System

Abstract

To provide a system capable of improving an overall learning level by providing a AI home teacher capable of inexpensively coping with personal needs by utilizing the Internet.SOLUTION: The method includes the following steps: a user starts an application and inputs login information; a terminal sends the login information to a server; the server acquires personal information of the user from a database; the server generates a learning plan based on a learning record and progress of the user; the server sends the generated learning plan to the terminal; the terminal presents a learning task based on the learning plan to the user; an AI tutor module supports the user in real time during learning of the user; the terminal sends learning progress data of the user to the server; the server analyzes the data and adjusts a next learning plan; and the server generates content for maintaining motivation of the user and sends the content to the terminal.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Conventional educational methods and in-company support have had the problem of not being able to fully accommodate individual learning paces and styles. This is particularly true for families who cannot afford cram schools or private tutors, as limited learning opportunities are a major issue. It has also been difficult for companies to provide centralized support for individual employees' career plans and mental and healthcare consultations. This invention aims to improve overall learning levels and provide efficient support within companies by providing AI private tutors and AI secretaries that can respond to individual needs at low cost using the Internet. [Means for solving the problem]

[0005] The present invention provides a system including the following means: a means for a user to launch an application and input login information; a means for a terminal to transmit the login information to a server; a means for the server to retrieve the user's personal information from a database; a means for the server to generate a study plan based on the user's study record and progress; a means for the server to transmit the generated study plan to the terminal; a means for the terminal to present study tasks based on the study plan to the user; a means for an AI tutor module to provide real-time support to the user while studying; a means for the terminal to transmit the user's study progress data to the server; a means for the server to analyze the data and adjust the next study plan; a means for the server to generate content to maintain the user's motivation and transmit it to the terminal; a means for the server to analyze the user's request using natural language processing technology and generate an appropriate plan and answer; a means for the terminal to display the plan and answer generated by the server to the user; and a means for the terminal to transmit user feedback to the server, which uses the feedback to improve the quality of future advice. This system allows students to receive individualized study support, thereby improving their learning efficiency, and enables companies to provide efficient career planning and mental health and healthcare support to employees.

[0006] "User" refers to an individual or member of an organization who uses the system, and specifically includes students, corporate employees, etc.

[0007] An "application" is software that users operate on their terminals, providing an interface for displaying learning tasks and career plans.

[0008] "Login information" refers to authentication information for a user to access a system, and typically includes an ID and password.

[0009] A "terminal" is a device on which an application is installed, and includes smartphones, tablets, PCs, etc.

[0010] A "server" is a back-end system that receives requests from terminals and provides the necessary data.

[0011] "Personal information" refers to data about the user, including grade level, learning status, learning goals, etc.

[0012] A "database" is an information management system for storing user information, learning records, and the like.

[0013] "Study record" is data on the user's learning history and progress.

[0014] A "learning plan" is a schedule of specific learning tasks generated by the server based on the user's learning progress.

[0015] A "learning task" is a specific learning activity or assignment assigned to a user.

[0016] The "AI Tutor Module" is a part of an artificial intelligence program that provides real-time support to users while they learn.

[0017] "Progress data" is data relating to the user's learning progress and level of understanding.

[0018] "Natural language processing technology" is a computer technology for analyzing and understanding human language.

[0019] "Feedback" refers to the opinions and reactions that users input regarding the advice and plans provided.

[0020] "Motivation maintenance content" refers to content that provides encouragement and motivation to increase the user's motivation to learn.

[0021] A "career plan" is a future career plan created based on the user's work history data and current skill set.

[0022] "Mental health consultation" refers to consultation regarding the user's psychological health condition.

[0023] A "healthcare consultation" is a consultation regarding the user's physical health condition. [Brief explanation of the drawings]

[0024] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0025] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0026] First, the terms used in the following description will be explained.

[0027] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0028] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0029] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0030] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0031] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0032] [First embodiment]

[0033] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0034] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0035] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0036] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0037] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0038] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0039] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0040] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0041] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0042] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0043] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0044] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0045] The system of the present invention is an AI system that allows users to receive learning support tailored to their individual learning pace and style, and allows companies to efficiently provide advice on career plans and mental and healthcare matters for individual employees. Specific embodiments of this system are described below.

[0046] Implementation of an AI tutor for students

[0047] The user launches the application

[0048] First, a user launches an application on a device such as a smartphone or tablet and enters their login information. The device sends this login information to the server, which then retrieves the user's personal information from a database.

[0049] The server generates the lesson plan

[0050] The server generates a study plan based on the user's past grades and learning progress. This study plan includes specific tasks and schedules for the user to study effectively. The server sends the generated study plan to the terminal, which displays it to the user.

[0051] Presenting and supporting learning tasks

[0052] When a user starts a learning task, the device launches the AI ​​tutor module. When the user inputs a question or concern, the device sends it to the server, which analyzes it using natural language processing technology and generates appropriate explanations and examples. The server then sends the generated explanations and examples to the device, which displays them to the user.

[0053] Learning progress and motivation

[0054] The device collects the user's learning progress data (such as the rate at which questions are answered correctly and the amount of time spent studying) and sends it to the server. The server analyzes this data and adjusts the next study plan. The server also analyzes the user's learning data, and if it determines that motivation is declining, it generates encouraging messages and motivational content, which it sends to the device and displays to the user.

[0055] Implementation of an AI secretary for businesses

[0056] The user launches the application

[0057] A user launches a desktop or mobile application and enters their login information. The device sends this login information to a server, which retrieves the user's personal information from a database.

[0058] Conversation with an AI secretary

[0059] When a user asks the AI ​​secretary for advice on training, career planning, mental health, etc., the device receives the user's request via voice recognition or text input. The device then sends the request to a server, which uses natural language processing technology to analyze the request and generate an appropriate plan or response.

[0060] Providing plans and advice

[0061] The server sends the generated plan and advice to the device, which then displays it to the user. For example, if a user asks, "What training courses are recommended for career advancement?", the server generates a list of recommended training courses based on the user's work history and current skill set and sends it to the device.

[0062] Gathering and implementing feedback

[0063] When a user inputs feedback on the provided advice, the device sends the feedback to the server, which analyzes the feedback and uses it as learning data to improve the quality of future advice.

[0064] Specific examples

[0065] As a concrete example, let's say a student uses an application to solve a math problem. The student launches the application, enters their login information, and receives a study plan generated by the server based on their past study data. If the student has questions while working on the assignment, the AI ​​tutor provides real-time explanations. After studying, the device sends progress data to the server, which then adjusts the next study plan. If the student's motivation is declining, encouraging messages are displayed on the device.

[0066] In this way, the system of the present invention is designed to enable students and corporate employees to study effectively and receive support for career planning and mental health.

[0067] The processing flow will be explained below.

[0068] Processing program for AI tutoring for students

[0069] Step 1:

[0070] A user launches an application on a smartphone or tablet.

[0071] A login screen will appear, and the user will enter their ID and password.

[0072] The terminal sends the entered login information to the server.

[0073] Step 2:

[0074] The server receives the login information and retrieves the user's personal information (grade, learning status, learning goals, etc.) from the database.

[0075] The server sends the acquired information to the terminal.

[0076] Step 3:

[0077] The server generates an optimal study plan based on the user's study records and progress.

[0078] The server sends the generated learning plan to the terminal.

[0079] Step 4:

[0080] The device breaks down the study plan received from the server into daily and weekly study tasks and presents them to the user.

[0081] The user confirms the learning task and begins execution.

[0082] Step 5:

[0083] As the user progresses through the learning task, if they come across something they don't understand or have questions about, they can input a question.

[0084] The terminal sends the user's question to the server.

[0085] Step 6:

[0086] The server analyzes the questions it receives using natural language processing technology and generates appropriate answers and example questions.

[0087] The server sends the generated answers and example questions to the terminal.

[0088] Step 7:

[0089] The terminal displays the answers and examples received from the server to the user.

[0090] The user reads and interprets it and continues learning.

[0091] Step 8:

[0092] As the learning progresses, the terminal collects the user's learning progress data (for example, the percentage of correct answers to questions and the time spent studying).

[0093] The terminal transmits the collected progress data to the server.

[0094] Step 9:

[0095] The server analyzes the progress data and adjusts the next learning plan appropriately.

[0096] Furthermore, if the server analyzes the progress data and determines that the user's motivation is declining, it generates encouraging messages and motivational content.

[0097] The server transmits the generated content and messages to the terminal.

[0098] Step 10:

[0099] The device displays encouraging messages and motivational content to the user.

[0100] This will motivate users to continue learning.

[0101] Processing AI secretary programs for businesses

[0102] Step 1:

[0103] A user launches a desktop or mobile application.

[0104] A login screen will appear, and the user will enter their ID and password.

[0105] The terminal sends the entered login information to the server.

[0106] Step 2:

[0107] The server receives the login information and retrieves the user's personal information from a database.

[0108] The server sends the acquired information to the terminal.

[0109] Step 3:

[0110] Users use the application's interface to ask the AI ​​secretary for training advice, career planning, and mental health advice.

[0111] A request is received by the device via voice recognition or text input.

[0112] Step 4:

[0113] The terminal transmits the received request to the server.

[0114] Step 5:

[0115] The server analyzes the request using natural language processing technology and generates an appropriate plan or answer.

[0116] Step 6:

[0117] The server sends the generated plan and answer to the terminal.

[0118] Step 7:

[0119] The terminal displays the plan and answer received from the server to the user.

[0120] For example, if a user asks "What training courses are recommended for career advancement?", the server generates a list of recommended training courses, sends it to the terminal, and displays it to the user.

[0121] Step 8:

[0122] Users provide feedback on the plans and answers provided.

[0123] Feedback is sent by the terminal to the server.

[0124] Step 9:

[0125] The server analyzes the feedback and uses it to improve future plans and advice.

[0126] This will realize a system that allows users to receive effective and efficient support for their individual learning and career plans.

[0127] Example 1

[0128] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0129] Conventional online learning systems and corporate support systems have difficulty responding to the individual needs of each user, and have been unable to provide efficient support for learning, career planning, or mental health consultations. As a result, users' motivation has declined and it has been difficult to provide effective learning support.

[0130] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0131] In this invention, the server includes means for acquiring personal information about the user, means for generating a study plan, means for generating content to maintain motivation, means for the terminal to provide the user with an individual study plan and support content in real time, means for analyzing the user's requests using natural language processing technology and generating appropriate explanations and examples, and means for collecting and analyzing feedback and using it to improve quality in the future. This makes it possible to efficiently provide optimal study support, career planning, and mental health consultations for each user in real time.

[0132] "User" refers to an individual or legal entity that uses an information system.

[0133] "Application" means a software program designed for use by a user.

[0134] "Authentication information" refers to information such as ID and password used when a user logs in.

[0135] "Device" refers to an electronic device (e.g., smartphone, tablet, or PC) on which a user runs an application.

[0136] "Server" refers to a central processing unit that processes user requests and provides the required information and services.

[0137] "Personal Information" means information about a user, including identifiable data (e.g., name, address, grades).

[0138] A "database" refers to data storage for efficiently managing large amounts of data used by an organization or system.

[0139] "Learning history" refers to records of a user's past learning activities and their results.

[0140] "Progress" refers to the progress a user makes toward a particular task or goal.

[0141] A "learning plan" refers to specific learning tasks and schedules generated by the server to achieve the user's learning goals.

[0142] "AI Tutor Module" refers to an artificial intelligence-based software component designed to assist users in learning.

[0143] "Real-time" refers to immediate processing or response without delay.

[0144] "Learning progress data" refers to data that details the results and activities achieved by a user through learning activities.

[0145] "Motivational content" refers to messages and materials provided to keep users excited and interested in their learning or work.

[0146] "Natural language processing technology" refers to artificial intelligence technology for interpreting, understanding, and generating human language.

[0147] "Explanations and examples" refers to supplementary information and sample questions provided to users during their studies.

[0148] "Feedback" refers to ratings and comments provided by users, and is information used to improve system performance and services.

[0149] An "AI assistant" refers to an artificial intelligence-based software component that helps users with career planning, mental health, and other issues.

[0150] "Analysis" refers to the act of examining, understanding, and processing data and information.

[0151] The system of this invention is an AI system that allows users to receive learning support tailored to their individual learning pace and style, and allows companies to efficiently provide advice on career plans and mental and healthcare matters for individual employees. Specific embodiments of this system are described below.

[0152] Implementation of an AI tutor for students

[0153] A user launches the application on their smartphone or tablet and enters their login information. The device then sends this login information to a server. The server connects to a database to retrieve the user's personal information, past grades, and learning progress. The server then uses the retrieved data to analyze it using a generative AI model (e.g., GPT-4) and generate a customized learning plan for the user. This learning plan includes specific tasks and a schedule. The server then sends the generated learning plan to the device, which then displays it to the user.

[0154] When the user begins a task according to the learning plan, the AI ​​tutor module is activated and provides real-time support. If a question arises during learning, the user can enter it into the device's question input field. For example, they could enter, "Please tell me how to solve a quadratic equation." This question is sent to the server, which uses natural language processing technology to analyze the question and generate the most appropriate answer or example problem. This is then sent to the device and displayed to the user.

[0155] Learning progress is recorded in real time by the device and periodically sent to the server. The server analyzes this data and adjusts the next learning plan as needed. For example, if the user's understanding of a particular topic is lacking, tasks to reinforce the related topic will be added. Also, if the server determines that the user's motivation is declining, it will generate content to maintain motivation (encouraging messages or motivational content), send it to the device, and display it to the user.

[0156] Implementation of an AI secretary for businesses

[0157] A user launches a desktop or mobile application and enters their login information. The device sends this login information to a server, which connects to a database to retrieve personal information about the user, such as their work history and skill set. The user enters their consultation or question into the application's input fields, which the device then sends to the server.

[0158] For example, a user might input, "Please recommend some training courses." The server analyzes this request using natural language processing technology and generates a list of training courses that are most suitable for the user. This list is then sent to the terminal and displayed to the user. Furthermore, if the user inputs feedback about the usefulness of the advice provided, the terminal sends that feedback to the server. The server analyzes the feedback and uses it to improve the quality of future advice.

[0159] Specific examples

[0160] For example, suppose a student uses an application to solve a math problem. The student launches the application, enters their login information, and receives a study plan generated by the server based on their past study data. If the student has questions while working on the assignment, the AI ​​tutor provides real-time explanations. After studying, the device sends progress data to the server, which then adjusts the next study plan. If the student's motivation is declining, encouraging messages are displayed on the device.

[0161] As an example of a prompt sentence, if you enter, "I want to solve a quadratic equation problem in math. Please tell me how to solve it and the specific steps," the server will use a generative AI model to generate an appropriate step-by-step guide and display it on the device to help the user solve the problem.

[0162] In this way, the system of the present invention is designed to enable students and corporate employees to study effectively and receive support for career planning and mental health.

[0163] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0164] Step 1:

[0165] A user launches an application and logs in. The user taps the icon on their smartphone or tablet to launch the application, enters their ID and password on the login screen, and presses the login button. The device sends this authentication information to the server. The server connects to the database to confirm the authentication information and obtain the user's personal information. The information entered here is the login ID and password, and the data output is the authentication result and the user's personal information.

[0166] Step 2:

[0167] The server obtains user information and generates a study plan. After successful authentication, the server retrieves the user's past grades and learning progress from a database. This information is input into a generative AI model (e.g., GPT-4) to generate a study plan for the user. This study plan includes specific tasks and their schedules. The server sends this generated study plan to the device. The input is the user's study history and progress data, and the output is a study plan optimized for the user.

[0168] Step 3:

[0169] The terminal displays the learning plan to the user. The terminal receives the learning plan sent from the server and displays it on the screen. The user can check the learning plan on the terminal screen and confirm the specific learning tasks and schedule. The learning plan is received as input, and the content of the learning plan displayed to the user is output.

[0170] Step 4:

[0171] The user begins a learning task. The user begins a specific task (e.g., solving a math problem) according to the learning plan. If the user has a question, they enter it into the question input field on the device. For example, they might enter, "Please tell me how to solve a quadratic equation."

[0172] Step 5:

[0173] The terminal sends the user's question to the server. The terminal receives the question entered by the user and sends it to the server. The input information is the content of the user's question, and the output data is the question sent to the server.

[0174] Step 6:

[0175] The server analyzes the user's question and generates an answer. The server analyzes the received question using natural language processing technology and generates the optimal answer or example problem. A generative AI model is used in this process. The server sends the generated answer or example problem to the terminal. The input is the user's question, and the output is the analyzed answer or example problem.

[0176] Step 7:

[0177] The terminal displays the answers from the server to the user. The terminal displays the answers and example questions received from the server to the user. The user can use this as a reference to continue learning. The input is the answers and example questions sent from the server, and the output is the answers and example questions displayed to the user.

[0178] Step 8:

[0179] The device records learning progress data and sends it to the server. As the user progresses with their studies, the device records learning progress data (correct answer rate for questions, study time). This data is periodically sent to the server. The input is the user's learning progress data, and the output is the transmission of progress data to the server.

[0180] Step 9:

[0181] The server analyzes the learning progress data and adjusts the next learning plan. The server analyzes the received learning progress data and adjusts the next learning plan. If the user lacks understanding of a specific topic, it adds reinforcement tasks. The input is the learning progress data, and the output is the adjusted next learning plan.

[0182] Step 10:

[0183] The server generates content to maintain motivation and sends it to the device. The server analyzes learning progress data, and if it determines that the user's motivation is declining, it generates encouraging messages and motivating content and sends it to the device. The input is learning progress data, and the output is the generated content to maintain motivation.

[0184] (Application example 1)

[0185] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0186] Conventional systems were unable to provide information or recommend products that adequately met customer needs in brick-and-mortar stores. It was also difficult to manage the progress and maintain motivation of students and employees, resulting in a lack of effective educational support and mental health support. Furthermore, the system was also inadequate in recommending appropriate products and services based on health status, creating challenges in improving customer satisfaction and managing employee health.

[0187] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0188] In this invention, the server includes: a means for a user to launch an application and input login information; a means for the terminal to send the login information to the server; a means for the server to retrieve the user's personal information from a database; a means for the server to generate a study plan based on the user's study record and progress; a means for the server to send the generated study plan to the terminal; a means for the terminal to present study tasks to the user based on the study plan; a means for an AI tutor module to provide real-time support to the user while he or she is studying; a means for the terminal to send the user's study progress data to the server; a means for the server to analyze the data and adjust the next study plan; a means for the server to generate content to maintain the user's motivation and send it to the terminal; and a means for selecting products, checking inventory, and suggesting recommended products in real time when a customer visits a physical store. This enables more efficient customer service in physical stores and improved customer satisfaction.

[0189] An "application" is software that is operated by a user and runs on a variety of terminals.

[0190] "Login information" is information used to authenticate a user, typically a combination of a username and password.

[0191] "Terminal" refers to the device that a user uses to access an application, including smartphones, tablets, and personal computers.

[0192] A "server" is a computer system that runs on the back end of an application, accessing a database and performing processing.

[0193] A "database" is a data storage system for managing users' personal information, learning records, product inventory information, and so on.

[0194] "Study record" is data showing the records and grades of the user's studies to date.

[0195] A "study plan" is a list of specific study schedules and tasks that are generated based on the user's progress and goals.

[0196] A "learning task" is a specific learning activity or problem-solving task that a user should perform based on a learning plan.

[0197] The "AI Tutor Module" is an artificial intelligence system that provides real-time support and answers questions while users are learning.

[0198] "Study progress data" is data that indicates how far the user has progressed in their studies, and includes the percentage of correct answers to questions and the study time.

[0199] "Motivation maintenance content" refers to messages and content generated to increase a user's motivation to learn.

[0200] "Product selection" is the process by which customers identify products they will consider purchasing in a physical store.

[0201] "Inventory check" is the task of checking the quantity and status of products in physical stores and warehouses.

[0202] "Recommended products" is the process of recommending appropriate products based on a customer's needs and preferences.

[0203] "Natural language processing technology" is a technology that allows computers to understand and analyze human language.

[0204] "Feedback" refers to the evaluation or opinion that a user inputs regarding the plan or advice provided.

[0205] "AI Secretary" is an artificial intelligence system that supports users with training, career planning, mental health counseling, and more.

[0206] "Speech recognition" is a technology that converts a user's speech into text.

[0207] A "prompt" is text that is input into a generative AI model and is an instruction statement to obtain an appropriate generated result.

[0208] A "generative AI model" is an artificial intelligence model that generates text and answers based on a prompt.

[0209] The system of the present invention is a system that allows users to receive support tailored to their individual learning pace and needs, and provides useful information even in physical stores. Specific embodiments of the system are described below.

[0210] System Configuration

[0211] The system mainly consists of a terminal, a server, a database, and a generative AI model. Terminals can be devices such as smartphones, tablets, and PCs. The server is a computer system that accesses the database and performs the necessary processing, and can be implemented using Python and the Flask framework. The generative AI model is built using natural language processing technologies such as HuggingFace's Transformers.

[0212] Login process

[0213] A user launches an application on a terminal and enters login information (user name, password). This information is sent from the terminal to the server, which retrieves the user's personal information from a database. This authenticates the user and allows them to access the system.

[0214] Generate a lesson plan

[0215] The server generates a learning plan based on the user's past learning records and current progress. This learning plan includes specific tasks and schedules. The generated learning plan is sent to the device and displayed to the user.

[0216] Learning task presentation and real-time support

[0217] When a user starts a learning task, the device launches the AI ​​tutor module. When the user enters a question or concern, the information is sent to the server. The server uses natural language processing technology to analyze the question and generate appropriate explanations and examples. The generated explanations are sent to the device and provided to the user.

[0218] Learning progress and maintaining motivation

[0219] The device collects the user's learning progress (correct answer rate, study time) and sends it to the server. The server analyzes this data and adjusts the next learning plan. If the server determines that the user's motivation is declining, it generates encouraging messages and motivational content and sends them to the device.

[0220] Application in physical stores

[0221] When customers visit a physical store, they can use a terminal (a tablet or smartphone installed in the store) to receive product information, check inventory, and receive recommended products. When a user asks a question about how to select a product or the inventory status, the information is sent to a server, which analyzes it using natural language processing technology and provides the appropriate answer or product suggestion to the terminal.

[0222] Specific examples

[0223] Consider a case where a customer asks, "What products can boost the immune system?" in a physical store. This question is sent from the device to the server, and the server generates a response using a generative AI model. An example of a prompt sentence is "What products can boost the immune system?" As a result, the server recommends an appropriate product (e.g., "vitamin C supplement") and sends that information to the device for display.

[0224] In this way, the system of the present invention integrates the user's learning activities with the provision of information in physical stores, providing effective support.

