system

Abstract

The system according to this embodiment aims to promote parent-child communication by suggesting appropriate tasks based on the child's interests and abilities. [Solution] The system according to the embodiment comprises an analysis unit, a proposal unit, a confirmation unit, and an advice unit. The analysis unit analyzes the child's interests and abilities. The proposal unit proposes appropriate tasks based on the results analyzed by the analysis unit. The confirmation unit allows parents to check the child's progress. The advice unit provides advice to promote parent-child communication.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor and includes 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] In the conventional technology, it cannot be said that appropriate tasks are sufficiently proposed based on the interests and abilities of children to promote parent-child communication, and there is room for improvement.

[0005] The system according to the embodiment aims to propose appropriate tasks based on the interests and abilities of children and promote parent-child communication.

Means for Solving the Problems

[0006] The system according to this embodiment comprises an analysis unit, a proposal unit, a confirmation unit, and an advice unit. The analysis unit analyzes the child's interests and abilities. The proposal unit proposes appropriate tasks based on the results analyzed by the analysis unit. The confirmation unit allows parents to check the child's progress. The advice unit provides advice to facilitate parent-child communication. [Effects of the Invention]

[0007] The system according to this embodiment can suggest appropriate tasks based on a child's interests and abilities, and can promote communication between parents and children. [Brief explanation of the drawing]

[0008] [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] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This 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] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Modes for carrying out the invention]

[0009] Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings.

[0010] First, let's explain the terminology used in the following explanation.

[0011] 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), APU (Accelerated Processing Unit), or TPU (Tensor Processing Unit).

[0012] 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.

[0013] 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.

[0014] In the following embodiments, the numbered communication I / F (Interface) is an interface including a communication processor, an antenna, and the like. The communication I / F manages communication between a plurality of computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0015] 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 only A, only B, or a combination of A and B. Also, in this specification, when expressing three or more matters connected by "and / or", the same concept as "A and / or B" is applied.

[0016] [First Embodiment] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0017] As shown in FIG. 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.

[0018] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. Also, the database 24 and the communication I / F 26 are connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0019] The smart device 14 comprises a computer 36, a receiving 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 receiving device 38, output device 40, and camera 42 are also connected to the bus 52.

[0020] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, and accepts user input. The touch panel 38A accepts user input via touch by detecting contact with an object (e.g., a pen or finger). The microphone 38B accepts user input via voice 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 unit 12. In the data processing unit 12, the specific processing unit 290 (see Figure 2) acquires the data indicating the user input.

[0021] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user by outputting the data in a form perceptible to the user (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.

[0022] 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.

[0023] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0024] 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.

[0025] 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. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0026] In the smart device 14, specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as a control unit 46A according to the specific processing program 60 executed on the RAM 48. The smart device 14 also has a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0027] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device (e.g., a generation server) may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device having the data generation model 58. The data processing device 12 may also be a server device or a terminal device owned by a user (e.g., a mobile phone, robot, home appliance, etc.). Next, an example of processing by the data processing system 10 according to the first embodiment will be described.

[0028] (Example of form 1) The AI ​​Kids Coach System according to an embodiment of the present invention is an AI-powered application for promoting children's independence and strengthening parent-child communication. This AI Kids Coach System sets daily life tasks and learning goals according to the child's age and developmental stage, and supports their achievement. The AI ​​Kids Coach System analyzes the child's interests and abilities and suggests appropriate tasks. For example, the AI ​​Kids Coach System sets tasks such as "getting ready in the morning independently," "planning and completing homework," and "doing chores," guiding the child to work on them independently. Parents can check the child's progress through the app and provide appropriate feedback. The AI ​​Kids Coach System also provides advice to promote parent-child communication, creating an environment where the whole family supports the child's independence. Furthermore, the AI ​​Kids Coach System analyzes the child's growth record and suggests individualized learning plans and suggestions for improving lifestyle habits. This enables detailed support for independence tailored to each child's individuality and developmental stage. The AI ​​Kids Coach System is a comprehensive independence support tool that fosters children's independence, deepens the parent-child bond, and supports the healthy growth of children. The target audience includes parents with children aged 4 to 12, dual-income families, parents with anxieties and worries about parenting, parents who want to encourage their children's independence, families who use digital devices daily, and education-focused parents. This application features AI-powered personalized independence support programs, an AI assistant to facilitate parent-child communication, child growth tracking and analysis functions, fun and continuous independence support using gamification, expert-supervised parenting advice, and a community function to provide a platform for parents to exchange information. The AI ​​utilizes technologies such as natural language processing for dialogue with children, image recognition for task completion confirmation, machine learning for analyzing and predicting children's behavioral patterns, emotion analysis for understanding children's psychological states, generation of individually optimized tasks and learning content, and generation of personalized advice for parents. As a result, the AI ​​Kids Coach system can promote children's independence and strengthen parent-child communication.

[0029] The AI ​​Kids Coach System according to this embodiment comprises an analysis unit, a suggestion unit, a confirmation unit, and an advice unit. The analysis unit analyzes the child's interests and abilities. For example, the analysis unit analyzes the child's interests based on survey results and behavioral history. The analysis unit can also analyze the child's abilities based on test results and observation records. For example, the analysis unit collects survey results and identifies areas of interest for the child. The analysis unit can also analyze behavioral history and grasp changes in the child's interests. Furthermore, the analysis unit can evaluate test results and measure the child's academic ability. The suggestion unit proposes appropriate tasks based on the results analyzed by the analysis unit. For example, the suggestion unit proposes tasks of varying difficulty and content depending on the child's interests and abilities. For example, the suggestion unit proposes tasks related to areas of interest for the child. The suggestion unit can also propose tasks of appropriate difficulty depending on the child's abilities. Furthermore, the suggestion unit can propose tasks of progressively increasing difficulty as the child grows. The confirmation unit allows parents to check the child's progress. The confirmation unit includes a function to display the child's achievement level and progress, for example. For example, the monitoring unit displays a list of tasks the child has completed. The monitoring unit can also visually display the child's progress using graphs and charts. Furthermore, the monitoring unit can include a function that allows parents to check the child's progress in real time. The advice unit provides advice to facilitate parent-child communication. For example, the advice unit advises on how parents should give feedback to their children. For instance, the advice unit suggests ways for parents to acknowledge their child's efforts. It can also suggest ways for parents to offer appropriate words of encouragement to their children. Furthermore, the advice unit can provide specific advice to help parents support their child's growth. As a result, the AI ​​kids coach system according to this embodiment can suggest appropriate tasks based on the child's interests and abilities, allow parents to check progress, and facilitate parent-child communication.

[0030] The analysis department utilizes various data sources to conduct a detailed analysis of children's interests and abilities. Specifically, it collects data such as survey results, behavioral history, test results, and observation records, and comprehensively analyzes them. Survey results are an important source of information for understanding what activities and learning interests children have. For example, surveys include questions about favorite subjects, hobbies, and future dreams, which can help identify the direction of a child's interests. Behavioral history is data that shows what activities children engage in on a daily basis, such as usage history of learning apps and participation in extracurricular activities. This allows for understanding changes in a child's interests and new interests. Test results are data used to evaluate a child's academic ability and comprehension, such as grades on regular tests and mock exams. This can clearly identify a child's strengths and weaknesses. Observation records are daily records of a child's behavior and reactions kept by teachers and parents, such as attitude in class and how they approach assignments. This allows for evaluation of a child's learning attitude and motivation. The analysis department uses AI to analyze this data and gain a detailed understanding of children's interests and abilities. AI recognizes patterns in data and provides insights into children's interests and abilities. For example, AI can identify areas of interest from survey results and assess how long those interests persist from behavioral history. It can also measure children's academic ability from test results and evaluate their learning attitudes and motivation from observation records. This allows the analytics department to create a comprehensive profile of children's interests and abilities and provide it to the recommendation department, which is the next step.

[0031] The suggestion department proposes appropriate tasks based on profiles of children's interests and abilities provided by the analysis department. The suggestion department uses AI to select and propose tasks best suited to each child's interests and abilities. Specifically, it proposes tasks related to the child's areas of interest and adjusts the difficulty level according to the child's abilities. For example, if a child is interested in science, the suggestion department will propose science-related experiments and projects. Furthermore, it can propose tasks with progressively increasing difficulty, from basic to advanced content, depending on the child's academic level. The suggestion department also adjusts the content and difficulty of tasks as the child grows, continuously providing appropriate tasks. For example, if a child achieves a particular task, it will propose a more difficult task as the next step. The suggestion department can also flexibly review tasks in response to changes in the child's interests and abilities. For example, if a child's interests shift to a new field, it will propose tasks related to that field. The suggestion department not only provides these tasks to children but also shares them with parents and teachers, providing information to support the child's learning. This allows the suggestion department to propose appropriate tasks based on the child's interests and abilities, increasing their motivation to learn and promoting their growth.

[0032] The monitoring section provides parents with the ability to check their child's progress in detail. It features an interface for visually displaying the child's achievements and progress. Specifically, it displays a list of tasks the child has completed and the status of ongoing assignments. The monitoring section also visually displays the child's progress using graphs and charts, allowing parents to grasp their child's learning situation at a glance. Examples include bar graphs showing the child's achievement level and pie charts showing progress. Furthermore, the monitoring section provides parents with the ability to check their child's progress in real time. This allows parents to constantly monitor their child's learning situation and provide support and feedback as needed. In addition to allowing parents to check their child's learning situation in detail, the monitoring section also provides a function to record the child's growth and progress and compare it with past data. This allows parents to track their child's growth over the long term and evaluate their learning outcomes. For example, they can compare past test results and assignment completion status to see their child's growth. Through these functions, the monitoring section provides parents with the information necessary to understand their child's learning situation in detail and provide appropriate support.

[0033] The Advice Department provides specific advice to promote parent-child communication. It offers concrete suggestions on how parents should provide feedback to their children. For example, it suggests ways for parents to acknowledge their children's efforts and offer appropriate words of encouragement. Specifically, it advises on specific phrases to use when praising children's achievements and how to encourage them when they face difficulties. The Advice Department also provides specific advice for parents to support their children's growth. For example, it suggests ways for parents to create a suitable learning environment and activities to stimulate children's interests. Furthermore, the Advice Department provides tips and techniques for parents to improve communication with their children. For example, it suggests ways for parents to ask questions that facilitate dialogue and ways to respect children's opinions. Through this advice, the Advice Department provides concrete assistance to promote parent-child communication and support children's growth. In this way, the Advice Department provides information to help parents provide appropriate feedback and support to their children, thereby improving parent-child relationships.

[0034] The AI ​​Kids Coaching System includes a Growth Analysis Department. This department analyzes children's growth records. For example, it collects and analyzes growth records such as height, weight, and learning outcomes. For instance, it records changes in a child's height and weight to understand growth trends. It can also evaluate a child's learning outcomes and confirm improvements in academic ability. Furthermore, the Growth Analysis Department can analyze a child's growth records over the long term to identify growth patterns. This allows the Growth Analysis Department to propose individualized learning plans and suggestions for improving lifestyle habits based on the child's growth records.

