system

Abstract

We provide the system. [Solution] A means for receiving input of learning goals and academic ability levels from the user and generating an individual learning plan, A means of receiving questions from users and generating answers to those questions using generative artificial intelligence, A means of providing multi-subject learning materials based on user selection, A means to track the user's learning progress and automatically adjust the learning plan as needed, A means of collecting relevant information from databases and the internet in response to a user's information request and summarizing it using generative artificial intelligence, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a 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] Conventional learning support systems have had problems in that it is difficult to effectively generate individual learning plans, and the means for users to obtain appropriate teaching materials suitable for their academic abilities are limited. In addition, there has been a problem that learning efficiency decreases because question answering available 24 hours a day and adjustment of learning plans according to the progress of users cannot be sufficiently performed. Furthermore, there has been a problem that the means for users to quickly and accurately access necessary information is insufficient.

Means for Solving the Problems

[0005] The present invention solves the above problems through a system that includes means for receiving input of learning goals and academic ability levels from the user and generating an individualized learning plan, means for receiving questions from the user and generating answers to those questions using generative artificial intelligence, means for providing learning materials for multiple subjects based on the user's selection, means for tracking the user's learning progress and automatically adjusting the learning plan as needed, and means for collecting relevant information from databases and the internet in response to the user's information requests and summarizing it using generative artificial intelligence. As a result, the user can proceed with learning efficiently and effectively and receive the necessary information and support 24 hours a day.

[0006] "Users" refer to individuals who use the tutoring system, particularly elementary and junior high school students.

[0007] "Learning objectives" refer to the specific learning items or performance goals that the user wants to achieve.

[0008] "Academic ability level" is an indicator that shows the user's current level of knowledge and skills.

[0009] An "individualized learning plan" is a plan that includes a learning schedule and materials optimized for a specific user, created based on the user's learning goals and academic level.

[0010] "Generative artificial intelligence" refers to artificial intelligence technology that generates answers and information in natural language in response to user questions and requests.

[0011] "Learning materials" refers to learning resources such as textbooks, videos, and workbooks that users use to study.

[0012] "Learning progress" refers to progress information that shows how far a user has progressed according to their learning plan.

[0013] An "information request" refers to a request from a user for specific information or materials.

[0014] A "database" refers to a system for centrally managing and storing various types of data, such as user information, learning materials, and progress data.

[0015] The "Internet" refers to a network that collects necessary information from external sources in response to user requests. [Brief explanation of the drawing]

[0016] [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. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when the emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when the emotion engine is combined.

Mode for Carrying Out the Invention

[0017] Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described according to the accompanying drawings.

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

[0019] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be one arithmetic unit or a combination of a plurality of arithmetic units. Also, the processor may be one type of arithmetic unit or a combination of a plurality of types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0020] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0021] In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0022] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0024] [First Embodiment]

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

[0026] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0027] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0028] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0029] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0030] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0031] 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.

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

[0033] 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.

[0034] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0035] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0036] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0037] The learning center system of the present invention provides the following main functions to effectively support the user's learning.

[0038] 1. User signup and login

[0039] Server: Provides signup and login functionality to authenticate users accessing the tutoring school's website or app. During new user registration, users enter information such as their name, email address, and password, which the server stores in a database. During login, the server uses the information in the database to authenticate the user.

[0040] Specific example: A primary school student registers for the system, then logs in and accesses the dashboard.

[0041] 2. Creating a study plan

[0042] Server: Receives information about the user's learning goals and academic level, and generates an individualized learning plan based on this information. The server executes a pre-configured algorithm to generate the optimal learning schedule and materials, and stores them in a database.

[0043] Specific example: When a middle school student user enters the goal "improve math skills," the server generates a weekly study schedule based on the user's academic level and displays it on the device.

[0044] 3. 24-hour support for questions

[0045] User: If you have any questions while learning, enter them here.

[0046] Terminal: Sends the question content to the server.

[0047] Server: Uses generative artificial intelligence to analyze questions and generate answers. The generated answers are sent to the terminal and displayed to the user.

[0048] Specific example: If a middle school student user asks, "I don't know how to solve quadratic equations," the server provides a detailed explanation and immediately returns the answer to the user.

[0049] 4. Provision of teaching materials covering multiple subjects

[0050] Server: Provides corresponding learning materials for the subject selected by the user. The server searches the database for appropriate materials and sends them to the terminal.

[0051] Specific example: When a user selects the "Biology" field under "Science," the server sends video materials and text documents related to biology to the user's device and displays them.

[0052] 5. Tracking learning progress and adjusting plans

[0053] Server: Tracks user learning progress in a database and automatically adjusts the learning plan as needed. Provides new schedules and supplementary materials based on the user's completed learning content and progress.

[0054] Specific example: If a user finishes basic math problems earlier than planned, the server notifies the user to move on to the next learning step, which is applied problems, and updates the learning plan.

[0055] 6. Efficient Information Access

[0056] Server: In response to information requests from users, it collects relevant information from databases and the internet. It uses generative artificial intelligence to summarize the information and present it to the user in an easy-to-understand manner.

[0057] Specific example: If a user searches for "an overview of the French Revolution," the server collects relevant information and provides the user with a summarized text.

[0058] In this way, the user, terminal, and server work together, enabling the user to learn efficiently and effectively, and to receive necessary information and support 24 hours a day. The system of the present invention realizes flexible learning support that meets the individual needs of the user.

[0059] The following describes the processing flow.

[0060] Step 1: Sign up and log in

[0061] User: Access the tutoring school's website or app and click the "Register" button.

[0062] Terminal: Displays a registration form and prompts the user to enter their name, email address, password, etc.

[0063] Server: Receives the entered information and saves it to the database. Generates a registration completion message and notifies the terminal.

[0064] Terminal: Displays a registration completion message to the user.

[0065] User: Enter your email address and password, then click the "Login" button.

[0066] Terminal: Sends input information to the server.

[0067] Server: Authenticates the user in the database to verify their legitimacy. Generates a login success message and notifies the terminal.

[0068] Terminal: Displays a message to the user and redirects them to the dashboard.

[0069] Step 2: Create a study plan

[0070] User: After logging in, fill out a questionnaire about your learning goals and current academic level.

[0071] Terminal: Sends the entered information to the server.

[0072] Server: Based on the received information, it executes a learning algorithm and generates the optimal learning plan.

[0073] Server: Saves the generated training plan to the database. Sends the plan details to the terminal.

[0074] Terminal: Displays the learning plan generated for the user.

[0075] Step 3: 24-hour support available for questions

[0076] User: If you have any questions while learning, click the "Ask a Question" button and enter your question.

[0077] Terminal: Sends the entered question to the server.

[0078] Server: Uses generative artificial intelligence to analyze the question and generate an answer. Sends the generated answer to the terminal.

[0079] Terminal: Displays the answer to the user.

[0080] Step 4: Providing multi-subject learning materials

[0081] User: Select the subjects to study (for example, select "Science" and "Biology").

[0082] Terminal: Sends the selection to the server.

[0083] Server: Searches the database for corresponding learning materials (textbooks, videos, workbooks, etc.) and sends them to the user.

[0084] Terminal: Displays the learning materials received by the user.

[0085] Step 5: Tracking learning progress and adjusting plans

[0086] User: Open the learning progress screen and check the progress status.

[0087] Terminal: Sends progress data to the server.

[0088] Server: Based on the latest progress data, it determines whether the learning plan is progressing smoothly and adjusts the plan if necessary.

[0089] Server: Sends the updated learning plan to the device.

[0090] Terminal: Displays the updated plan to the user.

[0091] Step 6: Efficient Information Access

[0092] User: Enter the required information or documents into the search bar and click the "Search" button.

[0093] Terminal: Sends a search request to the server.

[0094] Server: Collects relevant information from databases and the internet, and summarizes it using generative artificial intelligence.

[0095] Server: Sends organized information to the terminal.

[0096] Terminal: Displays information to the user.

[0097] By executing each step in detail in this way, users can learn efficiently and effectively.

[0098] (Example 1)

[0099] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0100] In recent years, there has been a growing demand for individualized instruction and learning support. However, traditional cram schools and online education services have struggled to provide efficient and effective learning support tailored to the individual needs of users. Specifically, the lack of a system that integrates the generation of individualized learning plans based on each user's academic level and learning goals, 24 / 7 question answering, provision of learning materials covering multiple subjects, automatic tracking of learning progress and plan adjustments, and efficient information access has been a major problem.

[0101] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0102] In this invention, the server includes means for receiving input of learning goals and academic ability levels from the user and generating an individualized learning plan; means for receiving questions from the user and generating answers to those questions using generative artificial intelligence; means for providing learning materials for multiple subjects based on the user's selection; means for tracking the user's learning progress and automatically adjusting the learning plan as needed; means for collecting relevant information from a database and the internet in response to the user's information requests and summarizing it using generative artificial intelligence; means for recording the learning content completed by the user and updating the learning plan according to the learning progress; and means for analyzing the user's information requests and summarizing the relevant information using a generative artificial intelligence model. This enables effective learning support that is tailored to the individual needs of the user.

[0103] "Learning objectives" are specific learning goals or objectives that the user wants to achieve.

[0104] "Academic ability level" is an indicator that shows the user's current academic ability and the degree to which they have acquired knowledge.

[0105] A "learning plan" is a schedule set up to guide the user to the optimal learning progress, based on their academic level and learning goals.

[0106] "Generative artificial intelligence" is an artificial intelligence technology that uses natural language processing to generate appropriate answers and information in response to input questions and requests.

[0107] "Educational materials" refer to educational resources and materials used for user learning.

[0108] "Learning progress" refers to the extent to which a user has progressed according to their learning plan.

[0109] An "information request" is a request made by a user to a system in order to obtain specific information or knowledge.

[0110] A "database" is a collection of data used to efficiently manage and operate user information, learning materials, and learning progress.

[0111] The "Internet" is a communication network that connects computer networks around the world, enabling the exchange and acquisition of information.

[0112] "Means" refer to the methods, devices, or parts of a system used to achieve a particular objective.

[0113] The "individualized learning plan generation method" is a function that creates an optimal learning schedule based on the user's academic level and learning goals.

[0114] A "question and answer generation method" is a function that generates appropriate answers to user questions using generative artificial intelligence.

[0115] "Methods for providing learning materials" refers to the function of selecting and providing learning materials for users.

[0116] A "learning progress tracking mechanism" is a function that tracks the user's learning progress and adjusts the learning plan as needed.

[0117] An "information summarization tool" is a function that collects relevant information in response to a user's information request and summarizes it using generative artificial intelligence.

[0118] This invention relates to a tutoring system for effectively supporting user learning. This system consists of a server, terminals, and users, with each component working in coordination.

[0119] Sign up and log in

[0120] The server provides signup and login functionality for users accessing the tutoring school's website or app. Users enter information such as their name, email address, and password, and the device sends this information to the server. The server stores the received information in a database and sends a registration completion message to the user. During login, the server authenticates the user by referencing the information in the database and allows them to access the dashboard.

[0121] A concrete example would be a primary school student registering as a new user, logging in, and accessing the dashboard.

[0122] Creating a study plan

[0123] The server receives information about the user's learning goals and academic level, and generates an individualized learning plan based on this information. The server executes a pre-configured algorithm (for example, a Python script on the Django framework) to generate the optimal learning schedule and materials, and saves them to the database. The terminal then displays the generated learning plan to the user.

[0124] A concrete example would be a middle school student who enters a goal such as "improve math skills," and the server generates a weekly study schedule based on that information, which is then displayed on the user's device.

[0125] 24-hour support available for questions

[0126] If the user has any questions during the learning process, they input them. The device sends the question to the server. The server analyzes the question using generative artificial intelligence (e.g., GPT-4®) and generates an answer. The generated answer is sent to the device and displayed to the user.

[0127] For example, if a middle school student user asks, "I don't know how to solve a quadratic equation," the server will provide a detailed explanation and return the answer to the user.

[0128] Example of a prompt

[0129] "I don't know how to solve quadratic equations. Could you please provide a detailed explanation?"

[0130] Providing teaching materials that cover multiple subjects

[0131] The server provides learning materials corresponding to the subject selected by the user. The server searches the database for appropriate materials and sends them to the terminal. The terminal displays the provided materials to the user.

[0132] As a concrete example, when a user selects the "Biology" field under "Science," the server sends video materials and text documents related to biology to the user's device for display.

[0133] Tracking learning progress and adjusting plans

[0134] The server tracks the user's learning progress in a database and automatically adjusts the learning plan as needed. Based on the user's completed learning content and progress, it provides new schedules and supplementary materials. The terminal displays the updated learning plan to the user.

[0135] For example, if a user finishes basic math problems earlier than planned, the server can notify them to move on to the next learning step, which is applied problems, and update their learning plan.

[0136] Efficient information access

[0137] The server collects relevant information from databases and the internet in response to information requests from users. It summarizes the information using a generative artificial intelligence model (e.g., GPT-4) and sends it to the terminal. The terminal displays the summarized information to the user.

[0138] For example, if a user searches for "an overview of the French Revolution," the server could collect relevant information, generate a summarized text, and provide it to the user's device.

[0139] The system of this invention allows users to learn efficiently and effectively, and to receive necessary information and support 24 hours a day.

[0140] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0141] Step 1:

[0142] sign up

[0143] User: Access the tutoring center's website or app and enter your name, email address, and password in the sign-up form.

[0144] Input: Name, email address, password

[0145] Terminal: Sends the entered information to the server.

[0146] Server: Stores the received information in the database, generates a registration completion message, and sends it back to the terminal.

[0147] Output: Registration complete message

[0148] Specific action: A primary school student registers for the system and a confirmation email is sent.

[0149] Step 2:

[0150] Log in

[0151] User: Enter your registered email address and password and submit the login form.

[0152] Input: Email address, password

[0153] Terminal: Sends the entered information to the server.

[0154] Server: Checks if the information matches the data stored in the database. If it matches, it grants login permission, generates a dashboard, and sends it to the device.

[0155] Output: Dashboard screen

[0156] Specific action: The user logs in and accesses their individual dashboard.

[0157] Step 3:

[0158] Input learning objectives and academic ability levels

[0159] User: Enter your learning goals and current academic level.

[0160] Input: Learning objectives, academic level

[0161] Terminal: Sends the entered information to the server.

[0162] Server: Based on the received information, it executes a pre-configured algorithm to generate a learning plan and saves it to the database.

[0163] Output: Study plan

[0164] Specific operation: The user inputs a goal such as "improve math skills" and their "current grades," and the server generates a study plan and displays it on the device.

[0165] Step 4:

[0166] Question input and answer generation

[0167] User: Enter your questions if you have any during your studies.

[0168] Input: Question content

[0169] Terminal: Sends the entered question to the server.

[0170] Server: Uses generative artificial intelligence to analyze questions, generate answers, and send them to the terminal.

[0171] Output: Answer to the question

[0172] Specific operation: The user enters "I don't know how to solve quadratic equations," and the server provides a detailed explanation.

[0173] Step 5:

[0174] Selection of subjects and fields

[0175] User: Select the subjects and fields you wish to study.

[0176] Input: Subject, field

[0177] Terminal: Sends the selected information to the server.

[0178] Server: Searches the database for teaching materials suitable for the selected subject and field, and sends them to the terminal.

[0179] Output: Teaching materials

[0180] Specific operation: The user selects the "Biology" field under "Science," and the server provides the corresponding educational materials.

[0181] Step 6:

[0182] Recording and updating learning progress

[0183] User: Record what you have completed learning.

[0184] Input: Completed learning content

[0185] Terminal: Sends recorded information to the server.

[0186] Server: Updates user learning progress in the database and automatically adjusts the learning plan as needed.

[0187] Output: Updated learning plan

[0188] Specific action: The user completes basic math problems ahead of schedule and receives a new plan.

[0189] Step 7:

[0190] Information Request and Summary

[0191] User: Enter the information you want to search for.

[0192] Input: Information Request

[0193] Terminal: Sends the entered information to the server.

[0194] Server: Collects relevant information from databases and the internet, summarizes it using generative artificial intelligence, and sends it to the terminal.

[0195] Output: Summarized information

[0196] Specific operation: The user searches for "an overview of the French Revolution," and the server summarizes and provides the information.

[0197] In this way, a system is built that enables effective learning support through the coordinated operation of users, terminals, and servers.

[0198] (Application Example 1)

[0199] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0200] Conventional factory robot maintenance systems face challenges in efficient maintenance because they do not adequately generate individual plans or track progress based on each worker's skill level and maintenance objectives. Furthermore, there is a need for a support system that can quickly address problems and questions that workers encounter during maintenance.

[0201] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0202] In this invention, the server includes means for receiving user input of maintenance goals and skill levels and generating individual maintenance plans; means for receiving user questions and generating answers to those questions using generative artificial intelligence; means for providing multidisciplinary learning materials based on user selection; means for tracking user progress and automatically adjusting the plan as needed; and means for collecting relevant information from databases and the internet in response to user information requests and summarizing it using generative artificial intelligence. This enables the provision of efficient and personalized maintenance plans, immediate question support, and the provision of diverse learning materials.

[0203] "Maintenance targets" are specific objectives and standards that should be achieved when maintaining or repairing factory robots.

[0204] "Skill level" is an indicator that shows the degree of maintenance knowledge and skills possessed by a worker.

[0205] An "individualized maintenance plan" is a plan that includes a customized maintenance schedule and procedures based on each worker's skill level and maintenance goals.

[0206] "Generative artificial intelligence" is an artificial intelligence technology that automatically generates answers and solutions based on input data and information.

[0207] "Multidisciplinary teaching materials" refers to learning materials, tool manuals, video materials, and other resources related to various fields of robot maintenance.

[0208] "Progress tracking" refers to the act of recording the progress of maintenance work performed by workers and saving it in a database.

[0209] A "database" is a collection of digital information designed to efficiently organize, store, and retrieve information.

[0210] The "Internet" is a communication network for sharing information through computer network systems worldwide.

[0211] An "information request" is a request to search for and provide the information that a user needs.

[0212] "Summarization" is the act of compiling collected detailed information into a concise and easy-to-understand format.

[0213] This invention is a system for streamlining maintenance work on factory robots and provides the following main functions.

[0214] 1. User signup and login

[0215] Server: Provides sign-up and login functionality to allow workers to access the system. During new registration, workers enter information such as their name, email address, and password, which the server stores in a database. During login, the server uses the information in the database to authenticate the worker.

[0216] Specific example: A new worker creates an account, logs in, and accesses the maintenance guide.

[0217] 2. Creating a maintenance plan

[0218] Server: Receives information on worker maintenance goals and skill levels, and generates individual maintenance plans based on this information. The server executes a pre-configured algorithm to generate the optimal maintenance schedule and procedures, and stores them in the database.

[0219] Specific example: When a worker with entry-level skills enters the objective "hydraulic system maintenance," the server generates a weekly maintenance schedule based on the worker's skill level and displays it on the terminal.

[0220] 3. 24-hour support for questions

[0221] User: If you have any questions during maintenance, please enter them here.

[0222] Terminal: Sends the question content to the server.

[0223] Server: Uses generative artificial intelligence to analyze questions and generate answers. The generated answers are sent to the terminal and displayed to the user.

[0224] Specific example: When a novice worker asks, "What should I do if the robot's movements become slow?", the server provides detailed instructions and returns the answer to the worker immediately.

[0225] 4. Provision of educational materials covering multiple fields.

[0226] Server: Provides training materials for the maintenance area selected by the worker. The server searches the database for appropriate training materials and sends them to the terminal.

[0227] Specific example: When a worker selects the "Electrical System Maintenance" field, the server sends video and text materials related to that field to the worker's terminal for display.

[0228] 5. Tracking maintenance progress and coordinating plans.

[0229] Server: Tracks the maintenance progress of workers in a database and automatically adjusts the maintenance plan as needed. Provides new schedules and supplementary materials based on the maintenance tasks and progress completed by workers.

[0230] Specific example: If a worker completes a particular maintenance task ahead of schedule, the server will suggest the next maintenance step and update the plan.

[0231] 6. Efficient Information Access

[0232] Server: In response to information requests from workers, it collects relevant information from databases and the internet. It uses generative artificial intelligence to summarize the information and present it to workers in an easy-to-understand manner.

[0233] Specific example: If a worker is researching "the latest maintenance techniques," the server collects the relevant information and provides the worker with a summarized text.

[0234] In this way, by having the user (worker), terminal, and server work together, the worker can carry out robot maintenance efficiently and effectively, and can receive necessary information and support 24 hours a day. The system of the present invention realizes flexible maintenance support that meets the individual needs of the worker.

[0235] Example of a prompt:

[0236] "New worker sign-up: Please enter your name, email address, and password."

[0237] "Please refer to the hydraulic system maintenance plan."

[0238] "What should I do if the robot's movements become slow?"

[0239] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0240] Step 1:

[0241] The user accesses the system and enters information on the sign-up or login screen. The required fields are name, email address, and password.

[0242] Input: Name, email address, password

[0243] Output: Data to send to the server

[0244] Specific action: The user enters the required information into the UI form and presses the "Submit" button.

[0245] Step 2:

[0246] The server saves the received input data to the database. For new registrations, it creates new user information; for logins, it performs authentication.

[0247] Input: Sign-up or login information

[0248] Output: Registration complete or authentication result

[0249] Specific operation: The server executes an SQL query to save or retrieve user information from the database.

[0250] Step 3:

[0251] After the user logs in, they enter the maintenance objectives and skill level on the maintenance plan creation screen.

[0252] Input: Maintenance objectives, skill level

[0253] Output: Plan creation request to the server

[0254] Specific operation: The user enters the goal and level into the UI form and presses the "Generate Plan" button.

[0255] Step 4:

[0256] The server executes an algorithm based on the received maintenance objectives and skill levels to generate individual maintenance plans.

[0257] Input: Maintenance objectives, skill level

[0258] Output: Maintenance plan

[0259] Specific operation: The server executes the plan generation algorithm and saves the generated plan to the database.

[0260] Step 5:

[0261] Users can enter questions if they have any while viewing the maintenance plan and performing each step.

[0262] Input: Question content

[0263] Output: Question request to the server

[0264] Specific action: The user enters a question into the UI form and presses the "Submit" button.

