system

Abstract

Provide a system. The system comprises: an input means for teachers to input data for administrative work and lesson preparation; a server means for receiving the data and storing it in a database; A generating means for analyzing the data and generating documents and materials using an AI algorithm; A transmitting means for transmitting the generated output to a teacher's terminal and displaying it. A system including:

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] In traditional educational settings, teachers are required to spend a great deal of time and effort on administrative tasks and lesson preparation. This increases stress on teachers and reduces the time they can devote to teaching itself. Specifically, creating lesson materials, writing correspondence to parents, and other daily administrative tasks place a heavy burden on teachers. There is a need to reduce these workloads and provide an environment in which teachers can carry out educational activities more effectively. [Means for solving the problem]

[0005] The present invention provides a system that includes a terminal equipped with an input means for teachers to input data for administrative work and lesson preparation, a server means for receiving the data and storing it in a database, a generation means for generating documents and materials using AI algorithms, and a transmission means for transmitting and displaying the generated output to the teacher's terminal. This allows teachers to easily create materials and perform administrative work, significantly reducing their workload. Furthermore, the system also includes a correction means for checking and correcting the output displayed on the terminal, allowing teachers to edit the content as needed. This system allows teachers to focus on their primary educational activities.

[0006] "Faculty" means a staff member at an educational institution whose role is to educate students.

[0007] "Administrative work" refers to routine tasks such as document preparation, data entry, and communication work that occur as part of educational activities.

[0008] "Lesson preparation" refers to planning the content of the lesson and creating and preparing the necessary teaching materials and resources.

[0009] "Input means" refers to the interface that teachers use to input data into the system, including keyboards and touchscreens.

[0010] "Terminal" refers to a computer or digital device used by a faculty member to access the system and input and check data.

[0011] "Server Means" means the computer equipment and software that receives and stores data and acts as a central control for the entire system.

[0012] "Database" means a system for systematically storing, managing and accessing received data.

[0013] "Generation means" refers to the process of using AI algorithms to analyze teachers' input data and automatically generate documents and materials.

[0014] An "AI algorithm" is a computational method that uses artificial intelligence to analyze and automatically generate data.

[0015] "Documents and materials" refers to documents such as lecture notes, PowerPoint slides, email templates, etc. used in educational activities.

[0016] "Transmission means" refers to the process and device that transmits the generated output to the teacher's terminal.

[0017] "Correction tools" refers to the functionality that allows teachers to review the generated output and make edits or corrections as necessary.

[0018] "System" refers to a comprehensive structure that includes all of the above means and processes and aims to improve the efficiency of educational activities. [Brief explanation of the drawings]

[0019] [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

[0020] 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.

[0021] First, the terms used in the following description will be explained.

[0022] 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).

[0023] 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.

[0024] 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.

[0025] 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.

[0026] 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."

[0027] [First embodiment]

[0028] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0029] 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.

[0030] 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).

[0031] 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.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0036] 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.

[0037] 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.

[0038] 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.

[0039] 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."

[0040] As an embodiment of the present invention, a system for automating and streamlining administrative work and lesson preparation for teachers is described below. This system includes a terminal for teachers to input data, a server that receives, analyzes, and generates data, and a means for presenting and modifying the generated materials to teachers.

[0041] System Overview

[0042] 1. Data entry by the teacher (terminal side)

[0043] The user (teacher) logs in to the terminal and inputs data related to the required lesson content and administrative work. For example, a teacher inputs related materials and assignments for the next lesson, "Fundamentals of Biology," into the terminal.

[0044] 2. Data processing and storage (server side)

[0045] The device sends the input data to a server, which receives it and stores it in a database. The server then analyzes the data and uses AI algorithms to automatically generate documents and materials.

[0046] 3. Document Generation (Server Side)

[0047] The server uses AI algorithms to generate optimal lesson materials and documents based on the input data, such as PowerPoint templates, lecture notes, and email templates for parents on "Fundamentals of Biology."

[0048] 4. Sending and displaying the results (terminal side)

[0049] The server sends the generated materials to the terminal, which displays them to the user, who can then use them to prepare for classes or perform administrative tasks.

[0050] 5. Checking and correcting materials (user side)

[0051] The user can review the submitted materials and make any necessary modifications, for example adding specific information to the generated PowerPoint template or modifying the content.

[0052] Specific examples

[0053] To enter the next week's lesson schedule, Teacher A logs in to the terminal and enters the following information: "The next lesson is 'Fundamentals of Biology', and the related materials are Chapter 3 of the textbook and the self-study assignment." The terminal then sends this data to the server.

[0054] The server receives the data and stores it in a database. AI algorithms analyze past lesson data and related materials to generate PowerPoint templates, lecture notes, and email templates for parents that are optimal for the next week's lesson.

[0055] The generated materials are sent from the server to the terminal and displayed on Teacher A's terminal. Teacher A reviews these materials and makes corrections as necessary, for example, by inserting additional slides into the PowerPoint template to emphasize specific content.

[0056] This system allows teachers to save time by manually creating materials, and to carry out lesson preparation and administrative work more efficiently. The present invention reduces the workload of teachers and provides sufficient support for them to concentrate on teaching activities.

[0057] The processing flow will be explained below.

[0058] Step 1:

[0059] Users log in to the terminal and enter the necessary data related to the course content and administrative work, such as the class schedule, student list, and past class materials.

[0060] Step 2:

[0061] The device sends the input data to the server using an encryption protocol that takes security into consideration.

[0062] Step 3:

[0063] The server receives the data sent from the terminal and stores it in a database using a database management system (DBMS).