[0035] The AI ​​Kids Coaching System includes an Improvement Suggestion Unit. This unit proposes individualized learning plans and suggestions for improving daily habits. For example, it proposes specific improvement plans based on the child's learning goals and daily habits. For instance, it creates an appropriate learning plan according to the child's learning goals. It can also provide specific suggestions for improving the child's daily habits. Furthermore, the Improvement Suggestion Unit can update its improvement plans in stages as the child grows. This allows the Improvement Suggestion Unit to support the child's independence by proposing individualized learning plans and suggestions for improving daily habits.

[0036] The AI ​​Kids Coach System includes a support unit. The support unit utilizes gamification to support independence. For example, the support unit provides tasks and reward systems that incorporate game elements. For example, the support unit provides a system in which children can earn points each time they complete a task. The support unit can also provide game-style challenges that allow children to learn while having fun. Furthermore, the support unit can provide a reward system in which children can earn badges and titles according to the tasks they complete. In this way, the support unit utilizes gamification to enable children to engage in independence support in an enjoyable way. Some or all of the above processing in the support unit may be performed using AI, for example, or without using AI.

[0037] The AI ​​Kids Coaching System includes an Expert Advice Section. This section provides expert-supervised parenting advice. For example, the Expert Advice Section provides appropriate advice to parents based on advice provided by qualified experts. For instance, the Expert Advice Section provides expert-supervised parenting guidelines. It can also provide expert-supervised Q&A on parenting. Furthermore, the Expert Advice Section can provide expert-supervised videos and articles on parenting. This allows parents to receive appropriate advice by providing expert-supervised parenting advice. Some or all of the above processes in the Expert Advice Section may be performed using AI, or not.

[0038] The AI ​​Kids Coaching System includes a Community Section. This section provides a platform for parents to exchange information. For example, the Community Section offers online forums and offline meetings where parents can share information. It can also host offline meetings where parents can meet in person to exchange information. Furthermore, the Community Section can provide a platform for parents to consult with experts. In this way, the Community Section facilitates information sharing among parents by providing a platform for information exchange.

[0039] The analytics department can analyze a child's past behavioral history and predict changes in their interests and abilities. For example, it can analyze a child's past work history to predict whether their areas of interest are changing. For example, it can analyze a child's past performance and feedback to predict improvements or declines in their abilities. Furthermore, the analytics department can analyze a child's past behavioral patterns to predict future changes in their interests and abilities. In short, by analyzing a child's past behavioral history, the analytics department can predict changes in their interests and abilities.

[0040] The analysis unit can apply different analysis algorithms depending on the child's learning style. For example, if a child prefers visual learning, the analysis unit will apply an analysis algorithm that emphasizes visual data. For example, if a child prefers auditory learning, the analysis unit will apply an analysis algorithm that emphasizes audio data. Furthermore, if a child prefers experiential learning, the analysis unit can also apply an analysis algorithm that emphasizes practical data. In this way, the analysis unit can obtain more appropriate analysis results by applying an analysis algorithm according to the child's learning style.

[0041] The analysis department can prioritize analyzing highly relevant data by considering the child's geographical location during the analysis process. For example, the analysis department can prioritize analyzing issues related to the region where the child lives by considering the characteristics of the area in which the child lives. For example, the analysis department can prioritize analyzing relevant data based on the curriculum of the school the child attends. The analysis department can also prioritize analyzing relevant data based on local events and activities in which the child participates. As a result, the analysis department can propose more appropriate issues by prioritizing the analysis of highly relevant data while considering the child's geographical location.

[0042] The analytics department can analyze children's social media activity during analysis to understand their interests and abilities. For example, the analytics department can analyze the content children frequently post on social media to identify areas of interest. For example, the analytics department can analyze the accounts and groups children follow to understand their areas of interest. The analytics department can also analyze the events and activities children participate in on social media to understand their interests and abilities. In this way, the analytics department can understand children's interests and abilities by analyzing their social media activity.

[0043] The proposal team can adjust the level of detail in their proposals based on the difficulty of the problem. For example, for easy problems, the proposal team provides a simple explanation. For difficult problems, the proposal team provides a detailed explanation or hints. For medium-difficulty problems, the proposal team can also provide an explanation with an appropriate level of detail. This allows the proposal team to propose more appropriate problems by adjusting the level of detail based on the difficulty of the problem.

[0044] The proposal function can apply different proposal algorithms depending on the category of the problem. For example, for learning problems, the proposal function applies an educational algorithm. For household chore problems, it applies a practical algorithm. Furthermore, for social problems, the proposal function can apply an algorithm that emphasizes communication skills. In this way, the proposal function can propose more appropriate problems by applying different proposal algorithms depending on the category of the problem.

[0045] The proposal team can prioritize proposals based on the submission deadlines for each assignment. For example, the team might prioritize assignments with approaching deadlines, while delaying assignments with later deadlines. They can also adjust the priority of assignments with medium-term deadlines. This allows the team to propose more appropriate assignments by prioritizing them based on their submission deadlines.

[0046] The proposal department can adjust the order of proposals based on the relevance of the issues. For example, the proposal department may prioritize issues related to the child's interests. For example, the proposal department may prioritize issues related to the child's abilities. It can also prioritize issues related to the child's current learning content. In this way, the proposal department can propose more appropriate issues by adjusting the order of proposals based on the relevance of the issues.

[0047] The verification unit can select the optimal verification method by referring to the child's past progress data during the verification process. For example, the verification unit analyzes the child's past progress data and selects the optimal verification method. For example, the verification unit adjusts the progress verification method by referring to the child's past performance. The verification unit can also select the progress verification method based on the child's past feedback. In this way, the verification unit can select the optimal verification method by referring to the child's past progress data.

[0048] The monitoring unit can customize the means of checking progress based on the child's current living situation. For example, if the child is busy, the monitoring unit will perform a brief progress check. For example, if the child is relaxed, the monitoring unit will perform a detailed progress check. Furthermore, if the child is stressed, the monitoring unit can perform a relaxing progress check. In this way, the monitoring unit can perform more appropriate progress checks by customizing the means of checking progress based on the child's current living situation.

[0049] The verification unit can select the most appropriate verification method by considering the parent's geographical location information during verification. For example, if the parent is at home, the verification unit will perform a detailed progress check. For example, if the parent is out, the verification unit will perform a concise progress check. Furthermore, if the parent is at work, the verification unit can perform a concise progress check. In this way, the verification unit can perform more appropriate progress checks by selecting the most appropriate verification method by considering the parent's geographical location information.

[0050] The verification unit can analyze the parent's social media activity during verification and propose methods for monitoring progress. For example, the verification unit can analyze the content that the parent frequently posts on social media and propose the most suitable method for monitoring progress. For example, the verification unit can analyze the accounts and groups that the parent follows and propose the most suitable method for monitoring progress. Furthermore, the verification unit can analyze the events and activities that the parent participates in on social media and propose the most suitable method for monitoring progress. In this way, the verification unit can perform more appropriate progress monitoring by analyzing the parent's social media activity and proposing methods for monitoring progress.

[0051] The advice function can provide optimal advice by referring to the parent's past feedback when offering advice. For example, the advice function can analyze the parent's past feedback to provide the best advice. For example, the advice function can adjust the content of the advice by referring to the parent's past advice history. The advice function can also select the method of providing advice based on the parent's past feedback. In this way, the advice function can provide more appropriate advice by referring to the parent's past feedback to provide the best advice.

[0052] The advice service can customize the content of advice based on the parents' current living situation. For example, if the parents are busy, the service will provide concise advice. If the parents are relaxed, the service will provide detailed advice. Furthermore, if the parents are stressed, the service can provide relaxing advice. This allows the service to provide more appropriate advice by customizing it based on the parents' current living situation.

[0053] The advice department can provide optimal advice by considering the parent's geographical location. For example, if the parent is at home, the advice department will provide detailed advice. For example, if the parent is out, the advice department will provide concise advice. Furthermore, if the parent is at work, the advice department can provide concise advice. In this way, the advice department can provide more appropriate advice by considering the parent's geographical location.

[0054] The advice department can analyze parents' social media activity when providing advice and suggest appropriate advice. For example, it can analyze the content parents frequently post on social media and provide the most suitable advice. For example, it can analyze the accounts and groups parents follow and provide the most suitable advice. It can also analyze the events and activities parents participate in on social media and provide the most suitable advice. In this way, the advice department can provide more appropriate advice by analyzing parents' social media activity and suggesting appropriate advice.

[0055] The growth analysis unit can predict growth trends by referring to past growth data when analyzing growth records. For example, the growth analysis unit can predict growth trends by analyzing a child's past growth data. For example, the growth analysis unit can predict growth trends by referring to a child's past performance and feedback. The growth analysis unit can also predict future growth trends by analyzing a child's past behavioral patterns. As a result, the growth analysis unit can perform more appropriate analysis of growth records by referring to past growth data to predict growth trends.

[0056] The Growth Analysis Department can apply different analytical methods to each child's category when analyzing growth records. For example, in the case of learning growth records, the Growth Analysis Department applies educational analytical methods. For example, in the case of social growth records, the Growth Analysis Department applies analytical methods that emphasize communication skills. Furthermore, in the case of physical growth records, the Growth Analysis Department can also apply analytical methods that emphasize health data. In this way, the Growth Analysis Department can perform more appropriate analysis of growth records by applying different analytical methods to each child's category.

[0057] The Growth Analysis Department can analyze changes in a child's growth based on when the growth records were submitted. For example, it can analyze growth records submitted by a child at a specific time and identify changes in growth during that period. For example, it can predict changes in growth based on when the child submitted the growth records. Furthermore, the Growth Analysis Department can analyze changes in growth based on when the child submitted the records and predict future growth. This allows the Growth Analysis Department to perform a more appropriate analysis of growth records by analyzing changes in growth based on when the child submitted the records.

[0058] The Growth Analysis Department can analyze growth by referencing relevant market data for children when analyzing growth records. For example, the Growth Analysis Department can compare children's growth records with relevant market data to analyze growth trends. For example, the Growth Analysis Department can identify changes in growth by comparing children's growth records with relevant market data. The Growth Analysis Department can also integrate children's growth records with relevant market data to make growth forecasts. This allows the Growth Analysis Department to perform more appropriate analysis of growth records by referencing relevant market data for children.

[0059] The Improvement Proposal Department can provide optimal improvement proposals by referring to past improvement data when proposing improvement plans. For example, the Improvement Proposal Department can analyze a child's past improvement data to provide the optimal improvement plan. For example, the Improvement Proposal Department can adjust improvement plans by referring to a child's past performance and feedback. The Improvement Proposal Department can also analyze a child's past behavioral patterns to provide the optimal improvement plan. In this way, the Improvement Proposal Department can propose more appropriate improvement plans by referring to past improvement data to provide the optimal improvement plan.

[0060] The improvement suggestion department can customize the content of improvement suggestions based on the child's current living situation. For example, if the child is busy, the department will provide a concise suggestion. For example, if the child is relaxed, the department will provide a detailed suggestion. Furthermore, if the child is stressed, the department can provide a suggestion that helps the child relax. In this way, the improvement suggestion department can propose more appropriate improvement suggestions by customizing the content of the suggestions based on the child's current living situation.