[0265] Step 6:

[0266] The server analyzes the received question and generates an answer using generative artificial intelligence (for example, an OpenAI® model).

[0267] Input: Question content

[0268] Output: Answer text

[0269] Specific operation: The server inputs a question as a prompt to the generative artificial intelligence, and returns the obtained answer to the user.

[0270] Step 7:

[0271] When the user requests teaching materials corresponding to the selected maintenance field, a request is sent to the server.

[0272] Input: Selection of maintenance field

[0273] Output: Request for teaching materials to the server

[0274] Specific operation: The user selects a field in the UI and presses the "Teaching material acquisition" button.

[0275] Step 8:

[0276] The server searches for relevant teaching materials from the database and sends them to the user.

[0277] Input: Selection of maintenance field

[0278] Output: Teaching material data

[0279] Specific operation: The server searches for appropriate teaching materials from the database on the server side and sends them to the user's terminal.

[0280] Step 9:

[0281] Track the user's maintenance progress and save the progress information to the database.

[0282] Input: Maintenance progress information

[0283] Output: Updated progress status

[0284] Specific operation: The user inputs the maintenance progress status and it is saved to the server.

[0285] Step 10:

[0286] If necessary, the server adjusts the maintenance plan and provides new steps and supplementary teaching materials.

[0287] Input: Updated progress

[0288] Output: Adjusted maintenance plan and supplementary teaching materials

[0289] Specific operation: The server re-evaluates the plan based on the progress information and adjusts it as appropriate.

[0290] Furthermore, an emotion engine for estimating the user's emotion may be combined. That is, the specific processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform specific processing using the user's emotion.

[0291] The learning school system of the present invention provides the following main functions in order to effectively support the user's learning. In addition, an emotion engine that recognizes the user's emotion and adjusts the learning plan according to the emotion is incorporated in this system. <​​​​​​​​​​​​​​​​​​Server: Receives information about the user's learning goals and academic level, and generates an individualized learning plan based on this information. The server executes a pre-configured algorithm to generate the optimal learning schedule and materials, and stores them in a database.

[0297] Specific example: When a middle school student user enters the goal "improve math skills," the server generates a weekly study schedule based on the user's academic level and displays it on the device.

[0298] 3. 24-hour support for questions

[0299] User: If you have any questions while learning, enter them here.

[0300] Terminal: Sends the question content to the server.

[0301] Server: Uses generative artificial intelligence to analyze questions and generate answers. The generated answers are sent to the terminal and displayed to the user.

[0302] Specific example: If a middle school student user asks, "I don't know how to solve quadratic equations," the server provides a detailed explanation and immediately returns the answer to the user.

[0303] 4. Provision of teaching materials covering multiple subjects

[0304] Server: Provides corresponding learning materials for the subject selected by the user. The server searches the database for appropriate materials and sends them to the terminal.

[0305] Specific example: When a user selects the "Biology" field under "Science," the server sends video materials and text documents related to biology to the user's device and displays them.

[0306] 5. Tracking learning progress and adjusting plans

[0307] Server: Track the user's learning progress in the database and automatically adjust the learning plan as needed. Provide new schedules and supplementary teaching materials based on the learning content and progress completed by the user.

[0308] Specific example: If the user finishes the basic math problems earlier than planned, the server notifies the user to proceed to the application problems, which are the next learning step, and updates the learning plan.

[0309] 6. Efficient Information Access

[0310] Server: Collect relevant information from the database and the Internet in response to information requests from the user. Use generative artificial intelligence to summarize the information and provide it to the user in an easy-to-understand manner.

[0311] Specific example: When the user searches for "an overview of the French Revolution", the server collects relevant information and provides the summarized text to the user.

[0312] 7. Emotion Recognition and Learning Plan Adjustment by Emotion Engine

[0313] Server: Recognize the user's emotions using the emotion engine during the user's learning. The emotion engine collects the user's emotion data using facial expression recognition and voice analysis.

[0314] Specific example: If the user feels stressed during learning, the emotion engine recognizes this, and the server recommends games or short breaks to relax the user.

[0315] Server: Save the emotion data in the database and analyze it regularly together with the user's learning history. This enables measures to be taken to improve long-term learning efficiency.

[0316] Specific example: If it is found based on the user's emotion data that the learning efficiency is decreasing during a specific time period, the server adjusts the plan so that lighter subjects are learned during that time period.

[0317] Thus, the system of the present invention, through the cooperation of the user, terminal, and server, realizes flexible learning support tailored to individual needs and supports efficient and effective learning by providing appropriate responses in accordance with the user's emotions.

[0318] The following describes the processing flow.

[0319] Step 1: Sign up and log in

[0320] User: Access the tutoring school's website or app and click the "Register" button.

[0321] Terminal: Displays a registration form and prompts the user to enter their name, email address, password, etc.

[0322] Server: Receives the entered information and saves it to the database. Generates a registration completion message and notifies the terminal.

[0323] Terminal: Displays a registration completion message to the user.

[0324] User: Enter your email address and password, then click the "Login" button.

[0325] Terminal: Sends input information to the server.

[0326] Server: Authenticates the user in the database to verify their legitimacy. Generates a login success message and notifies the terminal.

[0327] Terminal: Displays a message to the user and redirects them to the dashboard.

[0328] Step 2: Create a study plan

[0329] User: After logging in, fill out a questionnaire about your learning goals and current academic level.

[0330] Terminal: Sends the entered information to the server.

[0331] Server: Based on the received information, it executes a learning algorithm and generates the optimal learning plan.

[0332] Server: Saves the generated training plan to the database. Sends the plan details to the terminal.

[0333] Terminal: Displays the learning plan generated for the user.

[0334] Step 3: 24-hour support available for questions

[0335] User: If you have any questions while learning, click the "Ask a Question" button and enter your question.

[0336] Terminal: Sends the entered question to the server.

[0337] Server: Uses generative artificial intelligence to analyze the question and generate an answer. Sends the generated answer to the terminal.

[0338] Terminal: Displays the answer to the user.

[0339] Step 4: Providing multi-subject learning materials

[0340] User: Select the subjects to study (for example, select "Science" and "Biology").

[0341] Terminal: Sends the selection to the server.

[0342] Server: Searches the database for corresponding learning materials (textbooks, videos, workbooks, etc.) and sends them to the user.

[0343] Terminal: Displays the learning materials received by the user.

[0344] Step 5: Tracking learning progress and adjusting plans

[0345] User: Open the learning progress screen and check the progress status.

[0346] Terminal: Sends progress data to the server.

[0347] Server: Based on the latest progress data, it determines whether the learning plan is progressing smoothly and adjusts the plan if necessary.

[0348] Server: Sends the updated learning plan to the device.

[0349] Terminal: Displays the updated plan to the user.

[0350] Step 6: Efficient Information Access

[0351] User: Enter the required information or documents into the search bar and click the "Search" button.

[0352] Terminal: Sends a search request to the server.

[0353] Server: Collects relevant information from databases and the internet, and summarizes it using generative artificial intelligence.

[0354] Server: Sends organized information to the terminal.

[0355] Terminal: Displays information to the user.

[0356] Step 7: Emotion recognition by the emotion engine

[0357] User: Generates emotional data through facial expressions and voice during learning.

[0358] Terminal: Transfers the user's facial expressions and voice to the emotion engine.

[0359] Server: The emotion engine recognizes the user's emotions and analyzes that data.

[0360] Step 8: Adjusting your learning plan based on your emotions

[0361] Server: Adjusts the user's learning plan based on the emotion data recognized by the emotion engine.

[0362] Server: Stores the coordinated plan in the database and analyzes it along with user progress data.

[0363] Device: Displays feedback from the emotion engine and suggests appropriate learning methods and breaks to the user.

[0364] Step 9: Long-term analysis of emotional data

[0365] Server: Regularly collects emotional data and stores it in a database.

[0366] Server: Analyzes user learning history and sentiment data to propose measures for improving long-term learning efficiency.

[0367] Terminal: Based on the analysis results, it suggests a learning plan, break times, and learning materials that are suitable for the user.

[0368] By executing each step in detail in this way, users can learn efficiently and effectively. In particular, the introduction of an emotion engine enables flexible learning support that responds to the user's emotions.

[0369] (Example 2)

[0370] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0371] Traditional learning support systems have limitations in providing appropriate learning plans tailored to individual users' learning goals and academic levels, and in particular, they lack individualized support that takes into account the user's emotional state. This has led to challenges such as users being unable to maximize their learning effectiveness due to stress and decreased motivation. Furthermore, in traditional systems, tracking learning progress and adjusting plans often required manual intervention, resulting in inefficient support.

[0372] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0373] In this invention, the server includes means for receiving input of learning goals and academic ability levels from the user and generating an individualized learning plan; means for receiving questions from the user and generating answers to those questions using generative artificial intelligence; means for providing learning materials for multiple subjects based on the user's selection; means for tracking the user's learning progress and automatically adjusting the learning plan as needed; means for collecting relevant information from databases and the internet in response to the user's information requests and summarizing it using generative artificial intelligence; and means for recognizing the user's emotions and adjusting the learning plan accordingly. This enables flexible learning support based on the learning needs of each individual user.

[0374] A "learning objective" is the specific learning goal that the user wants to achieve.

[0375] "Academic ability level" is an indicator that shows the user's current level of academic ability and knowledge.

[0376] A "learning plan" is a combination of a schedule and learning materials created based on the user's learning goals and academic level, designed to facilitate effective learning.

[0377] "Generative artificial intelligence" is an artificial intelligence technology that generates responses to user questions and requests.

[0378] "Multi-subject learning materials" refer to learning materials that cover multiple subjects, and are provided according to the subjects selected by the user.

[0379] "Learning progress" is an indicator that shows how far a user has progressed in their learning.

[0380] An "information request" is a request that a user sends to seek specific information or knowledge.

[0381] A "database" is a digital storage system used to manage and organize information and materials necessary for learning.

[0382] An "emotion engine" is a system that recognizes the user's emotional state and adjusts the learning plan based on that state.

[0383] The learning center system of the present invention provides the following main functions to effectively support the user's learning. This system is established through the interaction of a server, terminals, and users. Specific embodiments of the system based on the claims are shown below.

[0384] 1. User signup and login

[0385] The server provides sign-up and login functionality to authenticate users accessing the tutoring school's website or app. During new user registration, users enter information such as their name, email address, and password, which the server stores in a database. During login, the server authenticates the user based on the information in the database.

[0386] Specific example: A primary school student registers for the system, then logs in and accesses the dashboard.

[0387] 2. Creating a study plan

[0388] The server receives information about the user's learning goals and academic level, and generates an individualized learning plan. The server executes a pre-configured algorithm to generate the optimal learning schedule and materials, and stores them in a database.

[0389] Specific example: If a middle school student user enters "improve math skills" as their goal, the server generates a weekly study schedule based on the user's academic level and displays it on their device.

[0390] 3. Answering questions

[0391] If a user encounters a question during the learning process, they input the question. The device sends the question to the server. The server uses generative artificial intelligence to analyze the question and generate an answer. This generated answer is then sent to the device and displayed to the user.

[0392] Specific example: When a middle school student asks, "I don't know how to solve quadratic equations," the server uses generative artificial intelligence to provide a detailed explanation and immediately returns the answer to the user.

[0393] 4. Providing teaching materials

[0394] The server provides the corresponding learning materials according to the subject selected by the user. The server searches the database for the appropriate materials and sends them to the terminal.

[0395] Specific example: When a user selects the "Biology" field under "Science," the server sends video materials and text documents related to biology to the user's device and displays them.

[0396] 5. Tracking learning progress and adjusting plans

[0397] The server tracks the user's learning progress in a database and automatically adjusts the learning plan as needed. Based on the user's completed learning content and progress, it provides new schedules and supplementary materials.

[0398] Specific example: If a user finishes basic math problems earlier than planned, the server notifies the user to move on to the next learning step, which is applied problems, and updates the learning plan.

[0399] 6. Access to Information

[0400] The server collects relevant information from databases and the internet in response to user information requests. It then uses generative artificial intelligence to summarize the information and present it to the user in an easily understandable format.

[0401] Specific example: If a user searches for "an overview of the French Revolution," the server collects relevant information and provides the user with a summarized text.

[0402] 7. Responses based on the emotion engine

[0403] The server uses an emotion engine to recognize the user's emotions. The emotion engine collects user emotion data using facial recognition and voice analysis, and adjusts the learning plan based on this data. The emotion data is stored in a database and periodically analyzed along with the user's learning history.

[0404] Specific examples: If a user is experiencing stress while learning, the emotion engine will recognize this, and the server will recommend games or short breaks to help the user relax. If learning efficiency is low during certain times, the plan will be adjusted to include lighter subjects during those times.

[0405] This allows the tutoring system to provide flexible learning support tailored to the individual needs of users, enabling efficient and effective learning.

[0406] Example of a prompt

[0407] "Please tell me about specific methods for detecting the stress that middle school students experience while studying and suggesting appropriate responses."

[0408] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0409] Program processing steps

[0410] Step 1: User Signup

[0411] 1. Input: The user accesses the tutoring center's website or app and enters their name, email address, and password.

[0412] 2. Specific operation: The terminal sends the entered information to the server.

[0413] 3. Data processing: The server receives the information and stores it in the database.

[0414] 4. Output: The server sends a registration completion message to the terminal.

[0415] 5. Specific action: The device displays "Registration complete."

[0416] Step 2: User Login

[0417] 1. Input: The user enters their email address and password on the website or app's login screen.

[0418] 2. Specific operation: The terminal sends the entered information to the server.

[0419] 3. Data processing: The server accesses the database and verifies that the user information matches the input information.

[0420] 4. Output: The server sends a login success signal to the terminal.

[0421] 5. Specific action: The device displays the user's dashboard.

[0422] Step 3: Create a study plan

[0423] 1. Input: The user enters their learning goals and current academic level.

[0424] 2. Specific actions: The terminal sends this information to the server.

[0425] 3. Data processing: The server uses algorithms to generate individual learning plans and stores them in the database.

[0426] 4. Output: The server sends the generated training plan to the terminal.

[0427] 5. Specific actions: The device displays the learning plan to the user.

[0428] Step 4: Answering Questions

[0429] 1. Input: The user enters a question.

[0430] 2. Specific action: The terminal sends the question to the server.

[0431] 3. Data processing: The server uses a generative AI model to analyze the question and generate an answer.

[0432] 4. Output: The server sends the generated response to the terminal.

[0433] 5. Specific action: The device displays the answer to the user.

[0434] Step 5: Provide teaching materials

[0435] 1. Input: The user selects the subject or field they wish to study.

[0436] 2. Specific action: The terminal sends that information to the server.

[0437] 3. Data processing: The server searches the database for appropriate teaching materials.

[0438] 4. Output: The server sends the selected learning materials to the terminal.

[0439] 5. Specific operation: The device displays the learning materials to the user.

[0440] Step 6: Tracking learning progress and adjusting plans

[0441] 1. Input: The user enters learning progress information.

[0442] 2. Specific action: The terminal sends that information to the server.

[0443] 3. Data processing: The server analyzes the learning progress data and updates the learning plan as needed.

[0444] 4. Output: The server sends the updated learning plan to the terminal.

[0445] 5. Specific action: The device displays a new learning plan to the user.

[0446] Step 7: Responding with an emotional engine

[0447] 1. Input: The emotion engine captures the user's facial expressions and voice data during the learning process.

[0448] 2. Specific action: The terminal sends this data to the server.

[0449] 3. Data processing: The server uses an emotion engine to analyze the user's emotions and determine if the learning plan needs to be adjusted.

[0450] 4. Output: The server sends the adjusted learning plan results, based on the user's emotions, to the terminal.

[0451] 5. Specific actions: The device displays a learning plan and relaxation menu tailored to the user.

[0452] In this way, the tutoring system, through the coordination of users, terminals, and servers, provides flexible learning support tailored to individual needs and enables efficient and effective learning by responding appropriately to the user's emotions.

[0453] (Application Example 2)

[0454] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0455] Traditional learning systems have a problem of reduced learning effectiveness because they provide a uniform learning plan without considering the learner's emotional state. Furthermore, the lack of flexible adjustments in response to emotional changes leads to increased learning stress. In addition, since emotional states affect work efficiency among factory workers, there is a need for efficient work support utilizing emotional data.

[0456] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0457] In this invention, the server includes means for receiving input of learning goals and academic ability levels from the user and generating individual learning plans; means for receiving questions from the user and generating answers to those questions using generative artificial intelligence; means for providing learning materials for multiple subjects based on the user's selection; means for tracking the user's learning progress and automatically adjusting the learning plan as needed; means for collecting relevant information from databases and the internet in response to the user's information requests and summarizing it using generative artificial intelligence; means for collecting emotional data from the user's facial expressions and voice and determining their emotional state using an emotion recognition model; and means for flexibly adjusting the learning plan based on the determined emotional state. This enables individualized responses that are tailored to the emotions of learners and workers.

[0458] A "user" refers to a learner or factory worker who uses the system.

[0459] "Learning objectives" are specific learning goals that the user wants to achieve.

[0460] "Academic ability level" refers to the user's current level of understanding and knowledge regarding learning.

[0461] An "individualized learning plan" refers to a user-specific learning schedule and content created based on the user's learning goals and academic level.

[0462] "Generative artificial intelligence" refers to artificial intelligence technology that generates answers to questions, summaries of information, and other data based on large amounts of data.

[0463] "Multi-subject learning materials" refer to learning materials that cover multiple subjects, including videos, textbooks, and workbooks.

[0464] "Learning progress" refers to the user's learning progress and indicates how far they have progressed in their learning.

[0465] A "database" is a digital repository for information, where various types of data such as user information, learning content, and questions and answers are stored.

[0466] The "Internet" is a vast source of information available online, and a means of searching for answers to users' information requests.

[0467] To "summarize" means to put detailed information into a concise and easy-to-understand format.

[0468] "Emotional data" refers to digital information about a user's emotional state, obtained from their facial expressions and voice.

[0469] An "emotion recognition model" is a machine learning or deep learning model that performs facial recognition and voice analysis to determine a user's emotions.

[0470] "Emotional state" refers to the psychological state a user experiences while learning or working, and includes stress, joy, sadness, and other similar emotions.

[0471] "Flexibly adjusting the learning plan" means changing the content and order of learning and tasks to reflect the user's current emotional state.

[0472] The system of the present invention provides multiple functions to effectively support user learning. This system includes an emotion engine that recognizes the user's emotional state and adjusts the learning plan accordingly.

[0473] 1. User signup and login

[0474] The server provides signup and login functionality to authenticate users accessing the tutoring school's website or mobile app. Users enter information such as their name, email address, and password during registration, which is stored in the database. During login, the server authenticates the user using the information in the database.

[0475] 2. Creating a study plan

[0476] The server receives information about the user's learning goals and academic level, and generates an individualized learning plan based on this information. It generates the optimal learning schedule and materials based on an algorithm and stores them in a database.

[0477] 3. 24-hour support for questions

[0478] If a user has questions during the learning process, they can input them using their device. The device sends the question to the server, which uses generative artificial intelligence to analyze the question and generate an answer. The generated answer is then sent back to the device and displayed to the user.

[0479] 4. Provision of teaching materials covering multiple subjects

[0480] The server provides learning materials corresponding to the subject selected by the user. It searches the database for appropriate materials, sends them to the terminal, and displays them to the user.

[0481] 5. Tracking learning progress and adjusting plans

[0482] The server tracks the user's learning progress in a database and automatically adjusts the learning plan as needed. Based on the user's completed learning content and progress, it provides new schedules and supplementary materials.

[0483] 6. Efficient Information Access

[0484] The server collects relevant information from databases and the internet in response to user information requests, and summarizes the information using generative artificial intelligence. It then presents the information to the user in an easy-to-understand manner.

[0485] 7. Emotion recognition and learning plan adjustment using an emotion engine.

[0486] The server uses an emotion engine to recognize the user's emotional state during training. The emotion engine collects user emotional data using facial recognition and speech analysis, and uses an emotion recognition model to determine the emotional state. Based on the results, it flexibly adjusts the training plan.

[0487] Hardware and software used

[0488] The emotion recognition feature, which is part of this system, uses the following hardware and software.

[0489] Hardware: Smart glasses and cameras (e.g., Google Glass®)

[0490] Software: Emotion recognition model (using Keras), OpenCV for face recognition

[0491] Specific example

[0492] For example, suppose a factory worker is wearing smart glasses while working. If the server can determine the worker's current stress level from their facial expressions, it will recognize this and automatically adjust the worker's work plan. For instance, if the worker is in a high-stress state requiring immediate attention, the server might reduce the workload or recommend a short break.

[0493] Example of a prompt

[0494] Design a smart work assistant application that analyzes employees' facial expressions and emotions in real time and adjusts work plans accordingly. Specifically, it uses a camera built into smart glasses to recognize the employee's face, determines their emotions using an emotion recognition model, and adjusts their work based on that emotion data. For example, if an employee is feeling stressed, the system should recommend relaxing tasks or breaks.

[0495] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0496] Step 1:

[0497] The device uses its camera to capture the user's face. The image data is acquired and converted to grayscale as a preprocessing step. This prepares the data necessary for face recognition.

[0498] Input: User's face image

[0499] Output: Grayscale facial image data

[0500] Specific operation: The smart glasses' camera captures a facial image in real time, and OpenCV is used to convert the image to grayscale.

[0501] Step 2:

[0502] The device performs facial recognition and identifies the facial region. The image of the facial region is resized to a standard size and converted to the format required by the model.

[0503] Input: Grayscale facial image data

[0504] Output: Resized face region image data

[0505] Specific operation: Use a face recognition algorithm (e.g., Haar Cascade) to obtain the coordinates of the face, and resize the face area to a standard size (e.g., 48x48 pixels).

[0506] Step 3:

[0507] The device inputs facial image data into an emotion recognition model, which then determines the emotion. The model outputs an emotion label and its corresponding probability.

[0508] Input: Resized facial region image data

[0509] Output: Sentiment labels and probabilities

[0510] Specific operation: Resized image data is input into an emotion recognition model using Keras, and the emotion determination result is obtained. For example, an output such as "Happy: 0.85, Sad: 0.10" may be obtained.