[0225] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0226] Step 1:

[0227] A user starts an application on a device and enters login information (user name, password). The device sends this login information to the server. Based on this input, the server retrieves the user's personal information from the database and sends it to the device.

[0228] Step 2:

[0229] The server retrieves the user's past learning records and current progress data from the database and generates a new learning plan based on that data. The generated learning plan includes learning tasks and a schedule. This data processing establishes an optimal learning plan for the user. The server then sends the generated learning plan to the terminal, which displays it to the user.

[0230] Step 3:

[0231] The user performs learning tasks based on the displayed learning plan. If a question or doubt arises during learning, the user inputs it. The device sends the input question to the server. To respond to this question, the server uses a generative AI model to analyze the question and generate appropriate answers and example problems. The generated answers are sent to the device and displayed to the user.

[0232] Step 4:

[0233] The device collects the user's learning progress data (correct answer rate, study time) and periodically sends it to the server. The server analyzes this data and dynamically adjusts the next study plan. If the server determines that the user's motivation to study is declining, it generates motivational messages and video content and sends them to the device.

[0234] Step 5:

[0235] When a customer visits a physical store, they use a device (a tablet or smartphone in the store) to input a question about a product (e.g., "What products boost immunity?"). The device sends this question to a server. The server uses a generative AI model to analyze the question and generate appropriate product recommendations and stock status information. Accurate product information is generated by processing the data using this prompt text. The generated information is sent to the device and displayed to the customer.

[0236] Step 6:

[0237] If the customer checks the recommended products and asks more detailed questions, the input is sent to the server in a similar manner, and the server generates an answer and sends it to the terminal. At this step, product selection, inventory check, and recommendation suggestions are performed in real time.

[0238] In this way, at each processing step of the system, the user, device, and server work together to provide efficient support by utilizing generative AI models and prompt sentences.

[0239] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0240] The present invention combines an emotion engine with an AI system that allows individual learners and corporate employees to receive individually customized learning plans, career support, and mental health consultations. A specific embodiment of this system is described below.

[0241] Implementation of an AI tutor for students

[0242] The user launches the application

[0243] First, a user launches an application on a device such as a smartphone or tablet and enters their login information. The device sends this login information to the server, which then retrieves the user's personal information from a database.

[0244] The server generates the lesson plan

[0245] The server generates a learning plan based on the user's past performance and learning progress. This learning plan includes specific tasks and schedules for the user to effectively study. The server sends the generated learning plan to the terminal, which then displays it to the user.

[0246] Presenting and supporting learning tasks

[0247] When a user starts a learning task, the device launches the AI ​​tutor module. When the user inputs a question or concern, the device sends it to the server, which analyzes it using natural language processing technology and generates appropriate explanations and examples. The server then sends the generated explanations and examples to the device, which displays them to the user.

[0248] Emotion engine monitoring

[0249] The device acquires emotional data from the user's facial expressions, voice, input, etc. This data is analyzed by the emotion engine to identify the user's emotional state. The device then transmits the emotional data to the server.

[0250] Learning progress and motivation

[0251] The device collects the user's learning progress data (e.g., percentage of correct answers and study time) and sends it to the server. The server analyzes this data and emotional data and adjusts the next learning plan appropriately. If the server determines that the user's motivation is declining, it generates encouraging messages and motivational content, sends them to the device, and displays them to the user.

[0252] Specific examples

[0253] For example, suppose a student uses an application to solve a math problem. The student launches the application, enters their login information, and receives a study plan generated by the server. If the student has questions while working on the problem, the AI ​​tutor will provide real-time explanations. Furthermore, if the emotion engine detects stress from the student's facial expressions or voice, the server will send and display encouraging messages or content to help them concentrate on the device. After studying, the device will send progress data and emotion data to the server, which will then adjust the next study plan.

[0254] Implementation of an AI secretary for businesses

[0255] The user launches the application

[0256] A user launches a desktop or mobile application and enters their login information. The device sends this login information to a server, which retrieves the user's personal information from a database.

[0257] Conversation with an AI secretary

[0258] When a user requests training advice, career planning, or mental health advice from an AI secretary, the device receives the user's request via voice recognition or text input and sends it to a server, which then uses natural language processing technology to analyze the request and generate an appropriate plan or response.

[0259] Support by Emotion Engine

[0260] When the device receives a request, it acquires emotional data from the user's facial expressions, voice, and input content. The emotion engine analyzes this data and generates a response or plan that corresponds to the user's emotional state.

[0261] Providing plans and advice

[0262] The server sends the generated plans and advice to the device, which then displays them to the user. For example, if a user asks, "What training courses are recommended for career advancement?", the server generates a list of recommended training courses, sends it to the device, and displays it to the user. Additionally, if the emotion engine determines that the user is feeling stressed, it can also provide advice on relaxation methods and mental health.

[0263] Gathering and implementing feedback

[0264] When a user inputs feedback on the provided plan or advice, the device sends the feedback to the server, which analyzes the feedback and uses it to improve the quality of future plans and advice.

[0265] In this way, by combining an emotion engine, the system of the present invention provides learning plans and career plans that correspond to the user's emotional state, thereby achieving more effective and personalized support.

[0266] The processing flow will be explained below.

[0267] Processing program for AI tutoring for students

[0268] Step 1:

[0269] When a user launches an application on their smartphone or tablet, a login screen appears, and the user enters their ID and password. The device then sends the login information to the server.

[0270] Step 2:

[0271] The server receives the login information and retrieves the user's personal information (grade, learning status, learning goals, etc.) from the database. The server then sends the retrieved information to the terminal.

[0272] Step 3:

[0273] The server generates a study plan based on the user's past grades and learning progress, and then sends the generated study plan to the device.

[0274] Step 4:

[0275] The device receives the learning plan from the server, breaks it down into daily and weekly learning tasks, and presents them to the user. The user confirms the learning tasks and begins executing them.

[0276] Step 5:

[0277] When a user has a question or concern while progressing through a learning task, they can input a question, and the device will send the user's question to the server.

[0278] Step 6:

[0279] The server analyzes the received questions using natural language processing technology and generates appropriate answers and examples, which are then sent to the device.

[0280] Step 7:

[0281] The device receives the answers and examples from the server and displays them to the user, who can then confirm them and continue learning.

[0282] Step 8:

[0283] The device acquires emotional data from the user's facial expressions, voice, and input, analyzes it using an emotion engine, identifies the user's emotional state, and sends the data to the server.

[0284] Step 9:

[0285] The device collects the user's learning progress data (such as the rate at which questions are answered correctly and the amount of time spent studying) and sends it to the server. The server analyzes the progress data and emotional data and adjusts the next study plan appropriately.

[0286] Step 10:

[0287] If the server determines that the user's motivation is declining, it generates encouraging messages and motivational content and sends them to the device, which then displays them to the user.

[0288] Processing AI secretary programs for businesses

[0289] Step 1:

[0290] When a user launches a desktop or mobile application, a login screen appears, where the user enters their ID and password, and the device sends the login information to the server.

[0291] Step 2:

[0292] The server receives the login information, retrieves the user's personal information from the database, and sends the retrieved information to the terminal.

[0293] Step 3:

[0294] Users can use the in-app interface to ask the AI ​​secretary for training advice, career planning, and mental health advice, with requests received by the device via voice recognition or text input.

[0295] Step 4:

[0296] The device sends the received request to the server.

[0297] Step 5:

[0298] The server analyzes the request using natural language processing technology and generates an appropriate plan or answer.

[0299] Step 6:

[0300] The device acquires emotional data from the user's facial expressions, voice, and input, and sends it to the server. The emotion engine analyzes this data and provides a plan based on the user's emotional state.

[0301] Step 7:

[0302] The server generates plans and answers and sends them to the device, which then displays them to the user. For example, if a user asks, "What training courses are recommended for my career?", the server generates a list of appropriate training courses, sends it to the device, and displays it to the user.

[0303] Step 8:

[0304] The user enters feedback on the provided plans and answers, which is then sent by the device to the server.

[0305] Step 9:

[0306] The server analyzes the feedback and uses it to improve future plans and advice.

[0307] In this way, the system of the present invention optimizes the user's studies and career plans according to the user's emotional state and provides effective support.

[0308] Example 2

[0309] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0310] In modern education and career support, personalized guidance and support for individual learners and employees is becoming increasingly important. However, existing systems do not adequately provide support that takes into account the user's emotional state, which can reduce the effectiveness of learning and career support. It is also difficult to maintain user motivation, leading to issues such as ineffective implementation of learning and career plans.

[0311] The specification process by the specification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for acquiring the user's personal information from a database, means for generating a study plan based on the user's study record and progress, and means for an emotion engine to identify the user's emotional state and analyze the data. This makes it possible to provide an individualized study plan or career plan that reflects the user's emotional state, thereby enabling effective study and career support while maintaining the user's motivation.

[0312] "User" refers to an individual who uses the Application to receive learning planning and career support services.

[0313] A "terminal" is a device that a user uses to run an application, and includes a smartphone, tablet, desktop, etc.

[0314] "Server" refers to a central computer system that receives, processes, and analyzes data sent by users.

[0315] "Login Information" refers to the authentication information required for a user to access a system, and typically consists of a username and password.

[0316] "Database" refers to an information management system for storing data such as users' personal information, learning records, and progress information.

[0317] A "study plan" refers to specific tasks and schedules generated by the server to help users study effectively.

[0318] "AI Tutor Module" refers to artificial intelligence that provides real-time support to users while they are learning.

[0319] An "emotion engine" refers to technology that acquires and analyzes emotional data from a user's facial expressions, voice, input content, etc.

[0320] "Natural language processing technology" refers to technology that enables computers to understand human language and generate appropriate responses.

[0321] "Feedback" refers to opinions and impressions that users input regarding the plans and advice provided.

[0322] "Motivation" refers to the user's will and motivation to achieve a goal.

[0323] The present invention combines an emotion engine with an AI system that allows individual learners and corporate employees to receive individually customized learning plans, career support, and mental health consultations. This system enables users to use applications to receive effective learning and career support. Specific embodiments of this system are described below.

[0324] Hardware and software used

[0325] 1. Hardware

[0326] Smartphones and tablets (student devices)

[0327] Desktop (devices for corporate employees)

[0328] Server (responsible for data processing and analysis)

[0329] 2. Software

[0330] Application platform (iOS, Android, Windows, etc.)

[0331] Database (e.g. MySQL, PostgreSQL)

[0332] Natural language processing technology (e.g., GPT-3, BERT)

[0333] Machine learning algorithms (e.g., scikit-learn)

[0334] Emotion engines (e.g., Affectiva, Microsoft Emotion API)

[0335] Example of operation

[0336] AI tutors for students

[0337] 1. Launching the application and logging in

[0338] A user launches an application on their smartphone or tablet and enters their login information. The device encrypts the login information and sends it to a server, which then retrieves the user's personal information from a database. The personal information is then sent to the device and displayed to the user.

[0339] 2. Generate a learning plan

[0340] The server uses a machine learning algorithm to generate an optimal study plan based on the user's past performance and learning progress. The generated information is sent to the device and displayed to the user.

[0341] 3. Support for learning tasks

[0342] When a user starts a learning task, the device launches an AI tutoring module (e.g., Dialogflow, GPT-3). When the user inputs a question, the device sends it to the server, which analyzes it using natural language processing technology and generates appropriate explanations and examples. These are then provided to the user via the device.

[0343] 4. Emotion Engine Monitoring

[0344] The device uses a camera and microphone to collect the user's facial expressions, voice, and input, and analyzes them with an emotion engine. The emotion data is sent to a server, and the analysis results are reflected in the next lesson plan.

[0345] 5. Staying motivated

[0346] The server analyzes the user's learning progress and emotional state, and generates encouraging messages and content to maintain motivation. These contents are provided to the user via their device.

[0347] Example prompt:

[0348] "Do you have any questions about the next math assignment? Type in any questions you may have."

[0349] AI secretaries for businesses

[0350] 1. Launching the application and logging in

[0351] A user launches an application on a desktop or mobile device and enters their login information. The device encrypts the login information and sends it to a server, which retrieves their personal information from a database. The retrieved information is then displayed to the user on the device.

[0352] 2. Conversation with an AI secretary

[0353] When a user requests training consultation or career planning through text or voice input, the device sends the request to the server. The server analyzes the request using natural language processing technology and generates an appropriate plan or answer. The generated plan is displayed to the user via the device.

[0354] 3. Support by Emotion Engine

[0355] The device collects the user's facial expressions and voice, analyzes them with an emotion engine, and sends the emotion data to the server, where it is reflected in the response and plan.

[0356] 4. Gather and incorporate feedback

[0357] The user enters feedback on the plan or advice provided, and the device sends the feedback to the server, which analyzes the feedback and uses it for future improvements.

[0358] Example prompt:

[0359] "Do you have a career plan you'd like to discuss? Please enter your specific question."

[0360] This system provides personalized learning and career plans that take into account the user's emotional state, enabling effective support while increasing the user's motivation.

[0361] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0362] AI Tutoring for Students

[0363] Step 1: Launch the application and log in

[0364] 1. The user launches the application on the device and the login screen appears.

[0365] 2. The user enters their login information (username and password).

[0366] Input: Username and Password

[0367] Output: Encrypted login information

[0368] 3. The device sends the encrypted login information to the server.

[0369] Data processing: Encryption of entered login information

[0370] Data calculation: Sending login information to the server

[0371] 4. The server retrieves the user's personal information from the database.

[0372] Input: Encrypted login information

[0373] Output: User's personal information

[0374] 5. The device displays the personal information to the user.

[0375] Data processing: Converting acquired personal information into a display format

[0376] Data calculation: Display on user screen

[0377] Step 2: Generate a lesson plan

[0378] 1. The server generates a study plan using a machine learning algorithm based on the user's past grades and learning progress data.

[0379] Input: User's past performance data, learning progress data

[0380] Output: personalized learning plan

[0381] Data calculation: Generating learning plans using machine learning algorithms

[0382] 2. The server sends the generated learning plan to the device.

[0383] Data calculation: Sending learning plans to the device

[0384] 3. The device displays the lesson plan to the user.

[0385] Data processing: Converting the learning plan into a display format

[0386] Data Calculation: Viewing the Learning Plan

[0387] Step 3: Supporting the learning task

[0388] 1. The user selects a task to begin the learning task.

[0389] Input: Select a learning task

[0390] Output: Details of the selected task

[0391] 2. The device will launch the AI ​​tutor module and display the task details.

[0392] Data calculation: Launching the AI ​​tutor module and generating display content

[0393] 3. The user enters their concern or question via text or voice.

[0394] Input: User's doubts or questions

[0395] Output: Questions and queries

[0396] 4. The device sends the question or inquiry to the server.

[0397] Data calculation: Send data to the server

[0398] 5. The server uses natural language processing technology to analyze the question and generate appropriate explanations and examples.

[0399] Input: Questions and questions

[0400] Output: Explanation and examples

[0401] Data processing: Analysis, explanations and example generation using natural language processing technology

[0402] 6. The server sends the generated explanations and examples to the terminal, which displays them.

[0403] Data calculation: Sending and displaying explanations and examples

[0404] Step 4: Monitoring with the Emotion Engine

[0405] 1. The device uses a camera and microphone to collect the user's facial expressions, voice, and input.

[0406] Input: facial expression data, voice data, input content

[0407] Output: Raw data

[0408] 2. The device's emotion engine analyzes the collected data and identifies the user's emotional state.

[0409] Data processing: analyzing data and identifying emotional states

[0410] Output: Emotional state data

[0411] 3. The device sends the emotional state data to the server.

[0412] Data calculation: Sending emotional state data

[0413] Step 5: Study progress and maintain motivation

[0414] 1. The device collects the user's learning progress data (correct answer rate and study time).

[0415] Input: Learning progress data

[0416] Output: Collected data

[0417] 2. The device sends the collected data to the server.

[0418] Data calculation: Sending progress data

[0419] 3. The server analyzes the progress and emotion data and adjusts the next learning plan.

[0420] Input: Learning progress data, emotion data

[0421] Output: Adjusted learning plan

[0422] Data calculations: analyzing data and adjusting learning plans

[0423] 4. The server generates encouraging messages and content to keep the user motivated and sends them to the device.

[0424] Input: User emotion data

[0425] Output: Support message and content

[0426] Data calculation: generating and sending support messages and content

[0427] 5. The device displays the support message or content received to the user.

[0428] Data processing: converting messages and content into a display format

[0429] Data operations: displaying messages and content

[0430] Processing steps for corporate AI secretary

[0431] Step 1: Launch the application and log in

[0432] 1. A user launches an application on a desktop or mobile app and is presented with a login screen.

[0433] 2. The user enters their login information.

[0434] Input: Username and Password

[0435] Output: Encrypted login information

[0436] 3. The device sends the encrypted login information to the server.

[0437] Data processing: Encryption of entered login information

[0438] Data calculation: Sending login information to the server

[0439] 4. The server retrieves the user's personal information and work history from the database.

[0440] Input: Encrypted login information

[0441] Output: Personal information and work history

[0442] 5. The device displays the user's personal information and work history.

[0443] Data processing: Converting acquired personal information into a display format

[0444] Data calculation: Display on user screen

[0445] Step 2: Interact with the AI ​​secretary

[0446] 1. The user inputs text or voice to consult about training, create a career plan, or receive mental health advice.

[0447] Input: User request

[0448] Output: Request data

[0449] 2. The device sends the user's request to the server.

[0450] Data calculation: Sending request data

[0451] 3. The server uses natural language processing technology to analyze the request and generate an appropriate plan or answer.

[0452] Input: User request data

[0453] Output: Plans and answers

[0454] Data processing: Natural language processing techniques for analysis, planning and answer generation

[0455] 4. The server sends the generated plan and answer to the terminal, which displays it.

[0456] Data calculation: Sending and displaying plans and answers

[0457] Step 3: Support with the Emotion Engine

[0458] 1. The device uses a camera and microphone to collect the user's facial expressions and voice.

[0459] Input: facial expression data, voice data

[0460] Output: Raw data

[0461] 2. The emotion engine analyzes the collected data and identifies the user's emotional state.

[0462] Data processing: analyzing data and identifying emotional states

[0463] Output: Emotional state data

[0464] 3. The device sends the emotional state data to the server.

[0465] Data calculation: Sending emotional state data

[0466] Step 4: Gather and incorporate feedback

[0467] 1. The user enters feedback on the plan or advice provided.

[0468] Input: Feedback

[0469] Output: Feedback data

[0470] 2. The device sends the feedback data to the server.

[0471] Data calculation: Sending feedback data

[0472] 3. The server analyzes the feedback and uses it to improve future plans and advice.

[0473] Input: Feedback data

[0474] Output: Improved plans and advice

[0475] Data processing: Analyzing feedback data, identifying and implementing improvements

[0476] 4. The device displays improved plans and advice to the user.

[0477] Data transformation: Transforming improved plans and advice into a display format

[0478] Data Calculation: Improved plans and advice display

[0479] (Application example 2)

[0480] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0481] Factory workers are prone to experiencing mental fatigue and a loss of concentration and motivation when performing long, monotonous tasks or working in a high-stress environment. If these conditions continue, it can lead to problems such as a decline in work efficiency, an increase in work errors, and even increased safety risks. Conventional methods have made it difficult to monitor workers' mental state in real time and provide appropriate feedback and break suggestions, so a means to effectively solve these problems is needed.

[0482] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0483] In this invention, the server includes means for acquiring the user's personal information from a database, means for generating a study plan based on the user's study record and progress, means for the terminal to acquire emotion data from the user's facial expressions, voice, and input content, and means for the emotion engine to analyze the user's emotion state and send it to the server. This makes it possible to monitor the emotion state of factory workers in real time and provide suggestions for work breaks or encouraging messages as needed.

[0484] "User" refers to an individual who uses the system, including a factory worker or a student.

[0485] An "application" is a software program that a user runs and uses on a terminal.

[0486] "Login information" refers to authentication information for accessing a system, such as a user name and password.

[0487] A "terminal" is a device used by a user, such as a smartphone, tablet, smart glasses, or head-mounted display.

[0488] A "server" is a computer system responsible for processing, storing, and transmitting user data.

[0489] A "database" is a system that organizes and stores data such as users' personal information and learning records.

[0490] A "study plan" is a general term for tasks and schedules designed to help users study efficiently.

[0491] The "AI Tutor Module" is an artificial intelligence system that provides real-time support to users while they are learning.

[0492] "Study progress data" refers to data such as the percentage of correct answers and study time as the user progresses with their studies.

[0493] "Facial expressions, voice, and input content" are data used to analyze the user's emotional state.

[0494] An "emotion engine" is an algorithm or system for analyzing a user's emotional state.

[0495] A "work break suggestion" is a notification or message that encourages a user who is working to take a break.

[0496] "Natural language processing technology" is a technology that analyzes text and voice input by users and generates appropriate answers.

[0497] MODE FOR CARRYING OUT THE INVENTION

[0498] The present invention is a support system for users to perform factory work efficiently and safely. This system uses a device such as smart glasses worn by the user to acquire emotional data from the user's facial expressions and voice, and manages the progress of the work.

[0499] The system is structured as follows: First, the user puts on the smart glasses and launches the application. After the user enters their login information, the device sends this information to the server, which then retrieves the user's personal information from a database. The server is equipped with a high-performance computer, a database, and an AI emotion engine. The software used includes Python, OpenCV, Keras, and TensorFlow.

[0500] The server then generates a work plan for each user and sends it to the device. The work plan includes specific tasks and schedules. As the worker works according to the plan, if a question arises, the worker sends a query to the server via the smart glasses. The server analyzes the query using natural language processing technology, generates an appropriate answer, and sends it to the device. At this time, the user's input and voice are also analyzed.

[0501] The emotion engine analyzes the user's facial expressions and voice in real time to identify their emotional state. For example, if the emotion engine detects stress, it will generate a message suggesting a break or offering encouragement, which will be sent to the user's device and displayed. It also adjusts the next task plan based on learning progress data and emotion data.

[0502] For example, if the emotion engine detects that a factory worker is very tired, the system will send a message like this: "The worker appears tired, so we recommend that you take a break." This will allow workers to take breaks at the appropriate time, improving safety and work efficiency.

[0503] An example of a prompt sentence might be:

[0504] "Transform the following sentence into a feedback message based on emotion data: 'The worker is showing clear signs of fatigue on his face.'"

[0505] The above is a specific embodiment for carrying out the present invention, and by using this system, the safety and efficiency of factory workers can be significantly improved.

[0506] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0507] Step 1:

[0508] The user puts on the smart glasses, launches the application, and enters their login information, which is then sent to the server via the device.