[0061] The Improvement Proposal Department can provide optimal improvement proposals by considering the child's geographical location when proposing improvements. For example, the Improvement Proposal Department can provide improvement proposals relevant to the area where the child lives by considering the characteristics of the area. For example, the Improvement Proposal Department can provide relevant improvement proposals based on the curriculum of the school the child attends. Furthermore, the Improvement Proposal Department can also provide relevant improvement proposals based on local events and activities in which the child participates. In this way, the Improvement Proposal Department can propose more appropriate improvement proposals by considering the child's geographical location.

[0062] The Improvement Proposal Department can analyze children's social media activity when proposing improvement plans. For example, it can analyze the content children frequently post on social media and provide optimal improvement plans. For example, it can analyze the accounts and groups children follow and provide optimal improvement plans. It can also analyze the events and activities children participate in on social media and provide optimal improvement plans. In this way, the Improvement Proposal Department can propose more appropriate improvement plans by analyzing children's social media activity and proposing improvement plans based on that analysis.

[0063] The support department can provide the most appropriate support methods by referring to past support data during the support process. For example, the support department can analyze a child's past support data to provide the most suitable support methods. For example, the support department can adjust support methods by referring to a child's past performance and feedback. The support department can also analyze a child's past behavioral patterns to provide the most appropriate support methods. In this way, the support department can provide more appropriate support by referring to past support data to provide the most appropriate support methods.

[0064] The support department can customize the content of support based on the child's current living situation. For example, if the child is busy, the support department can provide concise support methods. For example, if the child is relaxed, the support department can provide detailed support methods. Furthermore, if the child is stressed, the support department can provide support methods that help the child relax. In this way, the support department can provide more appropriate support by customizing the content of support based on the child's current living situation.

[0065] The support department can provide the most appropriate support method when providing assistance, taking into account the child's geographical location. For example, the support department can provide support methods relevant to the area where the child lives, taking into account the characteristics of the area in which the child lives. For example, the support department can provide relevant support methods based on the curriculum of the school the child attends. Furthermore, the support department can also provide relevant support methods based on local events and activities in which the child participates. In this way, the support department can provide more appropriate support by considering the child's geographical location and providing the most appropriate support method.

[0066] The support department can analyze a child's social media activity and propose appropriate support during the support process. For example, the support department can analyze the content a child frequently posts on social media and provide the most suitable support methods. For example, the support department can analyze the accounts and groups a child follows and provide the most suitable support methods. The support department can also analyze the events and activities a child participates in on social media and provide the most suitable support methods. This allows the support department to provide more appropriate support by analyzing a child's social media activity and proposing appropriate support methods.

[0067] The expert advice department can provide optimal advice by referring to past advice data when offering expert advice. For example, the expert advice department can analyze parents' past advice data to provide optimal advice. For example, the expert advice department can adjust the content of advice by referring to parents' past feedback. The expert advice department can also select the method of providing advice based on parents' past advice history. In this way, the expert advice department can provide more appropriate advice by referring to past advice data to provide optimal advice.

[0068] The expert advice department can customize the content of its advice based on the parents' current living situation. For example, if the parents are busy, the expert advice department will provide concise advice. For example, if the parents are relaxed, the expert advice department will provide detailed advice. Furthermore, if the parents are stressed, the expert advice department can also provide advice that helps them relax. In this way, the expert advice department can provide more appropriate advice by customizing the content of its advice based on the parents' current living situation.

[0069] The expert advice department can provide optimal advice by considering the parent's geographical location when offering expert advice. For example, if the parent is at home, the expert advice department can provide detailed expert advice. For example, if the parent is out, the expert advice department can provide concise expert advice. Furthermore, if the parent is at work, the expert advice department can provide concise expert advice. In this way, the expert advice department can provide more appropriate advice by considering the parent's geographical location.

[0070] The expert advice department can analyze parents' social media activity when providing expert advice and propose appropriate advice. For example, the expert advice department can analyze the content that parents frequently post on social media and provide the most suitable expert advice. For example, the expert advice department can analyze the accounts and groups that parents follow and provide the most suitable expert advice. In addition, the expert advice department can analyze the events and activities that parents participate in on social media and provide the most suitable expert advice. In this way, the expert advice department can provide more appropriate advice by analyzing parents' social media activity and proposing appropriate advice.

[0071] The Community Department can provide the most suitable community by referring to past community data when providing a community. For example, the Community Department can analyze parents' past community participation history to provide the most suitable community. For example, the Community Department can adjust the community content by referring to parents' past feedback. The Community Department can also provide the most suitable community based on parents' past community participation data. In this way, the Community Department can provide a more appropriate community by referring to past community data to provide the most suitable community.

[0072] The Community Department can customize the content of community services based on the parents' current living situation when providing them. For example, if the parents are busy, the Community Department can provide concise community information. For example, if the parents are relaxed, the Community Department can provide detailed community information. Furthermore, if the parents are stressed, the Community Department can provide relaxing community information. In this way, the Community Department can provide more appropriate community services by customizing the content of community services based on the parents' current living situation.

[0073] The Community Department can provide the most suitable community by considering the parent's geographical location when providing community information. For example, if the parent is at home, the Community Department can provide detailed community information. For example, if the parent is out, the Community Department can provide concise community information. Furthermore, if the parent is at work, the Community Department can provide concise community information. In this way, the Community Department can provide a more appropriate community by considering the parent's geographical location.

[0074] The Community Department can analyze parents' social media activity and suggest community content when providing a community. For example, the Community Department can analyze the content parents frequently post on social media and provide the most suitable community. For example, the Community Department can analyze the accounts and groups parents follow and provide the most suitable community. The Community Department can also analyze the events and activities parents participate in on social media and provide the most suitable community. In this way, the Community Department can provide more appropriate communities by analyzing parents' social media activity and suggesting community content.

[0075] The system according to the embodiment is not limited to the example described above, and various modifications are possible, for example, as follows.

[0076] The AI ​​Kids Coaching System also includes a reward management unit. This unit manages rewards for tasks that children complete. For example, it can award points for each task a child completes, and these points can be used to obtain virtual items and rewards. The reward management unit can also manage rewards set by parents and provide rewards according to the tasks that children complete. Furthermore, the reward management unit can record the history of tasks completed by children and manage the history of rewards. This allows the reward management unit to strengthen children's motivation to complete tasks and provide continuous support for their independence.

[0077] The AI ​​Kids Coaching System also includes a Health Management Department. This department manages the child's health status. For example, it collects records of the child's diet and exercise, and evaluates their health. It can also record the child's sleep patterns and suggest appropriate sleep durations. Furthermore, based on the child's health status, the Health Management Department can provide appropriate diet and exercise advice. In this way, the Health Management Department can comprehensively manage the child's health and support their healthy growth.

[0078] The AI ​​Kids Coaching System also includes a Friendship Management section. This section manages children's friendships. For example, it suggests tasks that children can work on with friends and encourages them to cooperate to achieve them. It can also provide advice on how children communicate with their friends. Furthermore, it can suggest events and activities that children can enjoy with their friends. In this way, the Friendship Management section can support children's friendships and promote their social development.

[0079] The AI ​​Kids Coaching System also includes a Time Management Unit. This unit manages how children spend their time. For example, it creates schedules to help children complete tasks systematically. It can also provide advice on how children can use their time effectively. Furthermore, it can provide reminder functions to help children adhere to schedules. In this way, the Time Management Unit can improve children's time management skills and promote independence.

[0080] The AI ​​Kids Coaching System also includes a Safety Management Department. This department manages the safety of children. For example, it provides filtering functions to ensure children can use the internet safely. It can also suggest safety measures for children when they are out and about. Furthermore, it can advise on how to handle situations if a child encounters a dangerous environment. This allows the Safety Management Department to ensure children's safety and promote their independence with peace of mind.

[0081] The following briefly describes the processing flow for example form 1.

[0082] Step 1: The analysis department analyzes the child's interests and abilities. For example, they analyze the child's interests based on survey results and behavioral history, and analyze the child's abilities based on test results and observation records. This makes it possible to identify the child's areas of interest and academic ability, and to understand changes in their interests. Step 2: The proposal department proposes appropriate tasks based on the results of the analysis conducted by the analysis department. For example, they can propose tasks of varying difficulty and content depending on the child's interests and abilities, and then propose tasks that gradually increase in difficulty as the child grows. Step 3: The monitoring section allows parents to check their child's progress. For example, it includes a function to display the child's achievement level and progress, visually showing a list of tasks and progress in graphs and charts, allowing parents to check in real time. Step 4: The advice section provides advice to facilitate parent-child communication. For example, it offers specific advice on how parents should give feedback to their children, how to acknowledge their efforts, how to offer appropriate words of encouragement, and how to support their growth.

[0083] (Example of form 2) The AI ​​Kids Coach System according to an embodiment of the present invention is an AI-powered application for promoting children's independence and strengthening parent-child communication. This AI Kids Coach System sets daily life tasks and learning goals according to the child's age and developmental stage, and supports their achievement. The AI ​​Kids Coach System analyzes the child's interests and abilities and suggests appropriate tasks. For example, the AI ​​Kids Coach System sets tasks such as "getting ready in the morning independently," "planning and completing homework," and "doing chores," guiding the child to work on them independently. Parents can check the child's progress through the app and provide appropriate feedback. The AI ​​Kids Coach System also provides advice to promote parent-child communication, creating an environment where the whole family supports the child's independence. Furthermore, the AI ​​Kids Coach System analyzes the child's growth record and suggests individualized learning plans and suggestions for improving lifestyle habits. This enables detailed support for independence tailored to each child's individuality and developmental stage. The AI ​​Kids Coach System is a comprehensive independence support tool that fosters children's independence, deepens the parent-child bond, and supports the healthy growth of children. The target audience includes parents with children aged 4 to 12, dual-income families, parents with anxieties and worries about parenting, parents who want to encourage their children's independence, families who use digital devices daily, and education-focused parents. This application features AI-powered personalized independence support programs, an AI assistant to facilitate parent-child communication, child growth tracking and analysis functions, fun and continuous independence support using gamification, expert-supervised parenting advice, and a community function to provide a platform for parents to exchange information. The AI ​​utilizes technologies such as natural language processing for dialogue with children, image recognition for task completion confirmation, machine learning for analyzing and predicting children's behavioral patterns, emotion analysis for understanding children's psychological states, generation of individually optimized tasks and learning content, and generation of personalized advice for parents. As a result, the AI ​​Kids Coach system can promote children's independence and strengthen parent-child communication.