[0511] Step 4:

[0512] The device sends the assessment result to the server. The server adjusts the learning plan based on the emotional state.

[0513] Input: Emotion labels and probabilities

[0514] Output: Instructions for adjusting the learning plan

[0515] Specific operation: The emotion recognition results are sent to the server, which executes an algorithm to generate a learning or work plan appropriate to the emotional state. For example, if a stressed state is detected, a recommendation for a break or assignment of light work may be made.

[0516] Step 5:

[0517] The server sends the adjusted learning plan to the terminal. The terminal displays the new learning or work plan to the user.

[0518] Input: Learning plan with adjustment instructions

[0519] Output: New learning plan displayed on the terminal

[0520] Specific operation: The server sends a newly generated learning plan to the terminal, which then displays it on the user's screen. For example, a message such as "You have 10 minutes until your next break" might be displayed.

[0521] 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.

[0522] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0523] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0524] [Second Embodiment]

[0525] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0526] 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.

[0527] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0528] 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.

[0529] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0530] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0531] 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.

[0532] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0533] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0534] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0535] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0536] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0537] The learning center system of the present invention provides the following main functions to effectively support the user's learning.

[0538] 1. User signup and login

[0539] Server: Provides signup and login functionality to authenticate users accessing the tutoring school's website or app. During new user registration, users enter information such as their name, email address, and password, which the server stores in a database. During login, the server uses the information in the database to authenticate the user.

[0540] Specific example: A primary school student registers for the system, then logs in and accesses the dashboard.

[0541] 2. Creating a study plan

[0542] Server: Receives information about the user's learning goals and academic level, and generates an individualized learning plan based on this information. The server executes a pre-configured algorithm to generate the optimal learning schedule and materials, and stores them in a database.

[0543] Specific example: When a middle school student user enters the goal "improve math skills," the server generates a weekly study schedule based on the user's academic level and displays it on the device.

[0544] 3. 24-hour support for questions

[0545] User: If you have any questions while learning, enter them here.

[0546] Terminal: Sends the question content to the server.

[0547] Server: Uses generative artificial intelligence to analyze questions and generate answers. The generated answers are sent to the terminal and displayed to the user.

[0548] Specific example: If a middle school student user asks, "I don't know how to solve quadratic equations," the server provides a detailed explanation and immediately returns the answer to the user.

[0549] 4. Provision of teaching materials covering multiple subjects

[0550] Server: Provides corresponding learning materials for the subject selected by the user. The server searches the database for appropriate materials and sends them to the terminal.

[0551] Specific example: When a user selects the "Biology" field under "Science," the server sends video materials and text documents related to biology to the user's device and displays them.

[0552] 5. Tracking learning progress and adjusting plans

[0553] Server: Tracks user learning progress in a database and automatically adjusts the learning plan as needed. Provides new schedules and supplementary materials based on the user's completed learning content and progress.

[0554] Specific example: If a user finishes basic math problems earlier than planned, the server notifies the user to move on to the next learning step, which is applied problems, and updates the learning plan.

[0555] 6. Efficient Information Access

[0556] Server: In response to information requests from users, it collects relevant information from databases and the internet. It uses generative artificial intelligence to summarize the information and present it to the user in an easy-to-understand manner.

[0557] Specific example: If a user searches for "an overview of the French Revolution," the server collects relevant information and provides the user with a summarized text.

[0558] In this way, the user, terminal, and server work together, enabling the user to learn efficiently and effectively, and to receive necessary information and support 24 hours a day. The system of the present invention realizes flexible learning support that meets the individual needs of the user.

[0559] The following describes the processing flow.

[0560] Step 1: Sign up and log in

[0561] User: Access the tutoring school's website or app and click the "Register" button.

[0562] Terminal: Displays a registration form and prompts the user to enter their name, email address, password, etc.

[0563] Server: Receives the entered information and saves it to the database. Generates a registration completion message and notifies the terminal.

[0564] Terminal: Displays a registration completion message to the user.

[0565] User: Enter your email address and password, then click the "Login" button.

[0566] Terminal: Sends input information to the server.

[0567] Server: Authenticates the user in the database to verify their legitimacy. Generates a login success message and notifies the terminal.

[0568] Terminal: Displays a message to the user and redirects them to the dashboard.

[0569] Step 2: Create a study plan

[0570] User: After logging in, fill out a questionnaire about your learning goals and current academic level.

[0571] Terminal: Sends the entered information to the server.

[0572] Server: Based on the received information, it executes a learning algorithm and generates the optimal learning plan.

[0573] Server: Saves the generated training plan to the database. Sends the plan details to the terminal.

[0574] Terminal: Displays the learning plan generated for the user.

[0575] Step 3: 24-hour support available for questions

[0576] User: If you have any questions while learning, click the "Ask a Question" button and enter your question.

[0577] Terminal: Sends the entered question to the server.

[0578] Server: Uses generative artificial intelligence to analyze the question and generate an answer. Sends the generated answer to the terminal.

[0579] Terminal: Displays the answer to the user.

[0580] Step 4: Providing multi-subject learning materials

[0581] User: Select the subjects to study (for example, select "Science" and "Biology").

[0582] Terminal: Sends the selection to the server.

[0583] Server: Searches the database for corresponding learning materials (textbooks, videos, workbooks, etc.) and sends them to the user.

[0584] Terminal: Displays the learning materials received by the user.

[0585] Step 5: Tracking learning progress and adjusting plans

[0586] User: Open the learning progress screen and check the progress status.

[0587] Terminal: Sends progress data to the server.

[0588] Server: Based on the latest progress data, it determines whether the learning plan is progressing smoothly and adjusts the plan if necessary.

[0589] Server: Sends the updated learning plan to the device.

[0590] Terminal: Displays the updated plan to the user.

[0591] Step 6: Efficient Information Access

[0592] User: Enter the required information or documents into the search bar and click the "Search" button.

[0593] Terminal: Sends a search request to the server.

[0594] Server: Collects relevant information from databases and the internet, and summarizes it using generative artificial intelligence.

[0595] Server: Sends organized information to the terminal.

[0596] Terminal: Displays information to the user.

[0597] By executing each step in detail in this way, users can learn efficiently and effectively.

[0598] (Example 1)

[0599] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0600] In recent years, there has been a growing demand for individualized instruction and learning support. However, traditional cram schools and online education services have struggled to provide efficient and effective learning support tailored to the individual needs of users. Specifically, the lack of a system that integrates the generation of individualized learning plans based on each user's academic level and learning goals, 24 / 7 question answering, provision of learning materials covering multiple subjects, automatic tracking of learning progress and plan adjustments, and efficient information access has been a major problem.

[0601] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0602] In this invention, the server includes means for receiving input of learning goals and academic ability levels from the user and generating an individualized learning plan; means for receiving questions from the user and generating answers to those questions using generative artificial intelligence; means for providing learning materials for multiple subjects based on the user's selection; means for tracking the user's learning progress and automatically adjusting the learning plan as needed; means for collecting relevant information from a database and the internet in response to the user's information requests and summarizing it using generative artificial intelligence; means for recording the learning content completed by the user and updating the learning plan according to the learning progress; and means for analyzing the user's information requests and summarizing the relevant information using a generative artificial intelligence model. This enables effective learning support that is tailored to the individual needs of the user.

[0603] "Learning objectives" are specific learning goals or objectives that the user wants to achieve.

[0604] "Academic ability level" is an indicator that shows the user's current academic ability and the degree to which they have acquired knowledge.

[0605] A "learning plan" is a schedule set up to guide the user to the optimal learning progress, based on their academic level and learning goals.

[0606] "Generative artificial intelligence" is an artificial intelligence technology that uses natural language processing to generate appropriate answers and information in response to input questions and requests.

[0607] "Educational materials" refer to educational resources and materials used for user learning.

[0608] "Learning progress" refers to the extent to which a user has progressed according to their learning plan.

[0609] An "information request" is a request made by a user to a system in order to obtain specific information or knowledge.

[0610] A "database" is a collection of data used to efficiently manage and operate user information, learning materials, and learning progress.

[0611] The "Internet" is a communication network that connects computer networks around the world, enabling the exchange and acquisition of information.

[0612] "Means" refer to the methods, devices, or parts of a system used to achieve a particular objective.

[0613] The "individualized learning plan generation method" is a function that creates an optimal learning schedule based on the user's academic level and learning goals.

[0614] A "question and answer generation method" is a function that generates appropriate answers to user questions using generative artificial intelligence.

[0615] "Methods for providing learning materials" refers to the function of selecting and providing learning materials for users.

[0616] A "learning progress tracking mechanism" is a function that tracks the user's learning progress and adjusts the learning plan as needed.

[0617] An "information summarization tool" is a function that collects relevant information in response to a user's information request and summarizes it using generative artificial intelligence.

[0618] This invention relates to a tutoring system for effectively supporting user learning. This system consists of a server, terminals, and users, with each component working in coordination.

[0619] Sign up and log in

[0620] The server provides signup and login functionality for users accessing the tutoring school's website or app. Users enter information such as their name, email address, and password, and the device sends this information to the server. The server stores the received information in a database and sends a registration completion message to the user. During login, the server authenticates the user by referencing the information in the database and allows them to access the dashboard.

[0621] A concrete example would be a primary school student registering as a new user, logging in, and accessing the dashboard.

[0622] Creating a study plan

[0623] The server receives information about the user's learning goals and academic level, and generates an individualized learning plan based on this information. The server executes a pre-configured algorithm (for example, a Python script on the Django framework) to generate the optimal learning schedule and materials, and saves them to the database. The terminal then displays the generated learning plan to the user.

[0624] A concrete example would be a middle school student who enters a goal such as "improve math skills," and the server generates a weekly study schedule based on that information, which is then displayed on the user's device.

[0625] 24-hour support available for questions

[0626] If the user encounters any questions during the learning process, they input them. The device sends the question to the server. The server analyzes the question using generative artificial intelligence (e.g., GPT-4) and generates an answer. The generated answer is sent to the device and displayed to the user.

[0627] For example, if a middle school student user asks, "I don't know how to solve a quadratic equation," the server will provide a detailed explanation and return the answer to the user.

[0628] Example of a prompt

[0629] "I don't know how to solve quadratic equations. Could you please provide a detailed explanation?"

[0630] Providing teaching materials that cover multiple subjects

[0631] The server provides learning materials corresponding to the subject selected by the user. The server searches the database for appropriate materials and sends them to the terminal. The terminal displays the provided materials to the user.

[0632] As a concrete example, when a user selects the "Biology" field under "Science," the server sends video materials and text documents related to biology to the user's device for display.

[0633] Tracking learning progress and adjusting plans

[0634] The server tracks the user's learning progress in a database and automatically adjusts the learning plan as needed. Based on the user's completed learning content and progress, it provides new schedules and supplementary materials. The terminal displays the updated learning plan to the user.

[0635] For example, if a user finishes basic math problems earlier than planned, the server can notify them to move on to the next learning step, which is applied problems, and update their learning plan.

[0636] Efficient information access

[0637] The server collects relevant information from databases and the internet in response to information requests from users. It summarizes the information using a generative artificial intelligence model (e.g., GPT-4) and sends it to the terminal. The terminal displays the summarized information to the user.

[0638] For example, if a user searches for "an overview of the French Revolution," the server could collect relevant information, generate a summarized text, and provide it to the user's device.

[0639] The system of this invention allows users to learn efficiently and effectively, and to receive necessary information and support 24 hours a day.

[0640] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0641] Step 1:

[0642] sign up

[0643] User: Access the tutoring center's website or app and enter your name, email address, and password in the sign-up form.

[0644] Input: Name, email address, password

[0645] Terminal: Sends the entered information to the server.

[0646] Server: Stores the received information in the database, generates a registration completion message, and sends it back to the terminal.

[0647] Output: Registration complete message

[0648] Specific action: A primary school student registers for the system and a confirmation email is sent.

[0649] Step 2:

[0650] Log in

[0651] User: Enter your registered email address and password and submit the login form.

[0652] Input: Email address, password

[0653] Terminal: Sends the entered information to the server.

[0654] Server: Checks if the information matches the data stored in the database. If it matches, it grants login permission, generates a dashboard, and sends it to the device.

[0655] Output: Dashboard screen

[0656] Specific action: The user logs in and accesses their individual dashboard.

[0657] Step 3:

[0658] Input learning objectives and academic ability levels

[0659] User: Enter your learning goals and current academic level.

[0660] Input: Learning objectives, academic level

[0661] Terminal: Sends the entered information to the server.

[0662] Server: Based on the received information, it executes a pre-configured algorithm to generate a learning plan and saves it to the database.

[0663] Output: Study plan

[0664] Specific operation: The user inputs a goal such as "improve math skills" and their "current grades," and the server generates a study plan and displays it on the device.

[0665] Step 4:

[0666] Question input and answer generation

[0667] User: Enter your questions if you have any during your studies.

[0668] Input: Question content

[0669] Terminal: Sends the entered question to the server.

[0670] Server: Uses generative artificial intelligence to analyze questions, generate answers, and send them to the terminal.

[0671] Output: Answer to the question

[0672] Specific operation: The user enters "I don't know how to solve quadratic equations," and the server provides a detailed explanation.

[0673] Step 5:

[0674] Selection of subjects and fields

[0675] User: Select the subjects and fields you wish to study.

[0676] Input: Subject, field

[0677] Terminal: Sends the selected information to the server.

[0678] Server: Searches the database for teaching materials suitable for the selected subject and field, and sends them to the terminal.

[0679] Output: Teaching materials

[0680] Specific operation: The user selects the "Biology" field under "Science," and the server provides the corresponding educational materials.

[0681] Step 6:

[0682] Recording and updating learning progress

[0683] User: Record what you have completed learning.

[0684] Input: Completed learning content

[0685] Terminal: Sends recorded information to the server.

[0686] Server: Updates user learning progress in the database and automatically adjusts the learning plan as needed.

[0687] Output: Updated learning plan

[0688] Specific action: The user completes basic math problems ahead of schedule and receives a new plan.

[0689] Step 7:

[0690] Information Request and Summary

[0691] User: Enter the information you want to search for.

[0692] Input: Information Request

[0693] Terminal: Sends the entered information to the server.

[0694] Server: Collects relevant information from databases and the internet, summarizes it using generative artificial intelligence, and sends it to the terminal.

[0695] Output: Summarized information

[0696] Specific operation: The user searches for "an overview of the French Revolution," and the server summarizes and provides the information.

[0697] In this way, a system is built that enables effective learning support through the coordinated operation of users, terminals, and servers.

[0698] (Application Example 1)

[0699] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0700] Conventional factory robot maintenance systems face challenges in efficient maintenance because they do not adequately generate individual plans or track progress based on each worker's skill level and maintenance objectives. Furthermore, there is a need for a support system that can quickly address problems and questions that workers encounter during maintenance.

[0701] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0702] In this invention, the server includes means for receiving user input of maintenance goals and skill levels and generating individual maintenance plans; means for receiving user questions and generating answers to those questions using generative artificial intelligence; means for providing multidisciplinary learning materials based on user selection; means for tracking user progress and automatically adjusting the plan as needed; and means for collecting relevant information from databases and the internet in response to user information requests and summarizing it using generative artificial intelligence. This enables the provision of efficient and personalized maintenance plans, immediate question support, and the provision of diverse learning materials.

[0703] "Maintenance targets" are specific objectives and standards that should be achieved when maintaining or repairing factory robots.

[0704] "Skill level" is an indicator that shows the degree of maintenance knowledge and skills possessed by a worker.

[0705] An "individualized maintenance plan" is a plan that includes a customized maintenance schedule and procedures based on each worker's skill level and maintenance goals.

[0706] "Generative artificial intelligence" is an artificial intelligence technology that automatically generates answers and solutions based on input data and information.

[0707] "Multidisciplinary teaching materials" refers to learning materials, tool manuals, video materials, and other resources related to various fields of robot maintenance.

[0708] "Progress tracking" refers to the act of recording the progress of maintenance work performed by workers and saving it in a database.

[0709] A "database" is a collection of digital information designed to efficiently organize, store, and retrieve information.

[0710] The "Internet" is a communication network for sharing information through computer network systems worldwide.

[0711] An "information request" is a request to search for and provide the information that a user needs.

[0712] "Summarization" is the act of compiling collected detailed information into a concise and easy-to-understand format.

[0713] This invention is a system for streamlining maintenance work on factory robots and provides the following main functions.

[0714] 1. User signup and login

[0715] Server: Provides sign-up and login functionality to allow workers to access the system. During new registration, workers enter information such as their name, email address, and password, which the server stores in a database. During login, the server uses the information in the database to authenticate the worker.

[0716] Specific example: A new worker creates an account, logs in, and accesses the maintenance guide.

[0717] 2. Creating a maintenance plan

[0718] Server: Receives information on worker maintenance goals and skill levels, and generates individual maintenance plans based on this information. The server executes a pre-configured algorithm to generate the optimal maintenance schedule and procedures, and stores them in the database.

[0719] Specific example: When a worker with entry-level skills enters the objective "hydraulic system maintenance," the server generates a weekly maintenance schedule based on the worker's skill level and displays it on the terminal.

[0720] 3. 24-hour support for questions

[0721] User: If you have any questions during maintenance, please enter them here.

[0722] Terminal: Sends the question content to the server.

[0723] Server: Uses generative artificial intelligence to analyze questions and generate answers. The generated answers are sent to the terminal and displayed to the user.

[0724] Specific example: When a novice worker asks, "What should I do if the robot's movements become slow?", the server provides detailed instructions and returns the answer to the worker immediately.

[0725] 4. Provision of educational materials covering multiple fields.

[0726] Server: Provides training materials for the maintenance area selected by the worker. The server searches the database for appropriate training materials and sends them to the terminal.

[0727] Specific example: When a worker selects the "Electrical System Maintenance" field, the server sends video and text materials related to that field to the worker's terminal for display.

[0728] 5. Tracking maintenance progress and coordinating plans.

[0729] Server: Tracks the maintenance progress of workers in a database and automatically adjusts the maintenance plan as needed. Provides new schedules and supplementary materials based on the maintenance tasks and progress completed by workers.

[0730] Specific example: If a worker completes a particular maintenance task ahead of schedule, the server will suggest the next maintenance step and update the plan.

[0731] 6. Efficient Information Access

[0732] Server: In response to information requests from workers, it collects relevant information from databases and the internet. It uses generative artificial intelligence to summarize the information and present it to workers in an easy-to-understand manner.

[0733] Specific example: If a worker is researching "the latest maintenance techniques," the server collects the relevant information and provides the worker with a summarized text.

[0734] In this way, by having the user (worker), terminal, and server work together, the worker can carry out robot maintenance efficiently and effectively, and can receive necessary information and support 24 hours a day. The system of the present invention realizes flexible maintenance support that meets the individual needs of the worker.

[0735] Example of a prompt:

[0736] "New worker sign-up: Please enter your name, email address, and password."

[0737] "Please refer to the hydraulic system maintenance plan."

[0738] "What should I do if the robot's movements become slow?"

[0739] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0740] Step 1:

[0741] The user accesses the system and enters information on the sign-up or login screen. The required fields are name, email address, and password.

[0742] Input: Name, email address, password

[0743] Output: Data to send to the server

[0744] Specific action: The user enters the required information into the UI form and presses the "Submit" button.

[0745] Step 2:

[0746] The server saves the received input data to the database. For new registrations, it creates new user information; for logins, it performs authentication.

[0747] Input: Sign-up or login information

[0748] Output: Registration complete or authentication result

[0749] Specific operation: The server executes an SQL query to save or retrieve user information from the database.

[0750] Step 3:

[0751] After the user logs in, they enter the maintenance objectives and skill level on the maintenance plan creation screen.

[0752] Input: Maintenance objectives, skill level

[0753] Output: Plan creation request to the server

[0754] Specific operation: The user enters the goal and level into the UI form and presses the "Generate Plan" button.

[0755] Step 4:

[0756] The server executes an algorithm based on the received maintenance objectives and skill levels to generate individual maintenance plans.

[0757] Input: Maintenance objectives, skill level

[0758] Output: Maintenance plan

[0759] Specific operation: The server executes the plan generation algorithm and saves the generated plan to the database.

[0760] Step 5:

[0761] Users can enter questions if they have any while viewing the maintenance plan and performing each step.

[0762] Input: Question content

[0763] Output: Question request to the server

[0764] Specific action: The user enters a question into the UI form and presses the "Submit" button.

[0765] Step 6:

[0766] The server analyzes the received question and generates an answer using generative artificial intelligence (e.g., an OpenAI model).

[0767] Input: Question content

[0768] Output: Answer text

[0769] Specific operation: The server inputs a question as a prompt to the generative artificial intelligence, and returns the obtained answer to the user.

[0770] Step 7:

[0771] When a user requests educational materials corresponding to their selected maintenance area, they send a request to the server.

[0772] Input: Selection of maintenance field

[0773] Output: Request for educational materials to the server

[0774] Specific action: The user selects a field in the UI and presses the "Get Course Materials" button.

[0775] Step 8:

[0776] The server searches the database for relevant educational materials and sends them to the user.

[0777] Input: Selection of maintenance field

[0778] Output: Educational material data

[0779] Specific operation: The server searches the database for appropriate learning materials and sends them to the user's terminal.

[0780] Step 9:

[0781] Track user maintenance progress and save progress information to a database.

[0782] Input: Maintenance progress information

[0783] Output: Updated progress

[0784] Specific operation: The user enters the maintenance progress, which is then saved to the server.

[0785] Step 10:

[0786] If necessary, the server will adjust its maintenance schedule and provide new steps or supplementary materials.

[0787] Input: Updated progress

[0788] Output: Adjusted maintenance plans and supplementary materials

[0789] Specific operation: The server re-evaluates the plan based on progress information and makes adjustments as needed.

[0790] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0791] The learning center system of the present invention provides the following main functions to effectively support the user's learning. Furthermore, this system incorporates an emotion engine that recognizes the user's emotions and adjusts the learning plan accordingly.

[0792] 1. User signup and login

[0793] Server: Provides signup and login functionality to authenticate users accessing the tutoring school's website or app. During new user registration, users enter information such as their name, email address, and password, which the server stores in a database. During login, the server uses the information in the database to authenticate the user.