[0509] Input: User login information (username, password)

[0510] Output: Login information sent to the server

[0511] Step 2:

[0512] The server receives the login information and retrieves the user's personal information from a database, making available a data set specific to the user.

[0513] Input: Login information received by the server

[0514] Output: User's personal information

[0515] Step 3:

[0516] The server generates an optimal work plan for the user based on the user's personal information and past learning and work records.

[0517] Input: User's personal information, learning records, work records

[0518] Output: Generated work plan

[0519] Step 4:

[0520] The server sends the generated work plan to the terminal, which then presents the work plan to the user, who then begins work according to the work plan.

[0521] Input: Generated Work Plan

[0522] Output: Submitted work plan, Work plan presentation

[0523] Step 5:

[0524] If a user has any questions or concerns while working, they can input the question via voice or text through the smart glasses, and the device will send it to the server.

[0525] Input: User question (voice or text)

[0526] Output: The question is sent to the server

[0527] Step 6:

[0528] The server uses natural language processing technology to analyze the received question and generate appropriate answers and instructions, thereby resolving the user's doubts.

[0529] Input: User question

[0530] Output: Generated answers and instructions

[0531] Step 7:

[0532] The server sends the generated answers and instructions to the terminal, which displays them to the user, who can then continue working based on the displayed information.

[0533] Input: Generated answers and instructions

[0534] Output: Submitted answers and instructions, presentation of answers and instructions

[0535] Step 8:

[0536] The device acquires emotional data from the user's facial expressions, voice, and input content and sends it to the server.

[0537] Input: User's facial expressions, voice, and input

[0538] Output: Emotion data is sent to the server

[0539] Step 9:

[0540] The server's emotion engine analyzes the emotion data to identify the user's emotional state, and generates break suggestions or encouraging messages as needed based on the analysis results.

[0541] Input: Emotion data

[0542] Output: Identified emotional state, suggestion to take a break, or a message of encouragement

[0543] Step 10:

[0544] The server sends the generated break suggestion or encouraging message to the terminal, which displays it to the user, who can then take a break or continue working.

[0545] Input: Generated break suggestions and encouraging messages

[0546] Output: Break suggestions and encouragement messages sent, display of suggestions and messages

[0547] Step 11:

[0548] The device collects the user's learning progress and emotional data and sends it to the server, which analyzes the data and adjusts the next task plan.

[0549] Input: learning progress data, emotion data

[0550] Output: Adjusted next work plan

[0551] As a specific example of how it works, if the emotion engine detects that a factory worker is very tired, the system will generate a message like this: "The worker appears tired, so we recommend that you take a break." This will allow workers to take breaks at appropriate times, improving safety and work efficiency.

[0552] An example prompt is, "Transform the following sentence into a feedback message based on emotion data: 'The worker is showing obvious signs of fatigue on his face.'"

[0553] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0554] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0555] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0556] [Second embodiment]

[0557] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0558] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0559] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0560] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0561] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0562] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0563] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0564] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0565] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0566] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0567] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0568] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0569] The system of the present invention is an AI system that allows users to receive learning support tailored to their individual learning pace and style, and allows companies to efficiently provide advice on career plans and mental and healthcare matters for individual employees. Specific embodiments of this system are described below.

[0570] Implementation of an AI tutor for students

[0571] The user launches the application

[0572] First, a user launches an application on a device such as a smartphone or tablet and enters their login information. The device sends this login information to the server, which then retrieves the user's personal information from a database.

[0573] The server generates the lesson plan

[0574] The server generates a study plan based on the user's past grades and learning progress. This study plan includes specific tasks and schedules for the user to study effectively. The server sends the generated study plan to the terminal, which displays it to the user.

[0575] Presenting and supporting learning tasks

[0576] When a user starts a learning task, the device launches the AI ​​tutor module. When the user inputs a question or concern, the device sends it to the server, which analyzes it using natural language processing technology and generates appropriate explanations and examples. The server then sends the generated explanations and examples to the device, which displays them to the user.

[0577] Learning progress and motivation

[0578] The device collects the user's learning progress data (such as the rate at which questions are answered correctly and the amount of time spent studying) and sends it to the server. The server analyzes this data and adjusts the next study plan. The server also analyzes the user's learning data, and if it determines that motivation is declining, it generates encouraging messages and motivational content, which it sends to the device and displays to the user.

[0579] Implementation of an AI secretary for businesses

[0580] The user launches the application

[0581] A user launches a desktop or mobile application and enters their login information. The device sends this login information to a server, which retrieves the user's personal information from a database.

[0582] Conversation with an AI secretary

[0583] When a user asks the AI ​​secretary for advice on training, career planning, mental health, etc., the device receives the user's request via voice recognition or text input. The device then sends the request to a server, which uses natural language processing technology to analyze the request and generate an appropriate plan or response.

[0584] Providing plans and advice

[0585] The server sends the generated plan and advice to the device, which then displays it to the user. For example, if a user asks, "What training courses are recommended for career advancement?", the server generates a list of recommended training courses based on the user's work history and current skill set and sends it to the device.

[0586] Gathering and implementing feedback

[0587] When a user inputs feedback on the provided advice, the device sends the feedback to the server, which analyzes the feedback and uses it as learning data to improve the quality of future advice.

[0588] Specific examples

[0589] As a concrete example, let's say a student uses an application to solve a math problem. The student launches the application, enters their login information, and receives a study plan generated by the server based on their past study data. If the student has questions while working on the assignment, the AI ​​tutor provides real-time explanations. After studying, the device sends progress data to the server, which then adjusts the next study plan. If the student's motivation is declining, encouraging messages are displayed on the device.

[0590] In this way, the system of the present invention is designed to enable students and corporate employees to study effectively and receive support for career planning and mental health.

[0591] The processing flow will be explained below.

[0592] Processing program for AI tutoring for students

[0593] Step 1:

[0594] A user launches an application on a smartphone or tablet.

[0595] A login screen will appear, and the user will enter their ID and password.

[0596] The terminal sends the entered login information to the server.

[0597] Step 2:

[0598] The server receives the login information and retrieves the user's personal information (grade, learning status, learning goals, etc.) from the database.

[0599] The server sends the acquired information to the terminal.

[0600] Step 3:

[0601] The server generates an optimal study plan based on the user's study records and progress.

[0602] The server sends the generated learning plan to the terminal.

[0603] Step 4:

[0604] The device breaks down the study plan received from the server into daily and weekly study tasks and presents them to the user.

[0605] The user confirms the learning task and begins execution.

[0606] Step 5:

[0607] As the user progresses through the learning task, if they come across something they don't understand or have questions about, they can input a question.

[0608] The terminal sends the user's question to the server.

[0609] Step 6:

[0610] The server analyzes the questions it receives using natural language processing technology and generates appropriate answers and example questions.

[0611] The server sends the generated answers and example questions to the terminal.

[0612] Step 7:

[0613] The terminal displays the answers and examples received from the server to the user.

[0614] The user reads and interprets it and continues learning.

[0615] Step 8:

[0616] As the learning progresses, the terminal collects the user's learning progress data (for example, the percentage of correct answers to questions and the time spent studying).

[0617] The terminal transmits the collected progress data to the server.

[0618] Step 9:

[0619] The server analyzes the progress data and adjusts the next learning plan appropriately.

[0620] Furthermore, if the server analyzes the progress data and determines that the user's motivation is declining, it generates encouraging messages and motivational content.

[0621] The server transmits the generated content and messages to the terminal.

[0622] Step 10:

[0623] The device displays encouraging messages and motivational content to the user.

[0624] This will motivate users to continue learning.

[0625] Processing AI secretary programs for businesses

[0626] Step 1:

[0627] A user launches a desktop or mobile application.

[0628] A login screen will appear, and the user will enter their ID and password.

[0629] The terminal sends the entered login information to the server.

[0630] Step 2:

[0631] The server receives the login information and retrieves the user's personal information from a database.

[0632] The server sends the acquired information to the terminal.

[0633] Step 3:

[0634] Users use the application's interface to ask the AI ​​secretary for training advice, career planning, and mental health advice.

[0635] A request is received by the device via voice recognition or text input.

[0636] Step 4:

[0637] The terminal transmits the received request to the server.

[0638] Step 5:

[0639] The server analyzes the request using natural language processing technology and generates an appropriate plan or answer.

[0640] Step 6:

[0641] The server sends the generated plan and answer to the terminal.

[0642] Step 7:

[0643] The terminal displays the plan and answer received from the server to the user.

[0644] For example, if a user asks "What training courses are recommended for career advancement?", the server generates a list of recommended training courses, sends it to the terminal, and displays it to the user.

[0645] Step 8:

[0646] Users provide feedback on the plans and answers provided.

[0647] Feedback is sent by the terminal to the server.

[0648] Step 9:

[0649] The server analyzes the feedback and uses it to improve future plans and advice.

[0650] This will realize a system that allows users to receive effective and efficient support for their individual learning and career plans.

[0651] Example 1

[0652] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0653] Conventional online learning systems and corporate support systems have difficulty responding to the individual needs of each user, and have been unable to provide efficient support for learning, career planning, or mental health consultations. As a result, users' motivation has declined and it has been difficult to provide effective learning support.

[0654] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0655] In this invention, the server includes means for acquiring personal information about the user, means for generating a study plan, means for generating content to maintain motivation, means for the terminal to provide the user with an individual study plan and support content in real time, means for analyzing the user's requests using natural language processing technology and generating appropriate explanations and examples, and means for collecting and analyzing feedback and using it to improve quality in the future. This makes it possible to efficiently provide optimal study support, career planning, and mental health consultations for each user in real time.

[0656] "User" refers to an individual or legal entity that uses an information system.

[0657] "Application" means a software program designed for use by a user.

[0658] "Authentication information" refers to information such as ID and password used when a user logs in.

[0659] "Device" refers to an electronic device (e.g., smartphone, tablet, or PC) on which a user runs an application.

[0660] "Server" refers to a central processing unit that processes user requests and provides the required information and services.

[0661] "Personal Information" means information about a user, including identifiable data (e.g., name, address, grades).

[0662] A "database" refers to data storage for efficiently managing large amounts of data used by an organization or system.

[0663] "Learning history" refers to records of a user's past learning activities and their results.

[0664] "Progress" refers to the progress a user makes toward a particular task or goal.

[0665] A "learning plan" refers to specific learning tasks and schedules generated by the server to achieve the user's learning goals.

[0666] "AI Tutor Module" refers to an artificial intelligence-based software component designed to assist users in learning.

[0667] "Real-time" refers to immediate processing or response without delay.

[0668] "Learning progress data" refers to data that details the results and activities achieved by a user through learning activities.

[0669] "Motivational content" refers to messages and materials provided to keep users excited and interested in their learning or work.

[0670] "Natural language processing technology" refers to artificial intelligence technology for interpreting, understanding, and generating human language.

[0671] "Explanations and examples" refers to supplementary information and sample questions provided to users during their studies.

[0672] "Feedback" refers to ratings and comments provided by users, and is information used to improve system performance and services.

[0673] An "AI assistant" refers to an artificial intelligence-based software component that helps users with career planning, mental health, and other issues.

[0674] "Analysis" refers to the act of examining, understanding, and processing data and information.

[0675] The system of this invention is an AI system that allows users to receive learning support tailored to their individual learning pace and style, and allows companies to efficiently provide advice on career plans and mental and healthcare matters for individual employees. Specific embodiments of this system are described below.

[0676] Implementation of an AI tutor for students

[0677] A user launches the application on their smartphone or tablet and enters their login information. The device then sends this login information to a server. The server connects to a database to retrieve the user's personal information, past grades, and learning progress. The server then uses the retrieved data to analyze it using a generative AI model (e.g., GPT-4) and generate a customized learning plan for the user. This learning plan includes specific tasks and a schedule. The server then sends the generated learning plan to the device, which then displays it to the user.

[0678] When the user begins a task according to the learning plan, the AI ​​tutor module is activated and provides real-time support. If a question arises during learning, the user can enter it into the device's question input field. For example, they could enter, "Please tell me how to solve a quadratic equation." This question is sent to the server, which uses natural language processing technology to analyze the question and generate the most appropriate answer or example problem. This is then sent to the device and displayed to the user.

[0679] Learning progress is recorded in real time by the device and periodically sent to the server. The server analyzes this data and adjusts the next learning plan as needed. For example, if the user's understanding of a particular topic is lacking, tasks to reinforce the related topic will be added. Also, if the server determines that the user's motivation is declining, it will generate content to maintain motivation (encouraging messages or motivational content), send it to the device, and display it to the user.

[0680] Implementation of an AI secretary for businesses

[0681] A user launches a desktop or mobile application and enters their login information. The device sends this login information to a server, which connects to a database to retrieve personal information about the user, such as their work history and skill set. The user enters their consultation or question into the application's input fields, which the device then sends to the server.

[0682] For example, a user might input, "Please recommend some training courses." The server analyzes this request using natural language processing technology and generates a list of training courses that are most suitable for the user. This list is then sent to the terminal and displayed to the user. Furthermore, if the user inputs feedback about the usefulness of the advice provided, the terminal sends that feedback to the server. The server analyzes the feedback and uses it to improve the quality of future advice.

[0683] Specific examples

[0684] For example, suppose a student uses an application to solve a math problem. The student launches the application, enters their login information, and receives a study plan generated by the server based on their past study data. If the student has questions while working on the assignment, the AI ​​tutor provides real-time explanations. After studying, the device sends progress data to the server, which then adjusts the next study plan. If the student's motivation is declining, encouraging messages are displayed on the device.

[0685] As an example of a prompt sentence, if you enter, "I want to solve a quadratic equation problem in math. Please tell me how to solve it and the specific steps," the server will use a generative AI model to generate an appropriate step-by-step guide and display it on the device to help the user solve the problem.

[0686] In this way, the system of the present invention is designed to enable students and corporate employees to study effectively and receive support for career planning and mental health.

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

[0688] Step 1:

[0689] A user launches an application and logs in. The user taps the icon on their smartphone or tablet to launch the application, enters their ID and password on the login screen, and presses the login button. The device sends this authentication information to the server. The server connects to the database to confirm the authentication information and obtain the user's personal information. The information entered here is the login ID and password, and the data output is the authentication result and the user's personal information.

[0690] Step 2:

[0691] The server obtains user information and generates a study plan. After successful authentication, the server retrieves the user's past grades and learning progress from a database. This information is input into a generative AI model (e.g., GPT-4) to generate a study plan for the user. This study plan includes specific tasks and their schedules. The server sends this generated study plan to the device. The input is the user's study history and progress data, and the output is a study plan optimized for the user.

[0692] Step 3:

[0693] The terminal displays the learning plan to the user. The terminal receives the learning plan sent from the server and displays it on the screen. The user can check the learning plan on the terminal screen and confirm the specific learning tasks and schedule. The learning plan is received as input, and the content of the learning plan displayed to the user is output.

[0694] Step 4:

[0695] The user begins a learning task. The user begins a specific task (e.g., solving a math problem) according to the learning plan. If the user has a question, they enter it into the question input field on the device. For example, they might enter, "Please tell me how to solve a quadratic equation."

[0696] Step 5:

[0697] The terminal sends the user's question to the server. The terminal receives the question entered by the user and sends it to the server. The input information is the content of the user's question, and the output data is the question sent to the server.

[0698] Step 6:

[0699] The server analyzes the user's question and generates an answer. The server analyzes the received question using natural language processing technology and generates the optimal answer or example problem. A generative AI model is used in this process. The server sends the generated answer or example problem to the terminal. The input is the user's question, and the output is the analyzed answer or example problem.

[0700] Step 7:

[0701] The terminal displays the answers from the server to the user. The terminal displays the answers and example questions received from the server to the user. The user can use this as a reference to continue learning. The input is the answers and example questions sent from the server, and the output is the answers and example questions displayed to the user.

[0702] Step 8:

[0703] The device records learning progress data and sends it to the server. As the user progresses with their studies, the device records learning progress data (correct answer rate for questions, study time). This data is periodically sent to the server. The input is the user's learning progress data, and the output is the transmission of progress data to the server.

[0704] Step 9:

[0705] The server analyzes the learning progress data and adjusts the next learning plan. The server analyzes the received learning progress data and adjusts the next learning plan. If the user lacks understanding of a specific topic, it adds reinforcement tasks. The input is the learning progress data, and the output is the adjusted next learning plan.

[0706] Step 10:

[0707] The server generates content to maintain motivation and sends it to the device. The server analyzes learning progress data, and if it determines that the user's motivation is declining, it generates encouraging messages and motivating content and sends it to the device. The input is learning progress data, and the output is the generated content to maintain motivation.

[0708] (Application example 1)

[0709] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0710] Conventional systems were unable to provide information or recommend products that adequately met customer needs in brick-and-mortar stores. It was also difficult to manage the progress and maintain motivation of students and employees, resulting in a lack of effective educational support and mental health support. Furthermore, the system was also inadequate in recommending appropriate products and services based on health status, creating challenges in improving customer satisfaction and managing employee health.

[0711] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0712] In this invention, the server includes: a means for a user to launch an application and input login information; a means for the terminal to send the login information to the server; a means for the server to retrieve the user's personal information from a database; a means for the server to generate a study plan based on the user's study record and progress; a means for the server to send the generated study plan to the terminal; a means for the terminal to present study tasks to the user based on the study plan; a means for an AI tutor module to provide real-time support to the user while he or she is studying; a means for the terminal to send the user's study progress data to the server; a means for the server to analyze the data and adjust the next study plan; a means for the server to generate content to maintain the user's motivation and send it to the terminal; and a means for selecting products, checking inventory, and suggesting recommended products in real time when a customer visits a physical store. This enables more efficient customer service in physical stores and improved customer satisfaction.

[0713] An "application" is software that is operated by a user and runs on a variety of terminals.

[0714] "Login information" is information used to authenticate a user, typically a combination of a username and password.

[0715] "Terminal" refers to the device that a user uses to access an application, including smartphones, tablets, and personal computers.

[0716] A "server" is a computer system that runs on the back end of an application, accessing a database and performing processing.

[0717] A "database" is a data storage system for managing users' personal information, learning records, product inventory information, and so on.

[0718] "Study record" is data showing the records and grades of the user's previous studies.

[0719] A "study plan" is a list of specific study schedules and tasks that are generated based on the user's progress and goals.

[0720] A "learning task" is a specific learning activity or problem-solving task that a user should perform based on a learning plan.

[0721] The "AI Tutor Module" is an artificial intelligence system that provides real-time support and answers questions while users are learning.

[0722] "Study progress data" is data that indicates how far the user has progressed in their studies, and includes the percentage of correct answers to questions and the study time.

[0723] "Motivation maintenance content" refers to messages and content generated to increase a user's motivation to learn.

[0724] "Product selection" is the process by which customers identify products they will consider purchasing in a physical store.

[0725] "Inventory check" is the task of checking the quantity and status of products in physical stores and warehouses.

[0726] "Recommended products" is the process of recommending appropriate products based on a customer's needs and preferences.

[0727] "Natural language processing technology" is a technology that allows computers to understand and analyze human language.

[0728] "Feedback" refers to the evaluation or opinion that a user inputs regarding the plan or advice provided.

[0729] "AI Secretary" is an artificial intelligence system that supports users with training, career planning, mental health counseling, and more.

[0730] "Speech recognition" is a technology that converts a user's speech into text.

[0731] A "prompt" is text that is input into a generative AI model and is an instruction statement to obtain an appropriate generated result.

[0732] A "generative AI model" is an artificial intelligence model that generates text and answers based on a prompt.

[0733] The system of the present invention is a system that allows users to receive support tailored to their individual learning pace and needs, and provides useful information even in physical stores. Specific embodiments of the system are described below.

[0734] System Configuration

[0735] The system mainly consists of a terminal, a server, a database, and a generative AI model. Terminals can be devices such as smartphones, tablets, and PCs. The server is a computer system that accesses the database and performs the necessary processing, and can be implemented using Python and the Flask framework. The generative AI model is built using natural language processing technologies such as HuggingFace's Transformers.

[0736] Login process

[0737] A user launches an application on a terminal and enters login information (user name, password). This information is sent from the terminal to the server, which retrieves the user's personal information from a database. This authenticates the user and allows them to access the system.

[0738] Generate a lesson plan

[0739] The server generates a learning plan based on the user's past learning records and current progress. This learning plan includes specific tasks and schedules. The generated learning plan is sent to the device and displayed to the user.

[0740] Learning task presentation and real-time support

[0741] When a user starts a learning task, the device launches the AI ​​tutor module. When the user enters a question or concern, the information is sent to the server. The server uses natural language processing technology to analyze the question and generate appropriate explanations and examples. The generated explanations are sent to the device and provided to the user.

[0742] Learning progress and maintaining motivation

[0743] The device collects the user's learning progress (correct answer rate, study time) and sends it to the server. The server analyzes this data and adjusts the next learning plan. If the server determines that the user's motivation is declining, it generates encouraging messages and motivational content and sends them to the device.

[0744] Application in physical stores

[0745] When customers visit a physical store, they can use a terminal (a tablet or smartphone installed in the store) to receive product information, check inventory, and receive recommended products. When a user asks a question about how to select a product or the inventory status, the information is sent to a server, which analyzes it using natural language processing technology and provides the appropriate answer or product suggestion to the terminal.

[0746] Specific examples

[0747] Consider a case where a customer asks, "What products can boost the immune system?" in a physical store. This question is sent from the device to the server, and the server generates a response using a generative AI model. An example of a prompt sentence is "What products can boost the immune system?" As a result, the server recommends an appropriate product (e.g., "vitamin C supplement") and sends that information to the device for display.

[0748] In this way, the system of the present invention integrates the user's learning activities with the provision of information in physical stores, providing effective support.

[0749] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0750] Step 1:

[0751] A user starts an application on a device and enters login information (user name, password). The device sends this login information to the server. Based on this input, the server retrieves the user's personal information from the database and sends it to the device.

[0752] Step 2:

[0753] The server retrieves the user's past learning records and current progress data from the database and generates a new learning plan based on that data. The generated learning plan includes learning tasks and a schedule. This data processing establishes an optimal learning plan for the user. The server then sends the generated learning plan to the terminal, which displays it to the user.

[0754] Step 3:

[0755] The user performs learning tasks based on the displayed learning plan. If a question or doubt arises during learning, the user inputs it. The device sends the input question to the server. To respond to this question, the server uses a generative AI model to analyze the question and generate appropriate answers and example problems. The generated answers are sent to the device and displayed to the user.

[0756] Step 4:

[0757] The device collects the user's learning progress data (correct answer rate, study time) and periodically sends it to the server. The server analyzes this data and dynamically adjusts the next study plan. If the server determines that the user's motivation to study is declining, it generates motivational messages and video content and sends them to the device.