[0064] Step 4:

[0065] The server reads the incoming data from the database and begins analyzing it, using AI algorithms to analyze the content of the input data.

[0066] Step 5:

[0067] The server generates specific documents and materials based on the analysis results, including PowerPoint templates for lessons, lecture notes, and email templates for parents.

[0068] Step 6:

[0069] The server sends the generated documents and materials to the terminal, using a real-time communication protocol to quickly deliver the data to the user.

[0070] Step 7:

[0071] The terminal displays the transmitted documents and materials to the user, who then checks the displayed materials.

[0072] Step 8:

[0073] The user can check the displayed document or material and make any necessary corrections. Once the corrections are complete, the document is saved back to the device.

[0074] This system allows teachers to prepare for classes and carry out administrative tasks quickly and efficiently. The specific processes performed at each step are explained in detail, making the operation of each step clear.

[0075] Example 1

[0076] 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."

[0077] Because administrative work and lesson preparation for teachers requires a great deal of time and effort, there is a need for greater efficiency. However, the traditional method of manually creating documents and generating materials is time-consuming and has limited effectiveness in reducing the burden on teachers. The present invention aims to solve these issues and significantly reduce the burden on teachers by automating and streamlining administrative work and lesson preparation for teachers.

[0078] 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.

[0079] In this invention, the server includes an input means for teachers to input information for administrative work and lesson preparation, a server means for receiving the information and storing it in a database, a generation means for analyzing the information and generating documents and materials using a generative AI model, a transmission means for sending the generated results to the teacher's terminal and displaying them, and a correction means for the teacher to check the results and correct them as necessary. This allows teachers to automatically generate optimal lesson materials and documents by simply inputting information, enabling them to efficiently perform administrative work and lesson preparation.

[0080] A "teacher" is a person who provides educational activities to students at an educational institution.

[0081] "Administrative work" refers to non-educational tasks performed by teachers, such as preparing for classes, managing student grades, and communicating with parents.

[0082] "Class preparation" refers to the preparatory work required to smoothly carry out educational activities, such as creating teaching materials and documents to be used in class and drawing up lesson plans.

[0083] "Input means" refers to devices and software that allow teachers to use terminals to input information related to lesson content and administrative work.

[0084] "Server means" refers to a device or software that receives input information, stores it in a database, and manages and processes it.

[0085] A "database" is a system for systematically storing received information so that it can be searched and used later.

[0086] "Generation means" refers to devices or software that automatically generate documents or materials using a generative AI model based on analyzed information.

[0087] A "generative AI model" is an artificial intelligence algorithm that performs natural language processing based on input information and generates appropriate documents and materials.

[0088] "Transmission means" refers to devices and software for transferring the generated documents and materials to the teacher's terminal and displaying them.

[0089] "Correction means" refers to devices or software that allow teachers to check the generated results and make corrections as necessary.

[0090] "Results" are documents and materials created by the generating means.

[0091] A "presentation template" is a template for slide-format materials used in classes, etc.

[0092] "Lecture notes" are materials in the form of notes that contain the content necessary for the progress of a class.

[0093] "Notification templates" are standardized email and letter templates used when contacting parents and other concerned parties.

[0094] A "terminal" is a computer or other device that allows a teacher to input information and view generated results.

[0095] "Information" refers to all data related to lesson content and administrative work entered by teachers.

[0096] This invention is a system that automates and streamlines administrative work and lesson preparation for teachers. This system includes a terminal for teachers to input information, a server that receives, analyzes, and generates information, and a means for presenting and modifying the generated results to teachers.

[0097] Users (teachers) log in to the system from terminals used at educational institutions. Using the input means of the terminal, teachers input information such as the content of the next lesson, related materials, and self-study assignments. For example, they input information such as "The next lesson is 'Fundamentals of Biology', and related materials are Chapter 3 of the textbook, and self-study assignments."

[0098] When the terminal receives the input information, it sends it to the server, which verifies the received information and stores it in a database. The server manages the information using a relational database management system (e.g., an SQL database).

[0099] The server then analyzes the stored information and generates optimal lesson materials and documents using a generative AI model (e.g., OpenAI's GPT-4). The server analyzes past lesson data and related materials and generates documents based on them. As a specific example, it generates presentation templates, lecture notes, and parent notification templates for "Fundamentals of Biology."

[0100] The generated results are sent from the server to the terminal. The terminal displays them on the user interface. The user (teacher) can check the generated results and make corrections as necessary. Corrections are made using the terminal's editing tools, and the final material is re-saved on the server.

[0101] With this system, teachers simply input information and the system automatically generates the most suitable lesson materials and documents. In addition, the generated materials can be easily edited, allowing for efficient administrative work and lesson preparation.

[0102] Specific examples

[0103] To enter the next week's lesson schedule, Teacher A logs in to the terminal and enters the following information: "The next lesson is 'Fundamentals of Biology', and the related materials are Chapter 3 of the textbook and the self-study assignment." The terminal then sends this information to the server.

[0104] The server receives the data and stores it in a database. A generative AI model analyzes past lesson data and related materials to generate presentation templates, lecture notes, and notification templates for parents that are optimal for "Fundamentals of Biology."

[0105] The generated materials are sent from the server to the terminal and displayed on Teacher A's terminal. Teacher A reviews these materials and makes corrections as necessary, for example, by inserting additional slides into the presentation template to emphasize specific content.