[0794] Specific example: A primary school student registers for the system, then logs in and accesses the dashboard.

[0795] 2. Creating a study plan

[0796] Server: Receives information about the user's learning goals and academic level, and generates an individualized learning plan based on this information. The server executes a pre-configured algorithm to generate the optimal learning schedule and materials, and stores them in a database.

[0797] Specific example: When a middle school student user enters the goal "improve math skills," the server generates a weekly study schedule based on the user's academic level and displays it on the device.

[0798] 3. 24-hour support for questions

[0799] User: If you have any questions while learning, enter them here.

[0800] Terminal: Sends the question content to the server.

[0801] Server: Uses generative artificial intelligence to analyze questions and generate answers. The generated answers are sent to the terminal and displayed to the user.

[0802] Specific example: If a middle school student user asks, "I don't know how to solve quadratic equations," the server provides a detailed explanation and immediately returns the answer to the user.

[0803] 4. Provision of teaching materials covering multiple subjects

[0804] Server: Provides corresponding learning materials for the subject selected by the user. The server searches the database for appropriate materials and sends them to the terminal.

[0805] Specific example: When a user selects the "Biology" field under "Science," the server sends video materials and text documents related to biology to the user's device and displays them.

[0806] 5. Tracking learning progress and adjusting plans

[0807] Server: Tracks user learning progress in a database and automatically adjusts the learning plan as needed. Provides new schedules and supplementary materials based on the user's completed learning content and progress.

[0808] Specific example: If a user finishes basic math problems earlier than planned, the server notifies the user to move on to the next learning step, which is applied problems, and updates the learning plan.

[0809] 6. Efficient Information Access

[0810] Server: In response to information requests from users, it collects relevant information from databases and the internet. It uses generative artificial intelligence to summarize the information and present it to the user in an easy-to-understand manner.

[0811] Specific example: If a user searches for "an overview of the French Revolution," the server collects relevant information and provides the user with a summarized text.

[0812] 7. Emotion recognition and learning plan adjustment using an emotion engine.

[0813] Server: During user training, the emotion engine recognizes the user's emotions. The emotion engine collects user emotion data using facial recognition and speech analysis.

[0814] Specific example: If a user is experiencing stress while learning, the emotion engine recognizes this, and the server recommends games or short breaks to help the user relax.

[0815] Server: Emotional data is stored in a database and periodically analyzed along with the user's learning history. This allows for the implementation of measures to improve long-term learning efficiency.

[0816] Specific example: If, based on user sentiment data, it is determined that learning efficiency is low during a particular time period, the server adjusts the plan to teach lighter subjects during that time.

[0817] Thus, the system of the present invention, through the cooperation of the user, terminal, and server, realizes flexible learning support tailored to individual needs and supports efficient and effective learning by providing appropriate responses in accordance with the user's emotions.

[0818] The following describes the processing flow.

[0819] Step 1: Sign up and log in

[0820] User: Access the tutoring school's website or app and click the "Register" button.

[0821] Terminal: Displays a registration form and prompts the user to enter their name, email address, password, etc.

[0822] Server: Receives the entered information and saves it to the database. Generates a registration completion message and notifies the terminal.

[0823] Terminal: Displays a registration completion message to the user.

[0824] User: Enter your email address and password, then click the "Login" button.

[0825] Terminal: Sends input information to the server.

[0826] Server: Authenticates the user in the database to verify their legitimacy. Generates a login success message and notifies the terminal.

[0827] Terminal: Displays a message to the user and redirects them to the dashboard.

[0828] Step 2: Create a study plan

[0829] User: After logging in, fill out a questionnaire about your learning goals and current academic level.

[0830] Terminal: Sends the entered information to the server.

[0831] Server: Based on the received information, it executes a learning algorithm and generates the optimal learning plan.

[0832] Server: Saves the generated training plan to the database. Sends the plan details to the terminal.

[0833] Terminal: Displays the learning plan generated for the user.

[0834] Step 3: 24-hour support available for questions

[0835] User: If you have any questions while learning, click the "Ask a Question" button and enter your question.

[0836] Terminal: Sends the entered question to the server.

[0837] Server: Uses generative artificial intelligence to analyze the question and generate an answer. Sends the generated answer to the terminal.

[0838] Terminal: Displays the answer to the user.

[0839] Step 4: Providing multi-subject learning materials

[0840] User: Select the subjects to study (for example, select "Science" and "Biology").

[0841] Terminal: Sends the selection to the server.

[0842] Server: Searches the database for corresponding learning materials (textbooks, videos, workbooks, etc.) and sends them to the user.

[0843] Terminal: Displays the learning materials received by the user.

[0844] Step 5: Tracking learning progress and adjusting plans

[0845] User: Open the learning progress screen and check the progress status.

[0846] Terminal: Sends progress data to the server.

[0847] Server: Based on the latest progress data, it determines whether the learning plan is progressing smoothly and adjusts the plan if necessary.

[0848] Server: Sends the updated learning plan to the device.

[0849] Terminal: Displays the updated plan to the user.

[0850] Step 6: Efficient Information Access

[0851] User: Enter the required information or documents into the search bar and click the "Search" button.

[0852] Terminal: Sends a search request to the server.

[0853] Server: Collects relevant information from databases and the internet, and summarizes it using generative artificial intelligence.

[0854] Server: Sends organized information to the terminal.

[0855] Terminal: Displays information to the user.

[0856] Step 7: Emotion recognition by the emotion engine

[0857] User: Generates emotional data through facial expressions and voice during learning.

[0858] Terminal: Transfers the user's facial expressions and voice to the emotion engine.

[0859] Server: The emotion engine recognizes the user's emotions and analyzes that data.

[0860] Step 8: Adjusting your learning plan based on your emotions

[0861] Server: Adjusts the user's learning plan based on the emotion data recognized by the emotion engine.

[0862] Server: Stores the coordinated plan in the database and analyzes it along with user progress data.

[0863] Device: Displays feedback from the emotion engine and suggests appropriate learning methods and breaks to the user.

[0864] Step 9: Long-term analysis of emotional data

[0865] Server: Regularly collects emotional data and stores it in a database.

[0866] Server: Analyzes user learning history and sentiment data to propose measures for improving long-term learning efficiency.

[0867] Terminal: Based on the analysis results, it suggests a learning plan, break times, and learning materials that are suitable for the user.

[0868] By executing each step in detail in this way, users can learn efficiently and effectively. In particular, the introduction of an emotion engine enables flexible learning support that responds to the user's emotions.

[0869] (Example 2)

[0870] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0871] Traditional learning support systems have limitations in providing appropriate learning plans tailored to individual users' learning goals and academic levels, and in particular, they lack individualized support that takes into account the user's emotional state. This has led to challenges such as users being unable to maximize their learning effectiveness due to stress and decreased motivation. Furthermore, in traditional systems, tracking learning progress and adjusting plans often required manual intervention, resulting in inefficient support.

[0872] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0873] In this invention, the server includes means for receiving input of learning goals and academic ability levels from the user and generating an individualized learning plan; means for receiving questions from the user and generating answers to those questions using generative artificial intelligence; means for providing learning materials for multiple subjects based on the user's selection; means for tracking the user's learning progress and automatically adjusting the learning plan as needed; means for collecting relevant information from databases and the internet in response to the user's information requests and summarizing it using generative artificial intelligence; and means for recognizing the user's emotions and adjusting the learning plan accordingly. This enables flexible learning support based on the learning needs of each individual user.

[0874] A "learning objective" is the specific learning goal that the user wants to achieve.

[0875] "Academic ability level" is an indicator that shows the user's current level of academic ability and knowledge.

[0876] A "learning plan" is a combination of a schedule and learning materials created based on the user's learning goals and academic level, designed to facilitate effective learning.

[0877] "Generative artificial intelligence" is an artificial intelligence technology that generates responses to user questions and requests.

[0878] "Multi-subject learning materials" refer to learning materials that cover multiple subjects, and are provided according to the subjects selected by the user.

[0879] "Learning progress" is an indicator that shows how far a user has progressed in their learning.

[0880] An "information request" is a request that a user sends to seek specific information or knowledge.

[0881] A "database" is a digital storage system used to manage and organize information and materials necessary for learning.

[0882] An "emotion engine" is a system that recognizes the user's emotional state and adjusts the learning plan based on that state.

[0883] The learning center system of the present invention provides the following main functions to effectively support the user's learning. This system is established through the interaction of a server, terminals, and users. Specific embodiments of the system based on the claims are shown below.

[0884] 1. User signup and login

[0885] The server provides sign-up and login functionality to authenticate users accessing the tutoring school's website or app. During new user registration, users enter information such as their name, email address, and password, which the server stores in a database. During login, the server authenticates the user based on the information in the database.

[0886] Specific example: A primary school student registers for the system, then logs in and accesses the dashboard.

[0887] 2. Creating a study plan

[0888] The server receives information about the user's learning goals and academic level, and generates an individualized learning plan. The server executes a pre-configured algorithm to generate the optimal learning schedule and materials, and stores them in a database.

[0889] Specific example: If a middle school student user enters "improve math skills" as their goal, the server generates a weekly study schedule based on the user's academic level and displays it on their device.

[0890] 3. Answering questions

[0891] If a user encounters a question during the learning process, they input the question. The device sends the question to the server. The server uses generative artificial intelligence to analyze the question and generate an answer. This generated answer is then sent to the device and displayed to the user.

[0892] Specific example: When a middle school student asks, "I don't know how to solve quadratic equations," the server uses generative artificial intelligence to provide a detailed explanation and immediately returns the answer to the user.

[0893] 4. Providing teaching materials

[0894] The server provides the corresponding learning materials according to the subject selected by the user. The server searches the database for the appropriate materials and sends them to the terminal.

[0895] Specific example: When a user selects the "Biology" field under "Science," the server sends video materials and text documents related to biology to the user's device and displays them.

[0896] 5. Tracking learning progress and adjusting plans

[0897] The server tracks the user's learning progress in a database and automatically adjusts the learning plan as needed. Based on the user's completed learning content and progress, it provides new schedules and supplementary materials.

[0898] Specific example: If a user finishes basic math problems earlier than planned, the server notifies the user to move on to the next learning step, which is applied problems, and updates the learning plan.

[0899] 6. Access to Information

[0900] The server collects relevant information from databases and the internet in response to user information requests. It then uses generative artificial intelligence to summarize the information and present it to the user in an easily understandable format.

[0901] Specific example: If a user searches for "an overview of the French Revolution," the server collects relevant information and provides the user with a summarized text.

[0902] 7. Responses based on the emotion engine

[0903] The server uses an emotion engine to recognize the user's emotions. The emotion engine collects user emotion data using facial recognition and voice analysis, and adjusts the learning plan based on this data. The emotion data is stored in a database and periodically analyzed along with the user's learning history.

[0904] Specific examples: If a user is experiencing stress while learning, the emotion engine will recognize this, and the server will recommend games or short breaks to help the user relax. If learning efficiency is low during certain times, the plan will be adjusted to include lighter subjects during those times.

[0905] This allows the tutoring system to provide flexible learning support tailored to the individual needs of users, enabling efficient and effective learning.

[0906] Example of a prompt

[0907] "Please tell me about specific methods for detecting the stress that middle school students experience while studying and suggesting appropriate responses."

[0908] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0909] Program processing steps

[0910] Step 1: User Signup

[0911] 1. Input: The user accesses the tutoring center's website or app and enters their name, email address, and password.

[0912] 2. Specific operation: The terminal sends the entered information to the server.

[0913] 3. Data processing: The server receives the information and stores it in the database.

[0914] 4. Output: The server sends a registration completion message to the terminal.

[0915] 5. Specific action: The device displays "Registration complete."

[0916] Step 2: User Login

[0917] 1. Input: The user enters their email address and password on the website or app's login screen.

[0918] 2. Specific operation: The terminal sends the entered information to the server.

[0919] 3. Data processing: The server accesses the database and verifies that the user information matches the input information.

[0920] 4. Output: The server sends a login success signal to the terminal.

[0921] 5. Specific action: The device displays the user's dashboard.

[0922] Step 3: Create a study plan

[0923] 1. Input: The user enters their learning goals and current academic level.

[0924] 2. Specific actions: The terminal sends this information to the server.

[0925] 3. Data processing: The server uses algorithms to generate individual learning plans and stores them in the database.

[0926] 4. Output: The server sends the generated training plan to the terminal.

[0927] 5. Specific actions: The device displays the learning plan to the user.

[0928] Step 4: Answering Questions

[0929] 1. Input: The user enters a question.

[0930] 2. Specific action: The terminal sends the question to the server.

[0931] 3. Data processing: The server uses a generative AI model to analyze the question and generate an answer.

[0932] 4. Output: The server sends the generated response to the terminal.

[0933] 5. Specific action: The device displays the answer to the user.

[0934] Step 5: Provide teaching materials

[0935] 1. Input: The user selects the subject or field they wish to study.

[0936] 2. Specific action: The terminal sends that information to the server.

[0937] 3. Data processing: The server searches the database for appropriate teaching materials.

[0938] 4. Output: The server sends the selected learning materials to the terminal.

[0939] 5. Specific operation: The device displays the learning materials to the user.

[0940] Step 6: Tracking learning progress and adjusting plans

[0941] 1. Input: The user enters learning progress information.

[0942] 2. Specific action: The terminal sends that information to the server.

[0943] 3. Data processing: The server analyzes the learning progress data and updates the learning plan as needed.

[0944] 4. Output: The server sends the updated learning plan to the terminal.

[0945] 5. Specific action: The device displays a new learning plan to the user.

[0946] Step 7: Responding with an emotional engine

[0947] 1. Input: The emotion engine captures the user's facial expressions and voice data during the learning process.

[0948] 2. Specific action: The terminal sends this data to the server.

[0949] 3. Data processing: The server uses an emotion engine to analyze the user's emotions and determine if the learning plan needs to be adjusted.

[0950] 4. Output: The server sends the adjusted learning plan results, based on the user's emotions, to the terminal.

[0951] 5. Specific actions: The device displays a learning plan and relaxation menu tailored to the user.

[0952] In this way, the tutoring system, through the coordination of users, terminals, and servers, provides flexible learning support tailored to individual needs and enables efficient and effective learning by responding appropriately to the user's emotions.

[0953] (Application Example 2)

[0954] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0955] Traditional learning systems have a problem of reduced learning effectiveness because they provide a uniform learning plan without considering the learner's emotional state. Furthermore, the lack of flexible adjustments in response to emotional changes leads to increased learning stress. In addition, since emotional states affect work efficiency among factory workers, there is a need for efficient work support utilizing emotional data.

[0956] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0957] In this invention, the server includes means for receiving input of learning goals and academic ability levels from the user and generating individual learning plans; means for receiving questions from the user and generating answers to those questions using generative artificial intelligence; means for providing learning materials for multiple subjects based on the user's selection; means for tracking the user's learning progress and automatically adjusting the learning plan as needed; means for collecting relevant information from databases and the internet in response to the user's information requests and summarizing it using generative artificial intelligence; means for collecting emotional data from the user's facial expressions and voice and determining their emotional state using an emotion recognition model; and means for flexibly adjusting the learning plan based on the determined emotional state. This enables individualized responses that are tailored to the emotions of learners and workers.

[0958] A "user" refers to a learner or factory worker who uses the system.

[0959] "Learning objectives" are specific learning goals that the user wants to achieve.

[0960] "Academic ability level" refers to the user's current level of understanding and knowledge regarding learning.

[0961] An "individualized learning plan" refers to a user-specific learning schedule and content created based on the user's learning goals and academic level.

[0962] "Generative artificial intelligence" refers to artificial intelligence technology that generates answers to questions, summaries of information, and other data based on large amounts of data.

[0963] "Multi-subject learning materials" refer to learning materials that cover multiple subjects, including videos, textbooks, and workbooks.

[0964] "Learning progress" refers to the user's learning progress and indicates how far they have progressed in their learning.

[0965] A "database" is a digital repository for information, where various types of data such as user information, learning content, and questions and answers are stored.

[0966] The "Internet" is a vast source of information available online, and a means of searching for answers to users' information requests.

[0967] To "summarize" means to put detailed information into a concise and easy-to-understand format.

[0968] "Emotional data" refers to digital information about a user's emotional state, obtained from their facial expressions and voice.

[0969] An "emotion recognition model" is a machine learning or deep learning model that performs facial recognition and voice analysis to determine a user's emotions.

[0970] "Emotional state" refers to the psychological state a user experiences while learning or working, and includes stress, joy, sadness, and other similar emotions.

[0971] "Flexibly adjusting the learning plan" means changing the content and order of learning and tasks to reflect the user's current emotional state.

[0972] The system of the present invention provides multiple functions to effectively support user learning. This system includes an emotion engine that recognizes the user's emotional state and adjusts the learning plan accordingly.

[0973] 1. User signup and login

[0974] The server provides signup and login functionality to authenticate users accessing the tutoring school's website or mobile app. Users enter information such as their name, email address, and password during registration, which is stored in the database. During login, the server authenticates the user using the information in the database.

[0975] 2. Creating a study plan

[0976] The server receives information about the user's learning goals and academic level, and generates an individualized learning plan based on this information. It generates the optimal learning schedule and materials based on an algorithm and stores them in a database.

[0977] 3. 24-hour support for questions

[0978] If a user has questions during the learning process, they can input them using their device. The device sends the question to the server, which uses generative artificial intelligence to analyze the question and generate an answer. The generated answer is then sent back to the device and displayed to the user.

[0979] 4. Provision of teaching materials covering multiple subjects

[0980] The server provides learning materials corresponding to the subject selected by the user. It searches the database for appropriate materials, sends them to the terminal, and displays them to the user.

[0981] 5. Tracking learning progress and adjusting plans

[0982] The server tracks the user's learning progress in a database and automatically adjusts the learning plan as needed. Based on the user's completed learning content and progress, it provides new schedules and supplementary materials.

[0983] 6. Efficient Information Access

[0984] The server collects relevant information from databases and the internet in response to user information requests, and summarizes the information using generative artificial intelligence. It then presents the information to the user in an easy-to-understand manner.

[0985] 7. Emotion recognition and learning plan adjustment using an emotion engine.

[0986] The server uses an emotion engine to recognize the user's emotional state during training. The emotion engine collects user emotional data using facial recognition and speech analysis, and uses an emotion recognition model to determine the emotional state. Based on the results, it flexibly adjusts the training plan.

[0987] Hardware and software used

[0988] The emotion recognition feature, which is part of this system, uses the following hardware and software.

[0989] Hardware: Smart glasses or cameras (e.g., Google Glass)

[0990] Software: Emotion recognition model (using Keras), OpenCV for face recognition

[0991] Specific example

[0992] For example, suppose a factory worker is wearing smart glasses while working. If the server can determine the worker's current stress level from their facial expressions, it will recognize this and automatically adjust the worker's work plan. For instance, if the worker is in a high-stress state requiring immediate attention, the server might reduce the workload or recommend a short break.

[0993] Example of a prompt

[0994] Design a smart work assistant application that analyzes employees' facial expressions and emotions in real time and adjusts work plans accordingly. Specifically, it uses a camera built into smart glasses to recognize the employee's face, determines their emotions using an emotion recognition model, and adjusts their work based on that emotion data. For example, if an employee is feeling stressed, the system should recommend relaxing tasks or breaks.

[0995] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0996] Step 1:

[0997] The device uses its camera to capture the user's face. The image data is acquired and converted to grayscale as a preprocessing step. This prepares the data necessary for face recognition.

[0998] Input: User's face image

[0999] Output: Grayscale facial image data

[1000] Specific operation: The smart glasses' camera captures a facial image in real time, and OpenCV is used to convert the image to grayscale.

[1001] Step 2:

[1002] The device performs facial recognition and identifies the facial region. The image of the facial region is resized to a standard size and converted to the format required by the model.

[1003] Input: Grayscale facial image data

[1004] Output: Resized face region image data

[1005] Specific operation: Use a face recognition algorithm (e.g., Haar Cascade) to obtain the coordinates of the face, and resize the face area to a standard size (e.g., 48x48 pixels).

[1006] Step 3:

[1007] The device inputs facial image data into an emotion recognition model, which then determines the emotion. The model outputs an emotion label and its corresponding probability.

[1008] Input: Resized facial region image data

[1009] Output: Sentiment labels and probabilities

[1010] Specific operation: Resized image data is input into an emotion recognition model using Keras, and the emotion determination result is obtained. For example, an output such as "Happy: 0.85, Sad: 0.10" may be obtained.

[1011] Step 4:

[1012] The device sends the assessment result to the server. The server adjusts the learning plan based on the emotional state.

[1013] Input: Emotion labels and probabilities

[1014] Output: Instructions for adjusting the learning plan

[1015] Specific operation: The emotion recognition results are sent to the server, which executes an algorithm to generate a learning or work plan appropriate to the emotional state. For example, if a stressed state is detected, a recommendation for a break or assignment of light work may be made.

[1016] Step 5:

[1017] The server sends the adjusted learning plan to the terminal. The terminal displays the new learning or work plan to the user.

[1018] Input: Learning plan with adjustment instructions

[1019] Output: New learning plan displayed on the terminal

[1020] Specific operation: The server sends a newly generated learning plan to the terminal, which then displays it on the user's screen. For example, a message such as "You have 10 minutes until your next break" might be displayed.

[1021] 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.

[1022] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1023] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[1024] [Third Embodiment]

[1025] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[1026] 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.

[1027] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1028] 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.

[1029] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1030] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1031] 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.

[1032] 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.

[1033] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1034] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1035] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1036] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[1037] The learning center system of the present invention provides the following main functions to effectively support the user's learning.

[1038] 1. User signup and login

[1039] Server: Provides signup and login functionality to authenticate users accessing the tutoring school's website or app. During new user registration, users enter information such as their name, email address, and password, which the server stores in a database. During login, the server uses the information in the database to authenticate the user.

[1040] Specific example: A primary school student registers for the system, then logs in and accesses the dashboard.

[1041] 2. Creating a study plan

[1042] Server: Receives information about the user's learning goals and academic level, and generates an individualized learning plan based on this information. The server executes a pre-configured algorithm to generate the optimal learning schedule and materials, and stores them in a database.