[0758] Step 5:

[0759] When a customer visits a physical store, they use a device (a tablet or smartphone in the store) to input a question about a product (e.g., "What products boost immunity?"). The device sends this question to a server. The server uses a generative AI model to analyze the question and generate appropriate product recommendations and stock status information. Accurate product information is generated by processing the data using this prompt text. The generated information is sent to the device and displayed to the customer.

[0760] Step 6:

[0761] If the customer checks the recommended products and asks more detailed questions, the input is sent to the server in a similar manner, and the server generates an answer and sends it to the terminal. At this step, product selection, inventory check, and recommendation suggestions are performed in real time.

[0762] In this way, at each processing step of the system, the user, device, and server work together to provide efficient support by utilizing generative AI models and prompt sentences.

[0763] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0764] The present invention combines an emotion engine with an AI system that allows individual learners and corporate employees to receive individually customized learning plans, career support, and mental health consultations. A specific embodiment of this system is described below.

[0765] Implementation of an AI tutor for students

[0766] The user launches the application

[0767] First, a user launches an application on a device such as a smartphone or tablet and enters their login information. The device sends this login information to the server, which then retrieves the user's personal information from a database.

[0768] The server generates the lesson plan

[0769] The server generates a learning plan based on the user's past performance and learning progress. This learning plan includes specific tasks and schedules for the user to effectively study. The server sends the generated learning plan to the terminal, which then displays it to the user.

[0770] Presenting and supporting learning tasks

[0771] When a user starts a learning task, the device launches the AI ​​tutor module. When the user inputs a question or concern, the device sends it to the server, which analyzes it using natural language processing technology and generates appropriate explanations and examples. The server then sends the generated explanations and examples to the device, which displays them to the user.

[0772] Emotion engine monitoring

[0773] The device acquires emotional data from the user's facial expressions, voice, input, etc. This data is analyzed by the emotion engine to identify the user's emotional state. The device then transmits the emotional data to the server.

[0774] Learning progress and motivation

[0775] The device collects the user's learning progress data (e.g., percentage of correct answers and study time) and sends it to the server. The server analyzes this data and emotional data and adjusts the next learning plan appropriately. If the server determines that the user's motivation is declining, it generates encouraging messages and motivational content, sends them to the device, and displays them to the user.

[0776] Specific examples

[0777] For example, suppose a student uses an application to solve a math problem. The student launches the application, enters their login information, and receives a study plan generated by the server. If the student has questions while working on the problem, the AI ​​tutor will provide real-time explanations. Furthermore, if the emotion engine detects stress from the student's facial expressions or voice, the server will send and display encouraging messages or content to help them concentrate on the device. After studying, the device will send progress data and emotion data to the server, which will then adjust the next study plan.

[0778] Implementation of an AI secretary for businesses

[0779] The user launches the application

[0780] A user launches a desktop or mobile application and enters their login information. The device sends this login information to a server, which retrieves the user's personal information from a database.

[0781] Conversation with an AI secretary

[0782] When a user asks the AI ​​secretary for advice on training, career planning, mental health, etc., the device receives the user's request via voice recognition or text input and sends it to the server, which then uses natural language processing technology to analyze the request and generate an appropriate plan or response.

[0783] Support by Emotion Engine

[0784] When the device receives a request, it acquires emotional data from the user's facial expressions, voice, and input. The emotion engine analyzes this data and generates a response or plan that reflects the user's emotional state.

[0785] Providing plans and advice

[0786] The server sends the generated plans and advice to the device, which then displays them to the user. For example, if a user asks, "What training courses are recommended for career advancement?", the server generates a list of recommended training courses, sends it to the device, and displays it to the user. Additionally, if the emotion engine determines that the user is feeling stressed, it can also provide advice on relaxation methods and mental health.

[0787] Gathering and implementing feedback

[0788] When a user inputs feedback on the provided plan or advice, the device sends the feedback to the server, which analyzes the feedback and uses it to improve the quality of future plans and advice.

[0789] In this way, by combining an emotion engine, the system of the present invention provides learning plans and career plans that correspond to the user's emotional state, thereby achieving more effective and personalized support.

[0790] The processing flow will be explained below.

[0791] Processing program for AI tutoring for students

[0792] Step 1:

[0793] When a user launches an application on their smartphone or tablet, a login screen appears, and the user enters their ID and password. The device then sends the login information to the server.

[0794] Step 2:

[0795] The server receives the login information and retrieves the user's personal information (grade, learning status, learning goals, etc.) from the database. The server then sends the retrieved information to the terminal.

[0796] Step 3:

[0797] The server generates a study plan based on the user's past grades and learning progress, and then sends the generated study plan to the device.

[0798] Step 4:

[0799] The device breaks down the study plan received from the server into daily and weekly study tasks and presents them to the user. The user confirms the study tasks and begins executing them.

[0800] Step 5:

[0801] When a user has a question or concern while progressing through a learning task, they can input a question, and the device will send the user's question to the server.

[0802] Step 6:

[0803] The server analyzes the received questions using natural language processing technology and generates appropriate answers and examples, which are then sent to the device.

[0804] Step 7:

[0805] The device receives the answers and examples from the server and displays them to the user, who can then confirm them and continue learning.

[0806] Step 8:

[0807] The device acquires emotional data from the user's facial expressions, voice, and input, analyzes it using an emotion engine, identifies the user's emotional state, and sends the data to the server.

[0808] Step 9:

[0809] The device collects the user's learning progress data (such as the rate at which questions are answered correctly and the amount of time spent studying) and sends it to the server. The server analyzes the progress data and emotional data and adjusts the next study plan appropriately.

[0810] Step 10:

[0811] If the server determines that the user's motivation is declining, it generates encouraging messages and motivational content and sends them to the device, which then displays them to the user.

[0812] Processing AI secretary programs for businesses

[0813] Step 1:

[0814] When a user launches a desktop or mobile application, a login screen appears, where the user enters their ID and password, and the device sends the login information to the server.

[0815] Step 2:

[0816] The server receives the login information, retrieves the user's personal information from the database, and sends the retrieved information to the terminal.

[0817] Step 3:

[0818] Users can use the in-app interface to ask the AI ​​secretary for training advice, career planning, and mental health advice, with requests received by the device via voice recognition or text input.

[0819] Step 4:

[0820] The device sends the received request to the server.

[0821] Step 5:

[0822] The server analyzes the request using natural language processing technology and generates an appropriate plan or answer.

[0823] Step 6:

[0824] The device acquires emotional data from the user's facial expressions, voice, and input, and sends it to the server. The emotion engine analyzes this data and provides a plan based on the user's emotional state.

[0825] Step 7:

[0826] The server generates plans and answers and sends them to the device, which then displays them to the user. For example, if a user asks, "What training courses are recommended for my career?", the server generates a list of appropriate training courses, sends it to the device, and displays it to the user.

[0827] Step 8:

[0828] The user enters feedback on the provided plans and answers, which is then sent by the device to the server.

[0829] Step 9:

[0830] The server analyzes the feedback and uses it to improve future plans and advice.

[0831] In this way, the system of the present invention optimizes the user's studies and career plans according to the user's emotional state and provides effective support.

[0832] Example 2

[0833] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0834] In modern education and career support, personalized guidance and support for individual learners and employees is becoming increasingly important. However, existing systems do not adequately provide support that takes into account the user's emotional state, which can reduce the effectiveness of learning and career support. It is also difficult to maintain user motivation, leading to issues such as ineffective implementation of learning and career plans.

[0835] The specification process by the specification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for acquiring the user's personal information from a database, means for generating a study plan based on the user's study record and progress, and means for an emotion engine to identify the user's emotional state and analyze the data. This makes it possible to provide an individualized study plan or career plan that reflects the user's emotional state, thereby enabling effective study and career support while maintaining the user's motivation.

[0836] "User" refers to an individual who uses the Application to receive learning planning and career support services.

[0837] A "terminal" is a device that a user uses to run an application, and includes a smartphone, tablet, desktop, etc.

[0838] "Server" refers to a central computer system that receives, processes, and analyzes data sent by users.

[0839] "Login Information" refers to the authentication information required for a user to access a system, and typically consists of a username and password.

[0840] "Database" refers to an information management system for storing data such as users' personal information, learning records, and progress information.

[0841] A "study plan" refers to specific tasks and schedules generated by the server to help users study effectively.

[0842] "AI Tutor Module" refers to artificial intelligence that provides real-time support to users while they are learning.

[0843] An "emotion engine" refers to a technology that acquires and analyzes emotional data from a user's facial expressions, voice, input content, etc.

[0844] "Natural language processing technology" refers to technology that enables computers to understand human language and generate appropriate responses.

[0845] "Feedback" refers to opinions and impressions that users input regarding the plans and advice provided.

[0846] "Motivation" refers to the user's will and motivation to achieve a goal.

[0847] The present invention combines an emotion engine with an AI system that enables individual learners and corporate employees to receive individually customized learning plans, career support, and mental health consultations. This system enables users to receive effective learning and career support using an application. A specific embodiment of this system is described below.

[0848] Hardware and software used

[0849] 1. Hardware

[0850] Smartphones and tablets (student devices)

[0851] Desktop (devices for corporate employees)

[0852] Server (responsible for data processing and analysis)

[0853] 2. Software

[0854] Application platform (iOS, Android, Windows, etc.)

[0855] Database (e.g. MySQL, PostgreSQL)

[0856] Natural language processing technology (e.g., GPT-3, BERT)

[0857] Machine learning algorithms (e.g., scikit-learn)

[0858] Emotion engines (e.g., Affectiva, Microsoft Emotion API)

[0859] Example of operation

[0860] AI tutors for students

[0861] 1. Launching the application and logging in

[0862] A user launches an application on their smartphone or tablet and enters their login information. The device encrypts the login information and sends it to a server, which then retrieves the user's personal information from a database. The personal information is then sent to the device and displayed to the user.

[0863] 2. Generate a learning plan

[0864] The server uses a machine learning algorithm to generate an optimal study plan based on the user's past performance and learning progress. The generated information is sent to the device and displayed to the user.

[0865] 3. Support for learning tasks

[0866] When a user starts a learning task, the device launches an AI tutoring module (e.g., Dialogflow, GPT-3). When the user inputs a question, the device sends it to the server, which analyzes it using natural language processing technology and generates appropriate explanations and examples. These are then provided to the user via the device.

[0867] 4. Emotion Engine Monitoring

[0868] The device uses a camera and microphone to collect the user's facial expressions, voice, and input, and analyzes them with an emotion engine. The emotion data is sent to a server, and the analysis results are reflected in the next lesson plan.

[0869] 5. Staying motivated

[0870] The server analyzes the user's learning progress and emotional state, and generates encouraging messages and content to maintain motivation. These contents are provided to the user via their device.

[0871] Example prompt:

[0872] "Do you have any questions about the next math assignment? Type in any questions you may have."

[0873] AI secretaries for businesses

[0874] 1. Launching the application and logging in

[0875] A user launches an application on a desktop or mobile device and enters their login information. The device encrypts the login information and sends it to a server, which retrieves their personal information from a database. The retrieved information is then displayed to the user on the device.

[0876] 2. Conversation with an AI secretary

[0877] When a user requests training consultation or career planning through text or voice input, the device sends the request to the server. The server analyzes the request using natural language processing technology and generates an appropriate plan or answer. The generated plan is displayed to the user via the device.

[0878] 3. Support by Emotion Engine

[0879] The device collects the user's facial expressions and voice, analyzes them with an emotion engine, and sends the emotion data to the server, where it is reflected in the response and plan.

[0880] 4. Gather and incorporate feedback

[0881] The user enters feedback on the plan or advice provided, and the device sends the feedback to the server, which analyzes the feedback and uses it for future improvements.

[0882] Example prompt:

[0883] "Do you have any questions about your career plans? Please enter your specific question."

[0884] This system provides personalized learning and career plans that take into account the user's emotional state, enabling effective support while increasing the user's motivation.

[0885] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0886] AI Tutoring for Students

[0887] Step 1: Launch the application and log in

[0888] 1. The user launches the application on the device and the login screen appears.

[0889] 2. The user enters their login information (username and password).

[0890] Input: Username and Password

[0891] Output: Encrypted login information

[0892] 3. The device sends the encrypted login information to the server.

[0893] Data processing: Encryption of entered login information

[0894] Data calculation: Sending login information to the server

[0895] 4. The server retrieves the user's personal information from the database.

[0896] Input: Encrypted login information

[0897] Output: User's personal information

[0898] 5. The device displays the personal information to the user.

[0899] Data processing: Converting acquired personal information into a display format

[0900] Data calculation: Display on user screen

[0901] Step 2: Generate a lesson plan

[0902] 1. The server generates a study plan using a machine learning algorithm based on the user's past grades and learning progress data.

[0903] Input: User's past performance data, learning progress data

[0904] Output: personalized learning plan

[0905] Data calculation: Generating learning plans using machine learning algorithms

[0906] 2. The server sends the generated learning plan to the device.

[0907] Data calculation: Sending learning plans to the device

[0908] 3. The device displays the lesson plan to the user.

[0909] Data processing: Converting the learning plan into a display format

[0910] Data Calculation: Viewing the Learning Plan

[0911] Step 3: Supporting the learning task

[0912] 1. The user selects a task to begin the learning task.

[0913] Input: Select a learning task

[0914] Output: Details of the selected task

[0915] 2. The device will launch the AI ​​tutor module and display the task details.

[0916] Data calculation: Launching the AI ​​tutor module and generating display content

[0917] 3. The user enters their concern or question via text or voice.

[0918] Input: User's doubts or questions

[0919] Output: Questions and queries

[0920] 4. The device sends the question or inquiry to the server.

[0921] Data calculation: Send data to the server

[0922] 5. The server uses natural language processing technology to analyze the question and generate appropriate explanations and examples.

[0923] Input: Questions and questions

[0924] Output: Explanation and examples

[0925] Data processing: Analysis, explanations and example generation using natural language processing technology

[0926] 6. The server sends the generated explanations and examples to the terminal, which displays them.

[0927] Data calculation: Sending and displaying explanations and examples

[0928] Step 4: Monitoring with the Emotion Engine

[0929] 1. The device uses a camera and microphone to collect the user's facial expressions, voice, and input.

[0930] Input: facial expression data, voice data, input content

[0931] Output: Raw data

[0932] 2. The device's emotion engine analyzes the collected data and identifies the user's emotional state.

[0933] Data processing: analyzing data and identifying emotional states

[0934] Output: Emotional state data

[0935] 3. The device sends the emotional state data to the server.

[0936] Data calculation: Sending emotional state data

[0937] Step 5: Study progress and maintain motivation

[0938] 1. The device collects the user's learning progress data (correct answer rate and study time).

[0939] Input: Learning progress data

[0940] Output: Collected data

[0941] 2. The device sends the collected data to the server.

[0942] Data calculation: Sending progress data

[0943] 3. The server analyzes the progress and emotion data and adjusts the next learning plan.

[0944] Input: Learning progress data, emotion data

[0945] Output: Adjusted learning plan

[0946] Data calculations: analyzing data and adjusting learning plans

[0947] 4. The server generates encouraging messages and content to keep the user motivated and sends them to the device.

[0948] Input: User emotion data

[0949] Output: Support message and content

[0950] Data calculation: generating and sending support messages and content

[0951] 5. The device displays the support message or content received to the user.

[0952] Data processing: converting messages and content into a display format

[0953] Data operations: displaying messages and content

[0954] Processing steps for corporate AI secretaries

[0955] Step 1: Launch the application and log in

[0956] 1. A user launches an application on a desktop or mobile app and is presented with a login screen.

[0957] 2. The user enters their login information.

[0958] Input: Username and Password

[0959] Output: Encrypted login information

[0960] 3. The device sends the encrypted login information to the server.

[0961] Data processing: Encryption of entered login information

[0962] Data calculation: Sending login information to the server

[0963] 4. The server retrieves the user's personal information and work history from the database.

[0964] Input: Encrypted login information

[0965] Output: Personal information and work history

[0966] 5. The device displays the user's personal information and work history.

[0967] Data processing: Converting acquired personal information into a display format

[0968] Data calculation: Display on user screen

[0969] Step 2: Interact with the AI ​​secretary

[0970] 1. The user inputs text or voice to consult about training, create a career plan, or receive mental health advice.

[0971] Input: User request

[0972] Output: Request data

[0973] 2. The device sends the user's request to the server.

[0974] Data calculation: Sending request data

[0975] 3. The server uses natural language processing technology to analyze the request and generate an appropriate plan or answer.

[0976] Input: User request data

[0977] Output: Plans and answers

[0978] Data processing: Natural language processing techniques for analysis, planning and answer generation

[0979] 4. The server sends the generated plan and answer to the terminal, which displays it.

[0980] Data calculation: Sending and displaying plans and answers

[0981] Step 3: Support with the Emotion Engine

[0982] 1. The device uses a camera and microphone to collect the user's facial expressions and voice.

[0983] Input: facial expression data, voice data

[0984] Output: Raw data

[0985] 2. The emotion engine analyzes the collected data and identifies the user's emotional state.

[0986] Data processing: analyzing data and identifying emotional states

[0987] Output: Emotional state data

[0988] 3. The device sends the emotional state data to the server.

[0989] Data calculation: Sending emotional state data

[0990] Step 4: Gather and incorporate feedback

[0991] 1. The user enters feedback on the plan or advice provided.

[0992] Input: Feedback

[0993] Output: Feedback data

[0994] 2. The device sends the feedback data to the server.

[0995] Data calculation: Sending feedback data

[0996] 3. The server analyzes the feedback and uses it to improve future plans and advice.

[0997] Input: Feedback data

[0998] Output: Improved plans and advice

[0999] Data processing: Analyzing feedback data, identifying and implementing improvements

[1000] 4. The device displays improved plans and advice to the user.

[1001] Data transformation: Transforming improved plans and advice into a display format

[1002] Data Calculation: Improved plans and advice display

[1003] (Application example 2)

[1004] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1005] Factory workers are prone to experiencing mental fatigue and a loss of concentration and motivation when performing long, monotonous tasks or working in a high-stress environment. If these conditions continue, it can lead to problems such as a decline in work efficiency, an increase in work errors, and even increased safety risks. Conventional methods have made it difficult to monitor workers' mental state in real time and provide appropriate feedback and break suggestions, so a means to effectively solve these problems is needed.

[1006] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1007] In this invention, the server includes means for acquiring the user's personal information from a database, means for generating a study plan based on the user's study record and progress, means for the terminal to acquire emotion data from the user's facial expressions, voice, and input content, and means for the emotion engine to analyze the user's emotion state and send it to the server. This makes it possible to monitor the emotion state of factory workers in real time and provide suggestions for work breaks or encouraging messages as needed.

[1008] "User" refers to an individual who uses the system, including a factory worker or a student.

[1009] An "application" is a software program that a user runs and uses on a terminal.

[1010] "Login information" refers to authentication information for accessing a system, such as a user name and password.

[1011] A "terminal" is a device used by a user, such as a smartphone, tablet, smart glasses, or head-mounted display.

[1012] A "server" is a computer system responsible for processing, storing, and transmitting user data.

[1013] A "database" is a system that organizes and stores data such as users' personal information and learning records.

[1014] A "study plan" is a general term for tasks and schedules designed to help users study efficiently.

[1015] The "AI Tutor Module" is an artificial intelligence system that provides real-time support to users while they are learning.

[1016] "Study progress data" refers to data such as the percentage of correct answers and study time as the user progresses with their studies.

[1017] "Facial expressions, voice, and input content" are data used to analyze the user's emotional state.

[1018] An "emotion engine" is an algorithm or system for analyzing a user's emotional state.

[1019] A "work break suggestion" is a notification or message that encourages a user who is working to take a break.

[1020] "Natural language processing technology" is a technology that analyzes text and voice input by users and generates appropriate answers.

[1021] MODE FOR CARRYING OUT THE INVENTION

[1022] The present invention is a support system for users to perform factory work efficiently and safely. This system uses a device such as smart glasses worn by the user to acquire emotional data from the user's facial expressions and voice, and manages the progress of the work.

[1023] The system is structured as follows: First, the user puts on the smart glasses and launches the application. After the user enters their login information, the device sends this information to the server, which then retrieves the user's personal information from a database. The server is equipped with a high-performance computer, a database, and an AI emotion engine. The software used includes Python, OpenCV, Keras, and TensorFlow.

[1024] The server then generates a work plan for each user and sends it to the device. The work plan includes specific tasks and schedules. As the worker works according to the plan, if a question arises, the worker sends a query to the server via the smart glasses. The server analyzes the query using natural language processing technology, generates an appropriate answer, and sends it to the device. At this time, the user's input and voice are also analyzed.

[1025] The emotion engine analyzes the user's facial expressions and voice in real time to identify their emotional state. For example, if the emotion engine detects stress, it will generate a message suggesting a break or offering encouragement, which will be sent to the user's device and displayed. It also adjusts the next task plan based on learning progress data and emotion data.

[1026] For example, if the emotion engine detects that a factory worker is very tired, the system will send a message like this: "The worker appears tired, so we recommend that you take a break." This will allow workers to take breaks at the appropriate time, improving safety and work efficiency.

[1027] An example of a prompt sentence might be:

[1028] "Transform the following sentence into a feedback message based on emotion data: 'The worker is showing clear signs of fatigue on his face.'"

[1029] The above is a specific embodiment for carrying out the present invention, and by using this system, the safety and efficiency of factory workers can be significantly improved.

[1030] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1031] Step 1:

[1032] The user puts on the smart glasses, launches the application, and enters their login information, which is then sent to the server via the device.

[1033] Input: User login information (username, password)

[1034] Output: Login information sent to the server

[1035] Step 2:

[1036] The server receives the login information and retrieves the user's personal information from a database, making available a data set specific to the user.

[1037] Input: Login information received by the server

[1038] Output: User's personal information

[1039] Step 3:

[1040] The server generates an optimal work plan for the user based on the user's personal information and past learning and work records.

[1041] Input: User's personal information, learning records, work records

[1042] Output: Generated work plan

[1043] Step 4:

[1044] The server sends the generated work plan to the terminal, which then presents the work plan to the user, who then begins work according to the work plan.

[1045] Input: Generated Work Plan

[1046] Output: Submitted work plan, Work plan presentation

[1047] Step 5:

[1048] If a user has any questions or concerns while working, they can input the question via voice or text through the smart glasses, and the device will send it to the server.

[1049] Input: User question (voice or text)

[1050] Output: The question is sent to the server

[1051] Step 6:

[1052] The server uses natural language processing technology to analyze the received question and generate appropriate answers and instructions, thereby resolving the user's doubts.

[1053] Input: User question

[1054] Output: Generated answers and instructions

[1055] Step 7:

[1056] The server sends the generated answers and instructions to the terminal, which displays them to the user, who can then continue working based on the displayed information.