[0106] Prompt Sentence Examples

[0107] Here are some examples of input prompts for a generative AI model:

[0108] "I'm teaching 'Basic Biology' for next week's class. Based on past lesson data and the content of Chapter 3 of the textbook, please generate a presentation template, lecture notes, and parent notification template."

[0109] In this way, teachers can efficiently carry out administrative tasks and prepare for lessons. This invention reduces the burden on teachers and provides practical support for providing high-quality education.

[0110] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0111] Step 1:

[0112] Logging in to a teacher's device

[0113] The user (teacher) logs in to the terminal. The teacher enters their user ID and password for authentication. The terminal sends the entered authentication information to the server, which then compares it with the user information in the database. If authentication is successful, the teacher is allowed to access the system.

[0114] Input: User ID, Password

[0115] Output: Authentication result (success / failure)

[0116] Specific behavior:

[0117] Teachers enter their ID and password into the login screen.

[0118] The terminal transmits the authentication information to the server.

[0119] The server checks the credentials against a database and returns the result.

[0120] The authentication result will be displayed on the device.

[0121] Step 2:

[0122] Data entry of lesson contents

[0123] The user (teacher) inputs information such as the content of the next class, related materials, and self-study assignments into the terminal. For example, the user might input "The next class is 'Fundamentals of Biology', related materials are Chapter 3 of the textbook, and self-study assignments." The terminal then converts this input data into a structured format (e.g., JSON).

[0124] Input: Course content, related materials, self-study assignments

[0125] Output: Structured data (JSON format)

[0126] Specific behavior:

[0127] Teachers fill out the input form with the lesson content and related materials.

[0128] The terminal converts the input data into JSON format.

[0129] Step 3:

[0130] Sending data

[0131] The device transmits the structured data to the server using a secure communication protocol (e.g., HTTPS).

[0132] Input: Structured data (JSON format)

[0133] Output: Sending to server completed

[0134] Specific behavior:

[0135] The terminal generates JSON data.

[0136] The terminal transmits the data to the server through secure communication.

[0137] The server acknowledges receipt of the data.

[0138] Step 4:

[0139] Receiving and storing data on the server side

[0140] The server receives the data sent from the terminal and verifies its contents. If the verification is successful, the server saves the data in a database, such as an SQL database.

[0141] Input: Structured data (JSON format)

[0142] Output: Saved to database

[0143] Specific behavior:

[0144] The server validates the received JSON data (schema checking and data integrity checking).

[0145] The server stores the data in a database.

[0146] The database notifies the server of the successful save.

[0147] Step 5:

[0148] Data analysis and documentation generation

[0149] The server analyzes the stored data and generates optimal lesson materials and documents using a generative AI model (such as OpenAI's GPT-4). In this process, it generates prompt sentences and inputs them into the AI ​​model.

[0150] Input: saved data, prompt

[0151] Output: Generated documents (presentation templates, lecture notes, announcement templates, etc.)

[0152] Specific behavior:

[0153] The server retrieves the relevant information from a database.

[0154] The server generates a prompt for the generative AI model.

[0155] The AI ​​model generates a document based on the prompt.

[0156] The generated document is saved in temporary storage.

[0157] Step 6:

[0158] Sending generated documents

[0159] The server sends the generated documents to the terminal, which displays these documents in its user interface.

[0160] Input: Generated document

[0161] Output: Sent to terminal

[0162] Specific behavior:

[0163] The server retrieves the generated document from temporary storage.

[0164] The server sends the document to the terminal.

[0165] The terminal displays the received document.

[0166] Step 7:

[0167] Check and correct the document

[0168] The user (teacher) checks the received document and makes any necessary corrections. The corrected document is then saved back to the server and becomes available as the final version.

[0169] Input: Generated document, corrections

[0170] Output: Final document

[0171] Specific behavior:

[0172] The teacher checks the generated document on the terminal.

[0173] The teacher will make any necessary corrections.

[0174] The terminal sends the modified document to the server.

[0175] The server stores the final document in a database.

[0176] These are the specific processing steps of the system. This flow allows teachers to efficiently generate and edit lesson materials simply by inputting information.

[0177] (Application example 1)

[0178] 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."

[0179] Traditionally, teachers' administrative work and lesson preparation requires a lot of time and effort, making it inefficient. Creating lesson materials and related documents in particular requires a great deal of time and effort, preventing teachers from concentrating on their teaching activities. Furthermore, there is a lack of convenient ways to easily check and revise lesson plans and related materials on smart devices. Therefore, a system is needed that allows teachers to perform administrative work and lesson preparation more efficiently and focus on their teaching activities.

[0180] 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.

[0181] In this invention, the server includes an input means for teachers to input data for administrative work and lesson preparation, a server means for receiving the data and storing it in a database, a generation means for analyzing the data and generating documents and materials using an AI algorithm, a transmission means for sending the generated output to the teacher's terminal and displaying it, and a means for the teacher to check and modify the generated materials using a smart device. This allows teachers to efficiently create and modify materials, significantly reducing the time spent on lesson preparation and administrative work. Furthermore, checking and modifying data on a smart device improves convenience and helps teachers focus on their teaching activities.

[0182] A "teacher" is a person who teaches classes at an educational institution and is engaged in the task of imparting knowledge and skills to students.

[0183] "Administrative work" refers to work outside of teaching, including administrative tasks, document preparation, and student evaluations at educational institutions.

[0184] "Lesson preparation" refers to the process of planning a lesson, creating necessary materials and documents, and preparing the content of the lesson in advance.

[0185] "Input means" refers to devices or interfaces that teachers use to input data, including keyboards, touchscreens, etc.

[0186] "Server means" refers to a computing system responsible for storing and analyzing received data.