[1043] Specific example: When a middle school student user enters the goal "improve math skills," the server generates a weekly study schedule based on the user's academic level and displays it on the device.

[1044] 3. 24-hour support for questions

[1045] User: If you have any questions while learning, enter them here.

[1046] Terminal: Sends the question content to the server.

[1047] Server: Uses generative artificial intelligence to analyze questions and generate answers. The generated answers are sent to the terminal and displayed to the user.

[1048] Specific example: If a middle school student user asks, "I don't know how to solve quadratic equations," the server provides a detailed explanation and immediately returns the answer to the user.

[1049] 4. Provision of teaching materials covering multiple subjects

[1050] Server: Provides corresponding learning materials for the subject selected by the user. The server searches the database for appropriate materials and sends them to the terminal.

[1051] Specific example: When a user selects the "Biology" field under "Science," the server sends video materials and text documents related to biology to the user's device and displays them.

[1052] 5. Tracking learning progress and adjusting plans

[1053] Server: Tracks user learning progress in a database and automatically adjusts the learning plan as needed. Provides new schedules and supplementary materials based on the user's completed learning content and progress.

[1054] Specific example: If a user finishes basic math problems earlier than planned, the server notifies the user to move on to the next learning step, which is applied problems, and updates the learning plan.

[1055] 6. Efficient Information Access

[1056] Server: In response to information requests from users, it collects relevant information from databases and the internet. It uses generative artificial intelligence to summarize the information and present it to the user in an easy-to-understand manner.

[1057] Specific example: If a user searches for "an overview of the French Revolution," the server collects relevant information and provides the user with a summarized text.

[1058] In this way, the user, terminal, and server work together, enabling the user to learn efficiently and effectively, and to receive necessary information and support 24 hours a day. The system of the present invention realizes flexible learning support that meets the individual needs of the user.

[1059] The following describes the processing flow.

[1060] Step 1: Sign up and log in

[1061] User: Access the tutoring school's website or app and click the "Register" button.

[1062] Terminal: Displays a registration form and prompts the user to enter their name, email address, password, etc.

[1063] Server: Receives the entered information and saves it to the database. Generates a registration completion message and notifies the terminal.

[1064] Terminal: Displays a registration completion message to the user.

[1065] User: Enter your email address and password, then click the "Login" button.

[1066] Terminal: Sends input information to the server.

[1067] Server: Authenticates the user in the database to verify their legitimacy. Generates a login success message and notifies the terminal.

[1068] Terminal: Displays a message to the user and redirects them to the dashboard.

[1069] Step 2: Create a study plan

[1070] User: After logging in, fill out a questionnaire about your learning goals and current academic level.

[1071] Terminal: Sends the entered information to the server.

[1072] Server: Based on the received information, it executes a learning algorithm and generates the optimal learning plan.

[1073] Server: Saves the generated training plan to the database. Sends the plan details to the terminal.

[1074] Terminal: Displays the learning plan generated for the user.

[1075] Step 3: 24-hour support available for questions

[1076] User: If you have any questions while learning, click the "Ask a Question" button and enter your question.

[1077] Terminal: Sends the entered question to the server.

[1078] Server: Uses generative artificial intelligence to analyze the question and generate an answer. Sends the generated answer to the terminal.

[1079] Terminal: Displays the answer to the user.

[1080] Step 4: Providing multi-subject learning materials

[1081] User: Select the subjects to study (for example, select "Science" and "Biology").

[1082] Terminal: Sends the selection to the server.

[1083] Server: Searches the database for corresponding learning materials (textbooks, videos, workbooks, etc.) and sends them to the user.

[1084] Terminal: Displays the learning materials received by the user.

[1085] Step 5: Tracking learning progress and adjusting plans

[1086] User: Open the learning progress screen and check the progress status.

[1087] Terminal: Sends progress data to the server.

[1088] Server: Based on the latest progress data, it determines whether the learning plan is progressing smoothly and adjusts the plan if necessary.

[1089] Server: Sends the updated learning plan to the device.

[1090] Terminal: Displays the updated plan to the user.

[1091] Step 6: Efficient Information Access

[1092] User: Enter the required information or documents into the search bar and click the "Search" button.

[1093] Terminal: Sends a search request to the server.

[1094] Server: Collects relevant information from databases and the internet, and summarizes it using generative artificial intelligence.

[1095] Server: Sends organized information to the terminal.

[1096] Terminal: Displays information to the user.

[1097] By executing each step in detail in this way, users can learn efficiently and effectively.

[1098] (Example 1)

[1099] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1100] In recent years, there has been a growing demand for individualized instruction and learning support. However, traditional cram schools and online education services have struggled to provide efficient and effective learning support tailored to the individual needs of users. Specifically, the lack of a system that integrates the generation of individualized learning plans based on each user's academic level and learning goals, 24 / 7 question answering, provision of learning materials covering multiple subjects, automatic tracking of learning progress and plan adjustments, and efficient information access has been a major problem.

[1101] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1102] In this invention, the server includes means for receiving input of learning goals and academic ability levels from the user and generating an individualized learning plan; means for receiving questions from the user and generating answers to those questions using generative artificial intelligence; means for providing learning materials for multiple subjects based on the user's selection; means for tracking the user's learning progress and automatically adjusting the learning plan as needed; means for collecting relevant information from a database and the internet in response to the user's information requests and summarizing it using generative artificial intelligence; means for recording the learning content completed by the user and updating the learning plan according to the learning progress; and means for analyzing the user's information requests and summarizing the relevant information using a generative artificial intelligence model. This enables effective learning support that is tailored to the individual needs of the user.

[1103] "Learning objectives" are specific learning goals or objectives that the user wants to achieve.

[1104] "Academic ability level" is an indicator that shows the user's current academic ability and the degree to which they have acquired knowledge.

[1105] A "learning plan" is a schedule set up to guide the user to the optimal learning progress, based on their academic level and learning goals.

[1106] "Generative artificial intelligence" is an artificial intelligence technology that uses natural language processing to generate appropriate answers and information in response to input questions and requests.

[1107] "Educational materials" refer to educational resources and materials used for user learning.

[1108] "Learning progress" refers to the extent to which a user has progressed according to their learning plan.

[1109] An "information request" is a request made by a user to a system in order to obtain specific information or knowledge.

[1110] A "database" is a collection of data used to efficiently manage and operate user information, learning materials, and learning progress.

[1111] The "Internet" is a communication network that connects computer networks around the world, enabling the exchange and acquisition of information.

[1112] "Means" refer to the methods, devices, or parts of a system used to achieve a particular objective.

[1113] The "individualized learning plan generation method" is a function that creates an optimal learning schedule based on the user's academic level and learning goals.

[1114] A "question and answer generation method" is a function that generates appropriate answers to user questions using generative artificial intelligence.

[1115] "Methods for providing learning materials" refers to the function of selecting and providing learning materials for users.

[1116] A "learning progress tracking mechanism" is a function that tracks the user's learning progress and adjusts the learning plan as needed.

[1117] An "information summarization tool" is a function that collects relevant information in response to a user's information request and summarizes it using generative artificial intelligence.

[1118] This invention relates to a tutoring system for effectively supporting user learning. This system consists of a server, terminals, and users, with each component working in coordination.

[1119] Sign up and log in

[1120] The server provides signup and login functionality for users accessing the tutoring school's website or app. Users enter information such as their name, email address, and password, and the device sends this information to the server. The server stores the received information in a database and sends a registration completion message to the user. During login, the server authenticates the user by referencing the information in the database and allows them to access the dashboard.

[1121] A concrete example would be a primary school student registering as a new user, logging in, and accessing the dashboard.

[1122] Creating a study plan

[1123] The server receives information about the user's learning goals and academic level, and generates an individualized learning plan based on this information. The server executes a pre-configured algorithm (for example, a Python script on the Django framework) to generate the optimal learning schedule and materials, and saves them to the database. The terminal then displays the generated learning plan to the user.

[1124] A concrete example would be a middle school student who enters a goal such as "improve math skills," and the server generates a weekly study schedule based on that information, which is then displayed on the user's device.

[1125] 24-hour support available for questions

[1126] If the user encounters any questions during the learning process, they input them. The device sends the question to the server. The server analyzes the question using generative artificial intelligence (e.g., GPT-4) and generates an answer. The generated answer is sent to the device and displayed to the user.

[1127] For example, if a middle school student user asks, "I don't know how to solve a quadratic equation," the server will provide a detailed explanation and return the answer to the user.

[1128] Example of a prompt

[1129] "I don't know how to solve quadratic equations. Could you please provide a detailed explanation?"

[1130] Providing teaching materials that cover multiple subjects

[1131] The server provides learning materials corresponding to the subject selected by the user. The server searches the database for appropriate materials and sends them to the terminal. The terminal displays the provided materials to the user.

[1132] As a concrete example, when a user selects the "Biology" field under "Science," the server sends video materials and text documents related to biology to the user's device for display.

[1133] Tracking learning progress and adjusting plans

[1134] The server tracks the user's learning progress in a database and automatically adjusts the learning plan as needed. Based on the user's completed learning content and progress, it provides new schedules and supplementary materials. The terminal displays the updated learning plan to the user.

[1135] For example, if a user finishes basic math problems earlier than planned, the server can notify them to move on to the next learning step, which is applied problems, and update their learning plan.

[1136] Efficient information access

[1137] The server collects relevant information from databases and the internet in response to information requests from users. It summarizes the information using a generative artificial intelligence model (e.g., GPT-4) and sends it to the terminal. The terminal displays the summarized information to the user.

[1138] For example, if a user searches for "an overview of the French Revolution," the server could collect relevant information, generate a summarized text, and provide it to the user's device.

[1139] The system of this invention allows users to learn efficiently and effectively, and to receive necessary information and support 24 hours a day.

[1140] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1141] Step 1:

[1142] sign up

[1143] User: Access the tutoring center's website or app and enter your name, email address, and password in the sign-up form.

[1144] Input: Name, email address, password

[1145] Terminal: Sends the entered information to the server.

[1146] Server: Stores the received information in the database, generates a registration completion message, and sends it back to the terminal.

[1147] Output: Registration complete message

[1148] Specific action: A primary school student registers for the system and a confirmation email is sent.

[1149] Step 2:

[1150] Log in

[1151] User: Enter your registered email address and password and submit the login form.

[1152] Input: Email address, password

[1153] Terminal: Sends the entered information to the server.

[1154] Server: Checks if the information matches the data stored in the database. If it matches, it grants login permission, generates a dashboard, and sends it to the device.

[1155] Output: Dashboard screen

[1156] Specific action: The user logs in and accesses their individual dashboard.

[1157] Step 3:

[1158] Input learning objectives and academic ability levels

[1159] User: Enter your learning goals and current academic level.

[1160] Input: Learning objectives, academic level

[1161] Terminal: Sends the entered information to the server.

[1162] Server: Based on the received information, it executes a pre-configured algorithm to generate a learning plan and saves it to the database.

[1163] Output: Study plan

[1164] Specific operation: The user inputs a goal such as "improve math skills" and their "current grades," and the server generates a study plan and displays it on the device.

[1165] Step 4:

[1166] Question input and answer generation

[1167] User: Enter your questions if you have any during your studies.

[1168] Input: Question content

[1169] Terminal: Sends the entered question to the server.

[1170] Server: Uses generative artificial intelligence to analyze questions, generate answers, and send them to the terminal.

[1171] Output: Answer to the question

[1172] Specific operation: The user enters "I don't know how to solve quadratic equations," and the server provides a detailed explanation.

[1173] Step 5:

[1174] Selection of subjects and fields

[1175] User: Select the subjects and fields you wish to study.

[1176] Input: Subject, field

[1177] Terminal: Sends the selected information to the server.

[1178] Server: Searches the database for teaching materials suitable for the selected subject and field, and sends them to the terminal.

[1179] Output: Teaching materials

[1180] Specific operation: The user selects the "Biology" field under "Science," and the server provides the corresponding educational materials.

[1181] Step 6:

[1182] Recording and updating learning progress

[1183] User: Record what you have completed learning.

[1184] Input: Completed learning content

[1185] Terminal: Sends recorded information to the server.

[1186] Server: Updates user learning progress in the database and automatically adjusts the learning plan as needed.

[1187] Output: Updated learning plan

[1188] Specific action: The user completes basic math problems ahead of schedule and receives a new plan.

[1189] Step 7:

[1190] Information Request and Summary

[1191] User: Enter the information you want to search for.

[1192] Input: Information Request

[1193] Terminal: Sends the entered information to the server.

[1194] Server: Collects relevant information from databases and the internet, summarizes it using generative artificial intelligence, and sends it to the terminal.

[1195] Output: Summarized information

[1196] Specific operation: The user searches for "an overview of the French Revolution," and the server summarizes and provides the information.

[1197] In this way, a system is built that enables effective learning support through the coordinated operation of users, terminals, and servers.

[1198] (Application Example 1)

[1199] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1200] Conventional factory robot maintenance systems face challenges in efficient maintenance because they do not adequately generate individual plans or track progress based on each worker's skill level and maintenance objectives. Furthermore, there is a need for a support system that can quickly address problems and questions that workers encounter during maintenance.

[1201] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1202] In this invention, the server includes means for receiving user input of maintenance goals and skill levels and generating individual maintenance plans; means for receiving user questions and generating answers to those questions using generative artificial intelligence; means for providing multidisciplinary learning materials based on user selection; means for tracking user progress and automatically adjusting the plan as needed; and means for collecting relevant information from databases and the internet in response to user information requests and summarizing it using generative artificial intelligence. This enables the provision of efficient and personalized maintenance plans, immediate question support, and the provision of diverse learning materials.

[1203] "Maintenance targets" are specific objectives and standards that should be achieved when maintaining or repairing factory robots.

[1204] "Skill level" is an indicator that shows the degree of maintenance knowledge and skills possessed by a worker.

[1205] An "individualized maintenance plan" is a plan that includes a customized maintenance schedule and procedures based on each worker's skill level and maintenance goals.

[1206] "Generative artificial intelligence" is an artificial intelligence technology that automatically generates answers and solutions based on input data and information.

[1207] "Multidisciplinary teaching materials" refers to learning materials, tool manuals, video materials, and other resources related to various fields of robot maintenance.

[1208] "Progress tracking" refers to the act of recording the progress of maintenance work performed by workers and saving it in a database.

[1209] A "database" is a collection of digital information designed to efficiently organize, store, and retrieve information.

[1210] The "Internet" is a communication network for sharing information through computer network systems worldwide.

[1211] An "information request" is a request to search for and provide the information that a user needs.

[1212] "Summarization" is the act of compiling collected detailed information into a concise and easy-to-understand format.

[1213] This invention is a system for streamlining maintenance work on factory robots and provides the following main functions.

[1214] 1. User signup and login

[1215] Server: Provides sign-up and login functionality to allow workers to access the system. During new registration, workers enter information such as their name, email address, and password, which the server stores in a database. During login, the server uses the information in the database to authenticate the worker.

[1216] Specific example: A new worker creates an account, logs in, and accesses the maintenance guide.

[1217] 2. Creating a maintenance plan

[1218] Server: Receives information on worker maintenance goals and skill levels, and generates individual maintenance plans based on this information. The server executes a pre-configured algorithm to generate the optimal maintenance schedule and procedures, and stores them in the database.

[1219] Specific example: When a worker with entry-level skills enters the objective "hydraulic system maintenance," the server generates a weekly maintenance schedule based on the worker's skill level and displays it on the terminal.

[1220] 3. 24-hour support for questions

[1221] User: If you have any questions during maintenance, please enter them here.

[1222] Terminal: Sends the question content to the server.

[1223] Server: Uses generative artificial intelligence to analyze questions and generate answers. The generated answers are sent to the terminal and displayed to the user.

[1224] Specific example: When a novice worker asks, "What should I do if the robot's movements become slow?", the server provides detailed instructions and returns the answer to the worker immediately.

[1225] 4. Provision of educational materials covering multiple fields.

[1226] Server: Provides training materials for the maintenance area selected by the worker. The server searches the database for appropriate training materials and sends them to the terminal.

[1227] Specific example: When a worker selects the "Electrical System Maintenance" field, the server sends video and text materials related to that field to the worker's terminal for display.

[1228] 5. Tracking maintenance progress and coordinating plans.

[1229] Server: Tracks the maintenance progress of workers in a database and automatically adjusts the maintenance plan as needed. Provides new schedules and supplementary materials based on the maintenance tasks and progress completed by workers.

[1230] Specific example: If a worker completes a particular maintenance task ahead of schedule, the server will suggest the next maintenance step and update the plan.

[1231] 6. Efficient Information Access

[1232] Server: In response to information requests from workers, it collects relevant information from databases and the internet. It uses generative artificial intelligence to summarize the information and present it to workers in an easy-to-understand manner.

[1233] Specific example: If a worker is researching "the latest maintenance techniques," the server collects the relevant information and provides the worker with a summarized text.

[1234] In this way, by having the user (worker), terminal, and server work together, the worker can carry out robot maintenance efficiently and effectively, and can receive necessary information and support 24 hours a day. The system of the present invention realizes flexible maintenance support that meets the individual needs of the worker.

[1235] Example of a prompt:

[1236] "New worker sign-up: Please enter your name, email address, and password."

[1237] "Please refer to the hydraulic system maintenance plan."

[1238] "What should I do if the robot's movements become slow?"

[1239] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1240] Step 1:

[1241] The user accesses the system and enters information on the sign-up or login screen. The required fields are name, email address, and password.

[1242] Input: Name, email address, password

[1243] Output: Data to send to the server

[1244] Specific action: The user enters the required information into the UI form and presses the "Submit" button.

[1245] Step 2:

[1246] The server saves the received input data to the database. For new registrations, it creates new user information; for logins, it performs authentication.

[1247] Input: Sign-up or login information

[1248] Output: Registration complete or authentication result

[1249] Specific operation: The server executes an SQL query to save or retrieve user information from the database.

[1250] Step 3:

[1251] After the user logs in, they enter the maintenance objectives and skill level on the maintenance plan creation screen.

[1252] Input: Maintenance objectives, skill level

[1253] Output: Plan creation request to the server

[1254] Specific operation: The user enters the goal and level into the UI form and presses the "Generate Plan" button.

[1255] Step 4:

[1256] The server executes an algorithm based on the received maintenance objectives and skill levels to generate individual maintenance plans.

[1257] Input: Maintenance objectives, skill level

[1258] Output: Maintenance plan

[1259] Specific operation: The server executes the plan generation algorithm and saves the generated plan to the database.

[1260] Step 5:

[1261] Users can enter questions if they have any while viewing the maintenance plan and performing each step.

[1262] Input: Question content

[1263] Output: Question request to the server

[1264] Specific action: The user enters a question into the UI form and presses the "Submit" button.

[1265] Step 6:

[1266] The server analyzes the received question and generates an answer using generative artificial intelligence (e.g., an OpenAI model).

[1267] Input: Question content

[1268] Output: Answer text

[1269] Specific operation: The server inputs a question as a prompt to the generative artificial intelligence, and returns the obtained answer to the user.

[1270] Step 7:

[1271] When a user requests educational materials corresponding to their selected maintenance area, they send a request to the server.

[1272] Input: Selection of maintenance field

[1273] Output: Request for educational materials to the server

[1274] Specific action: The user selects a field in the UI and presses the "Get Course Materials" button.

[1275] Step 8:

[1276] The server searches the database for relevant educational materials and sends them to the user.

[1277] Input: Selection of maintenance field

[1278] Output: Educational material data

[1279] Specific operation: The server searches the database for appropriate learning materials and sends them to the user's terminal.

[1280] Step 9:

[1281] Track user maintenance progress and save progress information to a database.

[1282] Input: Maintenance progress information

[1283] Output: Updated progress

[1284] Specific operation: The user enters the maintenance progress, which is then saved to the server.

[1285] Step 10:

[1286] If necessary, the server will adjust its maintenance schedule and provide new steps or supplementary materials.

[1287] Input: Updated progress

[1288] Output: Adjusted maintenance plans and supplementary materials

[1289] Specific operation: The server re-evaluates the plan based on progress information and makes adjustments as needed.

[1290] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1291] The learning center system of the present invention provides the following main functions to effectively support the user's learning. Furthermore, this system incorporates an emotion engine that recognizes the user's emotions and adjusts the learning plan accordingly.

[1292] 1. User signup and login

[1293] Server: Provides signup and login functionality to authenticate users accessing the tutoring school's website or app. During new user registration, users enter information such as their name, email address, and password, which the server stores in a database. During login, the server uses the information in the database to authenticate the user.

[1294] Specific example: A primary school student registers for the system, then logs in and accesses the dashboard.

[1295] 2. Creating a study plan

[1296] Server: Receives information about the user's learning goals and academic level, and generates an individualized learning plan based on this information. The server executes a pre-configured algorithm to generate the optimal learning schedule and materials, and stores them in a database.

[1297] Specific example: When a middle school student user enters the goal "improve math skills," the server generates a weekly study schedule based on the user's academic level and displays it on the device.

[1298] 3. 24-hour support for questions

[1299] User: If you have any questions while learning, enter them here.

[1300] Terminal: Sends the question content to the server.

[1301] Server: Uses generative artificial intelligence to analyze questions and generate answers. The generated answers are sent to the terminal and displayed to the user.

[1302] Specific example: If a middle school student user asks, "I don't know how to solve quadratic equations," the server provides a detailed explanation and immediately returns the answer to the user.

[1303] 4. Provision of teaching materials covering multiple subjects

[1304] Server: Provides corresponding learning materials for the subject selected by the user. The server searches the database for appropriate materials and sends them to the terminal.

[1305] Specific example: When a user selects the "Biology" field under "Science," the server sends video materials and text documents related to biology to the user's device and displays them.

[1306] 5. Tracking learning progress and adjusting plans

[1307] Server: Tracks user learning progress in a database and automatically adjusts the learning plan as needed. Provides new schedules and supplementary materials based on the user's completed learning content and progress.

[1308] Specific example: If a user finishes basic math problems earlier than planned, the server notifies the user to move on to the next learning step, which is applied problems, and updates the learning plan.

