【0796】 The notification function is also an important feature of this system, allowing users to receive reminders at the appropriate time. Reminders are adjusted to be sent at the right moment, taking into account the user's current emotional state. 【0797】 Furthermore, the server provides a dashboard to visualize the user's progress and emotional changes. This dashboard serves as a tool for users to monitor their learning efficiency and mental well-being in real time. 【0798】 For example, if a user feels anxious while monitoring their learning plan progress, the server uses an emotion analysis engine to identify that emotion and dynamically readjusts the priority and schedule of corresponding tasks. This allows the user to learn with peace of mind without feeling overwhelmed. 【0799】 By inputting prompts like the following into the AI ​​model, you can obtain more specific countermeasures and plans: 【0800】 "Propose an appropriate learning plan for users with high stress levels." 【0801】 "Please create a task schedule that takes my current emotional state into consideration." 【0802】 "How can I visualize user progress and emotional changes?" 【0803】 In this way, this system addresses the diverse needs of users and realizes a better learning environment and efficient task management. 【0804】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0805】 Step 1: 【0806】 Users access the system using a terminal and input information about their characteristics, goals, and emotional state. This input is in text format and is obtained by users entering specific numbers or text into input fields on the application. The entered data is sent to the server immediately. 【0807】 Step 2: 【0808】 The server stores information received from users in a database. The database updates individual user profiles with the latest information, ensuring consistent user data management. Input is user information (traits, goals, emotional state), and output is the updated user profile data. 【0809】 Step 3: 【0810】 The server activates the sentiment analysis engine based on the received data. The sentiment analysis engine analyzes the user's emotional state using natural language processing and machine learning techniques. In this process, it analyzes the input text data and outputs an emotion score. Specifically, it generates a numerical emotion index based on a standard model used by the scoring algorithm. 【0811】 Step 4: 【0812】 The server generates a personalized learning plan optimized for the user based on the results of the emotion analysis engine. Here, the learning plan is adjusted according to the user's emotional state to reduce stress and improve concentration. The input is the emotion score and user goals, and the output is a personalized learning plan. This plan includes actions such as suggesting specific tasks and their order. 【0813】 Step 5: 【0814】 The server creates reminder schedules and adjusts them based on the user's emotional state. Specifically, it sets appropriate reminder timings for the user's situation and manages them adaptively to avoid excessive notifications. The inputs are emotional state and task priority, and the output is an optimized reminder schedule. 【0815】 Step 6: 【0816】 The server visualizes progress and emotional changes, generating a user-friendly dashboard. Here, graphs and charts are used to visualize data, allowing users to track their progress and mental health. Inputs are progress and emotional data, and output is the visual information displayed as a dashboard. 【0817】 Step 7: 【0818】 The server analyzes users' long-term data and provides feedback. This process involves trend analysis based on historical data, pointing out areas for improvement and successful practices to the user. The input is cumulative data, and the output is a feedback report. This facilitates self-improvement and adaptive learning for the user. 【0819】 (Application Example 2) 【0820】 Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0821】 In today's busy lifestyle, providing personalized task management and learning plans tailored to individual characteristics and emotional states is crucial. However, existing systems struggle to respond flexibly to users' emotions, limiting the effectiveness of life support through integration with machines. Therefore, the challenge lies in providing a system that enables appropriate support in response to users' emotions. 【0822】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. 【0823】 In this invention, the server includes means for providing a personalized learning plan based on the user's characteristics and goals and tracking progress; means for estimating the user's emotional state and adjusting the learning plan and task schedule accordingly; and means for coordinating with household appliances to provide the user with suggestions to promote relaxation. This enables flexible task management and life support that responds to the user's emotions. 【0824】 A "user" refers to an individual who uses a system or service. 【0825】 "Characteristics" refer to the individual characteristics of a user, such as their personality, behavioral patterns, and preferences. 【0826】 "Goals" refer to the specific results or objectives that users want to achieve. 【0827】 A "personalized learning plan" refers to a learning plan specifically designed to suit each user's individual characteristics and goals. 【0828】 "Progress" indicates the current status of achievement towards the goals set by the user. 【0829】 The "Pomodoro Technique" is a time management method that involves repeating a cycle of work followed by breaks to improve work efficiency. 【0830】 "Work efficiency" refers to a user's ability to achieve high results in a short amount of time on a given task. 【0831】 A "reminder" refers to a notification function that periodically informs users of necessary information. 