[0187] "Generation means" refers to a system that automatically generates documents and materials based on input data using AI algorithms.

[0188] "Transmission means" refers to a system that has the function of transmitting the generated output to the teacher's terminal and displaying it.

[0189] "Smart device" refers to an advanced digital device that can connect to the Internet and install and run applications, including smartphones and tablets.

[0190] A "PowerPoint template" refers to a basic format for creating presentations, a file with a pre-determined slide design and layout.

[0191] "Lecture notes" refer to materials that contain the content and progress plan of a class, and are used by teachers as a guide when teaching a class.

[0192] An "email template" refers to a pre-created email template based on specific content and format, intended for efficient communication.

[0193] "Correction tools" refer to tools and interfaces that allow teachers to review the generated output and make changes or additions to content as needed.

[0194] "Output" includes results, materials, and documents generated by AI algorithms based on input data.

[0195] MODE FOR CARRYING OUT THE INVENTION

[0196] As an embodiment of the present invention, a system that enables teachers to efficiently prepare for lessons and perform administrative tasks using smart devices will be described. The system includes the following elements.

[0197] 1. Input Method

[0198] Users (teachers) log in to their smart devices (smartphones, tablets, etc.) and enter data related to class content and administrative tasks, such as the next week's class content, related materials, and self-study assignments.

[0199] 2. Server Means

[0200] The entered data is sent to a cloud server and stored in a database. The server then analyzes the stored data using AI algorithms to automatically generate lesson materials and documents (PowerPoint templates, lecture notes, email templates, etc.).

[0201] 3. Generation means

[0202] The AI ​​algorithm uses past lesson data and related materials to generate optimal lesson materials based on the input data, such as PowerPoint templates, lecture notes, and email templates for parents for the next week's lesson.

[0203] 4. Transmission Method

[0204] The generated documents are sent from the server to the user's smart device and displayed on the device, where the user can review them and make corrections as necessary.

[0205] 5. Corrective measures

[0206] Users can view the generated materials on their smart devices, add specific information, or modify the content, allowing instructors to efficiently create, review, and modify course materials and documents.

[0207] Specific examples

[0208] To prepare for next week's class, "Basic Chemistry," Teacher B logs into his smart device and enters the following lesson content: "Next class will be 'Basic Chemistry,' with related materials from Chapter 4 of the textbook and self-study assignments." This data is sent to a server and stored in a database. On the server, an AI algorithm analyzes past lesson data and related materials to generate PowerPoint templates, lecture notes, and even email templates for parents that are optimal for next week's class.

[0209] The generated materials are sent from the cloud server to Teacher B's smart device and displayed on the device. Teacher B reviews these materials and, if necessary, adds additional information to specific slides or modifies the content to emphasize key points.

[0210] Prompt Sentence Examples

[0211] "The next class is on basic chemistry, and the related materials are Chapter 4 of the textbook and a self-study assignment. Generate the best PowerPoint templates, lecture notes, and email templates for parents."

[0212] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0213] Step 1:

[0214] User login and data entry

[0215] The user (teacher) logs in to the smart device and inputs the content of the next lesson and related materials. The input fields include the lesson title, textbook chapter, self-study assignment, etc. This information is collected through the user interface of the smart device and sent to the server as JSON format data. An example of input data is "The next lesson is 'Basic Chemistry', related materials are textbook chapter 4, and self-study assignment." As output, the input data is sent to the server.

[0216] Step 2:

[0217] Data reception and storage by the server

[0218] The server receives data sent from the smart device. The received data includes information such as lesson content, textbook chapters, and self-study assignments. This data is then temporarily stored in the server's database. The input is the received JSON data, and the output is the stored database entries.

[0219] Step 3:

[0220] Data analysis and generation using AI algorithms

[0221] The server inputs the saved data into an AI algorithm for analysis. The AI ​​algorithm references past lesson data and related materials to generate documents (PowerPoint templates, lecture notes, email templates, etc.) that are most suitable for the next lesson. This generation process collects highly relevant information and places it appropriately in each document. The inputs are saved data and past lesson data, and the output is the generated document.

[0222] Step 4:

[0223] Sending and viewing generated materials

[0224] The server sends the generated lesson materials to the user's smart device. The data is sent in the form of PowerPoint templates, lecture notes, email templates, etc. The user's smart device receives and displays these materials. The input is the generated document, and the output is the display screen of the smart device.

[0225] Step 5:

[0226] Review and correct the materials

[0227] The user (teacher) reviews the generated materials on the smart device and makes corrections as necessary, adding additional slides, highlighting content, and making corrections through the smart device interface. The input is the user's feedback and corrections, and the output is the final revised document.

[0228] Step 6:

[0229] Save and share the final document

[0230] Once the corrections are complete, the document is sent back to the server and saved as the final version in the database. If necessary, the document can be shared with other faculty members or other stakeholders. The input is the corrected document, and the output is the saved document and a shared link.

[0231] Example prompt: "The next lesson will be on Basic Chemistry, and related materials will be Chapter 4 of the textbook, as well as a self-study assignment. Please generate the appropriate PowerPoint template, lecture notes, and email template for parents."

[0232] 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.

[0233] As an embodiment of the present invention, a system for automating and streamlining a teacher's administrative work and lesson preparation, and taking into account the teacher's emotional state, is described below. This system includes a terminal for the teacher to input data, a server for receiving, analyzing, and generating data, a means for presenting and correcting the generated materials to the teacher, and an emotion engine for recognizing the teacher's emotions.