[0084] The AI ​​Kids Coach System according to this embodiment comprises an analysis unit, a suggestion unit, a confirmation unit, and an advice unit. The analysis unit analyzes the child's interests and abilities. For example, the analysis unit analyzes the child's interests based on survey results and behavioral history. The analysis unit can also analyze the child's abilities based on test results and observation records. For example, the analysis unit collects survey results and identifies areas of interest for the child. The analysis unit can also analyze behavioral history and grasp changes in the child's interests. Furthermore, the analysis unit can evaluate test results and measure the child's academic ability. The suggestion unit proposes appropriate tasks based on the results analyzed by the analysis unit. For example, the suggestion unit proposes tasks of varying difficulty and content depending on the child's interests and abilities. For example, the suggestion unit proposes tasks related to areas of interest for the child. The suggestion unit can also propose tasks of appropriate difficulty depending on the child's abilities. Furthermore, the suggestion unit can propose tasks of progressively increasing difficulty as the child grows. The confirmation unit allows parents to check the child's progress. The confirmation unit includes a function to display the child's achievement level and progress, for example. For example, the monitoring unit displays a list of tasks the child has completed. The monitoring unit can also visually display the child's progress using graphs and charts. Furthermore, the monitoring unit can include a function that allows parents to check the child's progress in real time. The advice unit provides advice to facilitate parent-child communication. For example, the advice unit advises on how parents should give feedback to their children. For instance, the advice unit suggests ways for parents to acknowledge their child's efforts. It can also suggest ways for parents to offer appropriate words of encouragement to their children. Furthermore, the advice unit can provide specific advice to help parents support their child's growth. As a result, the AI ​​kids coach system according to this embodiment can suggest appropriate tasks based on the child's interests and abilities, allow parents to check progress, and facilitate parent-child communication.

[0085] The analysis department utilizes various data sources to conduct a detailed analysis of children's interests and abilities. Specifically, it collects data such as survey results, behavioral history, test results, and observation records, and comprehensively analyzes them. Survey results are an important source of information for understanding what activities and learning interests children have. For example, surveys include questions about favorite subjects, hobbies, and future dreams, which can help identify the direction of a child's interests. Behavioral history is data that shows what activities children engage in on a daily basis, such as usage history of learning apps and participation in extracurricular activities. This allows for understanding changes in a child's interests and new interests. Test results are data used to evaluate a child's academic ability and comprehension, such as grades on regular tests and mock exams. This can clearly identify a child's strengths and weaknesses. Observation records are daily records of a child's behavior and reactions kept by teachers and parents, such as attitude in class and how they approach assignments. This allows for evaluation of a child's learning attitude and motivation. The analysis department uses AI to analyze this data and gain a detailed understanding of children's interests and abilities. AI recognizes patterns in data and provides insights into children's interests and abilities. For example, AI can identify areas of interest from survey results and assess how long those interests persist from behavioral history. It can also measure children's academic ability from test results and evaluate their learning attitudes and motivation from observation records. This allows the analytics department to create a comprehensive profile of children's interests and abilities and provide it to the recommendation department, which is the next step.

[0086] The suggestion department proposes appropriate tasks based on profiles of children's interests and abilities provided by the analysis department. The suggestion department uses AI to select and propose tasks best suited to each child's interests and abilities. Specifically, it proposes tasks related to the child's areas of interest and adjusts the difficulty level according to the child's abilities. For example, if a child is interested in science, the suggestion department will propose science-related experiments and projects. Furthermore, it can propose tasks with progressively increasing difficulty, from basic to advanced content, depending on the child's academic level. The suggestion department also adjusts the content and difficulty of tasks as the child grows, continuously providing appropriate tasks. For example, if a child achieves a particular task, it will propose a more difficult task as the next step. The suggestion department can also flexibly review tasks in response to changes in the child's interests and abilities. For example, if a child's interests shift to a new field, it will propose tasks related to that field. The suggestion department not only provides these tasks to children but also shares them with parents and teachers, providing information to support the child's learning. This allows the suggestion department to propose appropriate tasks based on the child's interests and abilities, increasing their motivation to learn and promoting their growth.

[0087] The monitoring section provides parents with the ability to check their child's progress in detail. It features an interface for visually displaying the child's achievements and progress. Specifically, it displays a list of tasks the child has completed and the status of ongoing assignments. The monitoring section also visually displays the child's progress using graphs and charts, allowing parents to grasp their child's learning situation at a glance. Examples include bar graphs showing the child's achievement level and pie charts showing progress. Furthermore, the monitoring section provides parents with the ability to check their child's progress in real time. This allows parents to constantly monitor their child's learning situation and provide support and feedback as needed. In addition to allowing parents to check their child's learning situation in detail, the monitoring section also provides a function to record the child's growth and progress and compare it with past data. This allows parents to track their child's growth over the long term and evaluate their learning outcomes. For example, they can compare past test results and assignment completion status to see their child's growth. Through these functions, the monitoring section provides parents with the information necessary to understand their child's learning situation in detail and provide appropriate support.

[0088] The Advice Department provides specific advice to promote parent-child communication. It offers concrete suggestions on how parents should provide feedback to their children. For example, it suggests ways for parents to acknowledge their children's efforts and offer appropriate words of encouragement. Specifically, it advises on specific phrases to use when praising children's achievements and how to encourage them when they face difficulties. The Advice Department also provides specific advice for parents to support their children's growth. For example, it suggests ways for parents to create a suitable learning environment and activities to stimulate children's interests. Furthermore, the Advice Department provides tips and techniques for parents to improve communication with their children. For example, it suggests ways for parents to ask questions that facilitate dialogue and ways to respect children's opinions. Through this advice, the Advice Department provides concrete assistance to promote parent-child communication and support children's growth. In this way, the Advice Department provides information to help parents provide appropriate feedback and support to their children, thereby improving parent-child relationships.

[0089] The AI ​​Kids Coaching System includes a Growth Analysis Department. This department analyzes children's growth records. For example, it collects and analyzes growth records such as height, weight, and learning outcomes. For instance, it records changes in a child's height and weight to understand growth trends. It can also evaluate a child's learning outcomes and confirm improvements in academic ability. Furthermore, the Growth Analysis Department can analyze a child's growth records over the long term to identify growth patterns. This allows the Growth Analysis Department to propose individualized learning plans and suggestions for improving lifestyle habits based on the child's growth records.

[0090] The AI ​​Kids Coaching System includes an Improvement Suggestion Unit. This unit proposes individualized learning plans and suggestions for improving daily habits. For example, it proposes specific improvement plans based on the child's learning goals and daily habits. For instance, it creates an appropriate learning plan according to the child's learning goals. It can also provide specific suggestions for improving the child's daily habits. Furthermore, the Improvement Suggestion Unit can update its improvement plans in stages as the child grows. This allows the Improvement Suggestion Unit to support the child's independence by proposing individualized learning plans and suggestions for improving daily habits.

[0091] The AI ​​Kids Coach System includes a support unit. The support unit utilizes gamification to support independence. For example, the support unit provides tasks and reward systems that incorporate game elements. For example, the support unit provides a system in which children can earn points each time they complete a task. The support unit can also provide game-style challenges that allow children to learn while having fun. Furthermore, the support unit can provide a reward system in which children can earn badges and titles according to the tasks they complete. In this way, the support unit utilizes gamification to enable children to engage in independence support in an enjoyable way. Some or all of the above processing in the support unit may be performed using AI, for example, or without using AI.

[0092] The AI ​​Kids Coaching System includes an Expert Advice Section. This section provides expert-supervised parenting advice. For example, the Expert Advice Section provides appropriate advice to parents based on advice provided by qualified experts. For instance, the Expert Advice Section provides expert-supervised parenting guidelines. It can also provide expert-supervised Q&A on parenting. Furthermore, the Expert Advice Section can provide expert-supervised videos and articles on parenting. This allows parents to receive appropriate advice by providing expert-supervised parenting advice. Some or all of the above processes in the Expert Advice Section may be performed using AI, or not.

[0093] The AI ​​Kids Coaching System includes a Community Section. This section provides a platform for parents to exchange information. For example, the Community Section offers online forums and offline meetings where parents can share information. It can also host offline meetings where parents can meet in person to exchange information. Furthermore, the Community Section can provide a platform for parents to consult with experts. In this way, the Community Section facilitates information sharing among parents by providing a platform for information exchange.

[0094] The analysis unit can estimate a child's emotions and adjust its analysis methods for interests and abilities based on those estimated emotions. For example, the analysis unit can estimate a child's emotions using facial recognition or voice analysis. For instance, it can capture a child's facial expressions with a camera and estimate their emotions using an emotion estimation algorithm. It can also record a child's voice and estimate their emotions using voice analysis technology. Furthermore, the analysis unit can adjust its analysis methods for interests and abilities based on the child's emotions. For example, if the child is enjoying themselves, the analysis unit will prioritize areas of interest in order to suggest game-like tasks. If the child is stressed, the analysis unit will identify the cause of the stress and adjust its analysis methods accordingly to suggest relaxing tasks. Furthermore, if the child is focused, the analysis unit will perform analysis to suggest more challenging tasks to maintain their concentration. In this way, the analysis unit can suggest more appropriate tasks by adjusting its analysis methods based on the child's emotions.

[0095] The analytics department can analyze a child's past behavioral history and predict changes in their interests and abilities. For example, it can analyze a child's past work history to predict whether their areas of interest are changing. For example, it can analyze a child's past performance and feedback to predict improvements or declines in their abilities. Furthermore, the analytics department can analyze a child's past behavioral patterns to predict future changes in their interests and abilities. In short, by analyzing a child's past behavioral history, the analytics department can predict changes in their interests and abilities.

[0096] The analysis unit can apply different analysis algorithms depending on the child's learning style. For example, if a child prefers visual learning, the analysis unit will apply an analysis algorithm that emphasizes visual data. For example, if a child prefers auditory learning, the analysis unit will apply an analysis algorithm that emphasizes audio data. Furthermore, if a child prefers experiential learning, the analysis unit can also apply an analysis algorithm that emphasizes practical data. In this way, the analysis unit can obtain more appropriate analysis results by applying an analysis algorithm according to the child's learning style.

[0097] The analysis unit can estimate a child's emotions and prioritize the analysis results based on those emotions. For example, if a child is excited, the analysis unit will prioritize displaying analysis results related to areas of interest. For example, if a child is anxious, the analysis unit will prioritize displaying analysis results that provide a sense of security. Furthermore, if a child is tired, the analysis unit can prioritize displaying analysis results related to simple tasks. This allows the analysis unit to suggest more appropriate tasks by prioritizing analysis results based on the child's emotions.

[0098] The analysis department can prioritize analyzing highly relevant data by considering the child's geographical location during the analysis process. For example, the analysis department can prioritize analyzing issues related to the region where the child lives by considering the characteristics of the area in which the child lives. For example, the analysis department can prioritize analyzing relevant data based on the curriculum of the school the child attends. The analysis department can also prioritize analyzing relevant data based on local events and activities in which the child participates. As a result, the analysis department can propose more appropriate issues by prioritizing the analysis of highly relevant data while considering the child's geographical location.

[0099] The analytics department can analyze children's social media activity during analysis to understand their interests and abilities. For example, the analytics department can analyze the content children frequently post on social media to identify areas of interest. For example, the analytics department can analyze the accounts and groups children follow to understand their areas of interest. The analytics department can also analyze the events and activities children participate in on social media to understand their interests and abilities. In this way, the analytics department can understand children's interests and abilities by analyzing their social media activity.

[0100] The suggestion function can estimate a child's emotions and adjust how it suggests tasks based on those estimates. For example, if a child is having fun, it might suggest a game-style task. If a child is feeling stressed, it might suggest a relaxing task. Furthermore, if a child is concentrating, it might suggest a more challenging task to maintain their concentration. In this way, the suggestion function can suggest more appropriate tasks by adjusting its approach based on the child's emotions.