[1309] 6. Efficient Information Access

[1310] Server: In response to information requests from users, it collects relevant information from databases and the internet. It uses generative artificial intelligence to summarize the information and present it to the user in an easy-to-understand manner.

[1311] Specific example: If a user searches for "an overview of the French Revolution," the server collects relevant information and provides the user with a summarized text.

[1312] 7. Emotion recognition and learning plan adjustment using an emotion engine.

[1313] Server: During user training, the emotion engine recognizes the user's emotions. The emotion engine collects user emotion data using facial recognition and speech analysis.

[1314] Specific example: If a user is experiencing stress while learning, the emotion engine recognizes this, and the server recommends games or short breaks to help the user relax.

[1315] Server: Emotional data is stored in a database and periodically analyzed along with the user's learning history. This allows for the implementation of measures to improve long-term learning efficiency.

[1316] Specific example: If, based on user sentiment data, it is determined that learning efficiency is low during a particular time period, the server adjusts the plan to teach lighter subjects during that time.

[1317] Thus, the system of the present invention, through the cooperation of the user, terminal, and server, realizes flexible learning support tailored to individual needs and supports efficient and effective learning by providing appropriate responses in accordance with the user's emotions.

[1318] The following describes the processing flow.

[1319] Step 1: Sign up and log in

[1320] User: Access the tutoring school's website or app and click the "Register" button.

[1321] Terminal: Displays a registration form and prompts the user to enter their name, email address, password, etc.

[1322] Server: Receives the entered information and saves it to the database. Generates a registration completion message and notifies the terminal.

[1323] Terminal: Displays a registration completion message to the user.

[1324] User: Enter your email address and password, then click the "Login" button.

[1325] Terminal: Sends input information to the server.

[1326] Server: Authenticates the user in the database to verify their legitimacy. Generates a login success message and notifies the terminal.

[1327] Terminal: Displays a message to the user and redirects them to the dashboard.

[1328] Step 2: Create a study plan

[1329] User: After logging in, fill out a questionnaire about your learning goals and current academic level.

[1330] Terminal: Sends the entered information to the server.

[1331] Server: Based on the received information, it executes a learning algorithm and generates the optimal learning plan.

[1332] Server: Saves the generated training plan to the database. Sends the plan details to the terminal.

[1333] Terminal: Displays the learning plan generated for the user.

[1334] Step 3: 24-hour support available for questions

[1335] User: If you have any questions while learning, click the "Ask a Question" button and enter your question.

[1336] Terminal: Sends the entered question to the server.

[1337] Server: Uses generative artificial intelligence to analyze the question and generate an answer. Sends the generated answer to the terminal.

[1338] Terminal: Displays the answer to the user.

[1339] Step 4: Providing multi-subject learning materials

[1340] User: Select the subjects to study (for example, select "Science" and "Biology").

[1341] Terminal: Sends the selection to the server.

[1342] Server: Searches the database for corresponding learning materials (textbooks, videos, workbooks, etc.) and sends them to the user.

[1343] Terminal: Displays the learning materials received by the user.

[1344] Step 5: Tracking learning progress and adjusting plans

[1345] User: Open the learning progress screen and check the progress status.

[1346] Terminal: Sends progress data to the server.

[1347] Server: Based on the latest progress data, it determines whether the learning plan is progressing smoothly and adjusts the plan if necessary.

[1348] Server: Sends the updated learning plan to the device.

[1349] Terminal: Displays the updated plan to the user.

[1350] Step 6: Efficient Information Access

[1351] User: Enter the required information or documents into the search bar and click the "Search" button.

[1352] Terminal: Sends a search request to the server.

[1353] Server: Collects relevant information from databases and the internet, and summarizes it using generative artificial intelligence.

[1354] Server: Sends organized information to the terminal.

[1355] Terminal: Displays information to the user.

[1356] Step 7: Emotion recognition by the emotion engine

[1357] User: Generates emotional data through facial expressions and voice during learning.

[1358] Terminal: Transfers the user's facial expressions and voice to the emotion engine.

[1359] Server: The emotion engine recognizes the user's emotions and analyzes that data.

[1360] Step 8: Adjusting your learning plan based on your emotions

[1361] Server: Adjusts the user's learning plan based on the emotion data recognized by the emotion engine.

[1362] Server: Stores the coordinated plan in the database and analyzes it along with user progress data.

[1363] Device: Displays feedback from the emotion engine and suggests appropriate learning methods and breaks to the user.

[1364] Step 9: Long-term analysis of emotional data

[1365] Server: Regularly collects emotional data and stores it in a database.

[1366] Server: Analyzes user learning history and sentiment data to propose measures for improving long-term learning efficiency.

[1367] Terminal: Based on the analysis results, it suggests a learning plan, break times, and learning materials that are suitable for the user.

[1368] By executing each step in detail in this way, users can learn efficiently and effectively. In particular, the introduction of an emotion engine enables flexible learning support that responds to the user's emotions.

[1369] (Example 2)

[1370] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1371] Traditional learning support systems have limitations in providing appropriate learning plans tailored to individual users' learning goals and academic levels, and in particular, they lack individualized support that takes into account the user's emotional state. This has led to challenges such as users being unable to maximize their learning effectiveness due to stress and decreased motivation. Furthermore, in traditional systems, tracking learning progress and adjusting plans often required manual intervention, resulting in inefficient support.

[1372] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1373] In this invention, the server includes means for receiving input of learning goals and academic ability levels from the user and generating an individualized learning plan; means for receiving questions from the user and generating answers to those questions using generative artificial intelligence; means for providing learning materials for multiple subjects based on the user's selection; means for tracking the user's learning progress and automatically adjusting the learning plan as needed; means for collecting relevant information from databases and the internet in response to the user's information requests and summarizing it using generative artificial intelligence; and means for recognizing the user's emotions and adjusting the learning plan accordingly. This enables flexible learning support based on the learning needs of each individual user.

[1374] A "learning objective" is the specific learning goal that the user wants to achieve.

[1375] "Academic ability level" is an indicator that shows the user's current level of academic ability and knowledge.

[1376] A "learning plan" is a combination of a schedule and learning materials created based on the user's learning goals and academic level, designed to facilitate effective learning.

[1377] "Generative artificial intelligence" is an artificial intelligence technology that generates responses to user questions and requests.

[1378] "Multi-subject learning materials" refer to learning materials that cover multiple subjects, and are provided according to the subjects selected by the user.

[1379] "Learning progress" is an indicator that shows how far a user has progressed in their learning.

[1380] An "information request" is a request that a user sends to seek specific information or knowledge.

[1381] A "database" is a digital storage system used to manage and organize information and materials necessary for learning.

[1382] An "emotion engine" is a system that recognizes the user's emotional state and adjusts the learning plan based on that state.

[1383] The learning center system of the present invention provides the following main functions to effectively support the user's learning. This system is established through the interaction of a server, terminals, and users. Specific embodiments of the system based on the claims are shown below.

[1384] 1. User signup and login

[1385] The server provides sign-up and login functionality to authenticate users accessing the tutoring school's website or app. During new user registration, users enter information such as their name, email address, and password, which the server stores in a database. During login, the server authenticates the user based on the information in the database.

[1386] Specific example: A primary school student registers for the system, then logs in and accesses the dashboard.

[1387] 2. Creating a study plan

[1388] The server receives information about the user's learning goals and academic level, and generates an individualized learning plan. The server executes a pre-configured algorithm to generate the optimal learning schedule and materials, and stores them in a database.

[1389] Specific example: If a middle school student user enters "improve math skills" as their goal, the server generates a weekly study schedule based on the user's academic level and displays it on their device.

[1390] 3. Answering questions

[1391] If a user encounters a question during the learning process, they input the question. The device sends the question to the server. The server uses generative artificial intelligence to analyze the question and generate an answer. This generated answer is then sent to the device and displayed to the user.

[1392] Specific example: When a middle school student asks, "I don't know how to solve quadratic equations," the server uses generative artificial intelligence to provide a detailed explanation and immediately returns the answer to the user.

[1393] 4. Providing teaching materials

[1394] The server provides the corresponding learning materials according to the subject selected by the user. The server searches the database for the appropriate materials and sends them to the terminal.

[1395] Specific example: When a user selects the "Biology" field under "Science," the server sends video materials and text documents related to biology to the user's device and displays them.

[1396] 5. Tracking learning progress and adjusting plans

[1397] The server tracks the user's learning progress in a database and automatically adjusts the learning plan as needed. Based on the user's completed learning content and progress, it provides new schedules and supplementary materials.

[1398] Specific example: If a user finishes basic math problems earlier than planned, the server notifies the user to move on to the next learning step, which is applied problems, and updates the learning plan.

[1399] 6. Access to Information

[1400] The server collects relevant information from databases and the internet in response to user information requests. It then uses generative artificial intelligence to summarize the information and present it to the user in an easily understandable format.

[1401] Specific example: If a user searches for "an overview of the French Revolution," the server collects relevant information and provides the user with a summarized text.

[1402] 7. Responses based on the emotion engine

[1403] The server uses an emotion engine to recognize the user's emotions. The emotion engine collects user emotion data using facial recognition and voice analysis, and adjusts the learning plan based on this data. The emotion data is stored in a database and periodically analyzed along with the user's learning history.

[1404] Specific examples: If a user is experiencing stress while learning, the emotion engine will recognize this, and the server will recommend games or short breaks to help the user relax. If learning efficiency is low during certain times, the plan will be adjusted to include lighter subjects during those times.

[1405] This allows the tutoring system to provide flexible learning support tailored to the individual needs of users, enabling efficient and effective learning.

[1406] Example of a prompt

[1407] "Please tell me about specific methods for detecting the stress that middle school students experience while studying and suggesting appropriate responses."

[1408] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1409] Program processing steps

[1410] Step 1: User Signup

[1411] 1. Input: The user accesses the tutoring center's website or app and enters their name, email address, and password.

[1412] 2. Specific operation: The terminal sends the entered information to the server.

[1413] 3. Data processing: The server receives the information and stores it in the database.

[1414] 4. Output: The server sends a registration completion message to the terminal.

[1415] 5. Specific action: The device displays "Registration complete."

[1416] Step 2: User Login

[1417] 1. Input: The user enters their email address and password on the website or app's login screen.

[1418] 2. Specific operation: The terminal sends the entered information to the server.

[1419] 3. Data processing: The server accesses the database and verifies that the user information matches the input information.

[1420] 4. Output: The server sends a login success signal to the terminal.

[1421] 5. Specific action: The device displays the user's dashboard.

[1422] Step 3: Create a study plan

[1423] 1. Input: The user enters their learning goals and current academic level.

[1424] 2. Specific actions: The terminal sends this information to the server.

[1425] 3. Data processing: The server uses algorithms to generate individual learning plans and stores them in the database.

[1426] 4. Output: The server sends the generated training plan to the terminal.

[1427] 5. Specific actions: The device displays the learning plan to the user.

[1428] Step 4: Answering Questions

[1429] 1. Input: The user enters a question.

[1430] 2. Specific action: The terminal sends the question to the server.

[1431] 3. Data processing: The server uses a generative AI model to analyze the question and generate an answer.

[1432] 4. Output: The server sends the generated response to the terminal.

[1433] 5. Specific action: The device displays the answer to the user.

[1434] Step 5: Provide teaching materials

[1435] 1. Input: The user selects the subject or field they wish to study.

[1436] 2. Specific action: The terminal sends that information to the server.

[1437] 3. Data processing: The server searches the database for appropriate teaching materials.

[1438] 4. Output: The server sends the selected learning materials to the terminal.

[1439] 5. Specific operation: The device displays the learning materials to the user.

[1440] Step 6: Tracking learning progress and adjusting plans

[1441] 1. Input: The user enters learning progress information.

[1442] 2. Specific action: The terminal sends that information to the server.

[1443] 3. Data processing: The server analyzes the learning progress data and updates the learning plan as needed.

[1444] 4. Output: The server sends the updated learning plan to the terminal.

[1445] 5. Specific action: The device displays a new learning plan to the user.

[1446] Step 7: Responding with an emotional engine

[1447] 1. Input: The emotion engine captures the user's facial expressions and voice data during the learning process.

[1448] 2. Specific action: The terminal sends this data to the server.

[1449] 3. Data processing: The server uses an emotion engine to analyze the user's emotions and determine if the learning plan needs to be adjusted.

[1450] 4. Output: The server sends the adjusted learning plan results, based on the user's emotions, to the terminal.

[1451] 5. Specific actions: The device displays a learning plan and relaxation menu tailored to the user.

[1452] In this way, the tutoring system, through the coordination of users, terminals, and servers, provides flexible learning support tailored to individual needs and enables efficient and effective learning by responding appropriately to the user's emotions.

[1453] (Application Example 2)

[1454] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1455] Traditional learning systems have a problem of reduced learning effectiveness because they provide a uniform learning plan without considering the learner's emotional state. Furthermore, the lack of flexible adjustments in response to emotional changes leads to increased learning stress. In addition, since emotional states affect work efficiency among factory workers, there is a need for efficient work support utilizing emotional data.

[1456] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[1457] In this invention, the server includes means for receiving input of learning goals and academic ability levels from the user and generating individual learning plans; means for receiving questions from the user and generating answers to those questions using generative artificial intelligence; means for providing learning materials for multiple subjects based on the user's selection; means for tracking the user's learning progress and automatically adjusting the learning plan as needed; means for collecting relevant information from databases and the internet in response to the user's information requests and summarizing it using generative artificial intelligence; means for collecting emotional data from the user's facial expressions and voice and determining their emotional state using an emotion recognition model; and means for flexibly adjusting the learning plan based on the determined emotional state. This enables individualized responses that are tailored to the emotions of learners and workers.

[1458] A "user" refers to a learner or factory worker who uses the system.

[1459] "Learning objectives" are specific learning goals that the user wants to achieve.

[1460] "Academic ability level" refers to the user's current level of understanding and knowledge regarding learning.

[1461] An "individualized learning plan" refers to a user-specific learning schedule and content created based on the user's learning goals and academic level.

[1462] "Generative artificial intelligence" refers to artificial intelligence technology that generates answers to questions, summaries of information, and other data based on large amounts of data.

[1463] "Multi-subject learning materials" refer to learning materials that cover multiple subjects, including videos, textbooks, and workbooks.

[1464] "Learning progress" refers to the user's learning progress and indicates how far they have progressed in their learning.

[1465] A "database" is a digital repository for information, where various types of data such as user information, learning content, and questions and answers are stored.

[1466] The "Internet" is a vast source of information available online, and a means of searching for answers to users' information requests.

[1467] To "summarize" means to put detailed information into a concise and easy-to-understand format.

[1468] "Emotional data" refers to digital information about a user's emotional state, obtained from their facial expressions and voice.

[1469] An "emotion recognition model" is a machine learning or deep learning model that performs facial recognition and voice analysis to determine a user's emotions.

[1470] "Emotional state" refers to the psychological state a user experiences while learning or working, and includes stress, joy, sadness, and other similar emotions.

[1471] "Flexibly adjusting the learning plan" means changing the content and order of learning and tasks to reflect the user's current emotional state.

[1472] The system of the present invention provides multiple functions to effectively support user learning. This system includes an emotion engine that recognizes the user's emotional state and adjusts the learning plan accordingly.

[1473] 1. User signup and login

[1474] The server provides signup and login functionality to authenticate users accessing the tutoring school's website or mobile app. Users enter information such as their name, email address, and password during registration, which is stored in the database. During login, the server authenticates the user using the information in the database.

[1475] 2. Creating a study plan

[1476] The server receives information about the user's learning goals and academic level, and generates an individualized learning plan based on this information. It generates the optimal learning schedule and materials based on an algorithm and stores them in a database.

[1477] 3. 24-hour support for questions

[1478] If a user has questions during the learning process, they can input them using their device. The device sends the question to the server, which uses generative artificial intelligence to analyze the question and generate an answer. The generated answer is then sent back to the device and displayed to the user.

[1479] 4. Provision of teaching materials covering multiple subjects

[1480] The server provides learning materials corresponding to the subject selected by the user. It searches the database for appropriate materials, sends them to the terminal, and displays them to the user.

[1481] 5. Tracking learning progress and adjusting plans

[1482] The server tracks the user's learning progress in a database and automatically adjusts the learning plan as needed. Based on the user's completed learning content and progress, it provides new schedules and supplementary materials.

[1483] 6. Efficient Information Access

[1484] The server collects relevant information from databases and the internet in response to user information requests, and summarizes the information using generative artificial intelligence. It then presents the information to the user in an easy-to-understand manner.

[1485] 7. Emotion recognition and learning plan adjustment using an emotion engine.

[1486] The server uses an emotion engine to recognize the user's emotional state during training. The emotion engine collects user emotional data using facial recognition and speech analysis, and uses an emotion recognition model to determine the emotional state. Based on the results, it flexibly adjusts the training plan.

[1487] Hardware and software used

[1488] The emotion recognition feature, which is part of this system, uses the following hardware and software.

[1489] Hardware: Smart glasses or cameras (e.g., Google Glass)

[1490] Software: Emotion recognition model (using Keras), OpenCV for face recognition

[1491] Specific example

[1492] For example, suppose a factory worker is wearing smart glasses while working. If the server can determine the worker's current stress level from their facial expressions, it will recognize this and automatically adjust the worker's work plan. For instance, if the worker is in a high-stress state requiring immediate attention, the server might reduce the workload or recommend a short break.

[1493] Example of a prompt

[1494] Design a smart work assistant application that analyzes employees' facial expressions and emotions in real time and adjusts work plans accordingly. Specifically, it uses a camera built into smart glasses to recognize the employee's face, determines their emotions using an emotion recognition model, and adjusts their work based on that emotion data. For example, if an employee is feeling stressed, the system should recommend relaxing tasks or breaks.

[1495] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1496] Step 1:

[1497] The device uses its camera to capture the user's face. The image data is acquired and converted to grayscale as a preprocessing step. This prepares the data necessary for face recognition.

[1498] Input: User's face image

[1499] Output: Grayscale facial image data

[1500] Specific operation: The smart glasses' camera captures a facial image in real time, and OpenCV is used to convert the image to grayscale.

[1501] Step 2:

[1502] The device performs facial recognition and identifies the facial region. The image of the facial region is resized to a standard size and converted to the format required by the model.

[1503] Input: Grayscale facial image data

[1504] Output: Resized face region image data

[1505] Specific operation: Use a face recognition algorithm (e.g., Haar Cascade) to obtain the coordinates of the face, and resize the face area to a standard size (e.g., 48x48 pixels).

[1506] Step 3:

[1507] The device inputs facial image data into an emotion recognition model, which then determines the emotion. The model outputs an emotion label and its corresponding probability.

[1508] Input: Resized facial region image data

[1509] Output: Sentiment labels and probabilities

[1510] Specific operation: Resized image data is input into an emotion recognition model using Keras, and the emotion determination result is obtained. For example, an output such as "Happy: 0.85, Sad: 0.10" may be obtained.

[1511] Step 4:

[1512] The device sends the assessment result to the server. The server adjusts the learning plan based on the emotional state.

[1513] Input: Emotion labels and probabilities

[1514] Output: Instructions for adjusting the learning plan

[1515] Specific operation: The emotion recognition results are sent to the server, which executes an algorithm to generate a learning or work plan appropriate to the emotional state. For example, if a stressed state is detected, a recommendation for a break or assignment of light work may be made.

[1516] Step 5:

[1517] The server sends the adjusted learning plan to the terminal. The terminal displays the new learning or work plan to the user.

[1518] Input: Learning plan with adjustment instructions

[1519] Output: New learning plan displayed on the terminal

[1520] Specific operation: The server sends a newly generated learning plan to the terminal, which then displays it on the user's screen. For example, a message such as "You have 10 minutes until your next break" might be displayed.

[1521] 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.

[1522] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1523] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[1524] [Fourth Embodiment]

[1525] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1526] 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.

[1527] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1528] 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.

[1529] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1530] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1531] 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.

[1532] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[1533] 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.

[1534] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1535] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1536] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1537] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1538] The learning center system of the present invention provides the following main functions to effectively support the user's learning.

[1539] 1. User signup and login

[1540] Server: Provides signup and login functionality to authenticate users accessing the tutoring school's website or app. During new user registration, users enter information such as their name, email address, and password, which the server stores in a database. During login, the server uses the information in the database to authenticate the user.

[1541] Specific example: A primary school student registers for the system, then logs in and accesses the dashboard.

[1542] 2. Creating a study plan

[1543] Server: Receives information about the user's learning goals and academic level, and generates an individualized learning plan based on this information. The server executes a pre-configured algorithm to generate the optimal learning schedule and materials, and stores them in a database.

[1544] Specific example: When a middle school student user enters the goal "improve math skills," the server generates a weekly study schedule based on the user's academic level and displays it on the device.

[1545] 3. 24-hour support for questions

[1546] User: If you have any questions while learning, enter them here.

[1547] Terminal: Sends the question content to the server.

[1548] Server: Uses generative artificial intelligence to analyze questions and generate answers. The generated answers are sent to the terminal and displayed to the user.

[1549] Specific example: If a middle school student user asks, "I don't know how to solve quadratic equations," the server provides a detailed explanation and immediately returns the answer to the user.

[1550] 4. Provision of teaching materials covering multiple subjects

[1551] Server: Provides corresponding learning materials for the subject selected by the user. The server searches the database for appropriate materials and sends them to the terminal.

[1552] Specific example: When a user selects the "Biology" field under "Science," the server sends video materials and text documents related to biology to the user's device and displays them.

[1553] 5. Tracking learning progress and adjusting plans

[1554] Server: Tracks user learning progress in a database and automatically adjusts the learning plan as needed. Provides new schedules and supplementary materials based on the user's completed learning content and progress.

[1555] Specific example: If a user finishes basic math problems earlier than planned, the server notifies the user to move on to the next learning step, which is applied problems, and updates the learning plan.

[1556] 6. Efficient Information Access

[1557] Server: In response to information requests from users, it collects relevant information from databases and the internet. It uses generative artificial intelligence to summarize the information and present it to the user in an easy-to-understand manner.

[1558] Specific example: If a user searches for "an overview of the French Revolution," the server collects relevant information and provides the user with a summarized text.