[0234] System Overview

[0235] 1. Data entry by the teacher (terminal side)

[0236] The user (teacher) logs in to the device and inputs data related to the required lesson content and administrative work. For example, a teacher inputs related materials and assignments for the next lesson, "Fundamentals of Biology," into the device. The device also sends the teacher's input data and behavioral data during operation to the emotion engine.

[0237] 2. Data processing and storage (server side)

[0238] The device sends input data and emotional data to the server, which receives it and stores it in a database. The server analyzes the received data and uses AI algorithms to automatically generate documents and materials. It also takes into account the emotional state of the teacher, as analyzed by the emotion engine.

[0239] 3. Document Generation (Server Side)

[0240] The server uses AI algorithms to generate optimal lesson materials and documents based on the input data. It also adjusts the content and format of the materials based on the teacher's emotional state based on the analysis results of the emotion engine. For example, if a teacher is feeling stressed, the server will reduce the amount of material provided and soften their tone.

[0241] 4. Sending and displaying the results (terminal side)

[0242] The server sends the generated materials to the terminal, which displays them to the user, who can then use them to prepare for classes or perform administrative tasks.

[0243] 5. Checking and correcting materials (user side)

[0244] The user can review the submitted materials and make any necessary modifications, for example adding specific information to the generated PowerPoint template or modifying the content.

[0245] Specific examples

[0246] Teacher A logs in to the device to enter the next week's lesson schedule and enters the following: "The next lesson is 'Fundamentals of Biology', and the related materials are Chapter 3 of the textbook and the self-study assignment." The device sends this data, along with the teacher's input operation data, to the emotion engine.

[0247] The server receives the data and stores it in a database. An AI algorithm analyzes past lesson data and related materials to generate PowerPoint templates and lecture notes optimal for the next week's lesson, as well as email templates for parents. At the same time, an emotion engine analyzes Teacher A's emotional state and, if it determines that he is feeling stressed, makes adjustments such as reducing the amount of material or simplifying the content.

[0248] The generated materials are sent from the server to the terminal and displayed on Teacher A's terminal. Teacher A reviews these materials and makes corrections as necessary, for example, by inserting additional slides into the PowerPoint template to emphasize specific content.

[0249] This system allows teachers to save time by manually creating materials, enabling them to prepare lessons and perform administrative tasks more efficiently. Furthermore, the introduction of an emotion engine provides a system that takes into account the teacher's emotional state, improving the user experience. This invention reduces the workload of teachers and provides sufficient support for them to focus on their teaching activities.

[0250] The processing flow will be explained below.

[0251] Step 1:

[0252] Users log in to the terminal and enter data related to the required lesson content and administrative tasks. For example, a teacher may enter "Fundamentals of Biology" as the lesson content for next week, and enter related materials and assignments. At the same time, the terminal collects operation data such as the teacher's keystroke time and click frequency.

[0253] Step 2:

[0254] The terminal sends input data and operation data to the server using an encryption protocol that takes security into consideration.

[0255] Step 3:

[0256] The server receives the data sent from the device and stores it in a database. The stored data includes lesson content, related materials, assignments, and teacher operation data.

[0257] Step 4:

[0258] The server reads the incoming data from the database and begins analyzing it, using AI algorithms to analyze the content of the input data.

[0259] Step 5:

[0260] The server uses an emotion engine to analyze the teacher's operation data and estimate the teacher's emotional state. Specifically, it determines whether the teacher is feeling stressed based on data such as keystroke speed and click intervals.

[0261] Step 6:

[0262] Based on the analysis results, the server uses AI algorithms to generate optimal documents and materials. These include PowerPoint templates for lessons, lecture notes, and email templates for parents. Based on the analysis results of the emotion engine, if a teacher is feeling stressed, the server will adjust the amount of materials provided, such as reducing the content or making it more concise.

[0263] Step 7:

[0264] The server sends the generated documents and materials to the terminal, using a real-time communication protocol to quickly deliver the data to the user.

[0265] Step 8:

[0266] The terminal displays the sent documents and materials to the user, who can then use them to prepare for classes or perform administrative tasks.

[0267] Step 9:

[0268] The user can review the displayed document or material and make any necessary edits. The edited document is then saved back to the device. For example, the user can add specific information to the generated PowerPoint template to highlight the content.

[0269] This system will enable teachers to save time by manually creating materials, allowing them to prepare lessons and perform administrative tasks more efficiently. It will also improve the user experience by taking into account the emotional state of teachers, providing a less stressful work environment.

[0270] Example 2

[0271] 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."

[0272] Traditionally, administrative work and lesson preparation required a lot of time and effort, reducing productivity. These tasks can also affect teachers' emotional state and increase stress. This can reduce the time teachers have to concentrate on teaching activities, potentially resulting in a decline in the quality of education. Given this background, there was a need for a system that could streamline teachers' work and also take into account their emotional state.

[0273] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes an input means through which a teacher inputs data for administrative work and lesson preparation, a server means for receiving the data and storing it in a database, a generation means for analyzing the data and generating documents and materials using an AI algorithm, a transmission means for transmitting the generated output to the teacher's terminal and displaying it, an emotion recognition means for recognizing the teacher's emotional state based on the data, and an adjustment means for adjusting the document content based on the analysis results of the emotion recognition means. This automates the teacher's work and makes it possible to provide materials customized according to the teacher's emotional state. This reduces the teacher's workload and provides sufficient support for them to concentrate on their teaching activities.

[0274] "Input means" refers to the means by which teachers input data necessary for administrative work and lesson preparation into the system.