[1057] Input: Generated answers and instructions

[1058] Output: Submitted answers and instructions, presentation of answers and instructions

[1059] Step 8:

[1060] The device acquires emotional data from the user's facial expressions, voice, and input content and sends it to the server.

[1061] Input: User's facial expressions, voice, and input

[1062] Output: Emotion data is sent to the server

[1063] Step 9:

[1064] The server's emotion engine analyzes the emotion data to identify the user's emotional state, and generates break suggestions or encouraging messages as needed based on the analysis results.

[1065] Input: Emotion data

[1066] Output: Identified emotional state, suggestion to take a break, or a message of encouragement

[1067] Step 10:

[1068] The server sends the generated break suggestion or encouraging message to the terminal, which displays it to the user, who can then take a break or continue working.

[1069] Input: Generated break suggestions and encouraging messages

[1070] Output: Break suggestions and encouragement messages sent, display of suggestions and messages

[1071] Step 11:

[1072] The device collects the user's learning progress and emotional data and sends it to the server, which analyzes the data and adjusts the next task plan.

[1073] Input: learning progress data, emotion data

[1074] Output: Adjusted next work plan

[1075] As a specific example of how it works, if the emotion engine detects that a factory worker is very tired, the system will generate a message like this: "The worker appears tired, so we recommend that you take a break." This will allow workers to take breaks at appropriate times, improving safety and work efficiency.

[1076] An example prompt is, "Transform the following sentence into a feedback message based on emotion data: 'The worker is showing obvious signs of fatigue on his face.'"

[1077] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1078] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1079] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1080] [Third embodiment]

[1081] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1082] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1083] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1084] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1085] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1086] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1087] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1088] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1089] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1090] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1091] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1092] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1093] The system of the present invention is an AI system that allows users to receive learning support tailored to their individual learning pace and style, and allows companies to efficiently provide advice on career plans and mental and healthcare matters for individual employees. Specific embodiments of this system are described below.

[1094] Implementation of an AI tutor for students

[1095] The user launches the application

[1096] First, a user launches an application on a device such as a smartphone or tablet and enters their login information. The device sends this login information to the server, which then retrieves the user's personal information from a database.

[1097] The server generates the lesson plan

[1098] The server generates a study plan based on the user's past grades and learning progress. This study plan includes specific tasks and schedules for the user to study effectively. The server sends the generated study plan to the terminal, which displays it to the user.

[1099] Presenting and supporting learning tasks

[1100] When a user starts a learning task, the device launches the AI ​​tutor module. When the user inputs a question or concern, the device sends it to the server, which analyzes it using natural language processing technology and generates appropriate explanations and examples. The server then sends the generated explanations and examples to the device, which displays them to the user.

[1101] Learning progress and motivation

[1102] The device collects the user's learning progress data (such as the rate at which questions are answered correctly and the amount of time spent studying) and sends it to the server. The server analyzes this data and adjusts the next study plan. The server also analyzes the user's learning data, and if it determines that motivation is declining, it generates encouraging messages and motivational content, which it sends to the device and displays to the user.

[1103] Implementation of an AI secretary for businesses

[1104] The user launches the application

[1105] A user launches a desktop or mobile application and enters their login information. The device sends this login information to a server, which retrieves the user's personal information from a database.

[1106] Conversation with an AI secretary

[1107] When a user asks the AI ​​secretary for advice on training, career planning, mental health, etc., the device receives the user's request via voice recognition or text input. The device then sends the request to a server, which uses natural language processing technology to analyze the request and generate an appropriate plan or response.

[1108] Providing plans and advice

[1109] The server sends the generated plan and advice to the device, which then displays it to the user. For example, if a user asks, "What training courses are recommended for career advancement?", the server generates a list of recommended training courses based on the user's work history and current skill set and sends it to the device.

[1110] Gathering and implementing feedback

[1111] When a user inputs feedback on the provided advice, the device sends the feedback to the server, which analyzes the feedback and uses it as learning data to improve the quality of future advice.

[1112] Specific examples

[1113] As a concrete example, let's say a student uses an application to solve a math problem. The student launches the application, enters their login information, and receives a study plan generated by the server based on their past study data. If the student has questions while working on the assignment, the AI ​​tutor provides real-time explanations. After studying, the device sends progress data to the server, which then adjusts the next study plan. If the student's motivation is declining, encouraging messages are displayed on the device.

[1114] In this way, the system of the present invention is designed to enable students and corporate employees to study effectively and receive support for career planning and mental health.

[1115] The processing flow will be explained below.

[1116] Processing program for AI tutoring for students

[1117] Step 1:

[1118] A user launches an application on a smartphone or tablet.

[1119] A login screen will appear, and the user will enter their ID and password.

[1120] The terminal sends the entered login information to the server.

[1121] Step 2:

[1122] The server receives the login information and retrieves the user's personal information (grade, learning status, learning goals, etc.) from the database.

[1123] The server sends the acquired information to the terminal.

[1124] Step 3:

[1125] The server generates an optimal study plan based on the user's study records and progress.

[1126] The server sends the generated learning plan to the terminal.

[1127] Step 4:

[1128] The device breaks down the study plan received from the server into daily and weekly study tasks and presents them to the user.

[1129] The user confirms the learning task and begins execution.

[1130] Step 5:

[1131] As the user progresses through the learning task, if they come across something they don't understand or have questions about, they can input a question.

[1132] The terminal sends the user's question to the server.

[1133] Step 6:

[1134] The server analyzes the questions it receives using natural language processing technology and generates appropriate answers and example questions.

[1135] The server sends the generated answers and example questions to the terminal.

[1136] Step 7:

[1137] The terminal displays the answers and examples received from the server to the user.

[1138] The user reads and interprets it and continues learning.

[1139] Step 8:

[1140] As the learning progresses, the terminal collects the user's learning progress data (for example, the percentage of correct answers to questions and the time spent studying).

[1141] The terminal transmits the collected progress data to the server.

[1142] Step 9:

[1143] The server analyzes the progress data and adjusts the next learning plan appropriately.

[1144] Furthermore, if the server analyzes the progress data and determines that the user's motivation is declining, it generates encouraging messages and motivational content.

[1145] The server transmits the generated content and messages to the terminal.

[1146] Step 10:

[1147] The device displays encouraging messages and motivational content to the user.

[1148] This will motivate users to continue learning.

[1149] Processing AI secretary programs for businesses

[1150] Step 1:

[1151] A user launches a desktop or mobile application.

[1152] A login screen will appear, and the user will enter their ID and password.

[1153] The terminal sends the entered login information to the server.

[1154] Step 2:

[1155] The server receives the login information and retrieves the user's personal information from a database.

[1156] The server sends the acquired information to the terminal.

[1157] Step 3:

[1158] Users use the application's interface to ask the AI ​​secretary for training advice, career planning, and mental health advice.

[1159] A request is received by the device via voice recognition or text input.

[1160] Step 4:

[1161] The terminal transmits the received request to the server.

[1162] Step 5:

[1163] The server analyzes the request using natural language processing technology and generates an appropriate plan or answer.

[1164] Step 6:

[1165] The server sends the generated plan and answer to the terminal.

[1166] Step 7:

[1167] The terminal displays the plan and answer received from the server to the user.

[1168] For example, if a user asks "What training courses are recommended for career advancement?", the server generates a list of recommended training courses, sends it to the terminal, and displays it to the user.

[1169] Step 8:

[1170] Users provide feedback on the plans and answers provided.

[1171] Feedback is sent by the terminal to the server.

[1172] Step 9:

[1173] The server analyzes the feedback and uses it to improve future plans and advice.

[1174] This will realize a system that allows users to receive effective and efficient support for their individual learning and career plans.

[1175] Example 1

[1176] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1177] Conventional online learning systems and corporate support systems have difficulty responding to the individual needs of each user, and have been unable to provide efficient support for learning, career planning, or mental health consultations. As a result, users' motivation has declined and it has been difficult to provide effective learning support.

[1178] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1179] In this invention, the server includes means for acquiring personal information about the user, means for generating a study plan, means for generating content to maintain motivation, means for the terminal to provide the user with an individual study plan and support content in real time, means for analyzing the user's requests using natural language processing technology and generating appropriate explanations and examples, and means for collecting and analyzing feedback and using it to improve quality in the future. This makes it possible to efficiently provide optimal study support, career planning, and mental health consultations for each user in real time.

[1180] "User" refers to an individual or legal entity that uses an information system.

[1181] "Application" means a software program designed for use by a user.

[1182] "Authentication information" refers to information such as ID and password used when a user logs in.

[1183] "Device" refers to an electronic device (e.g., smartphone, tablet, or PC) on which a user runs an application.

[1184] "Server" refers to a central processing unit that processes user requests and provides the required information and services.

[1185] "Personal Information" means information about a user, including identifiable data (e.g., name, address, grades).

[1186] A "database" refers to data storage for efficiently managing large amounts of data used by an organization or system.

[1187] "Learning history" refers to records of a user's past learning activities and their results.

[1188] "Progress" refers to the progress a user makes toward a particular task or goal.

[1189] A "learning plan" refers to specific learning tasks and schedules generated by the server to achieve the user's learning goals.

[1190] "AI Tutor Module" refers to an artificial intelligence-based software component designed to assist users in learning.

[1191] "Real-time" refers to immediate processing or response without delay.

[1192] "Learning progress data" refers to data that details the results and activities achieved by a user through learning activities.

[1193] "Motivational content" refers to messages and materials provided to keep users excited and interested in their learning or work.

[1194] "Natural language processing technology" refers to artificial intelligence technology for interpreting, understanding, and generating human language.

[1195] "Explanations and examples" refers to supplementary information and sample questions provided to users during their studies.

[1196] "Feedback" refers to ratings and comments provided by users, and is information used to improve system performance and services.

[1197] An "AI assistant" refers to an artificial intelligence-based software component that helps users with career planning, mental health, and other issues.

[1198] "Analysis" refers to the act of examining, understanding, and processing data and information.

[1199] The system of this invention is an AI system that allows users to receive learning support tailored to their individual learning pace and style, and allows companies to efficiently provide advice on career plans and mental and healthcare matters for individual employees. Specific embodiments of this system are described below.

[1200] Implementation of an AI tutor for students

[1201] A user launches the application on their smartphone or tablet and enters their login information. The device then sends this login information to a server. The server connects to a database to retrieve the user's personal information, past grades, and learning progress. The server then uses the retrieved data to analyze it using a generative AI model (e.g., GPT-4) and generate a customized learning plan for the user. This learning plan includes specific tasks and a schedule. The server then sends the generated learning plan to the device, which then displays it to the user.

[1202] When the user begins a task according to the learning plan, the AI ​​tutor module is activated and provides real-time support. If a question arises during learning, the user can enter it into the device's question input field. For example, they could enter, "Please tell me how to solve a quadratic equation." This question is sent to the server, which uses natural language processing technology to analyze the question and generate the most appropriate answer or example problem. This is then sent to the device and displayed to the user.

[1203] Learning progress is recorded in real time by the device and periodically sent to the server. The server analyzes this data and adjusts the next learning plan as needed. For example, if the user's understanding of a particular topic is lacking, tasks to reinforce the related topic will be added. Also, if the server determines that the user's motivation is declining, it will generate content to maintain motivation (encouraging messages or motivational content), send it to the device, and display it to the user.

[1204] Implementation of an AI secretary for businesses

[1205] A user launches a desktop or mobile application and enters their login information. The device sends this login information to a server, which connects to a database to retrieve personal information about the user, such as their work history and skill set. The user enters their consultation or question into the application's input fields, which the device then sends to the server.

[1206] For example, a user might input, "Please recommend some training courses." The server analyzes this request using natural language processing technology and generates a list of training courses that are most suitable for the user. This list is then sent to the terminal and displayed to the user. Furthermore, if the user inputs feedback about the usefulness of the advice provided, the terminal sends that feedback to the server. The server analyzes the feedback and uses it to improve the quality of future advice.

[1207] Specific examples

[1208] For example, suppose a student uses an application to solve a math problem. The student launches the application, enters their login information, and receives a study plan generated by the server based on their past study data. If the student has questions while working on the assignment, the AI ​​tutor provides real-time explanations. After studying, the device sends progress data to the server, which then adjusts the next study plan. If the student's motivation is declining, encouraging messages are displayed on the device.

[1209] As an example of a prompt sentence, if you enter, "I want to solve a quadratic equation problem in math. Please tell me how to solve it and the specific steps," the server will use a generative AI model to generate an appropriate step-by-step guide and display it on the device to help the user solve the problem.

[1210] In this way, the system of the present invention is designed to enable students and corporate employees to study effectively and receive support for career planning and mental health.

[1211] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1212] Step 1:

[1213] A user launches an application and logs in. The user taps the icon on their smartphone or tablet to launch the application, enters their ID and password on the login screen, and presses the login button. The device sends this authentication information to the server. The server connects to the database to confirm the authentication information and obtain the user's personal information. The information entered here is the login ID and password, and the data output is the authentication result and the user's personal information.

[1214] Step 2:

[1215] The server obtains user information and generates a study plan. After successful authentication, the server retrieves the user's past grades and learning progress from a database. This information is input into a generative AI model (e.g., GPT-4) to generate a study plan for the user. This study plan includes specific tasks and their schedules. The server sends this generated study plan to the device. The input is the user's study history and progress data, and the output is a study plan optimized for the user.

[1216] Step 3:

[1217] The terminal displays the learning plan to the user. The terminal receives the learning plan sent from the server and displays it on the screen. The user can check the learning plan on the terminal screen and confirm the specific learning tasks and schedule. The learning plan is received as input, and the content of the learning plan displayed to the user is output.

[1218] Step 4:

[1219] The user begins a learning task. The user begins a specific task (e.g., solving a math problem) according to the learning plan. If the user has a question, they enter it into the question input field on the device. For example, they might enter, "Please tell me how to solve a quadratic equation."

[1220] Step 5:

[1221] The terminal sends the user's question to the server. The terminal receives the question entered by the user and sends it to the server. The input information is the content of the user's question, and the output data is the question sent to the server.

[1222] Step 6:

[1223] The server analyzes the user's question and generates an answer. The server analyzes the received question using natural language processing technology and generates the optimal answer or example problem. A generative AI model is used in this process. The server sends the generated answer or example problem to the terminal. The input is the user's question, and the output is the analyzed answer or example problem.

[1224] Step 7:

[1225] The terminal displays the answers from the server to the user. The terminal displays the answers and example questions received from the server to the user. The user can use this as a reference to continue learning. The input is the answers and example questions sent from the server, and the output is the answers and example questions displayed to the user.

[1226] Step 8:

[1227] The device records learning progress data and sends it to the server. As the user progresses with their studies, the device records learning progress data (correct answer rate for questions, study time). This data is periodically sent to the server. The input is the user's learning progress data, and the output is the transmission of progress data to the server.

[1228] Step 9:

[1229] The server analyzes the learning progress data and adjusts the next learning plan. The server analyzes the received learning progress data and adjusts the next learning plan. If the user lacks understanding of a specific topic, it adds reinforcement tasks. The input is the learning progress data, and the output is the adjusted next learning plan.

[1230] Step 10:

[1231] The server generates content to maintain motivation and sends it to the device. The server analyzes learning progress data, and if it determines that the user's motivation is declining, it generates encouraging messages and motivating content and sends it to the device. The input is learning progress data, and the output is the generated content to maintain motivation.

[1232] (Application example 1)

[1233] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1234] Conventional systems were unable to provide information or recommend products that adequately met customer needs in brick-and-mortar stores. It was also difficult to manage the progress and maintain motivation of students and employees, resulting in a lack of effective educational support and mental health support. Furthermore, the system was also inadequate in recommending appropriate products and services based on health status, creating challenges in improving customer satisfaction and managing employee health.

[1235] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1236] In this invention, the server includes: a means for a user to launch an application and input login information; a means for the terminal to send the login information to the server; a means for the server to retrieve the user's personal information from a database; a means for the server to generate a study plan based on the user's study record and progress; a means for the server to send the generated study plan to the terminal; a means for the terminal to present study tasks to the user based on the study plan; a means for an AI tutor module to provide real-time support to the user while he or she is studying; a means for the terminal to send the user's study progress data to the server; a means for the server to analyze the data and adjust the next study plan; a means for the server to generate content to maintain the user's motivation and send it to the terminal; and a means for selecting products, checking inventory, and suggesting recommended products in real time when a customer visits a physical store. This enables more efficient customer service in physical stores and improved customer satisfaction.

[1237] An "application" is software that is operated by a user and runs on a variety of terminals.

[1238] "Login information" is information used to authenticate a user, typically a combination of a username and password.

[1239] "Terminal" refers to the device that a user uses to access an application, including smartphones, tablets, and personal computers.

[1240] A "server" is a computer system that runs on the back end of an application, accessing a database and performing processing.

[1241] A "database" is a data storage system for managing users' personal information, learning records, product inventory information, and so on.

[1242] "Study record" is data showing the records and grades of the user's previous studies.

[1243] A "study plan" is a list of specific study schedules and tasks that are generated based on the user's progress and goals.

[1244] A "learning task" is a specific learning activity or problem-solving task that a user should perform based on a learning plan.

[1245] The "AI Tutor Module" is an artificial intelligence system that provides real-time support and answers questions while users are learning.

[1246] "Study progress data" is data that indicates how far the user has progressed in their studies, and includes the percentage of correct answers to questions and the study time.

[1247] "Motivation maintenance content" refers to messages and content generated to increase a user's motivation to learn.

[1248] "Product selection" is the process by which customers identify products they will consider purchasing in a physical store.

[1249] "Inventory check" is the task of checking the quantity and status of products in physical stores and warehouses.

[1250] "Recommended products" is the process of recommending appropriate products based on a customer's needs and preferences.

[1251] "Natural language processing technology" is a technology that allows computers to understand and analyze human language.

[1252] "Feedback" refers to the evaluation or opinion that a user inputs regarding the plan or advice provided.

[1253] "AI Secretary" is an artificial intelligence system that supports users with training, career planning, mental health counseling, and more.

[1254] "Speech recognition" is a technology that converts a user's speech into text.

[1255] A "prompt" is text that is input into a generative AI model and is an instruction statement to obtain an appropriate generated result.

[1256] A "generative AI model" is an artificial intelligence model that generates text and answers based on a prompt.

[1257] The system of the present invention is a system that allows users to receive support tailored to their individual learning pace and needs, and provides useful information even in physical stores. Specific embodiments of the system are described below.

[1258] System Configuration

[1259] The system mainly consists of a terminal, a server, a database, and a generative AI model. Terminals can be devices such as smartphones, tablets, and PCs. The server is a computer system that accesses the database and performs the necessary processing, and can be implemented using Python and the Flask framework. The generative AI model is built using natural language processing technologies such as HuggingFace's Transformers.

[1260] Login process

[1261] A user launches an application on a terminal and enters login information (user name, password). This information is sent from the terminal to the server, which retrieves the user's personal information from a database. This authenticates the user and allows them to access the system.

[1262] Generate a lesson plan

[1263] The server generates a learning plan based on the user's past learning records and current progress. This learning plan includes specific tasks and schedules. The generated learning plan is sent to the device and displayed to the user.

[1264] Learning task presentation and real-time support

[1265] When a user starts a learning task, the device launches the AI ​​tutor module. When the user enters a question or concern, the information is sent to the server. The server uses natural language processing technology to analyze the question and generate appropriate explanations and examples. The generated explanations are sent to the device and provided to the user.

[1266] Learning progress and maintaining motivation

[1267] The device collects the user's learning progress (correct answer rate, study time) and sends it to the server. The server analyzes this data and adjusts the next learning plan. If the server determines that the user's motivation is declining, it generates encouraging messages and motivational content and sends them to the device.

[1268] Application in physical stores

[1269] When customers visit a physical store, they can use a terminal (a tablet or smartphone installed in the store) to receive product information, check inventory, and receive recommended products. When a user asks a question about how to select a product or the inventory status, the information is sent to a server, which analyzes it using natural language processing technology and provides the appropriate answer or product suggestion to the terminal.

[1270] Specific examples

[1271] Consider a case where a customer asks, "What products can boost the immune system?" in a physical store. This question is sent from the device to the server, and the server generates a response using a generative AI model. An example of a prompt sentence is "What products can boost the immune system?" As a result, the server recommends an appropriate product (e.g., "vitamin C supplement") and sends that information to the device for display.

[1272] In this way, the system of the present invention integrates the user's learning activities with the provision of information in physical stores, providing effective support.

[1273] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1274] Step 1:

[1275] A user starts an application on a device and enters login information (user name, password). The device sends this login information to the server. Based on this input, the server retrieves the user's personal information from the database and sends it to the device.

[1276] Step 2:

[1277] The server retrieves the user's past learning records and current progress data from the database and generates a new learning plan based on that data. The generated learning plan includes learning tasks and a schedule. This data processing establishes an optimal learning plan for the user. The server then sends the generated learning plan to the terminal, which displays it to the user.

[1278] Step 3:

[1279] The user performs learning tasks based on the displayed learning plan. If a question or doubt arises during learning, the user inputs it. The device sends the input question to the server. To respond to this question, the server uses a generative AI model to analyze the question and generate appropriate answers and example problems. The generated answers are sent to the device and displayed to the user.

[1280] Step 4:

[1281] The device collects the user's learning progress data (correct answer rate, study time) and periodically sends it to the server. The server analyzes this data and dynamically adjusts the next study plan. If the server determines that the user's motivation to study is declining, it generates motivational messages and video content and sends them to the device.

[1282] Step 5:

[1283] When a customer visits a physical store, they use a device (a tablet or smartphone in the store) to input a question about a product (e.g., "What products boost immunity?"). The device sends this question to a server. The server uses a generative AI model to analyze the question and generate appropriate product recommendations and stock status information. Accurate product information is generated by processing the data using this prompt text. The generated information is sent to the device and displayed to the customer.

[1284] Step 6:

[1285] If the customer checks the recommended products and asks more detailed questions, the input is sent to the server in a similar manner, and the server generates an answer and sends it to the terminal. At this step, product selection, inventory check, and recommendation suggestions are performed in real time.

[1286] In this way, at each processing step of the system, the user, device, and server work together to provide efficient support by utilizing generative AI models and prompt sentences.

[1287] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1288] The present invention combines an emotion engine with an AI system that allows individual learners and corporate employees to receive individually customized learning plans, career support, and mental health consultations. A specific embodiment of this system is described below.

[1289] Implementation of an AI tutor for students

[1290] The user launches the application

[1291] First, a user launches an application on a device such as a smartphone or tablet and enters their login information. The device sends this login information to the server, which then retrieves the user's personal information from a database.