【0832】 "Visualization" refers to clearly displaying a user's progress and task history using graphs, charts, and other visual aids. 【0833】 "Feedback" refers to suggesting further improvements or next actions based on the user's behavior and results. 【0834】 "Emotional state" refers to the user's current psychological or emotional state. 【0835】 "Household machinery and equipment" refers to devices such as robots and smart devices used within the home. 【0836】 "Relaxation" refers to a state or activity that allows users to reduce stress and refresh their mind and body. 【0837】 A system for implementing this invention consists of a user terminal, a server, and a household appliance. 【0838】 Users use their devices to input their characteristics, goals, and current emotional state. This information is sent to the server and recorded in the database as a user profile. 【0839】 Based on this profile, the server uses a generative AI model to create a personalized learning plan for each user. It also uses an emotion engine to estimate emotions from user input and behavior, and adjusts the plan and task schedule accordingly. In this process, it analyzes changes in emotion using Google Cloud AI's emotion recognition API. 【0840】 Furthermore, the server interacts with home appliances and makes suggestions to promote relaxation when the user needs it. For example, if the user is feeling tired, it might play music or adjust the room temperature to a comfortable level. Such home appliances include common robots and smart home devices. 【0841】 For example, if a user feels that they are behind schedule to meet their monthly target, the server can use the prompt message "How to reduce stress" to suggest appropriate relaxation methods from home-use devices and adjust the user's work environment accordingly. 【0842】 In this embodiment, the system provided by the server enables flexible task management and life support tailored to the user's emotions and characteristics. 【0843】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0844】 Step 1: 【0845】 The user uses a terminal to input their characteristics, goals, and current emotional state. The input data is sent to the server in real time. The terminal functions as the user's interface, securing the input data and communicating with the server. 【0846】 Step 2: 【0847】 The server analyzes the received user data and records the user profile in a database. Here, a database management system is used to structure and store the input data. As part of the user profile, characteristics, goals, and emotional states are explicitly stated. 【0848】 Step 3: 【0849】 The server uses a generative AI model to generate a personalized learning plan based on recorded user profiles. User characteristics and goals are used as input data, resulting in an optimal learning plan. The generated plan is customized for each user. 【0850】 Step 4: 【0851】 The server uses an emotion engine to estimate the user's emotional state. The user's recent behavior and entered emotions are used as input data, and the emotion engine analyzes the emotional state. The output is an adjusted plan based on the estimated emotion. 【0852】 Step 5: 【0853】 The server communicates with home appliances and makes suggestions when the user needs relaxation. Based on the analysis of the emotional state, a generative AI model uses prompts to select relaxation methods. This information is sent to home robots and smart devices to instruct them on specific actions. 【0854】 Step 6: 【0855】 Home appliances follow instructions from a server and execute suggestions for the user. Specific examples include playing music or adjusting room temperature and lighting. The system's state after operation is fed back to the server, allowing for optimization in future operations. 【0856】 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 controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data. 【0857】 Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. 【0858】 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 this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414. 【0859】 Furthermore, the emotion identification model 59, acting 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 a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion. 【0860】 Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together. 【0861】 These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression. 【0862】 The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become. 【0863】 Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant. 【0864】 The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is 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 the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more." 【0865】 The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values. 【0866】 The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format. 【0867】 In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data. 【0868】 In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56. 【0869】 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. 【0870】 Furthermore, it is not necessary to store the entirety 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 the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56. 【0871】 The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory. 【0872】 The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of 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). Alternatively, the hardware resource that performs a specific process may consist of a single processor. 【0873】 Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources. 【0874】 Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose. 【0875】 The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above. 【0876】 All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference. 【0877】 The following is further disclosed regarding the embodiments described above. 