[1559] In this way, the user, terminal, and server work together, enabling the user to learn efficiently and effectively, and to receive necessary information and support 24 hours a day. The system of the present invention realizes flexible learning support that meets the individual needs of the user.

[1560] The following describes the processing flow.

[1561] Step 1: Sign up and log in

[1562] User: Access the tutoring school's website or app and click the "Register" button.

[1563] Terminal: Displays a registration form and prompts the user to enter their name, email address, password, etc.

[1564] Server: Receives the entered information and saves it to the database. Generates a registration completion message and notifies the terminal.

[1565] Terminal: Displays a registration completion message to the user.

[1566] User: Enter your email address and password, then click the "Login" button.

[1567] Terminal: Sends input information to the server.

[1568] Server: Authenticates the user in the database to verify their legitimacy. Generates a login success message and notifies the terminal.

[1569] Terminal: Displays a message to the user and redirects them to the dashboard.

[1570] Step 2: Create a study plan

[1571] User: After logging in, fill out a questionnaire about your learning goals and current academic level.

[1572] Terminal: Sends the entered information to the server.

[1573] Server: Based on the received information, it executes a learning algorithm and generates the optimal learning plan.

[1574] Server: Saves the generated training plan to the database. Sends the plan details to the terminal.

[1575] Terminal: Displays the learning plan generated for the user.

[1576] Step 3: 24-hour support available for questions

[1577] User: If you have any questions while learning, click the "Ask a Question" button and enter your question.

[1578] Terminal: Sends the entered question to the server.

[1579] Server: Uses generative artificial intelligence to analyze the question and generate an answer. Sends the generated answer to the terminal.

[1580] Terminal: Displays the answer to the user.

[1581] Step 4: Providing multi-subject learning materials

[1582] User: Select the subjects to study (for example, select "Science" and "Biology").

[1583] Terminal: Sends the selection to the server.

[1584] Server: Searches the database for corresponding learning materials (textbooks, videos, workbooks, etc.) and sends them to the user.

[1585] Terminal: Displays the learning materials received by the user.

[1586] Step 5: Tracking learning progress and adjusting plans

[1587] User: Open the learning progress screen and check the progress status.

[1588] Terminal: Sends progress data to the server.

[1589] Server: Based on the latest progress data, it determines whether the learning plan is progressing smoothly and adjusts the plan if necessary.

[1590] Server: Sends the updated learning plan to the device.

[1591] Terminal: Displays the updated plan to the user.

[1592] Step 6: Efficient Information Access

[1593] User: Enter the required information or documents into the search bar and click the "Search" button.

[1594] Terminal: Sends a search request to the server.

[1595] Server: Collects relevant information from databases and the internet, and summarizes it using generative artificial intelligence.

[1596] Server: Sends organized information to the terminal.

[1597] Terminal: Displays information to the user.

[1598] By executing each step in detail in this way, users can learn efficiently and effectively.

[1599] (Example 1)

[1600] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1601] In recent years, there has been a growing demand for individualized instruction and learning support. However, traditional cram schools and online education services have struggled to provide efficient and effective learning support tailored to the individual needs of users. Specifically, the lack of a system that integrates the generation of individualized learning plans based on each user's academic level and learning goals, 24 / 7 question answering, provision of learning materials covering multiple subjects, automatic tracking of learning progress and plan adjustments, and efficient information access has been a major problem.

[1602] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1603] In this invention, the server includes means for receiving input of learning goals and academic ability levels from the user and generating an individualized learning plan; means for receiving questions from the user and generating answers to those questions using generative artificial intelligence; means for providing learning materials for multiple subjects based on the user's selection; means for tracking the user's learning progress and automatically adjusting the learning plan as needed; means for collecting relevant information from a database and the internet in response to the user's information requests and summarizing it using generative artificial intelligence; means for recording the learning content completed by the user and updating the learning plan according to the learning progress; and means for analyzing the user's information requests and summarizing the relevant information using a generative artificial intelligence model. This enables effective learning support that is tailored to the individual needs of the user.

[1604] "Learning objectives" are specific learning goals or objectives that the user wants to achieve.

[1605] "Academic ability level" is an indicator that shows the user's current academic ability and the degree to which they have acquired knowledge.

[1606] A "learning plan" is a schedule set up to guide the user to the optimal learning progress, based on their academic level and learning goals.

[1607] "Generative artificial intelligence" is an artificial intelligence technology that uses natural language processing to generate appropriate answers and information in response to input questions and requests.

[1608] "Educational materials" refer to educational resources and materials used for user learning.

[1609] "Learning progress" refers to the extent to which a user has progressed according to their learning plan.

[1610] An "information request" is a request made by a user to a system in order to obtain specific information or knowledge.

[1611] A "database" is a collection of data used to efficiently manage and operate user information, learning materials, and learning progress.

[1612] The "Internet" is a communication network that connects computer networks around the world, enabling the exchange and acquisition of information.

[1613] "Means" refer to the methods, devices, or parts of a system used to achieve a particular objective.

[1614] The "individualized learning plan generation method" is a function that creates an optimal learning schedule based on the user's academic level and learning goals.

[1615] A "question and answer generation method" is a function that generates appropriate answers to user questions using generative artificial intelligence.

[1616] "Methods for providing learning materials" refers to the function of selecting and providing learning materials for users.

[1617] A "learning progress tracking mechanism" is a function that tracks the user's learning progress and adjusts the learning plan as needed.

[1618] An "information summarization tool" is a function that collects relevant information in response to a user's information request and summarizes it using generative artificial intelligence.

[1619] This invention relates to a tutoring system for effectively supporting user learning. This system consists of a server, terminals, and users, with each component working in coordination.

[1620] Sign up and log in

[1621] The server provides signup and login functionality for users accessing the tutoring school's website or app. Users enter information such as their name, email address, and password, and the device sends this information to the server. The server stores the received information in a database and sends a registration completion message to the user. During login, the server authenticates the user by referencing the information in the database and allows them to access the dashboard.

[1622] A concrete example would be a primary school student registering as a new user, logging in, and accessing the dashboard.

[1623] Creating a study plan

[1624] The server receives information about the user's learning goals and academic level, and generates an individualized learning plan based on this information. The server executes a pre-configured algorithm (for example, a Python script on the Django framework) to generate the optimal learning schedule and materials, and saves them to the database. The terminal then displays the generated learning plan to the user.

[1625] A concrete example would be a middle school student who enters a goal such as "improve math skills," and the server generates a weekly study schedule based on that information, which is then displayed on the user's device.

[1626] 24-hour support available for questions

[1627] If the user encounters any questions during the learning process, they input them. The device sends the question to the server. The server analyzes the question using generative artificial intelligence (e.g., GPT-4) and generates an answer. The generated answer is sent to the device and displayed to the user.

[1628] For example, if a middle school student user asks, "I don't know how to solve a quadratic equation," the server will provide a detailed explanation and return the answer to the user.

[1629] Example of a prompt

[1630] "I don't know how to solve quadratic equations. Could you please provide a detailed explanation?"

[1631] Providing teaching materials that cover multiple subjects

[1632] The server provides learning materials corresponding to the subject selected by the user. The server searches the database for appropriate materials and sends them to the terminal. The terminal displays the provided materials to the user.

[1633] As a concrete example, when a user selects the "Biology" field under "Science," the server sends video materials and text documents related to biology to the user's device for display.

[1634] Tracking learning progress and adjusting plans

[1635] The server tracks the user's learning progress in a database and automatically adjusts the learning plan as needed. Based on the user's completed learning content and progress, it provides new schedules and supplementary materials. The terminal displays the updated learning plan to the user.

[1636] For example, if a user finishes basic math problems earlier than planned, the server can notify them to move on to the next learning step, which is applied problems, and update their learning plan.

[1637] Efficient information access

[1638] The server collects relevant information from databases and the internet in response to information requests from users. It summarizes the information using a generative artificial intelligence model (e.g., GPT-4) and sends it to the terminal. The terminal displays the summarized information to the user.

[1639] For example, if a user searches for "an overview of the French Revolution," the server could collect relevant information, generate a summarized text, and provide it to the user's device.

[1640] The system of this invention allows users to learn efficiently and effectively, and to receive necessary information and support 24 hours a day.

[1641] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1642] Step 1:

[1643] sign up

[1644] User: Access the tutoring center's website or app and enter your name, email address, and password in the sign-up form.

[1645] Input: Name, email address, password

[1646] Terminal: Sends the entered information to the server.

[1647] Server: Stores the received information in the database, generates a registration completion message, and sends it back to the terminal.

[1648] Output: Registration complete message

[1649] Specific action: A primary school student registers for the system and a confirmation email is sent.

[1650] Step 2:

[1651] Log in

[1652] User: Enter your registered email address and password and submit the login form.

[1653] Input: Email address, password

[1654] Terminal: Sends the entered information to the server.

[1655] Server: Checks if the information matches the data stored in the database. If it matches, it grants login permission, generates a dashboard, and sends it to the device.

[1656] Output: Dashboard screen

[1657] Specific action: The user logs in and accesses their individual dashboard.

[1658] Step 3:

[1659] Input learning objectives and academic ability levels

[1660] User: Enter your learning goals and current academic level.

[1661] Input: Learning objectives, academic level

[1662] Terminal: Sends the entered information to the server.

[1663] Server: Based on the received information, it executes a pre-configured algorithm to generate a learning plan and saves it to the database.

[1664] Output: Study plan

[1665] Specific operation: The user inputs a goal such as "improve math skills" and their "current grades," and the server generates a study plan and displays it on the device.

[1666] Step 4:

[1667] Question input and answer generation

[1668] User: Enter your questions if you have any during your studies.

[1669] Input: Question content

[1670] Terminal: Sends the entered question to the server.

[1671] Server: Uses generative artificial intelligence to analyze questions, generate answers, and send them to the terminal.

[1672] Output: Answer to the question

[1673] Specific operation: The user enters "I don't know how to solve quadratic equations," and the server provides a detailed explanation.

[1674] Step 5:

[1675] Selection of subjects and fields

[1676] User: Select the subjects and fields you wish to study.

[1677] Input: Subject, field

[1678] Terminal: Sends the selected information to the server.

[1679] Server: Searches the database for teaching materials suitable for the selected subject and field, and sends them to the terminal.

[1680] Output: Teaching materials

[1681] Specific operation: The user selects the "Biology" field under "Science," and the server provides the corresponding educational materials.

[1682] Step 6:

[1683] Recording and updating learning progress

[1684] User: Record what you have completed learning.

[1685] Input: Completed learning content

[1686] Terminal: Sends recorded information to the server.

[1687] Server: Updates user learning progress in the database and automatically adjusts the learning plan as needed.

[1688] Output: Updated learning plan

[1689] Specific action: The user completes basic math problems ahead of schedule and receives a new plan.

[1690] Step 7:

[1691] Information Request and Summary

[1692] User: Enter the information you want to search for.

[1693] Input: Information Request

[1694] Terminal: Sends the entered information to the server.

[1695] Server: Collects relevant information from databases and the internet, summarizes it using generative artificial intelligence, and sends it to the terminal.

[1696] Output: Summarized information

[1697] Specific operation: The user searches for "an overview of the French Revolution," and the server summarizes and provides the information.

[1698] In this way, a system is built that enables effective learning support through the coordinated operation of users, terminals, and servers.

[1699] (Application Example 1)

[1700] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1701] Conventional factory robot maintenance systems face challenges in efficient maintenance because they do not adequately generate individual plans or track progress based on each worker's skill level and maintenance objectives. Furthermore, there is a need for a support system that can quickly address problems and questions that workers encounter during maintenance.

[1702] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1703] In this invention, the server includes means for receiving user input of maintenance goals and skill levels and generating individual maintenance plans; means for receiving user questions and generating answers to those questions using generative artificial intelligence; means for providing multidisciplinary learning materials based on user selection; means for tracking user progress and automatically adjusting the plan as needed; and means for collecting relevant information from databases and the internet in response to user information requests and summarizing it using generative artificial intelligence. This enables the provision of efficient and personalized maintenance plans, immediate question support, and the provision of diverse learning materials.

[1704] "Maintenance targets" are specific objectives and standards that should be achieved when maintaining or repairing factory robots.

[1705] "Skill level" is an indicator that shows the degree of maintenance knowledge and skills possessed by a worker.

[1706] An "individualized maintenance plan" is a plan that includes a customized maintenance schedule and procedures based on each worker's skill level and maintenance goals.

[1707] "Generative artificial intelligence" is an artificial intelligence technology that automatically generates answers and solutions based on input data and information.

[1708] "Multidisciplinary teaching materials" refers to learning materials, tool manuals, video materials, and other resources related to various fields of robot maintenance.

[1709] "Progress tracking" refers to the act of recording the progress of maintenance work performed by workers and saving it in a database.

[1710] A "database" is a collection of digital information designed to efficiently organize, store, and retrieve information.

[1711] The "Internet" is a communication network for sharing information through computer network systems worldwide.

[1712] An "information request" is a request to search for and provide the information that a user needs.

[1713] "Summarization" is the act of compiling collected detailed information into a concise and easy-to-understand format.

[1714] This invention is a system for streamlining maintenance work on factory robots and provides the following main functions.

[1715] 1. User signup and login

[1716] Server: Provides sign-up and login functionality to allow workers to access the system. During new registration, workers enter information such as their name, email address, and password, which the server stores in a database. During login, the server uses the information in the database to authenticate the worker.

[1717] Specific example: A new worker creates an account, logs in, and accesses the maintenance guide.

[1718] 2. Creating a maintenance plan

[1719] Server: Receives information on worker maintenance goals and skill levels, and generates individual maintenance plans based on this information. The server executes a pre-configured algorithm to generate the optimal maintenance schedule and procedures, and stores them in the database.

[1720] Specific example: When a worker with entry-level skills enters the objective "hydraulic system maintenance," the server generates a weekly maintenance schedule based on the worker's skill level and displays it on the terminal.

[1721] 3. 24-hour support for questions

[1722] User: If you have any questions during maintenance, please enter them here.

[1723] Terminal: Sends the question content to the server.

[1724] Server: Uses generative artificial intelligence to analyze questions and generate answers. The generated answers are sent to the terminal and displayed to the user.

[1725] Specific example: When a novice worker asks, "What should I do if the robot's movements become slow?", the server provides detailed instructions and returns the answer to the worker immediately.

[1726] 4. Provision of educational materials covering multiple fields.

[1727] Server: Provides training materials for the maintenance area selected by the worker. The server searches the database for appropriate training materials and sends them to the terminal.

[1728] Specific example: When a worker selects the "Electrical System Maintenance" field, the server sends video and text materials related to that field to the worker's terminal for display.

[1729] 5. Tracking maintenance progress and coordinating plans.

[1730] Server: Tracks the maintenance progress of workers in a database and automatically adjusts the maintenance plan as needed. Provides new schedules and supplementary materials based on the maintenance tasks and progress completed by workers.

[1731] Specific example: If a worker completes a particular maintenance task ahead of schedule, the server will suggest the next maintenance step and update the plan.

[1732] 6. Efficient Information Access

[1733] Server: In response to information requests from workers, it collects relevant information from databases and the internet. It uses generative artificial intelligence to summarize the information and present it to workers in an easy-to-understand manner.

[1734] Specific example: If a worker is researching "the latest maintenance techniques," the server collects the relevant information and provides the worker with a summarized text.

[1735] In this way, by having the user (worker), terminal, and server work together, the worker can carry out robot maintenance efficiently and effectively, and can receive necessary information and support 24 hours a day. The system of the present invention realizes flexible maintenance support that meets the individual needs of the worker.

[1736] Example of a prompt:

[1737] "New worker sign-up: Please enter your name, email address, and password."

[1738] "Please refer to the hydraulic system maintenance plan."

[1739] "What should I do if the robot's movements become slow?"

[1740] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1741] Step 1:

[1742] The user accesses the system and enters information on the sign-up or login screen. The required fields are name, email address, and password.

[1743] Input: Name, email address, password

[1744] Output: Data to send to the server

[1745] Specific action: The user enters the required information into the UI form and presses the "Submit" button.

[1746] Step 2:

[1747] The server saves the received input data to the database. For new registrations, it creates new user information; for logins, it performs authentication.

[1748] Input: Sign-up or login information

[1749] Output: Registration complete or authentication result

[1750] Specific operation: The server executes an SQL query to save or retrieve user information from the database.

[1751] Step 3:

[1752] After the user logs in, they enter the maintenance objectives and skill level on the maintenance plan creation screen.

[1753] Input: Maintenance objectives, skill level

[1754] Output: Plan creation request to the server

[1755] Specific operation: The user enters the goal and level into the UI form and presses the "Generate Plan" button.

[1756] Step 4:

[1757] The server executes an algorithm based on the received maintenance objectives and skill levels to generate individual maintenance plans.

[1758] Input: Maintenance objectives, skill level

[1759] Output: Maintenance plan

[1760] Specific operation: The server executes the plan generation algorithm and saves the generated plan to the database.

[1761] Step 5:

[1762] Users can enter questions if they have any while viewing the maintenance plan and performing each step.

[1763] Input: Question content

[1764] Output: Question request to the server

[1765] Specific action: The user enters a question into the UI form and presses the "Submit" button.

[1766] Step 6:

[1767] The server analyzes the received question and generates an answer using generative artificial intelligence (e.g., an OpenAI model).

[1768] Input: Question content

[1769] Output: Answer text

[1770] Specific operation: The server inputs a question as a prompt to the generative artificial intelligence, and returns the obtained answer to the user.

[1771] Step 7:

[1772] When a user requests educational materials corresponding to their selected maintenance area, they send a request to the server.

[1773] Input: Selection of maintenance field

[1774] Output: Request for educational materials to the server

[1775] Specific action: The user selects a field in the UI and presses the "Get Course Materials" button.

[1776] Step 8:

[1777] The server searches the database for relevant educational materials and sends them to the user.

[1778] Input: Selection of maintenance field

[1779] Output: Educational material data

[1780] Specific operation: The server searches the database for appropriate learning materials and sends them to the user's terminal.

[1781] Step 9:

[1782] Track user maintenance progress and save progress information to a database.

[1783] Input: Maintenance progress information

[1784] Output: Updated progress

[1785] Specific operation: The user enters the maintenance progress, which is then saved to the server.

[1786] Step 10:

[1787] If necessary, the server will adjust its maintenance schedule and provide new steps or supplementary materials.

[1788] Input: Updated progress

[1789] Output: Adjusted maintenance plans and supplementary materials

[1790] Specific operation: The server re-evaluates the plan based on progress information and makes adjustments as needed.

[1791] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1792] The learning center system of the present invention provides the following main functions to effectively support the user's learning. Furthermore, this system incorporates an emotion engine that recognizes the user's emotions and adjusts the learning plan accordingly.

[1793] 1. User signup and login

[1794] Server: Provides signup and login functionality to authenticate users accessing the tutoring school's website or app. During new user registration, users enter information such as their name, email address, and password, which the server stores in a database. During login, the server uses the information in the database to authenticate the user.

[1795] Specific example: A primary school student registers for the system, then logs in and accesses the dashboard.

[1796] 2. Creating a study plan

[1797] Server: Receives information about the user's learning goals and academic level, and generates an individualized learning plan based on this information. The server executes a pre-configured algorithm to generate the optimal learning schedule and materials, and stores them in a database.

[1798] Specific example: When a middle school student user enters the goal "improve math skills," the server generates a weekly study schedule based on the user's academic level and displays it on the device.

[1799] 3. 24-hour support for questions

[1800] User: If you have any questions while learning, enter them here.

[1801] Terminal: Sends the question content to the server.

[1802] Server: Uses generative artificial intelligence to analyze questions and generate answers. The generated answers are sent to the terminal and displayed to the user.

[1803] Specific example: If a middle school student user asks, "I don't know how to solve quadratic equations," the server provides a detailed explanation and immediately returns the answer to the user.

[1804] 4. Provision of teaching materials covering multiple subjects

[1805] Server: Provides corresponding learning materials for the subject selected by the user. The server searches the database for appropriate materials and sends them to the terminal.

[1806] Specific example: When a user selects the "Biology" field under "Science," the server sends video materials and text documents related to biology to the user's device and displays them.

[1807] 5. Tracking learning progress and adjusting plans

[1808] Server: Tracks user learning progress in a database and automatically adjusts the learning plan as needed. Provides new schedules and supplementary materials based on the user's completed learning content and progress.

[1809] Specific example: If a user finishes basic math problems earlier than planned, the server notifies the user to move on to the next learning step, which is applied problems, and updates the learning plan.

[1810] 6. Efficient Information Access

[1811] Server: In response to information requests from users, it collects relevant information from databases and the internet. It uses generative artificial intelligence to summarize the information and present it to the user in an easy-to-understand manner.

[1812] Specific example: If a user searches for "an overview of the French Revolution," the server collects relevant information and provides the user with a summarized text.

[1813] 7. Emotion recognition and learning plan adjustment using an emotion engine.

[1814] Server: During user training, the emotion engine recognizes the user's emotions. The emotion engine collects user emotion data using facial recognition and speech analysis.

[1815] Specific example: If a user is experiencing stress while learning, the emotion engine recognizes this, and the server recommends games or short breaks to help the user relax.

[1816] Server: Emotional data is stored in a database and periodically analyzed along with the user's learning history. This allows for the implementation of measures to improve long-term learning efficiency.

[1817] Specific example: If, based on user sentiment data, it is determined that learning efficiency is low during a particular time period, the server adjusts the plan to teach lighter subjects during that time.

[1818] Thus, the system of the present invention, through the cooperation of the user, terminal, and server, realizes flexible learning support tailored to individual needs and supports efficient and effective learning by providing appropriate responses in accordance with the user's emotions.

[1819] The following describes the processing flow.

[1820] Step 1: Sign up and log in

[1821] User: Access the tutoring school's website or app and click the "Register" button.

[1822] Terminal: Displays a registration form and prompts the user to enter their name, email address, password, etc.

[1823] Server: Receives the entered information and saves it to the database. Generates a registration completion message and notifies the terminal.

[1824] Terminal: Displays a registration completion message to the user.

[1825] User: Enter your email address and password, then click the "Login" button.

[1826] Terminal: Sends input information to the server.

[1827] Server: Authenticates the user in the database to verify their legitimacy. Generates a login success message and notifies the terminal.