[1292] The server generates the lesson plan

[1293] The server generates a learning plan based on the user's past performance and learning progress. This learning plan includes specific tasks and schedules for the user to effectively study. The server sends the generated learning plan to the terminal, which then displays it to the user.

[1294] Presenting and supporting learning tasks

[1295] When a user starts a learning task, the device launches the AI ​​tutor module. When the user inputs a question or concern, the device sends it to the server, which analyzes it using natural language processing technology and generates appropriate explanations and examples. The server then sends the generated explanations and examples to the device, which displays them to the user.

[1296] Emotion engine monitoring

[1297] The device acquires emotional data from the user's facial expressions, voice, input, etc. This data is analyzed by the emotion engine to identify the user's emotional state. The device then transmits the emotional data to the server.

[1298] Learning progress and motivation

[1299] The device collects the user's learning progress data (e.g., percentage of correct answers and study time) and sends it to the server. The server analyzes this data and emotional data and adjusts the next learning plan appropriately. If the server determines that the user's motivation is declining, it generates encouraging messages and motivational content, sends them to the device, and displays them to the user.

[1300] Specific examples

[1301] For example, suppose a student uses an application to solve a math problem. The student launches the application, enters their login information, and receives a study plan generated by the server. If the student has questions while working on the problem, the AI ​​tutor will provide real-time explanations. Furthermore, if the emotion engine detects stress from the student's facial expressions or voice, the server will send and display encouraging messages or content to help them concentrate on the device. After studying, the device will send progress data and emotion data to the server, which will then adjust the next study plan.

[1302] Implementation of an AI secretary for businesses

[1303] The user launches the application

[1304] A user launches a desktop or mobile application and enters their login information. The device sends this login information to a server, which retrieves the user's personal information from a database.

[1305] Conversation with an AI secretary

[1306] When a user asks the AI ​​secretary for advice on training, career planning, mental health, etc., the device receives the user's request via voice recognition or text input and sends it to the server, which then uses natural language processing technology to analyze the request and generate an appropriate plan or response.

[1307] Support by Emotion Engine

[1308] When the device receives a request, it acquires emotional data from the user's facial expressions, voice, and input. The emotion engine analyzes this data and generates a response or plan that reflects the user's emotional state.

[1309] Providing plans and advice

[1310] The server sends the generated plans and advice to the device, which then displays them to the user. For example, if a user asks, "What training courses are recommended for career advancement?", the server generates a list of recommended training courses, sends it to the device, and displays it to the user. Additionally, if the emotion engine determines that the user is feeling stressed, it can also provide advice on relaxation methods and mental health.

[1311] Gathering and implementing feedback

[1312] When a user inputs feedback on the provided plan or advice, the device sends the feedback to the server, which analyzes the feedback and uses it to improve the quality of future plans and advice.

[1313] In this way, by combining an emotion engine, the system of the present invention provides learning plans and career plans that correspond to the user's emotional state, thereby achieving more effective and personalized support.

[1314] The processing flow will be explained below.

[1315] Processing program for AI tutoring for students

[1316] Step 1:

[1317] When a user launches an application on their smartphone or tablet, a login screen appears, and the user enters their ID and password. The device then sends the login information to the server.

[1318] Step 2:

[1319] The server receives the login information and retrieves the user's personal information (grade, learning status, learning goals, etc.) from the database. The server then sends the retrieved information to the terminal.

[1320] Step 3:

[1321] The server generates a study plan based on the user's past grades and learning progress, and then sends the generated study plan to the device.

[1322] Step 4:

[1323] The device breaks down the study plan received from the server into daily and weekly study tasks and presents them to the user. The user confirms the study tasks and begins executing them.

[1324] Step 5:

[1325] When a user has a question or concern while progressing through a learning task, they can input a question, and the device will send the user's question to the server.

[1326] Step 6:

[1327] The server analyzes the received questions using natural language processing technology and generates appropriate answers and examples, which are then sent to the device.

[1328] Step 7:

[1329] The device receives the answers and examples from the server and displays them to the user, who can then confirm them and continue learning.

[1330] Step 8:

[1331] The device acquires emotional data from the user's facial expressions, voice, and input, analyzes it using an emotion engine, identifies the user's emotional state, and sends the data to the server.

[1332] Step 9:

[1333] The device collects the user's learning progress data (such as the rate at which questions are answered correctly and the amount of time spent studying) and sends it to the server. The server analyzes the progress data and emotional data and adjusts the next study plan appropriately.

[1334] Step 10:

[1335] If the server determines that the user's motivation is declining, it generates encouraging messages and motivational content and sends them to the device, which then displays them to the user.

[1336] Processing AI secretary programs for businesses

[1337] Step 1:

[1338] When a user launches a desktop or mobile application, a login screen appears, where the user enters their ID and password, and the device sends the login information to the server.

[1339] Step 2:

[1340] The server receives the login information, retrieves the user's personal information from the database, and sends the retrieved information to the terminal.

[1341] Step 3:

[1342] Users can use the in-app interface to ask the AI ​​secretary for training advice, career planning, and mental health advice, with requests received by the device via voice recognition or text input.

[1343] Step 4:

[1344] The device sends the received request to the server.

[1345] Step 5:

[1346] The server analyzes the request using natural language processing technology and generates an appropriate plan or answer.

[1347] Step 6:

[1348] The device acquires emotional data from the user's facial expressions, voice, and input, and sends it to the server. The emotion engine analyzes this data and provides a plan based on the user's emotional state.

[1349] Step 7:

[1350] The server generates plans and answers and sends them to the device, which then displays them to the user. For example, if a user asks, "What training courses are recommended for my career?", the server generates a list of appropriate training courses, sends it to the device, and displays it to the user.

[1351] Step 8:

[1352] The user enters feedback on the provided plans and answers, which is then sent by the device to the server.

[1353] Step 9:

[1354] The server analyzes the feedback and uses it to improve future plans and advice.

[1355] In this way, the system of the present invention optimizes the user's studies and career plans according to the user's emotional state and provides effective support.

[1356] Example 2

[1357] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1358] In modern education and career support, personalized guidance and support for individual learners and employees is becoming increasingly important. However, existing systems do not adequately provide support that takes into account the user's emotional state, which can reduce the effectiveness of learning and career support. It is also difficult to maintain user motivation, leading to issues such as ineffective implementation of learning and career plans.

[1359] The specification process by the specification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for acquiring the user's personal information from a database, means for generating a study plan based on the user's study record and progress, and means for an emotion engine to identify the user's emotional state and analyze the data. This makes it possible to provide an individualized study plan or career plan that reflects the user's emotional state, thereby enabling effective study and career support while maintaining the user's motivation.

[1360] "User" refers to an individual who uses the Application to receive learning planning and career support services.

[1361] A "terminal" is a device that a user uses to run an application, and includes a smartphone, tablet, desktop, etc.

[1362] "Server" refers to a central computer system that receives, processes, and analyzes data sent by users.

[1363] "Login Information" refers to the authentication information required for a user to access a system, and typically consists of a username and password.

[1364] "Database" refers to an information management system for storing data such as users' personal information, learning records, and progress information.

[1365] A "study plan" refers to specific tasks and schedules generated by the server to help users study effectively.

[1366] "AI Tutor Module" refers to artificial intelligence that provides real-time support to users while they are learning.

[1367] An "emotion engine" refers to a technology that acquires and analyzes emotional data from a user's facial expressions, voice, input content, etc.

[1368] "Natural language processing technology" refers to technology that enables computers to understand human language and generate appropriate responses.

[1369] "Feedback" refers to opinions and impressions that users input regarding the plans and advice provided.

[1370] "Motivation" refers to the user's will and motivation to achieve a goal.

[1371] The present invention combines an emotion engine with an AI system that enables individual learners and corporate employees to receive individually customized learning plans, career support, and mental health consultations. This system enables users to receive effective learning and career support using an application. A specific embodiment of this system is described below.

[1372] Hardware and software used

[1373] 1. Hardware

[1374] Smartphones and tablets (student devices)

[1375] Desktop (devices for corporate employees)

[1376] Server (responsible for data processing and analysis)

[1377] 2. Software

[1378] Application platform (iOS, Android, Windows, etc.)

[1379] Database (e.g. MySQL, PostgreSQL)

[1380] Natural language processing technology (e.g., GPT-3, BERT)

[1381] Machine learning algorithms (e.g., scikit-learn)

[1382] Emotion engines (e.g., Affectiva, Microsoft Emotion API)

[1383] Example of operation

[1384] AI tutors for students

[1385] 1. Launching the application and logging in

[1386] A user launches an application on their smartphone or tablet and enters their login information. The device encrypts the login information and sends it to a server, which then retrieves the user's personal information from a database. The personal information is then sent to the device and displayed to the user.

[1387] 2. Generate a learning plan

[1388] The server uses a machine learning algorithm to generate an optimal study plan based on the user's past performance and learning progress. The generated information is sent to the device and displayed to the user.

[1389] 3. Support for learning tasks

[1390] When a user starts a learning task, the device launches an AI tutoring module (e.g., Dialogflow, GPT-3). When the user inputs a question, the device sends it to the server, which analyzes it using natural language processing technology and generates appropriate explanations and examples. These are then provided to the user via the device.

[1391] 4. Emotion Engine Monitoring

[1392] The device uses a camera and microphone to collect the user's facial expressions, voice, and input, and analyzes them with an emotion engine. The emotion data is sent to a server, and the analysis results are reflected in the next lesson plan.

[1393] 5. Staying motivated

[1394] The server analyzes the user's learning progress and emotional state, and generates encouraging messages and content to maintain motivation. These contents are provided to the user via their device.

[1395] Example prompt:

[1396] "Do you have any questions about the next math assignment? Type in any questions you may have."

[1397] AI secretaries for businesses

[1398] 1. Launching the application and logging in

[1399] A user launches an application on a desktop or mobile device and enters their login information. The device encrypts the login information and sends it to a server, which retrieves their personal information from a database. The retrieved information is then displayed to the user on the device.

[1400] 2. Conversation with an AI secretary

[1401] When a user requests training consultation or career planning through text or voice input, the device sends the request to the server. The server analyzes the request using natural language processing technology and generates an appropriate plan or answer. The generated plan is displayed to the user via the device.

[1402] 3. Support by Emotion Engine

[1403] The device collects the user's facial expressions and voice, analyzes them with an emotion engine, and sends the emotion data to the server, where it is reflected in the response and plan.

[1404] 4. Gather and incorporate feedback

[1405] The user enters feedback on the plan or advice provided, and the device sends the feedback to the server, which analyzes the feedback and uses it for future improvements.

[1406] Example prompt:

[1407] "Do you have any questions about your career plans? Please enter your specific question."

[1408] This system provides personalized learning and career plans that take into account the user's emotional state, enabling effective support while increasing the user's motivation.

[1409] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1410] AI Tutoring for Students

[1411] Step 1: Launch the application and log in

[1412] 1. The user launches the application on the device and the login screen appears.

[1413] 2. The user enters their login information (username and password).

[1414] Input: Username and Password

[1415] Output: Encrypted login information

[1416] 3. The device sends the encrypted login information to the server.

[1417] Data processing: Encryption of entered login information

[1418] Data calculation: Sending login information to the server

[1419] 4. The server retrieves the user's personal information from the database.

[1420] Input: Encrypted login information

[1421] Output: User's personal information

[1422] 5. The device displays the personal information to the user.

[1423] Data processing: Converting acquired personal information into a display format

[1424] Data calculation: Display on user screen

[1425] Step 2: Generate a lesson plan

[1426] 1. The server generates a study plan using a machine learning algorithm based on the user's past grades and learning progress data.

[1427] Input: User's past performance data, learning progress data

[1428] Output: personalized learning plan

[1429] Data calculation: Generating learning plans using machine learning algorithms

[1430] 2. The server sends the generated learning plan to the device.

[1431] Data calculation: Sending learning plans to the device

[1432] 3. The device displays the lesson plan to the user.

[1433] Data processing: Converting the learning plan into a display format

[1434] Data Calculation: Viewing the Learning Plan

[1435] Step 3: Supporting the learning task

[1436] 1. The user selects a task to begin the learning task.

[1437] Input: Select a learning task

[1438] Output: Details of the selected task

[1439] 2. The device will launch the AI ​​tutor module and display the task details.

[1440] Data calculation: Launching the AI ​​tutor module and generating display content

[1441] 3. The user enters their concern or question via text or voice.

[1442] Input: User's doubts or questions

[1443] Output: Questions and queries

[1444] 4. The device sends the question or inquiry to the server.

[1445] Data calculation: Send data to the server

[1446] 5. The server uses natural language processing technology to analyze the question and generate appropriate explanations and examples.

[1447] Input: Questions and questions

[1448] Output: Explanation and examples

[1449] Data processing: Analysis, explanations and example generation using natural language processing technology

[1450] 6. The server sends the generated explanations and examples to the terminal, which displays them.

[1451] Data calculation: Sending and displaying explanations and examples

[1452] Step 4: Monitoring with the Emotion Engine

[1453] 1. The device uses a camera and microphone to collect the user's facial expressions, voice, and input.

[1454] Input: facial expression data, voice data, input content

[1455] Output: Raw data

[1456] 2. The device's emotion engine analyzes the collected data and identifies the user's emotional state.

[1457] Data processing: analyzing data and identifying emotional states

[1458] Output: Emotional state data

[1459] 3. The device sends the emotional state data to the server.

[1460] Data calculation: Sending emotional state data

[1461] Step 5: Study progress and maintain motivation

[1462] 1. The device collects the user's learning progress data (correct answer rate and study time).

[1463] Input: Learning progress data

[1464] Output: Collected data

[1465] 2. The device sends the collected data to the server.

[1466] Data calculation: Sending progress data

[1467] 3. The server analyzes the progress and emotion data and adjusts the next learning plan.

[1468] Input: Learning progress data, emotion data

[1469] Output: Adjusted learning plan

[1470] Data calculations: analyzing data and adjusting learning plans

[1471] 4. The server generates encouraging messages and content to keep the user motivated and sends them to the device.

[1472] Input: User emotion data

[1473] Output: Support message and content

[1474] Data calculation: generating and sending support messages and content

[1475] 5. The device displays the support message or content received to the user.

[1476] Data processing: converting messages and content into a display format

[1477] Data operations: displaying messages and content

[1478] Processing steps for corporate AI secretaries

[1479] Step 1: Launch the application and log in

[1480] 1. A user launches an application on a desktop or mobile app and is presented with a login screen.

[1481] 2. The user enters their login information.

[1482] Input: Username and Password

[1483] Output: Encrypted login information

[1484] 3. The device sends the encrypted login information to the server.

[1485] Data processing: Encryption of entered login information

[1486] Data calculation: Sending login information to the server

[1487] 4. The server retrieves the user's personal information and work history from the database.

[1488] Input: Encrypted login information

[1489] Output: Personal information and work history

[1490] 5. The device displays the user's personal information and work history.

[1491] Data processing: Converting acquired personal information into a display format

[1492] Data calculation: Display on user screen

[1493] Step 2: Interact with the AI ​​secretary

[1494] 1. The user inputs text or voice to consult about training, create a career plan, or receive mental health advice.

[1495] Input: User request

[1496] Output: Request data

[1497] 2. The device sends the user's request to the server.

[1498] Data calculation: Sending request data

[1499] 3. The server uses natural language processing technology to analyze the request and generate an appropriate plan or answer.

[1500] Input: User request data

[1501] Output: Plans and answers

[1502] Data processing: Natural language processing techniques for analysis, planning and answer generation

[1503] 4. The server sends the generated plan and answer to the terminal, which displays it.

[1504] Data calculation: Sending and displaying plans and answers

[1505] Step 3: Support with the Emotion Engine

[1506] 1. The device uses a camera and microphone to collect the user's facial expressions and voice.

[1507] Input: facial expression data, voice data

[1508] Output: Raw data

[1509] 2. The emotion engine analyzes the collected data and identifies the user's emotional state.

[1510] Data processing: analyzing data and identifying emotional states

[1511] Output: Emotional state data

[1512] 3. The device sends the emotional state data to the server.

[1513] Data calculation: Sending emotional state data

[1514] Step 4: Gather and incorporate feedback

[1515] 1. The user enters feedback on the plan or advice provided.

[1516] Input: Feedback

[1517] Output: Feedback data

[1518] 2. The device sends the feedback data to the server.

[1519] Data calculation: Sending feedback data

[1520] 3. The server analyzes the feedback and uses it to improve future plans and advice.

[1521] Input: Feedback data

[1522] Output: Improved plans and advice

[1523] Data processing: Analyzing feedback data, identifying and implementing improvements

[1524] 4. The device displays improved plans and advice to the user.

[1525] Data transformation: Transforming improved plans and advice into a display format

[1526] Data Calculation: Improved plans and advice display

[1527] (Application example 2)

[1528] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1529] Factory workers are prone to experiencing mental fatigue and a loss of concentration and motivation when performing long, monotonous tasks or working in a high-stress environment. If these conditions continue, it can lead to problems such as a decline in work efficiency, an increase in work errors, and even increased safety risks. Conventional methods have made it difficult to monitor workers' mental state in real time and provide appropriate feedback and break suggestions, so a means to effectively solve these problems is needed.

[1530] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1531] In this invention, the server includes means for acquiring the user's personal information from a database, means for generating a study plan based on the user's study record and progress, means for the terminal to acquire emotion data from the user's facial expressions, voice, and input content, and means for the emotion engine to analyze the user's emotion state and send it to the server. This makes it possible to monitor the emotion state of factory workers in real time and provide suggestions for work breaks or encouraging messages as needed.

[1532] "User" refers to an individual who uses the system, including a factory worker or a student.

[1533] An "application" is a software program that a user runs and uses on a terminal.

[1534] "Login information" refers to authentication information for accessing a system, such as a user name and password.

[1535] A "terminal" is a device used by a user, such as a smartphone, tablet, smart glasses, or head-mounted display.

[1536] A "server" is a computer system responsible for processing, storing, and transmitting user data.

[1537] A "database" is a system that organizes and stores data such as users' personal information and learning records.

[1538] A "study plan" is a general term for tasks and schedules designed to help users study efficiently.

[1539] The "AI Tutor Module" is an artificial intelligence system that provides real-time support to users while they are learning.

[1540] "Study progress data" refers to data such as the percentage of correct answers and study time as the user progresses with their studies.

[1541] "Facial expressions, voice, and input content" are data used to analyze the user's emotional state.

[1542] An "emotion engine" is an algorithm or system for analyzing a user's emotional state.

[1543] A "work break suggestion" is a notification or message that encourages a user who is working to take a break.

[1544] "Natural language processing technology" is a technology that analyzes text and voice input by users and generates appropriate answers.

[1545] MODE FOR CARRYING OUT THE INVENTION

[1546] The present invention is a support system for users to perform factory work efficiently and safely. This system uses a device such as smart glasses worn by the user to acquire emotional data from the user's facial expressions and voice, and manages the progress of the work.

[1547] The system is structured as follows: First, the user puts on the smart glasses and launches the application. After the user enters their login information, the device sends this information to the server, which then retrieves the user's personal information from a database. The server is equipped with a high-performance computer, a database, and an AI emotion engine. The software used includes Python, OpenCV, Keras, and TensorFlow.

[1548] The server then generates a work plan for each user and sends it to the device. The work plan includes specific tasks and schedules. As the worker works according to the plan, if a question arises, the worker sends a query to the server via the smart glasses. The server analyzes the query using natural language processing technology, generates an appropriate answer, and sends it to the device. At this time, the user's input and voice are also analyzed.

[1549] The emotion engine analyzes the user's facial expressions and voice in real time to identify their emotional state. For example, if the emotion engine detects stress, it will generate a message suggesting a break or offering encouragement, which will be sent to the user's device and displayed. It also adjusts the next task plan based on learning progress data and emotion data.

[1550] For example, if the emotion engine detects that a factory worker is very tired, the system will send a message like this: "The worker appears tired, so we recommend that you take a break." This will allow workers to take breaks at the appropriate time, improving safety and work efficiency.

[1551] An example of a prompt sentence might be:

[1552] "Transform the following sentence into a feedback message based on emotion data: 'The worker is showing clear signs of fatigue on his face.'"

[1553] The above is a specific embodiment for carrying out the present invention, and by using this system, the safety and efficiency of factory workers can be significantly improved.

[1554] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1555] Step 1:

[1556] The user puts on the smart glasses, launches the application, and enters their login information, which is then sent to the server via the device.

[1557] Input: User login information (username, password)

[1558] Output: Login information sent to the server

[1559] Step 2:

[1560] The server receives the login information and retrieves the user's personal information from a database, making available a data set specific to the user.

[1561] Input: Login information received by the server

[1562] Output: User's personal information

[1563] Step 3:

[1564] The server generates an optimal work plan for the user based on the user's personal information and past learning and work records.

[1565] Input: User's personal information, learning records, work records

[1566] Output: Generated work plan

[1567] Step 4:

[1568] The server sends the generated work plan to the terminal, which then presents the work plan to the user, who then begins work according to the work plan.

[1569] Input: Generated Work Plan

[1570] Output: Submitted work plan, Work plan presentation

[1571] Step 5:

[1572] If a user has any questions or concerns while working, they can input the question via voice or text through the smart glasses, and the device will send it to the server.

[1573] Input: User question (voice or text)

[1574] Output: The question is sent to the server

[1575] Step 6:

[1576] The server uses natural language processing technology to analyze the received question and generate appropriate answers and instructions, thereby resolving the user's doubts.

[1577] Input: User question

[1578] Output: Generated answers and instructions

[1579] Step 7:

[1580] The server sends the generated answers and instructions to the terminal, which displays them to the user, who can then continue working based on the displayed information.

[1581] Input: Generated answers and instructions

[1582] Output: Submitted answers and instructions, presentation of answers and instructions

[1583] Step 8:

[1584] The device acquires emotional data from the user's facial expressions, voice, and input content and sends it to the server.

[1585] Input: User's facial expressions, voice, and input

[1586] Output: Emotion data is sent to the server

[1587] Step 9:

[1588] The server's emotion engine analyzes the emotion data to identify the user's emotional state, and generates break suggestions or encouraging messages as needed based on the analysis results.

[1589] Input: Emotion data

[1590] Output: Identified emotional state, suggestion to take a break, or a message of encouragement

[1591] Step 10:

[1592] The server sends the generated break suggestion or encouraging message to the terminal, which displays it to the user, who can then take a break or continue working.

[1593] Input: Generated break suggestions and encouraging messages

[1594] Output: Break suggestions and encouragement messages sent, display of suggestions and messages

[1595] Step 11:

[1596] The device collects data on the user's learning progress and emotions and sends it to the server, which analyzes the data and adjusts the next task plan.