【0878】 (Claim 1) 【0879】 A means of providing personalized learning plans based on user characteristics and goals, and tracking progress. 【0880】 A method for managing users' time and improving work efficiency using the Pomodoro Technique, 【0881】 A means of providing users with customized reminders through visual or auditory means, 【0882】 A means of visualizing the user's completed tasks and progress, 【0883】 An automated feedback system that analyzes the user's task history and suggests the next action, 【0884】 A system that includes this. 【0885】 (Claim 2) 【0886】 The system according to claim 1, which automatically generates a task schedule based on user input data. 【0887】 (Claim 3) 【0888】 The system according to claim 1, which learns the user's behavior patterns and provides optimal support in real time. 【0889】 "Example 1" 【0890】 (Claim 1) 【0891】 A device that provides personalized learning plans based on the user's characteristics and goals, and tracks their progress. 【0892】 A device that improves the user's work efficiency using time management technology, 【0893】 A device that provides user-specific notifications visually or audibly, 【0894】 A device that visually displays the user's completed tasks and progress, 【0895】 An automated response system that analyzes the user's task history and suggests the next action, 【0896】 A device that sends and receives information through a user interface, 【0897】 A system that includes this. 【0898】 (Claim 2) 【0899】 The system according to claim 1, which automatically generates a task plan based on user input information. 【0900】 (Claim 3) 【0901】 The system according to claim 1, which analyzes user behavior trends and provides timely and optimal support. 【0902】 "Application Example 1" 【0903】 (Claim 1) 【0904】 A means of providing personalized learning plans based on user characteristics and goals, and tracking progress. 【0905】 A method for managing users' time and improving work efficiency using the Pomodoro Technique, 【0906】 A means of providing users with customized reminders through visual or auditory means, 【0907】 A means of visualizing the user's completed tasks and progress, 【0908】 An automated feedback system that analyzes the user's task history and suggests the next action, 【0909】 A means of assisting users in managing their tasks through voice and visual displays using automated home devices, 【0910】 A system that includes this. 【0911】 (Claim 2) 【0912】 The system according to claim 1, which automatically generates a task schedule based on user input data. 【0913】 (Claim 3) 【0914】 The system according to claim 1, which learns the user's behavior patterns and provides optimal support in real time. 【0915】 "Example 2 of combining an emotion engine" 【0916】 (Claim 1) 【0917】 A means of providing individualized educational plans based on the user's characteristics, goals, and emotional state, 【0918】 A means of estimating a user's mental state using an emotion analysis engine and providing information based on that, 【0919】 A means of optimizing user work efficiency by using time management techniques, 【0920】 A means to adjust notification functions and provide flexible reminders according to the user's status, 【0921】 A means of regularly visualizing the user's progress and emotional state, and helping the user monitor their own efficiency and mental health, 【0922】 A means of analyzing information and providing long-term feedback, 【0923】 A system that includes this. 【0924】 (Claim 2) 【0925】 The system according to claim 1, which dynamically generates a task schedule in response to user input information and adapts it based on the user's emotional state. 【0926】 (Claim 3) 【0927】 The system according to claim 1, which learns the user's behavioral and emotional patterns and provides optimal assistance in real time accordingly. 【0928】 "Application example 2 when combining with an emotional engine" 【0929】 (Claim 1) 【0930】 A means of providing personalized learning plans based on user characteristics and goals, and tracking progress. 【0931】 A method for managing users' time and improving work efficiency using the Pomodoro Technique, 【0932】 A means of providing users with customized reminders through visual or auditory means, 【0933】 A means of visualizing the user's completed tasks and progress, 【0934】 An automated feedback system that analyzes the user's task history and suggests the next action, 【0935】 A means of estimating the user's emotional state and adjusting the learning plan and task schedule accordingly, 【0936】 A means of providing suggestions to promote relaxation to users in conjunction with home-use machinery and devices, 【0937】 A system that includes this. 【0938】 (Claim 2) 【0939】 The system according to claim 1, which automatically generates a task schedule based on user input data and adjusts it according to the user's emotions. 【0940】 (Claim 3) 【0941】 The system according to claim 1, which learns the user's behavior patterns and emotional state and provides optimal support in real time. [Explanation of symbols] 【0942】 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

[Claim 1] A means of providing personalized learning plans based on user characteristics and goals, and tracking progress. A method for managing users' time and improving work efficiency using the Pomodoro Technique, A means of providing users with customized reminders through visual or auditory means, A means of visualizing the user's completed tasks and progress, An automated feedback system that analyzes the user's task history and suggests the next action, A system that includes this. [Claim 2] The system according to claim 1, which automatically generates a task schedule based on user input data. [Claim 3] The system according to claim 1, which learns the user's behavior patterns and provides optimal support in real time.

Images