[0101] The proposal team can adjust the level of detail in their proposals based on the difficulty of the problem. For example, for easy problems, the proposal team provides a simple explanation. For difficult problems, the proposal team provides a detailed explanation or hints. For medium-difficulty problems, the proposal team can also provide an explanation with an appropriate level of detail. This allows the proposal team to propose more appropriate problems by adjusting the level of detail based on the difficulty of the problem.

[0102] The proposal function can apply different proposal algorithms depending on the category of the problem. For example, for learning problems, the proposal function applies an educational algorithm. For household chore problems, it applies a practical algorithm. Furthermore, for social problems, the proposal function can apply an algorithm that emphasizes communication skills. In this way, the proposal function can propose more appropriate problems by applying different proposal algorithms depending on the category of the problem.

[0103] The suggestion function can estimate the child's emotions and adjust the length of the suggestion based on that estimation. For example, if the child is in a hurry, the suggestion function will provide a short, to-the-point suggestion. For example, if the child is relaxed, the suggestion function will provide a longer suggestion with more detailed explanations. It can also provide a visually stimulating suggestion if the child is excited. In this way, the suggestion function can suggest more appropriate tasks by adjusting the length of the suggestion based on the child's emotions.

[0104] The proposal team can prioritize proposals based on the submission deadlines for each assignment. For example, the team might prioritize assignments with approaching deadlines, while delaying assignments with later deadlines. They can also adjust the priority of assignments with medium-term deadlines. This allows the team to propose more appropriate assignments by prioritizing them based on their submission deadlines.

[0105] The proposal department can adjust the order of proposals based on the relevance of the issues. For example, the proposal department may prioritize issues related to the child's interests. For example, the proposal department may prioritize issues related to the child's abilities. It can also prioritize issues related to the child's current learning content. In this way, the proposal department can propose more appropriate issues by adjusting the order of proposals based on the relevance of the issues.

[0106] The monitoring unit can estimate the parent's emotions and adjust the progress monitoring method based on the estimated emotions. For example, if the parent is worried, the monitoring unit will provide a detailed progress report. For example, if the parent is relaxed, the monitoring unit will provide a concise progress report. The monitoring unit can also provide a summary progress report if the parent is busy. In this way, the monitoring unit can perform more appropriate progress monitoring by adjusting the progress monitoring method based on the parent's emotions.

[0107] The verification unit can select the optimal verification method by referring to the child's past progress data during the verification process. For example, the verification unit analyzes the child's past progress data and selects the optimal verification method. For example, the verification unit adjusts the progress verification method by referring to the child's past performance. The verification unit can also select the progress verification method based on the child's past feedback. In this way, the verification unit can select the optimal verification method by referring to the child's past progress data.

[0108] The monitoring unit can customize the means of checking progress based on the child's current living situation. For example, if the child is busy, the monitoring unit will perform a brief progress check. For example, if the child is relaxed, the monitoring unit will perform a detailed progress check. Furthermore, if the child is stressed, the monitoring unit can perform a relaxing progress check. In this way, the monitoring unit can perform more appropriate progress checks by customizing the means of checking progress based on the child's current living situation.

[0109] The monitoring unit can estimate the parent's emotions and determine the priority of progress checks based on those estimated emotions. For example, if the parent is worried, the monitoring unit will prioritize progress checks higher. For example, if the parent is relaxed, the monitoring unit will prioritize progress checks lower. The monitoring unit can also adjust the priority of progress checks if the parent is busy. In this way, the monitoring unit can perform more appropriate progress checks by determining the priority of progress checks based on the parent's emotions.

[0110] The verification unit can select the most appropriate verification method by considering the parent's geographical location information during verification. For example, if the parent is at home, the verification unit will perform a detailed progress check. For example, if the parent is out, the verification unit will perform a concise progress check. Furthermore, if the parent is at work, the verification unit can perform a concise progress check. In this way, the verification unit can perform more appropriate progress checks by selecting the most appropriate verification method by considering the parent's geographical location information.

[0111] The verification unit can analyze the parent's social media activity during verification and propose methods for monitoring progress. For example, the verification unit can analyze the content that the parent frequently posts on social media and propose the most suitable method for monitoring progress. For example, the verification unit can analyze the accounts and groups that the parent follows and propose the most suitable method for monitoring progress. Furthermore, the verification unit can analyze the events and activities that the parent participates in on social media and propose the most suitable method for monitoring progress. In this way, the verification unit can perform more appropriate progress monitoring by analyzing the parent's social media activity and proposing methods for monitoring progress.

[0112] The advice function can estimate the parent's emotions and adjust how it delivers advice based on those emotions. For example, if the parent is worried, it will provide detailed advice. If the parent is relaxed, it will provide concise advice. It can also provide to the point if the parent is busy. In this way, the advice function can provide more appropriate advice by adjusting how it delivers advice based on the parent's emotions.

[0113] The advice function can provide optimal advice by referring to the parent's past feedback when offering advice. For example, the advice function can analyze the parent's past feedback to provide the best advice. For example, the advice function can adjust the content of the advice by referring to the parent's past advice history. The advice function can also select the method of providing advice based on the parent's past feedback. In this way, the advice function can provide more appropriate advice by referring to the parent's past feedback to provide the best advice.

[0114] The advice service can customize the content of advice based on the parents' current living situation. For example, if the parents are busy, the service will provide concise advice. If the parents are relaxed, the service will provide detailed advice. Furthermore, if the parents are stressed, the service can provide relaxing advice. This allows the service to provide more appropriate advice by customizing it based on the parents' current living situation.

[0115] The advice function can estimate the parent's emotions and prioritize advice based on those emotions. For example, if the parent is worried, the advice function will give a higher priority to the advice. For example, if the parent is relaxed, the advice function will give a lower priority to the advice. The advice function can also adjust the priority of advice if the parent is busy. In this way, the advice function can provide more appropriate advice by prioritizing advice based on the parent's emotions.

[0116] The advice department can provide optimal advice by considering the parent's geographical location. For example, if the parent is at home, the advice department will provide detailed advice. For example, if the parent is out, the advice department will provide concise advice. Furthermore, if the parent is at work, the advice department can provide concise advice. In this way, the advice department can provide more appropriate advice by considering the parent's geographical location.

[0117] The advice department can analyze parents' social media activity when providing advice and suggest appropriate advice. For example, it can analyze the content parents frequently post on social media and provide the most suitable advice. For example, it can analyze the accounts and groups parents follow and provide the most suitable advice. It can also analyze the events and activities parents participate in on social media and provide the most suitable advice. In this way, the advice department can provide more appropriate advice by analyzing parents' social media activity and suggesting appropriate advice.

[0118] The Growth Analysis Department can estimate a child's emotions and adjust the analysis method of growth records based on those estimated emotions. For example, if a child is having fun, the Growth Analysis Department will prioritize analyzing positive growth records. For example, if a child is stressed, the Growth Analysis Department will identify the cause of the stress and analyze the growth records accordingly. Furthermore, if a child is concentrating, the Growth Analysis Department can analyze detailed growth records to help maintain that concentration. In this way, the Growth Analysis Department can perform more appropriate analysis of growth records by adjusting the analysis method based on the child's emotions.

[0119] The growth analysis unit can predict growth trends by referring to past growth data when analyzing growth records. For example, the growth analysis unit can predict growth trends by analyzing a child's past growth data. For example, the growth analysis unit can predict growth trends by referring to a child's past performance and feedback. The growth analysis unit can also predict future growth trends by analyzing a child's past behavioral patterns. As a result, the growth analysis unit can perform more appropriate analysis of growth records by referring to past growth data to predict growth trends.

[0120] The Growth Analysis Department can apply different analytical methods to each child's category when analyzing growth records. For example, in the case of learning growth records, the Growth Analysis Department applies educational analytical methods. For example, in the case of social growth records, the Growth Analysis Department applies analytical methods that emphasize communication skills. Furthermore, in the case of physical growth records, the Growth Analysis Department can also apply analytical methods that emphasize health data. In this way, the Growth Analysis Department can perform more appropriate analysis of growth records by applying different analytical methods to each child's category.

[0121] The growth analysis unit can estimate a child's emotions and adjust the importance of growth records based on those estimates. For example, if a child is having fun, the growth analysis unit will prioritize displaying positive growth records. For example, if a child is stressed, the growth analysis unit will identify the cause of the stress and adjust the importance of growth records accordingly. Furthermore, if a child is concentrating, the growth analysis unit can prioritize displaying detailed growth records to help maintain that concentration. In this way, the growth analysis unit can perform a more appropriate analysis of growth records by adjusting the importance of growth records based on the child's emotions.

[0122] The Growth Analysis Department can analyze changes in a child's growth based on when the growth records were submitted. For example, it can analyze growth records submitted by a child at a specific time and identify changes in growth during that period. For example, it can predict changes in growth based on when the child submitted the growth records. Furthermore, the Growth Analysis Department can analyze changes in growth based on when the child submitted the records and predict future growth. This allows the Growth Analysis Department to perform a more appropriate analysis of growth records by analyzing changes in growth based on when the child submitted the records.

[0123] The Growth Analysis Department can analyze growth by referencing relevant market data for children when analyzing growth records. For example, the Growth Analysis Department can compare children's growth records with relevant market data to analyze growth trends. For example, the Growth Analysis Department can identify changes in growth by comparing children's growth records with relevant market data. The Growth Analysis Department can also integrate children's growth records with relevant market data to make growth forecasts. This allows the Growth Analysis Department to perform more appropriate analysis of growth records by referencing relevant market data for children.

[0124] The improvement suggestion department can estimate a child's emotions and adjust its approach to suggesting improvements based on those emotions. For example, if a child is having fun, the department will suggest positive improvements. If a child is stressed, the department will suggest improvements to reduce stress. If a child is concentrating, the department can also suggest improvements to maintain concentration. In this way, the improvement suggestion department can suggest more appropriate improvements by adjusting its approach based on the child's emotions.

[0125] The Improvement Proposal Department can provide optimal improvement proposals by referring to past improvement data when proposing improvement plans. For example, the Improvement Proposal Department can analyze a child's past improvement data to provide the optimal improvement plan. For example, the Improvement Proposal Department can adjust improvement plans by referring to a child's past performance and feedback. The Improvement Proposal Department can also analyze a child's past behavioral patterns to provide the optimal improvement plan. In this way, the Improvement Proposal Department can propose more appropriate improvement plans by referring to past improvement data to provide the optimal improvement plan.

[0126] The improvement suggestion department can customize the content of improvement suggestions based on the child's current living situation. For example, if the child is busy, the department will provide a concise suggestion. For example, if the child is relaxed, the department will provide a detailed suggestion. Furthermore, if the child is stressed, the department can provide a suggestion that helps the child relax. In this way, the improvement suggestion department can propose more appropriate improvement suggestions by customizing the content of the suggestions based on the child's current living situation.

[0127] The improvement suggestion department can estimate a child's emotions and prioritize improvement suggestions based on those emotions. For example, if a child is having fun, the improvement suggestion department will prioritize suggesting positive improvements. For example, if a child is stressed, the improvement suggestion department will prioritize suggesting improvements that reduce stress. Also, if a child is concentrating, the improvement suggestion department can prioritize suggesting improvements that help maintain concentration. In this way, the improvement suggestion department can propose more appropriate improvements by prioritizing suggestions based on the child's emotions.