[0275] "Server means" refers to means having a server function for receiving data entered by a teacher and storing it in a database.

[0276] "Generation means" refers to the means for analyzing received data and generating documents or materials using AI algorithms.

[0277] The "transmission means" is a means for transmitting the generated output to the teacher's terminal and displaying it.

[0278] The "emotion recognition means" is a means for recognizing the emotional state of the teacher based on the input data and operation data.

[0279] The "adjustment means" is a means for adjusting the document contents based on the analysis results of the emotion recognition means.

[0280] "Documents" refers to all documents used by teachers, including course materials.

[0281] "Materials" refers to various documents used by faculty for classes and administrative work, including PowerPoint templates, lecture notes, and email templates.

[0282] "Teacher" refers to anyone engaged in educational activities.

[0283] This invention relates to a system that automates and streamlines the administrative work and lesson preparation of teachers and takes into account the emotional state of the teacher. This system includes a terminal for teachers to input data, a server that receives, analyzes, and generates data, a means for presenting and correcting the generated materials to the teacher, and an emotion engine that recognizes the teacher's emotions.

[0284] Teachers log in to the terminal and input data related to the next class content and administrative work. For example, a teacher can input related materials and assignments for next week's class content, "Fundamentals of Biology," into the terminal. At this time, the teacher's input data and behavioral data during operation are sent to the emotion engine.

[0285] The device sends input data and emotional data to a server, which receives the data and stores it in a database. The server then analyzes the received data and uses an AI algorithm to automatically generate documents and materials. One example of the algorithm used is OpenAI's GPT-3 (registered trademark). The system also takes into account the emotional state of the teacher analyzed by the emotion engine.

[0286] The server uses an AI algorithm to generate optimal lesson materials and documents based on the input data. For example, if a teacher is feeling stressed, the server will adjust the amount of material provided, soften the tone, and make other adjustments. An example of a specific prompt could be, "The next class will be on 'Fundamentals of Biology,' and the related materials will be Chapter 3 of the textbook and self-study assignments. Please simplify the materials for teachers who are feeling stressed."

[0287] The generated materials are sent from the server to the terminal and displayed on the teacher's terminal. Teachers can use these materials to efficiently prepare for classes and perform administrative tasks. Teachers can also review the sent materials and make corrections as necessary. For example, they can add specific information to the generated PowerPoint template or modify the content.

[0288] This system reduces the workload of teachers and provides sufficient support for them to concentrate on teaching activities. In addition, by using an emotion engine, services are provided that take into account the emotional state of teachers, improving the user experience.

[0289] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0290] Step 1:

[0291] The user (teacher) logs into the terminal and inputs the data necessary for lesson preparation and administrative work. Specifically, they input the next lesson content, "Fundamentals of Biology," related materials, "Textbook Chapter 3," and assignment content, "Self-Study Assignment." This input data is acquired through the terminal's interface. The terminal also simultaneously collects operation data such as the teacher's keystroke speed and mouse operation, and sends this data to the emotion engine. The input data is text data related to the lesson content and administrative work, while the operation data is behavioral data used to determine the teacher's emotional state.

[0292] Step 2:

[0293] The terminal uses a communication module to send input data and operation data to the server in real time. The server temporarily stores the received data and then stores it in a database. Specifically, the server receives input data and operation data in a standard format such as JSON and temporarily stores it in a buffer area. This data is then stored in a structured or relational database. The input is the data stream from the terminal, and the output is the data stored in the database.

[0294] Step 3:

[0295] The server uses AI algorithms to analyze the data stored in the database. First, it analyzes the lesson content data and extracts the information necessary to generate related materials and documents. Next, the emotion engine analyzes the operation data and determines the teacher's emotional state. For example, it can identify whether the teacher is feeling stressed based on the speed of keystrokes and frequency of mouse operations. The input is lesson content data and operation data obtained from the database, and the output is lesson information and emotional state data as the analytical results.

[0296] Step 4:

[0297] Based on the analysis results, the server uses an AI algorithm to automatically generate lesson materials and documents. For example, it uses a generative AI model such as OpenAI GPT-3 to generate relevant materials (e.g., PowerPoint templates, lecture notes, email templates). At this time, the content and amount of the materials are adjusted based on the analysis results of the emotion engine, taking into account the teacher's emotional state. The input is the analysis results and emotional state data obtained from Step 3, and the output is the generated lesson materials and documents. The generated materials are created according to a prompt. For example, a prompt might be used: "The next class is 'Fundamentals of Biology,' and the related materials are Chapter 3 of the textbook and self-study assignments. Please keep the materials concise for teachers who are feeling stressed."

[0298] Step 5:

[0299] The server sends the generated lesson materials and documents to the terminal. This transmission process uses a secure communication protocol (e.g., HTTPS). The terminal displays the received materials on the teacher's screen. The input is the generated materials sent from the server, and the output is the visual information displayed through the terminal's interface.

[0300] Step 6:

[0301] The user (teacher) checks the materials displayed on the terminal and edits or modifies them as necessary. For example, they can insert additional slides into the generated PowerPoint template to emphasize specific content. They can also customize the content of their lecture notes. The input is the generated material displayed on the terminal, and the output is the final material to which the teacher has made modifications. The results of these modifications are saved back in the database and used to prepare for future lessons.

[0302] (Application example 2)

[0303] 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."

[0304] In brick-and-mortar stores, it takes a lot of time and effort for staff to efficiently perform their daily tasks and respond to customers. Furthermore, performing tasks without considering the emotional state of staff can cause stress and fatigue, resulting in a decline in the quality of work and customer satisfaction. This invention aims to provide a system that automates and streamlines work management and customer response in brick-and-mortar stores, while also taking into account the emotional state of staff.