[1828] Terminal: Displays a message to the user and redirects them to the dashboard.

[1829] Step 2: Create a study plan

[1830] User: After logging in, fill out a questionnaire about your learning goals and current academic level.

[1831] Terminal: Sends the entered information to the server.

[1832] Server: Based on the received information, it executes a learning algorithm and generates the optimal learning plan.

[1833] Server: Saves the generated training plan to the database. Sends the plan details to the terminal.

[1834] Terminal: Displays the learning plan generated for the user.

[1835] Step 3: 24-hour support available for questions

[1836] User: If you have any questions while learning, click the "Ask a Question" button and enter your question.

[1837] Terminal: Sends the entered question to the server.

[1838] Server: Uses generative artificial intelligence to analyze the question and generate an answer. Sends the generated answer to the terminal.

[1839] Terminal: Displays the answer to the user.

[1840] Step 4: Providing multi-subject learning materials

[1841] User: Select the subjects to study (for example, select "Science" and "Biology").

[1842] Terminal: Sends the selection to the server.

[1843] Server: Searches the database for corresponding learning materials (textbooks, videos, workbooks, etc.) and sends them to the user.

[1844] Terminal: Displays the learning materials received by the user.

[1845] Step 5: Tracking learning progress and adjusting plans

[1846] User: Open the learning progress screen and check the progress status.

[1847] Terminal: Sends progress data to the server.

[1848] Server: Based on the latest progress data, it determines whether the learning plan is progressing smoothly and adjusts the plan if necessary.

[1849] Server: Sends the updated learning plan to the device.

[1850] Terminal: Displays the updated plan to the user.

[1851] Step 6: Efficient Information Access

[1852] User: Enter the required information or documents into the search bar and click the "Search" button.

[1853] Terminal: Sends a search request to the server.

[1854] Server: Collects relevant information from databases and the internet, and summarizes it using generative artificial intelligence.

[1855] Server: Sends organized information to the terminal.

[1856] Terminal: Displays information to the user.

[1857] Step 7: Emotion recognition by the emotion engine

[1858] User: Generates emotional data through facial expressions and voice during learning.

[1859] Terminal: Transfers the user's facial expressions and voice to the emotion engine.

[1860] Server: The emotion engine recognizes the user's emotions and analyzes that data.

[1861] Step 8: Adjusting your learning plan based on your emotions

[1862] Server: Adjusts the user's learning plan based on the emotion data recognized by the emotion engine.

[1863] Server: Stores the coordinated plan in the database and analyzes it along with user progress data.

[1864] Device: Displays feedback from the emotion engine and suggests appropriate learning methods and breaks to the user.

[1865] Step 9: Long-term analysis of emotional data

[1866] Server: Regularly collects emotional data and stores it in a database.

[1867] Server: Analyzes user learning history and sentiment data to propose measures for improving long-term learning efficiency.

[1868] Terminal: Based on the analysis results, it suggests a learning plan, break times, and learning materials that are suitable for the user.

[1869] By executing each step in detail in this way, users can learn efficiently and effectively. In particular, the introduction of an emotion engine enables flexible learning support that responds to the user's emotions.

[1870] (Example 2)

[1871] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1872] Traditional learning support systems have limitations in providing appropriate learning plans tailored to individual users' learning goals and academic levels, and in particular, they lack individualized support that takes into account the user's emotional state. This has led to challenges such as users being unable to maximize their learning effectiveness due to stress and decreased motivation. Furthermore, in traditional systems, tracking learning progress and adjusting plans often required manual intervention, resulting in inefficient support.

[1873] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1874] In this invention, the server includes means for receiving input of learning goals and academic ability levels from the user and generating an individualized learning plan; means for receiving questions from the user and generating answers to those questions using generative artificial intelligence; means for providing learning materials for multiple subjects based on the user's selection; means for tracking the user's learning progress and automatically adjusting the learning plan as needed; means for collecting relevant information from databases and the internet in response to the user's information requests and summarizing it using generative artificial intelligence; and means for recognizing the user's emotions and adjusting the learning plan accordingly. This enables flexible learning support based on the learning needs of each individual user.

[1875] A "learning objective" is the specific learning goal that the user wants to achieve.

[1876] "Academic ability level" is an indicator that shows the user's current level of academic ability and knowledge.

[1877] A "learning plan" is a combination of a schedule and learning materials created based on the user's learning goals and academic level, designed to facilitate effective learning.

[1878] "Generative artificial intelligence" is an artificial intelligence technology that generates responses to user questions and requests.

[1879] "Multi-subject learning materials" refer to learning materials that cover multiple subjects, and are provided according to the subjects selected by the user.

[1880] "Learning progress" is an indicator that shows how far a user has progressed in their learning.

[1881] An "information request" is a request that a user sends to seek specific information or knowledge.

[1882] A "database" is a digital storage system used to manage and organize information and materials necessary for learning.

[1883] An "emotion engine" is a system that recognizes the user's emotional state and adjusts the learning plan based on that state.

[1884] The learning center system of the present invention provides the following main functions to effectively support the user's learning. This system is established through the interaction of a server, terminals, and users. Specific embodiments of the system based on the claims are shown below.

[1885] 1. User signup and login

[1886] The server provides sign-up and login functionality to authenticate users accessing the tutoring school's website or app. During new user registration, users enter information such as their name, email address, and password, which the server stores in a database. During login, the server authenticates the user based on the information in the database.

[1887] Specific example: A primary school student registers for the system, then logs in and accesses the dashboard.

[1888] 2. Creating a study plan

[1889] The server receives information about the user's learning goals and academic level, and generates an individualized learning plan. The server executes a pre-configured algorithm to generate the optimal learning schedule and materials, and stores them in a database.

[1890] Specific example: If a middle school student user enters "improve math skills" as their goal, the server generates a weekly study schedule based on the user's academic level and displays it on their device.

[1891] 3. Answering questions

[1892] If a user encounters a question during the learning process, they input the question. The device sends the question to the server. The server uses generative artificial intelligence to analyze the question and generate an answer. This generated answer is then sent to the device and displayed to the user.

[1893] Specific example: When a middle school student asks, "I don't know how to solve quadratic equations," the server uses generative artificial intelligence to provide a detailed explanation and immediately returns the answer to the user.

[1894] 4. Providing teaching materials

[1895] The server provides the corresponding learning materials according to the subject selected by the user. The server searches the database for the appropriate materials and sends them to the terminal.

[1896] Specific example: When a user selects the "Biology" field under "Science," the server sends video materials and text documents related to biology to the user's device and displays them.

[1897] 5. Tracking learning progress and adjusting plans

[1898] The server tracks the user's learning progress in a database and automatically adjusts the learning plan as needed. Based on the user's completed learning content and progress, it provides new schedules and supplementary materials.

[1899] Specific example: If a user finishes basic math problems earlier than planned, the server notifies the user to move on to the next learning step, which is applied problems, and updates the learning plan.

[1900] 6. Access to Information

[1901] The server collects relevant information from databases and the internet in response to user information requests. It then uses generative artificial intelligence to summarize the information and present it to the user in an easily understandable format.

[1902] Specific example: If a user searches for "an overview of the French Revolution," the server collects relevant information and provides the user with a summarized text.

[1903] 7. Responses based on the emotion engine

[1904] The server uses an emotion engine to recognize the user's emotions. The emotion engine collects user emotion data using facial recognition and voice analysis, and adjusts the learning plan based on this data. The emotion data is stored in a database and periodically analyzed along with the user's learning history.

[1905] Specific examples: If a user is experiencing stress while learning, the emotion engine will recognize this, and the server will recommend games or short breaks to help the user relax. If learning efficiency is low during certain times, the plan will be adjusted to include lighter subjects during those times.

[1906] This allows the tutoring system to provide flexible learning support tailored to the individual needs of users, enabling efficient and effective learning.

[1907] Example of a prompt

[1908] "Please tell me about specific methods for detecting the stress that middle school students experience while studying and suggesting appropriate responses."

[1909] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1910] Program processing steps

[1911] Step 1: User Signup

[1912] 1. Input: The user accesses the tutoring center's website or app and enters their name, email address, and password.

[1913] 2. Specific operation: The terminal sends the entered information to the server.

[1914] 3. Data processing: The server receives the information and stores it in the database.

[1915] 4. Output: The server sends a registration completion message to the terminal.

[1916] 5. Specific action: The device displays "Registration complete."

[1917] Step 2: User Login

[1918] 1. Input: The user enters their email address and password on the website or app's login screen.

[1919] 2. Specific operation: The terminal sends the entered information to the server.

[1920] 3. Data processing: The server accesses the database and verifies that the user information matches the input information.

[1921] 4. Output: The server sends a login success signal to the terminal.

[1922] 5. Specific action: The device displays the user's dashboard.

[1923] Step 3: Create a study plan

[1924] 1. Input: The user enters their learning goals and current academic level.

[1925] 2. Specific actions: The terminal sends this information to the server.

[1926] 3. Data processing: The server uses algorithms to generate individual learning plans and stores them in the database.

[1927] 4. Output: The server sends the generated training plan to the terminal.

[1928] 5. Specific actions: The device displays the learning plan to the user.

[1929] Step 4: Answering Questions

[1930] 1. Input: The user enters a question.

[1931] 2. Specific action: The terminal sends the question to the server.

[1932] 3. Data processing: The server uses a generative AI model to analyze the question and generate an answer.

[1933] 4. Output: The server sends the generated response to the terminal.

[1934] 5. Specific action: The device displays the answer to the user.

[1935] Step 5: Provide teaching materials

[1936] 1. Input: The user selects the subject or field they wish to study.

[1937] 2. Specific action: The terminal sends that information to the server.

[1938] 3. Data processing: The server searches the database for appropriate teaching materials.

[1939] 4. Output: The server sends the selected learning materials to the terminal.

[1940] 5. Specific operation: The device displays the learning materials to the user.

[1941] Step 6: Tracking learning progress and adjusting plans

[1942] 1. Input: The user enters learning progress information.

[1943] 2. Specific action: The terminal sends that information to the server.

[1944] 3. Data processing: The server analyzes the learning progress data and updates the learning plan as needed.

[1945] 4. Output: The server sends the updated learning plan to the terminal.

[1946] 5. Specific action: The device displays a new learning plan to the user.

[1947] Step 7: Responding with an emotional engine

[1948] 1. Input: The emotion engine captures the user's facial expressions and voice data during the learning process.

[1949] 2. Specific action: The terminal sends this data to the server.

[1950] 3. Data processing: The server uses an emotion engine to analyze the user's emotions and determine if the learning plan needs to be adjusted.

[1951] 4. Output: The server sends the adjusted learning plan results, based on the user's emotions, to the terminal.

[1952] 5. Specific actions: The device displays a learning plan and relaxation menu tailored to the user.

[1953] In this way, the tutoring system, through the coordination of users, terminals, and servers, provides flexible learning support tailored to individual needs and enables efficient and effective learning by responding appropriately to the user's emotions.

[1954] (Application Example 2)

[1955] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1956] Traditional learning systems have a problem of reduced learning effectiveness because they provide a uniform learning plan without considering the learner's emotional state. Furthermore, the lack of flexible adjustments in response to emotional changes leads to increased learning stress. In addition, since emotional states affect work efficiency among factory workers, there is a need for efficient work support utilizing emotional data.

[1957] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[1958] In this invention, the server includes means for receiving input of learning goals and academic ability levels from the user and generating individual learning plans; means for receiving questions from the user and generating answers to those questions using generative artificial intelligence; means for providing learning materials for multiple subjects based on the user's selection; means for tracking the user's learning progress and automatically adjusting the learning plan as needed; means for collecting relevant information from databases and the internet in response to the user's information requests and summarizing it using generative artificial intelligence; means for collecting emotional data from the user's facial expressions and voice and determining their emotional state using an emotion recognition model; and means for flexibly adjusting the learning plan based on the determined emotional state. This enables individualized responses that are tailored to the emotions of learners and workers.

[1959] A "user" refers to a learner or factory worker who uses the system.

[1960] "Learning objectives" are specific learning goals that the user wants to achieve.

[1961] "Academic ability level" refers to the user's current level of understanding and knowledge regarding learning.

[1962] An "individualized learning plan" refers to a user-specific learning schedule and content created based on the user's learning goals and academic level.

[1963] "Generative artificial intelligence" refers to artificial intelligence technology that generates answers to questions, summaries of information, and other data based on large amounts of data.

[1964] "Multi-subject learning materials" refer to learning materials that cover multiple subjects, including videos, textbooks, and workbooks.

[1965] "Learning progress" refers to the user's learning progress and indicates how far they have progressed in their learning.

[1966] A "database" is a digital repository for information, where various types of data such as user information, learning content, and questions and answers are stored.

[1967] The "Internet" is a vast source of information available online, and a means of searching for answers to users' information requests.

[1968] To "summarize" means to put detailed information into a concise and easy-to-understand format.

[1969] "Emotional data" refers to digital information about a user's emotional state, obtained from their facial expressions and voice.

[1970] An "emotion recognition model" is a machine learning or deep learning model that performs facial recognition and voice analysis to determine a user's emotions.

[1971] "Emotional state" refers to the psychological state a user experiences while learning or working, and includes stress, joy, sadness, and other similar emotions.

[1972] "Flexibly adjusting the learning plan" means changing the content and order of learning and tasks to reflect the user's current emotional state.

[1973] The system of the present invention provides multiple functions to effectively support user learning. This system includes an emotion engine that recognizes the user's emotional state and adjusts the learning plan accordingly.

[1974] 1. User signup and login

[1975] The server provides signup and login functionality to authenticate users accessing the tutoring school's website or mobile app. Users enter information such as their name, email address, and password during registration, which is stored in the database. During login, the server authenticates the user using the information in the database.

[1976] 2. Creating a study plan

[1977] The server receives information about the user's learning goals and academic level, and generates an individualized learning plan based on this information. It generates the optimal learning schedule and materials based on an algorithm and stores them in a database.

[1978] 3. 24-hour support for questions

[1979] If a user has questions during the learning process, they can input them using their device. The device sends the question to the server, which uses generative artificial intelligence to analyze the question and generate an answer. The generated answer is then sent back to the device and displayed to the user.

[1980] 4. Provision of teaching materials covering multiple subjects

[1981] The server provides learning materials corresponding to the subject selected by the user. It searches the database for appropriate materials, sends them to the terminal, and displays them to the user.

[1982] 5. Tracking learning progress and adjusting plans

[1983] The server tracks the user's learning progress in a database and automatically adjusts the learning plan as needed. Based on the user's completed learning content and progress, it provides new schedules and supplementary materials.

[1984] 6. Efficient Information Access

[1985] The server collects relevant information from databases and the internet in response to user information requests, and summarizes the information using generative artificial intelligence. It then presents the information to the user in an easy-to-understand manner.

[1986] 7. Emotion recognition and learning plan adjustment using an emotion engine.

[1987] The server uses an emotion engine to recognize the user's emotional state during training. The emotion engine collects user emotional data using facial recognition and speech analysis, and uses an emotion recognition model to determine the emotional state. Based on the results, it flexibly adjusts the training plan.

[1988] Hardware and software used

[1989] The emotion recognition feature, which is part of this system, uses the following hardware and software.

[1990] Hardware: Smart glasses or cameras (e.g., Google Glass)

[1991] Software: Emotion recognition model (using Keras), OpenCV for face recognition

[1992] Specific example

[1993] For example, suppose a factory worker is wearing smart glasses while working. If the server can determine the worker's current stress level from their facial expressions, it will recognize this and automatically adjust the worker's work plan. For instance, if the worker is in a high-stress state requiring immediate attention, the server might reduce the workload or recommend a short break.

[1994] Example of a prompt

[1995] Design a smart work assistant application that analyzes employees' facial expressions and emotions in real time and adjusts work plans accordingly. Specifically, it uses a camera built into smart glasses to recognize the employee's face, determines their emotions using an emotion recognition model, and adjusts their work based on that emotion data. For example, if an employee is feeling stressed, the system should recommend relaxing tasks or breaks.

[1996] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1997] Step 1:

[1998] The device uses its camera to capture the user's face. The image data is acquired and converted to grayscale as a preprocessing step. This prepares the data necessary for face recognition.

[1999] Input: User's face image

[2000] Output: Grayscale facial image data

[2001] Specific operation: The smart glasses' camera captures a facial image in real time, and OpenCV is used to convert the image to grayscale.

[2002] Step 2:

[2003] The device performs facial recognition and identifies the facial region. The image of the facial region is resized to a standard size and converted to the format required by the model.

[2004] Input: Grayscale facial image data

[2005] Output: Resized face region image data

[2006] Specific operation: Use a face recognition algorithm (e.g., Haar Cascade) to obtain the coordinates of the face, and resize the face area to a standard size (e.g., 48x48 pixels).

[2007] Step 3:

[2008] The device inputs facial image data into an emotion recognition model, which then determines the emotion. The model outputs an emotion label and its corresponding probability.

[2009] Input: Resized facial region image data

[2010] Output: Sentiment labels and probabilities

[2011] Specific operation: Resized image data is input into an emotion recognition model using Keras, and the emotion determination result is obtained. For example, an output such as "Happy: 0.85, Sad: 0.10" may be obtained.

[2012] Step 4:

[2013] The device sends the assessment result to the server. The server adjusts the learning plan based on the emotional state.

[2014] Input: Emotion labels and probabilities

[2015] Output: Instructions for adjusting the learning plan

[2016] Specific operation: The emotion recognition results are sent to the server, which executes an algorithm to generate a learning or work plan appropriate to the emotional state. For example, if a stressed state is detected, a recommendation for a break or assignment of light work may be made.

[2017] Step 5:

[2018] The server sends the adjusted learning plan to the terminal. The terminal displays the new learning or work plan to the user.

[2019] Input: Learning plan with adjustment instructions

[2020] Output: New learning plan displayed on the terminal

[2021] Specific operation: The server sends a newly generated learning plan to the terminal, which then displays it on the user's screen. For example, a message such as "You have 10 minutes until your next break" might be displayed.

[2022] 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.

[2023] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[2024] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[2025] 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.

[2026] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[2027] 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.

[2028] 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.

[2029] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[2030] 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."

[2031] 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.

[2032] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[2033] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[2034] 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.

[2035] 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.

[2036] 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.

[2037] 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.

[2038] 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.

[2039] 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.

[2040] 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.

[2041] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[2042] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[2043] The following is further disclosed regarding the embodiments described above.

[2044] (Claim 1)

[2045] A means for receiving input from users regarding learning goals and academic ability levels, and generating individual learning plans,

[2046] A means of receiving questions from users and generating answers to those questions using generative artificial intelligence,

[2047] A means of providing multi-subject learning materials based on user selection,

[2048] A means to track the user's learning progress and automatically adjust the learning plan as needed,

[2049] A means of collecting relevant information from databases and the internet in response to a user's information request and summarizing it using generative artificial intelligence,

[2050] A system that includes this.

[2051] (Claim 2)

[2052] The system according to claim 1, wherein the individual learning plan generation means executes an algorithm based on the user's learning goals and academic level.

[2053] (Claim 3)

[2054] The system according to claim 1, wherein the means for tracking the user's learning progress stores the learning content completed by the user in a database and adjusts the plan according to the progress.

[2055] "Example 1"

[2056] (Claim 1)

[2057] A means for receiving input from users regarding learning goals and academic ability levels, and generating individual learning plans,

[2058] A means of receiving questions from users and generating answers to those questions using generative artificial intelligence,

[2059] A means of providing multi-subject learning materials based on user selection,

[2060] A means to track the user's learning progress and automatically adjust the learning plan as needed,

[2061] A means of collecting relevant information from databases and the internet in response to a user's information request and summarizing it using generative artificial intelligence,

[2062] A means to record the learning content completed by the user and update the learning plan according to the learning progress,

[2063] A means of analyzing user information requests and summarizing relevant information using a generative artificial intelligence model,

[2064] A system that includes this.

[2065] (Claim 2)

[2066] The system according to claim 1, wherein the individual learning plan generation means executes an algorithm based on the user's learning goals and academic level.

[2067] (Claim 3)

[2068] The system according to claim 1, wherein the means for tracking the user's learning progress stores the learning content completed by the user in a database and adjusts the plan according to the progress.

[2069] "Application Example 1"

[2070] (Claim 1)

[2071] A means for receiving user input regarding maintenance objectives and skill levels, and generating individual maintenance plans,

[2072] A means of receiving questions from users and generating answers to those questions using generative artificial intelligence,

[2073] A means of providing educational materials in multiple fields based on user selection,

[2074] A means to track user progress and automatically adjust the plan as needed,

[2075] A means of collecting relevant information from databases and the internet in response to a user's information request and summarizing it using generative artificial intelligence,

[2076] A system that includes this.

[2077] (Claim 2)

[2078] The system according to claim 1, wherein the individual maintenance plan generation means executes an algorithm based on the user's maintenance goals and skill level.

[2079] (Claim 3)

[2080] The system according to claim 1, wherein the user's progress tracking means saves the maintenance details completed by the user in a database and adjusts the plan according to the progress status.

[2081] "Example 2 of combining an emotion engine"

[2082] (Claim 1)

[2083] A means for receiving input from users regarding learning goals and academic ability levels, and generating individual learning plans,

[2084] A means of receiving questions from users and generating answers to those questions using generative artificial intelligence,

[2085] A means of providing multi-subject learning materials based on user selection,

[2086] A means to track the user's learning progress and automatically adjust the learning plan as needed,

[2087] A means of collecting relevant information from databases and the internet in response to a user's information request an...

Claims

1. A means for receiving input from users regarding learning goals and academic ability levels, and generating individual learning plans, A means of receiving questions from users and generating answers to those questions using generative artificial intelligence, A means of providing multi-subject learning materials based on user selection, A means to track the user's learning progress and automatically adjust the learning plan as needed, A means of collecting relevant information from databases and the internet in response to a user's information request and summarizing it using generative artificial intelligence, A system that includes this.

2. The system according to claim 1, wherein the individual learning plan generation means executes an algorithm based on the user's learning goals and academic level.

3. The system according to claim 1, wherein the means for tracking the user's learning progress stores the learning content completed by the user in a database and adjusts the plan according to the progress.

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