[0128] The Improvement Proposal Department can provide optimal improvement proposals by considering the child's geographical location when proposing improvements. For example, the Improvement Proposal Department can provide improvement proposals relevant to the area where the child lives by considering the characteristics of the area. For example, the Improvement Proposal Department can provide relevant improvement proposals based on the curriculum of the school the child attends. Furthermore, the Improvement Proposal Department can also provide relevant improvement proposals based on local events and activities in which the child participates. In this way, the Improvement Proposal Department can propose more appropriate improvement proposals by considering the child's geographical location.

[0129] The Improvement Proposal Department can analyze children's social media activity when proposing improvement plans. For example, it can analyze the content children frequently post on social media and provide optimal improvement plans. For example, it can analyze the accounts and groups children follow and provide optimal improvement plans. It can also analyze the events and activities children participate in on social media and provide optimal improvement plans. In this way, the Improvement Proposal Department can propose more appropriate improvement plans by analyzing children's social media activity and proposing improvement plans based on that analysis.

[0130] The support department can estimate a child's emotions and adjust its support methods based on those estimates. For example, if a child is having fun, the support department will provide positive support methods. For example, if a child is feeling stressed, the support department will provide support methods to reduce stress. Furthermore, if a child is concentrating, the support department can provide support methods to maintain concentration. This allows the support department to provide more appropriate support by adjusting its methods based on the child's emotions.

[0131] The support department can provide the most appropriate support methods by referring to past support data during the support process. For example, the support department can analyze a child's past support data to provide the most suitable support methods. For example, the support department can adjust support methods by referring to a child's past performance and feedback. The support department can also analyze a child's past behavioral patterns to provide the most appropriate support methods. In this way, the support department can provide more appropriate support by referring to past support data to provide the most appropriate support methods.

[0132] The support department can customize the content of support based on the child's current living situation. For example, if the child is busy, the support department can provide concise support methods. For example, if the child is relaxed, the support department can provide detailed support methods. Furthermore, if the child is stressed, the support department can provide support methods that help the child relax. In this way, the support department can provide more appropriate support by customizing the content of support based on the child's current living situation.

[0133] The support department can estimate a child's emotions and prioritize support based on those estimates. For example, if a child is having fun, the support department will prioritize providing positive support methods. For example, if a child is stressed, the support department will prioritize providing support methods to reduce stress. Also, if a child is concentrating, the support department can prioritize providing support methods to maintain concentration. In this way, the support department can provide more appropriate support by prioritizing support based on the child's emotions.

[0134] The support department can provide the most appropriate support method when providing assistance, taking into account the child's geographical location. For example, the support department can provide support methods relevant to the area where the child lives, taking into account the characteristics of the area in which the child lives. For example, the support department can provide relevant support methods based on the curriculum of the school the child attends. Furthermore, the support department can also provide relevant support methods based on local events and activities in which the child participates. In this way, the support department can provide more appropriate support by considering the child's geographical location and providing the most appropriate support method.

[0135] The support department can analyze a child's social media activity and propose appropriate support during the support process. For example, the support department can analyze the content a child frequently posts on social media and provide the most suitable support methods. For example, the support department can analyze the accounts and groups a child follows and provide the most suitable support methods. The support department can also analyze the events and activities a child participates in on social media and provide the most suitable support methods. This allows the support department to provide more appropriate support by analyzing a child's social media activity and proposing appropriate support methods.

[0136] The expert advice department can estimate the parents' emotions and adjust how it delivers expert advice based on those estimates. For example, if the parents are worried, the expert advice department will provide detailed advice. For example, if the parents are relaxed, the expert advice department will provide concise advice. Furthermore, if the parents are busy, the expert advice department can provide concise advice. In this way, the expert advice department can provide more appropriate advice by adjusting how it delivers expert advice based on the parents' emotions.

[0137] The expert advice department can provide optimal advice by referring to past advice data when offering expert advice. For example, the expert advice department can analyze parents' past advice data to provide optimal advice. For example, the expert advice department can adjust the content of advice by referring to parents' past feedback. The expert advice department can also select the method of providing advice based on parents' past advice history. In this way, the expert advice department can provide more appropriate advice by referring to past advice data to provide optimal advice.

[0138] The expert advice department can customize the content of its advice based on the parents' current living situation. For example, if the parents are busy, the expert advice department will provide concise advice. For example, if the parents are relaxed, the expert advice department will provide detailed advice. Furthermore, if the parents are stressed, the expert advice department can also provide advice that helps them relax. In this way, the expert advice department can provide more appropriate advice by customizing the content of its advice based on the parents' current living situation.

[0139] The expert advice department can estimate the parents' emotions and prioritize expert advice based on those emotions. For example, if the parents are worried, the expert advice department will prioritize expert advice more highly. For example, if the parents are relaxed, the expert advice department will prioritize expert advice less highly. The expert advice department can also adjust the priority of expert advice if the parents are busy. In this way, the expert advice department can provide more appropriate advice by prioritizing expert advice based on the parents' emotions.

[0140] The expert advice department can provide optimal advice by considering the parent's geographical location when offering expert advice. For example, if the parent is at home, the expert advice department can provide detailed expert advice. For example, if the parent is out, the expert advice department can provide concise expert advice. Furthermore, if the parent is at work, the expert advice department can provide concise expert advice. In this way, the expert advice department can provide more appropriate advice by considering the parent's geographical location.

[0141] The expert advice department can analyze parents' social media activity when providing expert advice and propose appropriate advice. For example, the expert advice department can analyze the content that parents frequently post on social media and provide the most suitable expert advice. For example, the expert advice department can analyze the accounts and groups that parents follow and provide the most suitable expert advice. In addition, the expert advice department can analyze the events and activities that parents participate in on social media and provide the most suitable expert advice. In this way, the expert advice department can provide more appropriate advice by analyzing parents' social media activity and proposing appropriate advice.

[0142] The community department can estimate parents' emotions and adjust how it provides community services based on those estimates. For example, if a parent is worried, the community department will prioritize providing support groups. For example, if a parent is relaxed, the community department will provide a space for information exchange. Furthermore, if a parent is busy, the community department can provide concise information. In this way, the community department can provide a more appropriate community by adjusting how it provides services based on parents' emotions.

[0143] The Community Department can provide the most suitable community by referring to past community data when providing a community. For example, the Community Department can analyze parents' past community participation history to provide the most suitable community. For example, the Community Department can adjust the community content by referring to parents' past feedback. The Community Department can also provide the most suitable community based on parents' past community participation data. In this way, the Community Department can provide a more appropriate community by referring to past community data to provide the most suitable community.

[0144] The Community Department can customize the content of community services based on the parents' current living situation when providing them. For example, if the parents are busy, the Community Department can provide concise community information. For example, if the parents are relaxed, the Community Department can provide detailed community information. Furthermore, if the parents are stressed, the Community Department can provide relaxing community information. In this way, the Community Department can provide more appropriate community services by customizing the content of community services based on the parents' current living situation.

[0145] The community department can estimate parents' emotions and prioritize communities based on those estimates. For example, if a parent is worried, the community department will prioritize support groups more highly. For example, if a parent is relaxed, the community department will prioritize information exchange spaces less highly. The community department can also adjust community priorities if a parent is busy. In this way, the community department can provide more appropriate communities by prioritizing them based on parents' emotions.

[0146] The Community Department can provide the most suitable community by considering the parent's geographical location when providing community information. For example, if the parent is at home, the Community Department can provide detailed community information. For example, if the parent is out, the Community Department can provide concise community information. Furthermore, if the parent is at work, the Community Department can provide concise community information. In this way, the Community Department can provide a more appropriate community by considering the parent's geographical location.

[0147] The Community Department can analyze parents' social media activity and suggest community content when providing a community. For example, the Community Department can analyze the content parents frequently post on social media and provide the most suitable community. For example, the Community Department can analyze the accounts and groups parents follow and provide the most suitable community. The Community Department can also analyze the events and activities parents participate in on social media and provide the most suitable community. In this way, the Community Department can provide more appropriate communities by analyzing parents' social media activity and suggesting community content.

[0148] The system according to the embodiment is not limited to the example described above, and various modifications are possible, for example, as follows.

[0149] The AI ​​Kids Coaching System also includes a reward management unit. This unit manages rewards for tasks that children complete. For example, it can award points for each task a child completes, and these points can be used to obtain virtual items and rewards. The reward management unit can also manage rewards set by parents and provide rewards according to the tasks that children complete. Furthermore, the reward management unit can record the history of tasks completed by children and manage the history of rewards. This allows the reward management unit to strengthen children's motivation to complete tasks and provide continuous support for their independence.

[0150] The AI ​​Kids Coaching System also includes a Health Management Department. This department manages the child's health status. For example, it collects records of the child's diet and exercise, and evaluates their health. It can also record the child's sleep patterns and suggest appropriate sleep durations. Furthermore, based on the child's health status, the Health Management Department can provide appropriate diet and exercise advice. In this way, the Health Management Department can comprehensively manage the child's health and support their healthy growth.

[0151] The AI ​​Kids Coaching System also includes a Friendship Management section. This section manages children's friendships. For example, it suggests tasks that children can work on with friends and encourages them to cooperate to achieve them. It can also provide advice on how children communicate with their friends. Furthermore, it can suggest events and activities that children can enjoy with their friends. In this way, the Friendship Management section can support children's friendships and promote their social development.

[0152] The AI ​​Kids Coaching System also includes a Time Management Unit. This unit manages how children spend their time. For example, it creates schedules to help children complete tasks systematically. It can also provide advice on how children can use their time effectively. Furthermore, it can provide reminder functions to help children adhere to schedules. In this way, the Time Management Unit can improve children's time management skills and promote independence.

[0153] The AI ​​Kids Coaching System also includes a Safety Management Department. This department manages the safety of children. For example, it provides filtering functions to ensure children can use the internet safely. It can also suggest safety measures for children when they are out and about. Furthermore, it can advise on how to handle situations if a child encounters a dangerous environment. This allows the Safety Management Department to ensure children's safety and promote their independence with peace of mind.

[0154] The AI ​​Kids Coaching System also includes an Emotional Support Unit. This unit supports children's emotions. For example, if a child is feeling stressed, it suggests ways to relax. It can also suggest activities to cheer up a sad child. Furthermore, if a child is angry, it can offer advice on how to calm down. In this way, the Emotional Support Unit supports children's emotions and helps them maintain a healthy mental state.

[0155] The AI ​​Kids Coaching System also includes an emotional feedback unit. This unit provides feedback based on the child's emotions. For example, if the child is having fun, it provides positive feedback. It can also offer words of encouragement if the child is feeling stressed. Furthermore, if the child is concentrating, it can provide feedback to help maintain that concentration. In this way, the emotional feedback unit can provide appropriate feedback based on the child's emotions.

[0156] The AI ​​Kids Coaching System also includes an emotion monitoring unit. This unit monitors the child's emotions. For example, it analyzes the child's facial expressions and tone of voice to estimate their emotions. It can also analyze the child's behavioral patterns to understand changes in their emotions. Furthermore, it can suggest appropriate responses based on the child's emotions. As a result, the emotion monitoring unit can understand the child's emotions in real time and provide appropriate support.