[1597] Input: learning progress data, emotion data

[1598] Output: Adjusted next work plan

[1599] As a specific example of how it works, if the emotion engine detects that a factory worker is very tired, the system will generate a message like this: "The worker appears tired, so we recommend that you take a break." This will allow workers to take breaks at appropriate times, improving safety and work efficiency.

[1600] An example prompt is, "Transform the following sentence into a feedback message based on emotion data: 'The worker is showing obvious signs of fatigue on his face.'"

[1601] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1602] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1603] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1604] [Fourth embodiment]

[1605] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1606] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1607] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1608] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1609] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1610] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1611] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1612] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1613] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1614] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1615] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1616] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1617] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1618] The system of the present invention is an AI system that allows users to receive learning support tailored to their individual learning pace and style, and allows companies to efficiently provide advice on career plans and mental and healthcare matters for individual employees. Specific embodiments of this system are described below.

[1619] Implementation of an AI tutor for students

[1620] The user launches the application

[1621] First, a user launches an application on a device such as a smartphone or tablet and enters their login information. The device sends this login information to the server, which then retrieves the user's personal information from a database.

[1622] The server generates the lesson plan

[1623] The server generates a study plan based on the user's past grades and learning progress. This study plan includes specific tasks and schedules for the user to study effectively. The server sends the generated study plan to the terminal, which displays it to the user.

[1624] Presenting and supporting learning tasks

[1625] When a user starts a learning task, the device launches the AI ​​tutor module. When the user inputs a question or concern, the device sends it to the server, which analyzes it using natural language processing technology and generates appropriate explanations and examples. The server then sends the generated explanations and examples to the device, which displays them to the user.

[1626] Learning progress and motivation

[1627] The device collects the user's learning progress data (such as the rate at which questions are answered correctly and the amount of time spent studying) and sends it to the server. The server analyzes this data and adjusts the next study plan. The server also analyzes the user's learning data, and if it determines that motivation is declining, it generates encouraging messages and motivational content, which it sends to the device and displays to the user.

[1628] Implementation of an AI secretary for businesses

[1629] The user launches the application

[1630] A user launches a desktop or mobile application and enters their login information. The device sends this login information to a server, which retrieves the user's personal information from a database.

[1631] Conversation with an AI secretary

[1632] When a user asks the AI ​​secretary for advice on training, career planning, mental health, etc., the device receives the user's request via voice recognition or text input. The device then sends the request to a server, which uses natural language processing technology to analyze the request and generate an appropriate plan or response.

[1633] Providing plans and advice

[1634] The server sends the generated plan and advice to the device, which then displays it to the user. For example, if a user asks, "What training courses are recommended for career advancement?", the server generates a list of recommended training courses based on the user's work history and current skill set and sends it to the device.

[1635] Gathering and implementing feedback

[1636] When a user inputs feedback on the provided advice, the device sends the feedback to the server, which analyzes the feedback and uses it as learning data to improve the quality of future advice.

[1637] Specific examples

[1638] As a concrete example, let's say a student uses an application to solve a math problem. The student launches the application, enters their login information, and receives a study plan generated by the server based on their past study data. If the student has questions while working on the assignment, the AI ​​tutor provides real-time explanations. After studying, the device sends progress data to the server, which then adjusts the next study plan. If the student's motivation is declining, encouraging messages are displayed on the device.

[1639] In this way, the system of the present invention is designed to enable students and corporate employees to study effectively and receive support for career planning and mental health.

[1640] The processing flow will be explained below.

[1641] Processing program for AI tutoring for students

[1642] Step 1:

[1643] A user launches an application on a smartphone or tablet.

[1644] A login screen will appear, and the user will enter their ID and password.

[1645] The terminal sends the entered login information to the server.

[1646] Step 2:

[1647] The server receives the login information and retrieves the user's personal information (grade, learning status, learning goals, etc.) from the database.

[1648] The server sends the acquired information to the terminal.

[1649] Step 3:

[1650] The server generates an optimal study plan based on the user's study records and progress.

[1651] The server sends the generated learning plan to the terminal.

[1652] Step 4:

[1653] The device breaks down the study plan received from the server into daily and weekly study tasks and presents them to the user.

[1654] The user confirms the learning task and begins execution.

[1655] Step 5:

[1656] As the user progresses through the learning task, if they come across something they don't understand or have questions about, they can input a question.

[1657] The terminal sends the user's question to the server.

[1658] Step 6:

[1659] The server analyzes the questions it receives using natural language processing technology and generates appropriate answers and example questions.

[1660] The server sends the generated answers and example questions to the terminal.

[1661] Step 7:

[1662] The terminal displays the answers and examples received from the server to the user.

[1663] The user reads and interprets it and continues learning.

[1664] Step 8:

[1665] As the learning progresses, the terminal collects the user's learning progress data (for example, the percentage of correct answers to questions and the time spent studying).

[1666] The terminal transmits the collected progress data to the server.

[1667] Step 9:

[1668] The server analyzes the progress data and adjusts the next learning plan appropriately.

[1669] Furthermore, if the server analyzes the progress data and determines that the user's motivation is declining, it generates encouraging messages and motivational content.

[1670] The server transmits the generated content and messages to the terminal.

[1671] Step 10:

[1672] The device displays encouraging messages and motivational content to the user.

[1673] This will motivate users to continue learning.

[1674] Processing AI secretary programs for businesses

[1675] Step 1:

[1676] A user launches a desktop or mobile application.

[1677] A login screen will appear, and the user will enter their ID and password.

[1678] The terminal sends the entered login information to the server.

[1679] Step 2:

[1680] The server receives the login information and retrieves the user's personal information from a database.

[1681] The server sends the acquired information to the terminal.

[1682] Step 3:

[1683] Users use the application's interface to ask the AI ​​secretary for training advice, career planning, and mental health advice.

[1684] A request is received by the device via voice recognition or text input.

[1685] Step 4:

[1686] The terminal transmits the received request to the server.

[1687] Step 5:

[1688] The server analyzes the request using natural language processing technology and generates an appropriate plan or answer.

[1689] Step 6:

[1690] The server sends the generated plan and answer to the terminal.

[1691] Step 7:

[1692] The terminal displays the plan and answer received from the server to the user.

[1693] For example, if a user asks "What training courses are recommended for career advancement?", the server generates a list of recommended training courses, sends it to the terminal, and displays it to the user.

[1694] Step 8:

[1695] Users provide feedback on the plans and answers provided.

[1696] Feedback is sent by the terminal to the server.

[1697] Step 9:

[1698] The server analyzes the feedback and uses it to improve future plans and advice.

[1699] This will realize a system that allows users to receive effective and efficient support for their individual learning and career plans.

[1700] Example 1

[1701] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1702] Conventional online learning systems and corporate support systems have difficulty responding to the individual needs of each user, and have been unable to provide efficient support for learning, career planning, or mental health consultations. As a result, users' motivation has declined and it has been difficult to provide effective learning support.

[1703] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1704] In this invention, the server includes means for acquiring personal information about the user, means for generating a study plan, means for generating content to maintain motivation, means for the terminal to provide the user with an individual study plan and support content in real time, means for analyzing the user's requests using natural language processing technology and generating appropriate explanations and examples, and means for collecting and analyzing feedback and using it to improve quality in the future. This makes it possible to efficiently provide optimal study support, career planning, and mental health consultations for each user in real time.

[1705] "User" refers to an individual or legal entity that uses an information system.

[1706] "Application" means a software program designed for use by a user.

[1707] "Authentication information" refers to information such as ID and password used when a user logs in.

[1708] "Device" refers to an electronic device (e.g., smartphone, tablet, or PC) on which a user runs an application.

[1709] "Server" refers to a central processing unit that processes user requests and provides the required information and services.

[1710] "Personal Information" means information about a user, including identifiable data (e.g., name, address, grades).

[1711] A "database" refers to data storage for efficiently managing large amounts of data used by an organization or system.

[1712] "Learning history" refers to records of a user's past learning activities and their results.

[1713] "Progress" refers to the progress a user makes toward a particular task or goal.

[1714] A "learning plan" refers to specific learning tasks and schedules generated by the server to achieve the user's learning goals.

[1715] "AI Tutor Module" refers to an artificial intelligence-based software component designed to assist users in learning.

[1716] "Real-time" refers to immediate processing or response without delay.

[1717] "Learning progress data" refers to data that details the results and activities achieved by a user through learning activities.

[1718] "Motivational content" refers to messages and materials provided to keep users excited and interested in their learning or work.

[1719] "Natural language processing technology" refers to artificial intelligence technology for interpreting, understanding, and generating human language.

[1720] "Explanations and examples" refers to supplementary information and sample questions provided to users during their studies.

[1721] "Feedback" refers to ratings and comments provided by users, and is information used to improve system performance and services.

[1722] An "AI assistant" refers to an artificial intelligence-based software component that helps users with career planning, mental health, and other issues.

[1723] "Analysis" refers to the act of examining, understanding, and processing data and information.

[1724] The system of this invention is an AI system that allows users to receive learning support tailored to their individual learning pace and style, and allows companies to efficiently provide advice on career plans and mental and healthcare matters for individual employees. Specific embodiments of this system are described below.

[1725] Implementation of an AI tutor for students

[1726] A user launches the application on their smartphone or tablet and enters their login information. The device then sends this login information to a server. The server connects to a database to retrieve the user's personal information, past grades, and learning progress. The server then uses the retrieved data to analyze it using a generative AI model (e.g., GPT-4) and generate a customized learning plan for the user. This learning plan includes specific tasks and a schedule. The server then sends the generated learning plan to the device, which then displays it to the user.

[1727] When the user begins a task according to the learning plan, the AI ​​tutor module is activated and provides real-time support. If a question arises during learning, the user can enter it into the device's question input field. For example, they could enter, "Please tell me how to solve a quadratic equation." This question is sent to the server, which uses natural language processing technology to analyze the question and generate the most appropriate answer or example problem. This is then sent to the device and displayed to the user.

[1728] Learning progress is recorded in real time by the device and periodically sent to the server. The server analyzes this data and adjusts the next learning plan as needed. For example, if the user's understanding of a particular topic is lacking, tasks to reinforce the related topic will be added. Also, if the server determines that the user's motivation is declining, it will generate content to maintain motivation (encouraging messages or motivational content), send it to the device, and display it to the user.

[1729] Implementation of an AI secretary for businesses

[1730] A user launches a desktop or mobile application and enters their login information. The device sends this login information to a server, which connects to a database to retrieve personal information about the user, such as their work history and skill set. The user enters their consultation or question into the application's input fields, which the device then sends to the server.

[1731] For example, a user might input, "Please recommend some training courses." The server analyzes this request using natural language processing technology and generates a list of training courses that are most suitable for the user. This list is then sent to the terminal and displayed to the user. Furthermore, if the user inputs feedback about the usefulness of the advice provided, the terminal sends that feedback to the server. The server analyzes the feedback and uses it to improve the quality of future advice.

[1732] Specific examples

[1733] For example, suppose a student uses an application to solve a math problem. The student launches the application, enters their login information, and receives a study plan generated by the server based on their past study data. If the student has questions while working on the assignment, the AI ​​tutor provides real-time explanations. After studying, the device sends progress data to the server, which then adjusts the next study plan. If the student's motivation is declining, encouraging messages are displayed on the device.

[1734] As an example of a prompt sentence, if you enter, "I want to solve a quadratic equation problem in math. Please tell me how to solve it and the specific steps," the server will use a generative AI model to generate an appropriate step-by-step guide and display it on the device to help the user solve the problem.

[1735] In this way, the system of the present invention is designed to enable students and corporate employees to study effectively and receive support for career planning and mental health.

[1736] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1737] Step 1:

[1738] A user launches an application and logs in. The user taps the icon on their smartphone or tablet to launch the application, enters their ID and password on the login screen, and presses the login button. The device sends this authentication information to the server. The server connects to the database to confirm the authentication information and obtain the user's personal information. The information entered here is the login ID and password, and the data output is the authentication result and the user's personal information.

[1739] Step 2:

[1740] The server obtains user information and generates a study plan. After successful authentication, the server retrieves the user's past grades and learning progress from a database. This information is input into a generative AI model (e.g., GPT-4) to generate a study plan for the user. This study plan includes specific tasks and their schedules. The server sends this generated study plan to the device. The input is the user's study history and progress data, and the output is a study plan optimized for the user.

[1741] Step 3:

[1742] The terminal displays the learning plan to the user. The terminal receives the learning plan sent from the server and displays it on the screen. The user can check the learning plan on the terminal screen and confirm the specific learning tasks and schedule. The learning plan is received as input, and the content of the learning plan displayed to the user is output.

[1743] Step 4:

[1744] The user begins a learning task. The user begins a specific task (e.g., solving a math problem) according to the learning plan. If the user has a question, they enter it into the question input field on the device. For example, they might enter, "Please tell me how to solve a quadratic equation."

[1745] Step 5:

[1746] The terminal sends the user's question to the server. The terminal receives the question entered by the user and sends it to the server. The input information is the content of the user's question, and the output data is the question sent to the server.

[1747] Step 6:

[1748] The server analyzes the user's question and generates an answer. The server analyzes the received question using natural language processing technology and generates the optimal answer or example problem. A generative AI model is used in this process. The server sends the generated answer or example problem to the terminal. The input is the user's question, and the output is the analyzed answer or example problem.

[1749] Step 7:

[1750] The terminal displays the answers from the server to the user. The terminal displays the answers and example questions received from the server to the user. The user can use this as a reference to continue learning. The input is the answers and example questions sent from the server, and the output is the answers and example questions displayed to the user.

[1751] Step 8:

[1752] The device records learning progress data and sends it to the server. As the user progresses with their studies, the device records learning progress data (correct answer rate for questions, study time). This data is periodically sent to the server. The input is the user's learning progress data, and the output is the transmission of progress data to the server.

[1753] Step 9:

[1754] The server analyzes the learning progress data and adjusts the next learning plan. The server analyzes the received learning progress data and adjusts the next learning plan. If the user lacks understanding of a specific topic, it adds reinforcement tasks. The input is the learning progress data, and the output is the adjusted next learning plan.

[1755] Step 10:

[1756] The server generates content to maintain motivation and sends it to the device. The server analyzes learning progress data, and if it determines that the user's motivation is declining, it generates encouraging messages and motivating content and sends it to the device. The input is learning progress data, and the output is the generated content to maintain motivation.

[1757] (Application example 1)

[1758] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1759] Conventional systems were unable to provide information or recommend products that adequately met customer needs in brick-and-mortar stores. It was also difficult to manage the progress and maintain motivation of students and employees, resulting in a lack of effective educational support and mental health support. Furthermore, the system was also inadequate in recommending appropriate products and services based on health status, creating challenges in improving customer satisfaction and managing employee health.

[1760] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1761] In this invention, the server includes: a means for a user to launch an application and input login information; a means for the terminal to send the login information to the server; a means for the server to retrieve the user's personal information from a database; a means for the server to generate a study plan based on the user's study record and progress; a means for the server to send the generated study plan to the terminal; a means for the terminal to present study tasks to the user based on the study plan; a means for an AI tutor module to provide real-time support to the user while he or she is studying; a means for the terminal to send the user's study progress data to the server; a means for the server to analyze the data and adjust the next study plan; a means for the server to generate content to maintain the user's motivation and send it to the terminal; and a means for selecting products, checking inventory, and suggesting recommended products in real time when a customer visits a physical store. This enables more efficient customer service in physical stores and improved customer satisfaction.

[1762] An "application" is software that is operated by a user and runs on a variety of terminals.

[1763] "Login information" is information used to authenticate a user, typically a combination of a username and password.

[1764] "Terminal" refers to the device that a user uses to access an application, including smartphones, tablets, and personal computers.

[1765] A "server" is a computer system that runs on the back end of an application, accessing a database and performing processing.

[1766] A "database" is a data storage system for managing users' personal information, learning records, product inventory information, and so on.

[1767] "Study record" is data showing the records and grades of the user's previous studies.

[1768] A "study plan" is a list of specific study schedules and tasks that are generated based on the user's progress and goals.

[1769] A "learning task" is a specific learning activity or problem-solving task that a user should perform based on a learning plan.

[1770] The "AI Tutor Module" is an artificial intelligence system that provides real-time support and answers questions while users are learning.

[1771] "Study progress data" is data that indicates how far the user has progressed in their studies, and includes the percentage of correct answers to questions and the study time.

[1772] "Motivation maintenance content" refers to messages and content generated to increase a user's motivation to learn.

[1773] "Product selection" is the process by which customers identify products they will consider purchasing in a physical store.

[1774] "Inventory check" is the task of checking the quantity and status of products in physical stores and warehouses.

[1775] "Recommended products" is the process of recommending appropriate products based on a customer's needs and preferences.

[1776] "Natural language processing technology" is a technology that allows computers to understand and analyze human language.

[1777] "Feedback" refers to the evaluation or opinion that a user inputs regarding the plan or advice provided.

[1778] "AI Secretary" is an artificial intelligence system that supports users with training, career planning, mental health counseling, and more.

[1779] "Speech recognition" is a technology that converts a user's speech into text.

[1780] A "prompt" is text that is input into a generative AI model and is an instruction statement to obtain an appropriate generated result.

[1781] A "generative AI model" is an artificial intelligence model that generates text and answers based on a prompt.

[1782] The system of the present invention is a system that allows users to receive support tailored to their individual learning pace and needs, and provides useful information even in physical stores. Specific embodiments of the system are described below.

[1783] System Configuration

[1784] The system mainly consists of a terminal, a server, a database, and a generative AI model. Terminals can be devices such as smartphones, tablets, and PCs. The server is a computer system that accesses the database and performs the necessary processing, and can be implemented using Python and the Flask framework. The generative AI model is built using natural language processing technologies such as HuggingFace's Transformers.

[1785] Login process

[1786] A user launches an application on a terminal and enters login information (user name, password). This information is sent from the terminal to the server, which retrieves the user's personal information from a database. This authenticates the user and allows them to access the system.

[1787] Generate a lesson plan

[1788] The server generates a learning plan based on the user's past learning records and current progress. This learning plan includes specific tasks and schedules. The generated learning plan is sent to the device and displayed to the user.

[1789] Learning task presentation and real-time support

[1790] When a user starts a learning task, the device launches the AI ​​tutor module. When the user enters a question or concern, the information is sent to the server. The server uses natural language processing technology to analyze the question and generate appropriate explanations and examples. The generated explanations are sent to the device and provided to the user.

[1791] Learning progress and maintaining motivation

[1792] The device collects the user's learning progress (correct answer rate, study time) and sends it to the server. The server analyzes this data and adjusts the next learning plan. If the server determines that the user's motivation is declining, it generates encouraging messages and motivational content and sends them to the device.

[1793] Application in physical stores

[1794] When customers visit a physical store, they can use a terminal (a tablet or smartphone installed in the store) to receive product information, check inventory, and receive recommended products. When a user asks a question about how to select a product or the inventory status, the information is sent to a server, which analyzes it using natural language processing technology and provides the appropriate answer or product suggestion to the terminal.

[1795] Specific examples

[1796] Consider a case where a customer asks, "What products can boost the immune system?" in a physical store. This question is sent from the device to the server, and the server generates a response using a generative AI model. An example of a prompt sentence is "What products can boost the immune system?" As a result, the server recommends an appropriate product (e.g., "vitamin C supplement") and sends that information to the device for display.

[1797] In this way, the system of the present invention integrates the user's learning activities with the provision of information in physical stores, providing effective support.

[1798] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1799] Step 1:

[1800] A user starts an application on a device and enters login information (user name, password). The device sends this login information to the server. Based on this input, the server retrieves the user's personal information from the database and sends it to the device.

[1801] Step 2:

[1802] The server retrieves the user's past learning records and current progress data from the database and generates a new learning plan based on that data. The generated learning plan includes learning tasks and a schedule. This data processing establishes an optimal learning plan for the user. The server then sends the generated learning plan to the terminal, which displays it to the user.

[1803] Step 3:

[1804] The user performs learning tasks based on the displayed learning plan. If a question or doubt arises during learning, the user inputs it. The device sends the input question to the server. To respond to this question, the server uses a generative AI model to analyze the question and generate appropriate answers and example problems. The generated answers are sent to the device and displayed to the user.

[1805] Step 4:

[1806] The device collects the user's learning progress data (correct answer rate, study time) and periodically sends it to the server. The server analyzes this data and dynamically adjusts the next study plan. If the server determines that the user's motivation to study is declining, it generates motivational messages and video content and sends them to the device.

[1807] Step 5:

[1808] When a customer visits a physical store, they use a device (a tablet or smartphone in the store) to input a question about a product (e.g., "What products boost immunity?"). The device sends this question to a server. The server uses a generative AI model to analyze the question and generate appropriate product recommendations and stock status information. Accurate product information is generated by processing the data using this prompt text. The generated information is sent to the device and displayed to the customer.

[1809] Step 6:

[1810] If the customer checks the recommended products and asks more detailed questions, the input is sent to the server in a similar manner, and the server generates an answer and sends it to the terminal. At this step, product selection, inventory check, and recommendation suggestions are performed in real time.

[1811] In this way, at each processing step of the system, the user, device, and server work together to provide efficient support by utilizing generative AI models and prompt sentences.

[1812] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1813] The present invention combines an emotion engine with an AI system that allows individual learners and corporate employees to receive individually customized learning plans, career support, and mental health consultations. A specific embodiment of this system is described below.

[1814] Implementation of an AI tutor for students

[1815] The user launches the application

[1816] First, a user launches an application on a device such as a smartphone or tablet and enters their login information. The device sends this login information to the server, which then retrieves the user's personal information from a database.

[1817] The server generates the lesson plan

[1818] The server generates a learning plan based on the user's past performance and learning progress. This learning plan includes specific tasks and schedules for the user to effectively study. The server sends the generated learning plan to the terminal, which then displays it to the user.

[1819] Presenting and supporting learning tasks

[1820] When a user starts a learning task, the device launches the AI ​​tutor module. When the user inputs a question or concern, the device sends it to the server, which analyzes it using natural language processing technology and generates appropriate explanations and examples. The server then sends the generated explanations and examples to the device, which displays them to the user.

[1821] Emotion engine monitoring

[1822] The device acquires emotional data from the user's facial expressions, voice, input, etc. This data is analyzed by the emotion engine to identify the user's emotional state. The device then transmits the emotional data to the server.

[1823] Learning progress and motivation

[1824] The device collects the user's learning progress data (e.g., percentage of correct answers and study time) and sends it to the server. The server analyzes this data and emotional data and adjusts the next learning plan appropriately. If the server determines that the user's motivation is declining, it generates encouraging messages and motivational content, sends them to the device, and displays them to the user.