[0305] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes an input means through which a teacher inputs data for clerical work and lesson preparation, a server means for receiving the data and storing it in a database, a generation means for analyzing the data and generating documents and materials using an AI algorithm, a transmission means for sending the generated output to the teacher's terminal and displaying it, an input means through which staff input customer service and work content based on the input data, a generation means for generating procedure manuals and scripts based on the work content, and an emotion analysis means for analyzing the emotional state of staff and optimizing information based on this. This not only efficiently automates work and customer service in physical stores, but also enables appropriate support that takes the emotional state of staff into consideration.

[0306] A "teacher" is a person whose job is to provide education to pupils or students at an educational institution.

[0307] "Office work" is a general term for everyday work tasks such as creating documents, processing data, and organizing information necessary for general business operations.

[0308] "Class preparation" refers to a series of preparatory activities that teachers at educational institutions undertake, such as preparing teaching materials, formulating lesson plans, and creating materials, in order to teach a class.

[0309] "Data" is a collective term for information and records that are input into a system for processing.

[0310] "Input means" is a general term for interfaces and devices that allow a user to input data into the system.

[0311] "Server means" is a general term for a computer system that receives data, stores it in a database, and performs processing such as analysis.

[0312] "Generation means" is a general term for functions and devices that automatically generate documents and materials using AI algorithms based on input data.

[0313] "Transmission means" is a general term for functions and devices for transmitting the generated output to the user's terminal and displaying it.

[0314] "Customer service" refers to a series of actions and activities that store staff take to provide service in response to customer requests and inquiries and improve customer satisfaction.

[0315] "Work content" refers to the details and content of the work and tasks that staff perform on a daily basis.

[0316] "Emotion analysis means" is a general term for functions and devices that analyze the user's emotional state and generate optimized information based on the results.

[0317] A "procedure manual" is a document that contains detailed instructions and procedures for carrying out a specific task or work.

[0318] A "script" is a document that contains standard phrases and conversational guidelines used in specific tasks or customer interactions.

[0319] "Output" refers to documents and materials that are the result of a system's generation.

[0320] As an embodiment of the present invention, a system that improves the efficiency of staff work management and customer service and also takes into account the emotional state of staff is described below. This system includes a terminal for staff to input data, a server that receives, analyzes, and stores the data, a means for presenting and correcting the generated materials to staff, and an emotion analysis engine that recognizes the emotions of staff.

[0321] System Overview

[0322] 1. Data entry by staff (terminal side)

[0323] Users (staff) log in to a smartphone app and input their daily work and customer service details. The input method sends the work details and behavioral data to the emotion analysis engine. Specifically, data such as "New product A has arrived" or "Customer B has an inquiry about a product" is entered into the app.

[0324] 2. Data processing and storage (server side)

[0325] The terminal sends input data and emotional data to the server, which receives it and stores it in a database. The server then uses AI algorithms to analyze the input data and generate appropriate work procedures and customer service scripts. It also takes into account the emotional state of the staff analyzed by the emotion analysis engine.

[0326] 3. Document generation and display (server side and terminal side)

[0327] The server uses an AI algorithm to generate optimal procedures and scripts based on the input data. Furthermore, based on the analysis results of the emotion analysis engine, if a staff member is feeling stressed, the server will adjust the procedure by simplifying it or softening the tone of the script. The generated materials are sent from the server to the terminal, where they are displayed to the staff member.

[0328] 4. Checking and correcting materials (staff side)

[0329] Staff can review the submitted materials and make corrections as needed, for example by adding additional information to the generated customer response script or by amending the content.

[0330] Program processing explanation

[0331] The server runs on the Flask framework and stores data in a SQLite database. Task details and emotional data entered by users through a smartphone app are sent to the server and analyzed by an AI algorithm. The AI ​​algorithm generates optimal procedures and scripts based on a database containing past data and related information. The emotion analysis engine also analyzes the emotional state of staff and adjusts the content and format of the generated materials.

[0332] Specifically, if a staff member inputs "New product A has arrived" or "Customer B has an inquiry about a product," the server will generate the optimal receiving procedure manual and customer response script based on this data. Also, if a staff member is feeling stressed, the server will simplify the procedure or generate a script using a gentler tone.

[0333] Prompt Sentence Examples

[0334] Task: New product A has arrived, and customer B has inquired about the product.

[0335] Emotional data: tired, stressed

[0336] The above is a detailed description of the embodiment of the present invention. This system not only efficiently automates operations and customer service in brick-and-mortar stores, but also enables appropriate support that takes into account the emotional state of staff. Implementing the system in accordance with this embodiment will improve work efficiency and reduce staff stress.

[0337] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0338] Step 1:

[0339] The user logs into the smartphone app and inputs details of their daily work and customer service. For example, this data might include "New product A has arrived" or "Customer B has an inquiry about a product." The device then sends this input data and behavioral data during operation to the emotion analysis engine.

[0340] Step 2:

[0341] The device sends input data and emotion data to the server, which receives it and stores it in a database. The SQLite database ensures data persistence and efficient management.

[0342] Step 3:

[0343] The server analyzes the received data and uses an AI algorithm to generate optimal procedures and scripts based on the input work content, while referring to related past data and materials. The AI ​​model uses a pre-trained generative AI model.

[0344] Step 4:

[0345] The emotion analysis engine analyzes the emotional data sent from the device, evaluating the emotional state of the staff member and determining whether they are feeling stressed or fatigued. Emotion analysis is performed using behavioral data during operation and facial expression recognition technology.