[0157] The AI ​​Kids Coaching System also includes an emotion prediction unit. This unit predicts a child's emotions. For example, it analyzes a child's past emotional data to predict future emotional changes. It can also analyze a child's behavioral patterns to predict emotional changes. Furthermore, it can suggest appropriate responses based on the child's emotions. As a result, the emotion prediction unit can anticipate changes in a child's emotions and provide appropriate support.

[0158] The AI ​​Kids Coaching System also includes an emotion regulation unit. This unit regulates the child's emotions. For example, if a child is feeling stressed, it suggests ways to relax. It can also provide advice on how to calm down if a child is agitated. Furthermore, if a child is sad, it can suggest activities to lift their spirits. In this way, the emotion regulation unit can appropriately regulate the child's emotions and maintain a healthy mental state.

[0159] The following briefly describes the processing flow for example form 2.

[0160] Step 1: The analysis department analyzes the child's interests and abilities. For example, they analyze the child's interests based on survey results and behavioral history, and analyze the child's abilities based on test results and observation records. This makes it possible to identify the child's areas of interest and academic ability, and to understand changes in their interests. Step 2: The proposal department proposes appropriate tasks based on the results of the analysis conducted by the analysis department. For example, they can propose tasks of varying difficulty and content depending on the child's interests and abilities, and then propose tasks that gradually increase in difficulty as the child grows. Step 3: The monitoring section allows parents to check their child's progress. For example, it includes a function to display the child's achievement level and progress, visually showing a list of tasks and progress in graphs and charts, allowing parents to check in real time. Step 4: The advice section provides advice to facilitate parent-child communication. For example, it offers specific advice on how parents should give feedback to their children, how to acknowledge their efforts, how to offer appropriate words of encouragement, and how to support their growth.

[0161] 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.

[0162] Data generation model 58 is a form of 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> Examples of generative AI include text generation AI, image generation AI, and multimodal generation AI. 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 (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats from audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVMs), k-means clustering, convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each of the above parts is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example.Furthermore, processing performed by AI, including generative AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by AI, including generative AI.

[0163] Furthermore, the processing performed by the data processing system 10 described above is carried out by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but it may also be carried out by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0164] Each of the multiple elements mentioned above, including the analysis unit, proposal unit, confirmation unit, advice unit, growth analysis unit, improvement proposal unit, support unit, expert advice unit, and community unit, is implemented, for example, in at least one of the smart device 14 and the data processing unit 12. For example, the analysis unit is implemented by the control unit 46A of the smart device 14 and analyzes the child's interests and abilities. The proposal unit is implemented, for example, by the specific processing unit 290 of the data processing unit 12 and proposes appropriate tasks. The confirmation unit is implemented, for example, by the control unit 46A of the smart device 14 and allows parents to check the child's progress. The advice unit is implemented, for example, by the specific processing unit 290 of the data processing unit 12 and provides advice to promote parent-child communication. The growth analysis unit is implemented, for example, by the specific processing unit 290 of the data processing unit 12 and analyzes the child's growth record. The improvement proposal unit is implemented, for example, by the control unit 46A of the smart device 14 and proposes individual learning plans and suggestions for improving lifestyle habits. The support unit is implemented, for example, by the control unit 46A of the smart device 14, and provides support for independence using gamification. The expert advice unit is implemented, for example, by the specific processing unit 290 of the data processing device 12, and provides parenting advice supervised by experts. The community unit is implemented, for example, by the control unit 46A of the smart device 14, and provides a place for parents to exchange information with each other. The correspondence between each unit and the devices and control units is not limited to the examples described above, and various changes are possible.

[0165] [Second Embodiment] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0166] 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.

[0167] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. 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 and / or LAN.

[0168] 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.

[0169] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, 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.

[0170] 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, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0171] 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.

[0172] 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 by the processor 28. The storage 32 stores the specific processing program 56.

[0173] The processor 28 reads a 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 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0174] 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. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0175] In the smart glasses 214, specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 acting as a control unit 46A according to the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0176] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0177] 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.

[0178] The data generation model 58 is a so-called generative AI. An example of a data generation model 58 is a generative AI such as ChatGPT. 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 inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0179] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but it may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart glasses 214 or an external device, and the smart glasses 214 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0180] Each of the multiple elements mentioned above, including the analysis unit, proposal unit, confirmation unit, advice unit, growth analysis unit, improvement proposal unit, support unit, expert advice unit, and community unit, is implemented, for example, in at least one of the smart glasses 214 and the data processing unit 12. For example, the analysis unit is implemented by the control unit 46A of the smart glasses 214 and analyzes the child's interests and abilities. The proposal unit is implemented, for example, by the specific processing unit 290 of the data processing unit 12 and proposes appropriate tasks. The confirmation unit is implemented, for example, by the control unit 46A of the smart glasses 214 and allows parents to check the child's progress. The advice unit is implemented, for example, by the specific processing unit 290 of the data processing unit 12 and provides advice to promote parent-child communication. The growth analysis unit is implemented, for example, by the specific processing unit 290 of the data processing unit 12 and analyzes the child's growth record. The improvement proposal unit is implemented, for example, by the control unit 46A of the smart glasses 214 and proposes individual learning plans and suggestions for improving lifestyle habits. The support unit is implemented, for example, by the control unit 46A of the smart glasses 214, and provides support for independence using gamification. The expert advice unit is implemented, for example, by the specific processing unit 290 of the data processing device 12, and provides parenting advice supervised by experts. The community unit is implemented, for example, by the control unit 46A of the smart glasses 214, and provides a place for parents to exchange information with each other. The correspondence between each unit and the devices and control units is not limited to the examples described above, and various changes are possible.

[0181] [Third Embodiment] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0182] 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.

[0183] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. 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 and / or LAN.

[0184] 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.

[0185] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, 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.

[0186] 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, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0187] 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.

[0188] 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.

[0189] The processor 28 reads a 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 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0190] 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. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0191] In the headset terminal 314, specific processing is performed by the processor 46. The storage 50 stores a specific program 60. The processor 46 reads the specific program 60 from the storage 50 and executes the read specific program 60 on the RAM 48. The specific processing is realized by the processor 46 acting as a control unit 46A according to the specific program 60 executed on the RAM 48. The headset terminal 314 also has a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0192] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0193] 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.

[0194] The data generation model 58 is a so-called generative AI. An example of a data generation model 58 is a generative AI such as ChatGPT. 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 inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0195] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset terminal 314, but may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset terminal 314. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the headset terminal 314 or an external device, and the headset terminal 314 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0196] Each of the multiple elements mentioned above, including the analysis unit, proposal unit, confirmation unit, advice unit, growth analysis unit, improvement proposal unit, support unit, expert advice unit, and community unit, is implemented by, for example, at least one of the headset terminal 314 and the data processing unit 12. For example, the analysis unit is implemented by the control unit 46A of the headset terminal 314 and analyzes the child's interests and abilities. The proposal unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12 and proposes appropriate tasks. The confirmation unit is implemented by, for example, the control unit 46A of the headset terminal 314 and allows parents to check the child's progress. The advice unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12 and provides advice to promote parent-child communication. The growth analysis unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12 and analyzes the child's growth record. The improvement proposal unit is implemented by, for example, the control unit 46A of the headset terminal 314 and proposes individual learning plans and suggestions for improving lifestyle habits. The support unit is implemented, for example, by the control unit 46A of the headset terminal 314, and provides support for independence using gamification. The expert advice unit is implemented, for example, by the specific processing unit 290 of the data processing device 12, and provides parenting advice supervised by experts. The community unit is implemented, for example, by the control unit 46A of the headset terminal 314, and provides a place for parents to exchange information with each other. The correspondence between each unit and the devices and control units is not limited to the examples described above, and various changes are possible.

[0197] [Fourth Embodiment] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0198] 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.

[0199] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. 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 and / or LAN.

[0200] 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.

[0201] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, 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.

[0202] 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 image sensor or CCD image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0203] 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.

[0204] 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. The robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0205] 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.

[0206] The processor 28 reads a 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 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0207] 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. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0208] In robot 414, specific processing is performed by processor 46. A specific program 60 is stored in storage 50. Processor 46 reads the specific program 60 from storage 50 and executes it on RAM 48. The specific processing is achieved by processor 46 acting as a control unit 46A according to the specific program 60 executed on RAM 48. Robot 414 also has data generation model 58 and emotion identification model 59, similar to those of the robot, and can perform processing similar to that of the specific processing unit 290 using these models.

[0209] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0210] 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.

[0211] The data generation model 58 is a so-called generative AI. An example of a data generation model 58 is a generative AI such as ChatGPT. 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 inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0212] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but it may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the robot 414 or an external device, and the robot 414 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0213] Each of the multiple elements described above, including the analysis unit, proposal unit, confirmation unit, advice unit, growth analysis unit, improvement proposal unit, support unit, expert advice unit, and community unit, is implemented by, for example, at least one of the robot 414 and the data processing unit 12. For example, the analysis unit is implemented by the control unit 46A of the robot 414 and analyzes the child's interests and abilities. The proposal unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12 and proposes appropriate tasks. The confirmation unit is implemented by, for example, the control unit 46A of the robot 414 and allows parents to check the child's progress. The advice unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12 and provides advice to promote parent-child communication. The growth analysis unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12 and analyzes the child's growth record. The improvement proposal unit is implemented by, for example, the control unit 46A of the robot 414 and proposes individual learning plans and suggestions for improving lifestyle habits. The support unit is implemented, for example, by the control unit 46A of the robot 414, and provides support for independence using gamification. The expert advice unit is implemented, for example, by the specific processing unit 290 of the data processing device 12, and provides parenting advice supervised by experts. The community unit is implemented, for example, by the control unit 46A of the robot 414, and provides a place for parents to exchange information with each other. The correspondence between each unit and the devices and control units is not limited to the examples described above, and various changes are possible.

[0214] 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.

[0215] Figure 9 shows the 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.

[0216] 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.

[0217] 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.

[0218] 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, and motorcycles, 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 based, for example, 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.

[0219] 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."

[0220] 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.

[0221] 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 method for the specific process may be used, which includes computer 22 and multiple other computers.

[0222] 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.

[0223] 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.

[0224] 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.

[0225] 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.

[0226] 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.

[0227] 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.

[0228] 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.

[0229] Furthermore, although the above-described examples were divided into four embodiments, some or all of these embodiments may be combined. Also, the smart device 14, smart glasses 214, headset terminal 314, and robot 414 are just examples, and they may be combined, or other devices may be used. Also, although the above-described examples were divided into two embodiments, Embodiment 1 and Embodiment 2, these may be combined.

[0230] 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 other things 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.

[0231] 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 to be incorporated by reference.