[1825] Specific examples

[1826] For example, suppose a student uses an application to solve a math problem. The student launches the application, enters their login information, and receives a study plan generated by the server. If the student has questions while working on the problem, the AI ​​tutor will provide real-time explanations. Furthermore, if the emotion engine detects stress from the student's facial expressions or voice, the server will send and display encouraging messages or content to help them concentrate on the device. After studying, the device will send progress data and emotion data to the server, which will then adjust the next study plan.

[1827] Implementation of an AI secretary for businesses

[1828] The user launches the application

[1829] A user launches a desktop or mobile application and enters their login information. The device sends this login information to a server, which retrieves the user's personal information from a database.

[1830] Conversation with an AI secretary

[1831] When a user asks the AI ​​secretary for advice on training, career planning, mental health, etc., the device receives the user's request via voice recognition or text input and sends it to the server, which then uses natural language processing technology to analyze the request and generate an appropriate plan or response.

[1832] Support by Emotion Engine

[1833] When the device receives a request, it acquires emotional data from the user's facial expressions, voice, and input. The emotion engine analyzes this data and generates a response or plan that reflects the user's emotional state.

[1834] Providing plans and advice

[1835] The server sends the generated plans and advice to the device, which then displays them to the user. For example, if a user asks, "What training courses are recommended for career advancement?", the server generates a list of recommended training courses, sends it to the device, and displays it to the user. Additionally, if the emotion engine determines that the user is feeling stressed, it can also provide advice on relaxation methods and mental health.

[1836] Gathering and implementing feedback

[1837] When a user inputs feedback on the provided plan or advice, the device sends the feedback to the server, which analyzes the feedback and uses it to improve the quality of future plans and advice.

[1838] In this way, by combining an emotion engine, the system of the present invention provides learning plans and career plans that correspond to the user's emotional state, thereby achieving more effective and personalized support.

[1839] The processing flow will be explained below.

[1840] Processing program for AI tutoring for students

[1841] Step 1:

[1842] When a user launches an application on their smartphone or tablet, a login screen appears, and the user enters their ID and password. The device then sends the login information to the server.

[1843] Step 2:

[1844] The server receives the login information and retrieves the user's personal information (grade, learning status, learning goals, etc.) from the database. The server then sends the retrieved information to the terminal.

[1845] Step 3:

[1846] The server generates a study plan based on the user's past grades and learning progress, and then sends the generated study plan to the device.

[1847] Step 4:

[1848] The device breaks down the study plan received from the server into daily and weekly study tasks and presents them to the user. The user confirms the study tasks and begins executing them.

[1849] Step 5:

[1850] When a user has a question or concern while progressing through a learning task, they can input a question, and the device will send the user's question to the server.

[1851] Step 6:

[1852] The server analyzes the received questions using natural language processing technology and generates appropriate answers and examples, which are then sent to the device.

[1853] Step 7:

[1854] The device receives the answers and examples from the server and displays them to the user, who can then confirm them and continue learning.

[1855] Step 8:

[1856] The device acquires emotional data from the user's facial expressions, voice, and input, analyzes it using an emotion engine, identifies the user's emotional state, and sends the data to the server.

[1857] Step 9:

[1858] The device collects the user's learning progress data (such as the rate at which questions are answered correctly and the amount of time spent studying) and sends it to the server. The server analyzes the progress data and emotional data and adjusts the next study plan appropriately.

[1859] Step 10:

[1860] If the server determines that the user's motivation is declining, it generates encouraging messages and motivational content and sends them to the device, which then displays them to the user.

[1861] Processing AI secretary programs for businesses

[1862] Step 1:

[1863] When a user launches a desktop or mobile application, a login screen appears, where the user enters their ID and password, and the device sends the login information to the server.

[1864] Step 2:

[1865] The server receives the login information, retrieves the user's personal information from the database, and sends the retrieved information to the terminal.

[1866] Step 3:

[1867] Users can use the in-app interface to ask the AI ​​secretary for training advice, career planning, and mental health advice, with requests received by the device via voice recognition or text input.

[1868] Step 4:

[1869] The device sends the received request to the server.

[1870] Step 5:

[1871] The server analyzes the request using natural language processing technology and generates an appropriate plan or answer.

[1872] Step 6:

[1873] The device acquires emotional data from the user's facial expressions, voice, and input, and sends it to the server. The emotion engine analyzes this data and provides a plan based on the user's emotional state.

[1874] Step 7:

[1875] The server generates plans and answers and sends them to the device, which then displays them to the user. For example, if a user asks, "What training courses are recommended for my career?", the server generates a list of appropriate training courses, sends it to the device, and displays it to the user.

[1876] Step 8:

[1877] The user enters feedback on the provided plans and answers, which is then sent by the device to the server.

[1878] Step 9:

[1879] The server analyzes the feedback and uses it to improve future plans and advice.

[1880] In this way, the system of the present invention optimizes the user's studies and career plans according to the user's emotional state and provides effective support.

[1881] Example 2

[1882] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1883] In modern education and career support, personalized guidance and support for individual learners and employees is becoming increasingly important. However, existing systems do not adequately provide support that takes into account the user's emotional state, which can reduce the effectiveness of learning and career support. It is also difficult to maintain user motivation, leading to issues such as ineffective implementation of learning and career plans.

[1884] The specification process by the specification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for acquiring the user's personal information from a database, means for generating a study plan based on the user's study record and progress, and means for an emotion engine to identify the user's emotional state and analyze the data. This makes it possible to provide an individualized study plan or career plan that reflects the user's emotional state, thereby enabling effective study and career support while maintaining the user's motivation.

[1885] "User" refers to an individual who uses the Application to receive learning planning and career support services.

[1886] A "terminal" is a device that a user uses to run an application, and includes a smartphone, tablet, desktop, etc.

[1887] "Server" refers to a central computer system that receives, processes, and analyzes data sent by users.

[1888] "Login Information" refers to the authentication information required for a user to access a system, and typically consists of a username and password.

[1889] "Database" refers to an information management system for storing data such as users' personal information, learning records, and progress information.

[1890] A "study plan" refers to specific tasks and schedules generated by the server to help users study effectively.

[1891] "AI Tutor Module" refers to artificial intelligence that provides real-time support to users while they are learning.

[1892] An "emotion engine" refers to a technology that acquires and analyzes emotional data from a user's facial expressions, voice, input content, etc.

[1893] "Natural language processing technology" refers to technology that enables computers to understand human language and generate appropriate responses.

[1894] "Feedback" refers to opinions and impressions that users input regarding the plans and advice provided.

[1895] "Motivation" refers to the user's will and motivation to achieve a goal.

[1896] The present invention combines an emotion engine with an AI system that enables individual learners and corporate employees to receive individually customized learning plans, career support, and mental health consultations. This system enables users to receive effective learning and career support using an application. A specific embodiment of this system is described below.

[1897] Hardware and software used

[1898] 1. Hardware

[1899] Smartphones and tablets (student devices)

[1900] Desktop (devices for corporate employees)

[1901] Server (responsible for data processing and analysis)

[1902] 2. Software

[1903] Application platform (iOS, Android, Windows, etc.)

[1904] Database (e.g. MySQL, PostgreSQL)

[1905] Natural language processing technology (e.g., GPT-3, BERT)

[1906] Machine learning algorithms (e.g., scikit-learn)

[1907] Emotion engines (e.g., Affectiva, Microsoft Emotion API)

[1908] Example of operation

[1909] AI tutors for students

[1910] 1. Launching the application and logging in

[1911] A user launches an application on their smartphone or tablet and enters their login information. The device encrypts the login information and sends it to a server, which then retrieves the user's personal information from a database. The personal information is then sent to the device and displayed to the user.

[1912] 2. Generate a learning plan

[1913] The server uses a machine learning algorithm to generate an optimal study plan based on the user's past performance and learning progress. The generated information is sent to the device and displayed to the user.

[1914] 3. Support for learning tasks

[1915] When a user starts a learning task, the device launches an AI tutoring module (e.g., Dialogflow, GPT-3). When the user inputs a question, the device sends it to the server, which analyzes it using natural language processing technology and generates appropriate explanations and examples. These are then provided to the user via the device.

[1916] 4. Emotion Engine Monitoring

[1917] The device uses a camera and microphone to collect the user's facial expressions, voice, and input, and analyzes them with an emotion engine. The emotion data is sent to a server, and the analysis results are reflected in the next lesson plan.

[1918] 5. Staying motivated

[1919] The server analyzes the user's learning progress and emotional state, and generates encouraging messages and content to maintain motivation. These contents are provided to the user via their device.

[1920] Example prompt:

[1921] "Do you have any questions about the next math assignment? Type in any questions you may have."

[1922] AI secretaries for businesses

[1923] 1. Launching the application and logging in

[1924] A user launches an application on a desktop or mobile device and enters their login information. The device encrypts the login information and sends it to a server, which retrieves their personal information from a database. The retrieved information is then displayed to the user on the device.

[1925] 2. Conversation with an AI secretary

[1926] When a user requests training consultation or career planning through text or voice input, the device sends the request to the server. The server analyzes the request using natural language processing technology and generates an appropriate plan or answer. The generated plan is displayed to the user via the device.

[1927] 3. Support by Emotion Engine

[1928] The device collects the user's facial expressions and voice, analyzes them with an emotion engine, and sends the emotion data to the server, where it is reflected in the response and plan.

[1929] 4. Gather and incorporate feedback

[1930] The user enters feedback on the plan or advice provided, and the device sends the feedback to the server, which analyzes the feedback and uses it for future improvements.

[1931] Example prompt:

[1932] "Do you have any questions about your career plans? Please enter your specific question."

[1933] This system provides personalized learning and career plans that take into account the user's emotional state, enabling effective support while increasing the user's motivation.

[1934] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1935] AI Tutoring for Students

[1936] Step 1: Launch the application and log in

[1937] 1. The user launches the application on the device and the login screen appears.

[1938] 2. The user enters their login information (username and password).

[1939] Input: Username and Password

[1940] Output: Encrypted login information

[1941] 3. The device sends the encrypted login information to the server.

[1942] Data processing: Encryption of entered login information

[1943] Data calculation: Sending login information to the server

[1944] 4. The server retrieves the user's personal information from the database.

[1945] Input: Encrypted login information

[1946] Output: User's personal information

[1947] 5. The device displays the personal information to the user.

[1948] Data processing: Converting acquired personal information into a display format

[1949] Data calculation: Display on user screen

[1950] Step 2: Generate a lesson plan

[1951] 1. The server generates a study plan using a machine learning algorithm based on the user's past grades and learning progress data.

[1952] Input: User's past performance data, learning progress data

[1953] Output: personalized learning plan

[1954] Data calculation: Generating learning plans using machine learning algorithms

[1955] 2. The server sends the generated learning plan to the device.

[1956] Data calculation: Sending learning plans to the device

[1957] 3. The device displays the lesson plan to the user.

[1958] Data processing: Converting the learning plan into a display format

[1959] Data Calculation: Viewing the Learning Plan

[1960] Step 3: Supporting the learning task

[1961] 1. The user selects a task to begin the learning task.

[1962] Input: Select a learning task

[1963] Output: Details of the selected task

[1964] 2. The device will launch the AI ​​tutor module and display the task details.

[1965] Data calculation: Launching the AI ​​tutor module and generating display content

[1966] 3. The user enters their concern or question via text or voice.

[1967] Input: User's doubts or questions

[1968] Output: Questions and queries

[1969] 4. The device sends the question or inquiry to the server.

[1970] Data calculation: Send data to the server

[1971] 5. The server uses natural language processing technology to analyze the question and generate appropriate explanations and examples.

[1972] Input: Questions and questions

[1973] Output: Explanation and examples

[1974] Data processing: Analysis, explanations and example generation using natural language processing technology

[1975] 6. The server sends the generated explanations and examples to the terminal, which displays them.

[1976] Data calculation: Sending and displaying explanations and examples

[1977] Step 4: Monitoring with the Emotion Engine

[1978] 1. The device uses a camera and microphone to collect the user's facial expressions, voice, and input.

[1979] Input: facial expression data, voice data, input content

[1980] Output: Raw data

[1981] 2. The device's emotion engine analyzes the collected data and identifies the user's emotional state.

[1982] Data processing: analyzing data and identifying emotional states

[1983] Output: Emotional state data

[1984] 3. The device sends the emotional state data to the server.

[1985] Data calculation: Sending emotional state data

[1986] Step 5: Study progress and maintain motivation

[1987] 1. The device collects the user's learning progress data (correct answer rate and study time).

[1988] Input: Learning progress data

[1989] Output: Collected data

[1990] 2. The device sends the collected data to the server.

[1991] Data calculation: Sending progress data

[1992] 3. The server analyzes the progress and emotion data and adjusts the next learning plan.

[1993] Input: Learning progress data, emotion data

[1994] Output: Adjusted learning plan

[1995] Data calculations: analyzing data and adjusting learning plans

[1996] 4. The server generates encouraging messages and content to keep the user motivated and sends them to the device.

[1997] Input: User emotion data

[1998] Output: Support message and content

[1999] Data calculation: generating and sending support messages and content

[2000] 5. The device displays the support message or content received to the user.

[2001] Data processing: converting messages and content into a display format

[2002] Data operations: displaying messages and content

[2003] Processing steps for corporate AI secretaries

[2004] Step 1: Launch the application and log in

[2005] 1. A user launches an application on a desktop or mobile app and is presented with a login screen.

[2006] 2. The user enters their login information.

[2007] Input: Username and Password

[2008] Output: Encrypted login information

[2009] 3. The device sends the encrypted login information to the server.

[2010] Data processing: Encryption of entered login information

[2011] Data calculation: Sending login information to the server

[2012] 4. The server retrieves the user's personal information and work history from the database.

[2013] Input: Encrypted login information

[2014] Output: Personal information and work history

[2015] 5. The device displays the user's personal information and work history.

[2016] Data processing: Converting acquired personal information into a display format

[2017] Data calculation: Display on user screen

[2018] Step 2: Interact with the AI ​​secretary

[2019] 1. The user inputs text or voice to consult about training, create a career plan, or receive mental health advice.

[2020] Input: User request

[2021] Output: Request data

[2022] 2. The device sends the user's request to the server.

[2023] Data calculation: Sending request data

[2024] 3. The server uses natural language processing technology to analyze the request and generate an appropriate plan or answer.

[2025] Input: User request data

[2026] Output: Plans and answers

[2027] Data processing: Natural language processing techniques for analysis, planning and answer generation

[2028] 4. The server sends the generated plan and answer to the terminal, which displays it.

[2029] Data calculation: Sending and displaying plans and answers

[2030] Step 3: Support with the Emotion Engine

[2031] 1. The device uses a camera and microphone to collect the user's facial expressions and voice.

[2032] Input: facial expression data, voice data

[2033] Output: Raw data

[2034] 2. The emotion engine analyzes the collected data and identifies the user's emotional state.

[2035] Data processing: analyzing data and identifying emotional states

[2036] Output: Emotional state data

[2037] 3. The device sends the emotional state data to the server.

[2038] Data calculation: Sending emotional state data

[2039] Step 4: Gather and incorporate feedback

[2040] 1. The user enters feedback on the plan or advice provided.

[2041] Input: Feedback

[2042] Output: Feedback data

[2043] 2. The device sends the feedback data to the server.

[2044] Data calculation: Sending feedback data

[2045] 3. The server analyzes the feedback and uses it to improve future plans and advice.

[2046] Input: Feedback data

[2047] Output: Improved plans and advice

[2048] Data processing: Analyzing feedback data, identifying and implementing improvements

[2049] 4. The device displays improved plans and advice to the user.

[2050] Data transformation: Transforming improved plans and advice into a display format

[2051] Data Calculation: Improved plans and advice display

[2052] (Application example 2)

[2053] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2054] Factory workers are prone to experiencing mental fatigue and a loss of concentration and motivation when performing long, monotonous tasks or working in a high-stress environment. If these conditions continue, it can lead to problems such as a decline in work efficiency, an increase in work errors, and even increased safety risks. Conventional methods have made it difficult to monitor workers' mental state in real time and provide appropriate feedback and break suggestions, so a means to effectively solve these problems is needed.

[2055] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[2056] In this invention, the server includes means for acquiring the user's personal information from a database, means for generating a study plan based on the user's study record and progress, means for the terminal to acquire emotion data from the user's facial expressions, voice, and input content, and means for the emotion engine to analyze the user's emotion state and send it to the server. This makes it possible to monitor the emotion state of factory workers in real time and provide suggestions for work breaks or encouraging messages as needed.

[2057] "User" refers to an individual who uses the system, including a factory worker or a student.

[2058] An "application" is a software program that a user runs and uses on a terminal.

[2059] "Login information" refers to authentication information for accessing a system, such as a user name and password.

[2060] A "terminal" is a device used by a user, such as a smartphone, tablet, smart glasses, or head-mounted display.

[2061] A "server" is a computer system responsible for processing, storing, and transmitting user data.

[2062] A "database" is a system that organizes and stores data such as users' personal information and learning records.

[2063] A "study plan" is a general term for tasks and schedules designed to help users study efficiently.

[2064] The "AI Tutor Module" is an artificial intelligence system that provides real-time support to users while they are learning.

[2065] "Study progress data" refers to data such as the percentage of correct answers and study time as the user progresses with their studies.

[2066] "Facial expressions, voice, and input content" are data used to analyze the user's emotional state.

[2067] An "emotion engine" is an algorithm or system for analyzing a user's emotional state.

[2068] A "work break suggestion" is a notification or message that encourages a user who is working to take a break.

[2069] "Natural language processing technology" is a technology that analyzes text and voice input by users and generates appropriate answers.

[2070] MODE FOR CARRYING OUT THE INVENTION

[2071] The present invention is a support system for users to perform factory work efficiently and safely. This system uses a device such as smart glasses worn by the user to acquire emotional data from the user's facial expressions and voice, and manages the progress of the work.

[2072] The system is structured as follows: First, the user puts on the smart glasses and launches the application. After the user enters their login information, the device sends this information to the server, which then retrieves the user's personal information from a database. The server is equipped with a high-performance computer, a database, and an AI emotion engine. The software used includes Python, OpenCV, Keras, and TensorFlow.

[2073] The server then generates a work plan for each user and sends it to the device. The work plan includes specific tasks and schedules. As the worker works according to the plan, if a question arises, the worker sends a query to the server via the smart glasses. The server analyzes the query using natural language processing technology, generates an appropriate answer, and sends it to the device. At this time, the user's input and voice are also analyzed.

[2074] The emotion engine analyzes the user's facial expressions and voice in real time to identify their emotional state. For example, if the emotion engine detects stress, it will generate a message suggesting a break or offering encouragement, which will be sent to the user's device and displayed. It also adjusts the next task plan based on learning progress data and emotion data.

[2075] For example, if the emotion engine detects that a factory worker is very tired, the system will send a message like this: "The worker appears tired, so we recommend that you take a break." This will allow workers to take breaks at the appropriate time, improving safety and work efficiency.

[2076] An example of a prompt sentence might be:

[2077] "Transform the following sentence into a feedback message based on emotion data: 'The worker is showing clear signs of fatigue on his face.'"

[2078] The above is a specific embodiment for carrying out the present invention, and by using this system, the safety and efficiency of factory workers can be significantly improved.

[2079] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2080] Step 1:

[2081] The user puts on the smart glasses, launches the application, and enters their login information, which is then sent to the server via the device.

[2082] Input: User login information (username, password)

[2083] Output: Login information sent to the server

[2084] Step 2:

[2085] The server receives the login information and retrieves the user's personal information from a database, making available a data set specific to the user.

[2086] Input: Login information received by the server

[2087] Output: User's personal information

[2088] Step 3:

[2089] The server generates an optimal work plan for the user based on the user's personal information and past learning and work records.

[2090] Input: User's personal information, learning records, work records

[2091] Output: Generated work plan

[2092] Step 4:

[2093] The server sends the generated work plan to the terminal, which then presents the work plan to the user, who then begins work according to the work plan.

[2094] Input: Generated Work Plan

[2095] Output: Submitted work plan, Work plan presentation

[2096] Step 5:

[2097] If a user has any questions or concerns while working, they can input the question via voice or text through the smart glasses, and the device will send it to the server.

[2098] Input: User question (voice or text)

[2099] Output: The question is sent to the server

[2100] Step 6:

[2101] The server uses natural language processing technology to analyze the received question and generate appropriate answers and instructions, thereby resolving the user's doubts.

[2102] Input: User question

[2103] Output: Generated answers and instructions

[2104] Step 7:

[2105] The server sends the generated answers and instructions to the terminal, which displays them to the user, who can then continue working based on the displayed information.

[2106] Input: Generated answers and instructions

[2107] Output: Submitted answers and instructions, presentation of answers and instructions

[2108] Step 8:

[2109] The device acquires emotional data from the user's facial expressions, voice, and input content and sends it to the server.

[2110] Input: User's facial expressions, voice, and input

[2111] Output: Emotion data is sent to the server

[2112] Step 9:

[2113] The server's emotion engine analyzes the emotion data to identify the user's emotional state, and generates break suggestions or encouraging messages as needed based on the analysis results.

[2114] Input: Emotion data

[2115] Output: Identified emotional state, suggestion to take a break, or a message of encouragement

[2116] Step 10:

[2117] The server sends the generated break suggestion or encouraging message to the terminal, which displays it to the user, who can then take a break or continue working.

[2118] Input: Generated break suggestions and encouraging messages

[2119] Output: Break suggestions and encouragement messages sent, display...

Claims

1. a means by which a user launches an application and enters login information; A means for the terminal to transmit login information to a server; A means for the server to retrieve the user's personal information from the database; A means for the server to generate a study plan based on the user's study record and progress; A means for transmitting the generated learning plan to the terminal; a means for the terminal to present a learning task based on the learning plan to the user; A means for the AI ​​tutor module to provide real-time support to users while they are learning; A means for the terminal to transmit the user's learning progress data to the server; A means for the server to analyze the data and adjust the next learning plan; A means for the server to generate content for maintaining the user's motivation and transmit the content to the terminal; A system including:

2. The server analyzes the user's request using natural language processing technology and generates an appropriate plan or answer. means for the terminal to display the plan or answer generated from the server to the user; a means for the device to transmit user feedback to the server, and for the server to use the feedback to improve the quality of future advice; The system of claim 1 , comprising:

3. The user can launch the application and ask the AI ​​secretary for training advice, career planning, and mental health advice. means for the terminal to receive a user request by voice recognition or text input; A means for the server to analyze the user's request, generate an appropriate plan or answer, and send it to the terminal; means for the terminal to display the plans and answers to the user; The system of claim 1 , comprising:

Images