[0232] (Note 1) The analysis department analyzes children's interests and abilities, Based on the results of the analysis conducted by the aforementioned analysis unit, the proposal unit proposes appropriate issues, A section for parents to check their child's progress, The advice department provides advice to promote parent-child communication, Equipped with A system characterized by the following features. (Note 2) It has a growth analysis department that analyzes children's growth records. The system described in Appendix 1, characterized by the features described herein. (Note 3) The department includes an improvement proposal department that offers individualized learning plans and suggestions for improving lifestyle habits. The system described in Appendix 1, characterized by the features described herein. (Note 4) We have a support department that utilizes gamification to provide support for independent living. The system described in Appendix 1, characterized by the features described herein. (Note 5) It has an expert advice department that provides parenting advice supervised by experts. The system described in Appendix 1, characterized by the features described herein. (Note 6) It includes a community section that provides a platform for parents to exchange information. The system described in Appendix 1, characterized by the features described herein. (Note 7) The aforementioned analysis unit is We estimate the child's emotions and adjust the analysis methods for interests and abilities based on the estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 8) The aforementioned analysis unit is Analyzing a child's past behavioral history to predict changes in their interests and abilities The system described in Appendix 1, characterized by the features described herein. (Note 9) The aforementioned analysis unit is Apply different analysis algorithms depending on the child's learning style. The system described in Appendix 1, characterized by the features described herein. (Note 10) The aforementioned analysis unit is The system estimates the child's emotions and prioritizes the analysis results based on the estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 11) The aforementioned analysis unit is During analysis, the data is prioritized for analysis based on its relevance, taking into account the children's geographical location. The system described in Appendix 1, characterized by the features described herein. (Note 12) The aforementioned analysis unit is During the analysis, we analyze children's social media activity to understand their interests and abilities. The system described in Appendix 1, characterized by the features described herein. (Note 13) The aforementioned proposal section is, The system estimates the child's emotions and adjusts the way tasks are proposed based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 14) The aforementioned proposal section is, When submitting a proposal, adjust the level of detail based on the difficulty of the problem. The system described in Appendix 1, characterized by the features described herein. (Note 15) The aforementioned proposal section is, When making a proposal, apply a different proposal algorithm depending on the category of the problem. The system described in Appendix 1, characterized by the features described herein. (Note 16) The aforementioned proposal section is, The system estimates the child's emotions and adjusts the length of the suggestion based on the estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 17) The aforementioned proposal section is, When submitting proposals, prioritize them based on the submission deadline for the assignment. The system described in Appendix 1, characterized by the features described herein. (Note 18) The aforementioned proposal section is, When making proposals, adjust the order of proposals based on the relevance of the issues. The system described in Appendix 1, characterized by the features described herein. (Note 19) The aforementioned verification unit is We estimate the parents' emotions and adjust the progress monitoring method based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 20) The aforementioned verification unit is During the review process, the most suitable review method is selected by referring to the child's past progress data. The system described in Appendix 1, characterized by the features described herein. (Note 21) The aforementioned verification unit is During the review process, customize the method of checking progress based on the child's current living situation. The system described in Appendix 1, characterized by the features described herein. (Note 22) The aforementioned verification unit is Estimate the parents' emotions and prioritize progress checks based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 23) The aforementioned verification unit is During verification, the optimal verification method will be selected considering the parent's geographical location information. The system described in Appendix 1, characterized by the features described herein. (Note 24) The aforementioned verification unit is During the review process, we will analyze the parents' social media activity and propose methods for monitoring progress. The system described in Appendix 1, characterized by the features described herein. (Note 25) The aforementioned advice section, It estimates the parents' emotions and adjusts the way advice is given based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 26) The aforementioned advice section, When providing advice, refer to past feedback from parents to provide the best possible advice. The system described in Appendix 1, characterized by the features described herein. (Note 27) The aforementioned advice section, When providing advice, customize the content of the advice based on the parents' current living situation. The system described in Appendix 1, characterized by the features described herein. (Note 28) The aforementioned advice section, It estimates the parents' emotions and prioritizes advice based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 29) The aforementioned advice section, When providing advice, we take into account the parents' geographical location to provide the most appropriate advice. The system described in Appendix 1, characterized by the features described herein. (Note 30) The aforementioned advice section, When providing advice, we analyze the parents' social media activity and propose advice accordingly. The system described in Appendix 1, characterized by the features described herein. (Note 31) The aforementioned growth analysis unit, We estimate the child's emotions and adjust the method of analyzing the child's growth record based on the estimated emotions. The system described in Appendix 2, characterized by the features described herein. (Note 32) The aforementioned growth analysis unit, When analyzing growth records, past growth data is used to predict growth trends. The system described in Appendix 2, characterized by the features described herein. (Note 33) The aforementioned growth analysis unit, When analyzing growth records, different analytical methods are applied to each child's category. The system described in Appendix 2, characterized by the features described herein. (Note 34) The aforementioned growth analysis unit, The system estimates the child's emotions and adjusts the importance of growth records based on the estimated emotions. The system described in Appendix 2, characterized by the features described herein. (Supplementary Note 35) The growth analysis unit analyzes the changes in growth based on the submission time of the child when analyzing the growth record. The system according to Supplementary Note 2, characterized in that. (Supplementary Note 36) The growth analysis unit analyzes the growth by referring to the relevant market data of the child when analyzing the growth record. The system according to Supplementary Note 2, characterized in that. [[ID=第十六条]] [[ID=第十七条]](Supplementary Note 37)[[ID=第十八条]] [[ID=第十九条]]The improvement proposal unit [[ID=第二十条]] [[ID=第二十一条]]estimates the emotion of the child and adjusts the method of proposing improvement plans based on the estimated emotion of the child. [[ID=第二十二条]] [[ID=第二十三条]]The system according to Supplementary Note 3, characterized in that. [[ID=第二十四条]] [[ID=第二十五条]](Supplementary Note 38)[[ID=第二十六条]] [[ID=第二十七条]]The improvement proposal unit [[ID=第二十八条]] [[ID=第二十九条]]provides an optimal improvement plan by referring to past improvement data when proposing an improvement plan. [[ID=第三十条]] [[ID=第三十一条]]The system according to Supplementary Note 3, characterized in that. [[ID=第三十二条]] [[ID=第三十三条]](Supplementary Note 39)[[ID=第三十四条]] [[ID=第三十五条]]The improvement proposal unit [[ID=第三十六条]] [[ID=第三十七条]]customizes the content of the improvement plan based on the current living situation of the child when proposing an improvement plan. [[ID=第三十八条]] [[ID=第三十九条]]The system according to Supplementary Note 3, characterized in that. [[ID=第四十条]] [[ID=第四十一条]](Supplementary Note 40)[[ID=第四十二条]] [[ID=第四十三条]]The improvement proposal unit [[ID=第四十四条]]<unk> [[ID=第四十五条]]estimates the emotion of the child and determines the priority order of the improvement plans based on the estimated emotion of the child. [[ID=第四十六条]] [[ID=第四十七条]]The system according to Supplementary Note 3, characterized in that. [[ID=第四十八条]] [[ID=第四十九条]](Supplementary Note 41)[[ID=第五十条]] [[ID=第五十一条]]The improvement proposal unit [[ID=第五十二条]] [[ID=第五十三条]]provides an optimal improvement plan by considering the geographical location information of the child when proposing an improvement plan. [[ID=第五十四条]] [[ID=第五十五条]]The system according to Supplementary Note 3, characterized in that. [[ID=第五十六条]] [[ID=第五十七条]](Supplementary Note 42)[[ID=第五十八条]] [[ID=第五十九条]]The improvement proposal unit [[ID=第六十条]]<unk> [[ID=第六十一条]]proposes the content of the improvement plan by analyzing the social media activities of the child when proposing an improvement plan. [[ID=第六十二条]] [[ID=第六十三条]]The system according to Supplementary Note 3, characterized in that. [[ID=第六十四条]] [[ID=第六十五条]](Supplementary Note 43) The aforementioned support unit, The system estimates the child's emotions and adjusts support methods based on those estimates. The system described in Appendix 4, characterized by the features described herein. (Note 44) The aforementioned support unit, When providing support, we refer to past support data to provide the most suitable support method. The system described in Appendix 4, characterized by the features described herein. (Note 45) The aforementioned support unit, During support, the content of the support will be customized based on the child's current living situation. The system described in Appendix 4, characterized by the features described herein. (Note 46) The aforementioned support unit, The system estimates the child's emotions and determines the priority of support based on those estimated emotions. The system described in Appendix 4, characterized by the features described herein. (Note 47) The aforementioned support unit, When providing support, we take into account the child's geographical location to provide the most appropriate support method. The system described in Appendix 4, characterized by the features described herein. (Note 48) The aforementioned support unit, During support, we analyze the child's social media activity and propose support strategies. The system described in Appendix 4, characterized by the features described herein. (Note 49) The aforementioned expert advice department, We estimate the parents' emotions and adjust how expert advice is provided based on those estimated emotions. The system described in Appendix 5, characterized by the features described herein. (Note 50) The aforementioned expert advice department, When providing expert advice, we refer to past advice data to provide the most suitable advice. The system described in Appendix 5, characterized by the features described herein. (Note 51) The aforementioned expert advice department, When providing expert advice, customize the content of the advice based on the current living situation of the parent. The system according to Appendix 5, characterized by this. (Appendix 52) The expert advice department Estimate the parent's emotions and determine the priority of expert advice based on the estimated parent's emotions. The system according to Appendix 5, characterized by this. (Appendix 53) The expert advice department When providing expert advice, provide optimal advice considering the geographical location information of the parent. The system according to Appendix 5, characterized by this. (Appendix 54) The expert advice department When providing expert advice, analyze the parent's social media activities and propose the content of the advice. The system according to Appendix 5, characterized by this. (Appendix 55) The community department Estimate the parent's emotions and adjust the method of providing the community based on the estimated parent's emotions. The system according to Appendix 6, characterized by this. (Appendix 56) The community department When providing the community, provide the optimal community by referring to past community data. The system according to Appendix 6, characterized by this. (Appendix 57) The community department When providing the community, customize the content of the community based on the current living situation of the parent. The system according to Appendix 6, characterized by this. (Appendix 58) The community department Estimate the parent's emotions and determine the priority of the community based on the estimated parent's emotions. The system described in Appendix 6, characterized by the features described herein. (Note 59) The aforementioned community department, When providing a community, we consider the parents' geographical location to provide the most suitable community. The system described in Appendix 6, characterized by the features described herein. (Note 60) The aforementioned community department, When providing a community, we analyze parents' social media activity to suggest community content. The system described in Appendix 6, characterized by the features described herein. [Explanation of symbols]

[0233] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots

Claims

1. The analysis department analyzes children's interests and abilities, Based on the results of the analysis conducted by the aforementioned analysis unit, the proposal unit proposes appropriate issues, A section for parents to check their child's progress, The advice department provides advice to promote parent-child communication, Equipped with A system characterized by the following features.

2. It has a growth analysis department that analyzes children's growth records. The system according to feature 1.

3. The department includes an improvement proposal department that offers individualized learning plans and suggestions for improving lifestyle habits. The system according to feature 1.

4. We have a support department that utilizes gamification to provide assistance for independent living. The system according to feature 1.

5. It has an expert advice department that provides parenting advice supervised by experts. The system according to feature 1.

6. It includes a community section that provides a platform for parents to exchange information. The system according to feature 1.

7. The aforementioned analysis unit is We estimate the child's emotions and adjust the analysis methods for interests and abilities based on the estimated emotions. The system according to feature 1.

8. The aforementioned analysis unit is Analyzing a child's past behavioral history to predict changes in their interests and abilities The system according to feature 1.

Images