[0346] Step 5:

[0347] The server adjusts the generated procedures and scripts based on the results of the emotion analysis engine. For example, if a staff member is feeling stressed, it will simplify the work procedures or soften the tone of the script.

[0348] Step 6:

[0349] The server sends the generated optimized procedures and scripts to the terminal, which displays them to the staff, who can then view them through the app.

[0350] Step 7:

[0351] Staff members can review the displayed procedures and scripts and make any necessary corrections. For example, they can add additional information to a customer support script or modify its content. The corrected materials are then sent back to the server and updated in the database.

[0352] 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.

[0353] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (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.

[0354] 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.

[0355] [Second embodiment]

[0356] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0357] 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.

[0358] 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).

[0359] 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.

[0360] 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.

[0361] 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).

[0362] 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.

[0363] 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.

[0364] 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.

[0365] 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.

[0366] 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.

[0367] 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."

[0368] As an embodiment of the present invention, a system for automating and streamlining administrative work and lesson preparation for teachers is described below. This system includes a terminal for teachers to input data, a server that receives, analyzes, and generates data, and a means for presenting and modifying the generated materials to teachers.

[0369] System Overview

[0370] 1. Data entry by the teacher (terminal side)

[0371] The user (teacher) logs in to the terminal and inputs data related to the required lesson content and administrative work. For example, a teacher inputs related materials and assignments for the next lesson, "Fundamentals of Biology," into the terminal.

[0372] 2. Data processing and storage (server side)

[0373] The device sends the input data to a server, which receives it and stores it in a database. The server then analyzes the data and uses AI algorithms to automatically generate documents and materials.

[0374] 3. Document Generation (Server Side)

[0375] The server uses AI algorithms to generate optimal lesson materials and documents based on the input data, such as PowerPoint templates, lecture notes, and email templates for parents on "Fundamentals of Biology."

[0376] 4. Sending and displaying the results (terminal side)

[0377] The server sends the generated materials to the terminal, which displays them to the user, who can then use them to prepare for classes or perform administrative tasks.

[0378] 5. Checking and correcting materials (user side)

[0379] The user can review the submitted materials and make any necessary modifications, for example adding specific information to the generated PowerPoint template or modifying the content.

[0380] Specific examples

[0381] To enter the next week's lesson schedule, Teacher A logs in to the terminal and enters the following information: "The next lesson is 'Fundamentals of Biology', and the related materials are Chapter 3 of the textbook and the self-study assignment." The terminal then sends this data to the server.

[0382] The server receives the data and stores it in a database. AI algorithms analyze past lesson data and related materials to generate PowerPoint templates, lecture notes, and email templates for parents that are optimal for the next week's lesson.

[0383] The generated materials are sent from the server to the terminal and displayed on Teacher A's terminal. Teacher A reviews these materials and makes corrections as necessary, for example, by inserting additional slides into the PowerPoint template to emphasize specific content.

[0384] This system allows teachers to save time by manually creating materials, and to carry out lesson preparation and administrative work more efficiently. The present invention reduces the workload of teachers and provides sufficient support for them to concentrate on teaching activities.

[0385] The processing flow will be explained below.

[0386] Step 1:

[0387] Users log in to the terminal and enter the necessary data related to the course content and administrative work, such as the class schedule, student list, and past class materials.

[0388] Step 2:

[0389] The device sends the input data to the server using an encryption protocol that takes security into consideration.

[0390] Step 3:

[0391] The server receives the data sent from the terminal and stores it in a database using a database management system (DBMS).

[0392] Step 4:

[0393] The server reads the incoming data from the database and begins analyzing it, using AI algorithms to analyze the content of the input data.

[0394] Step 5:

[0395] The server generates specific documents and materials based on the analysis results, including PowerPoint templates for lessons, lecture notes, and email templates for parents.

[0396] Step 6:

[0397] The server sends the generated documents and materials to the terminal, using a real-time communication protocol to quickly deliver the data to the user.

[0398] Step 7:

[0399] The terminal displays the transmitted documents and materials to the user, who then checks the displayed materials.

[0400] Step 8:

[0401] The user can check the displayed document or material and make any necessary corrections. Once the corrections are complete, the document is saved back to the device.

[0402] This system allows teachers to prepare for classes and carry out administrative tasks quickly and efficiently. The specific processes performed at each step are explained in detail, making the operation of each step clear.

[0403] Example 1

[0404] 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."

[0405] Because administrative work and lesson preparation for teachers requires a great deal of time and effort, there is a need for greater efficiency. However, the traditional method of manually creating documents and generating materials is time-consuming and has limited effectiveness in reducing the burden on teachers. The present invention aims to solve these issues and significantly reduce the burden on teachers by automating and streamlining administrative work and lesson preparation for teachers.

[0406] 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.

[0407] In this invention, the server includes an input means for teachers to input information for administrative work and lesson preparation, a server means for receiving the information and storing it in a database, a generation means for analyzing the information and generating documents and materials using a generative AI model, a transmission means for sending the generated results to the teacher's terminal and displaying them, and a correction means for the teacher to check the results and correct them as necessary. This allows teachers to automatically generate optimal lesson materials and documents by simply inputting information, enabling them to efficiently perform administrative work and lesson preparation.

[0408] A "teacher" is a person who provides educational activities to students at an educational institution.

[0409] "Administrative work" refers to non-educational tasks performed by teachers, such as preparing for classes, managing student grades, and communicating with parents.

[0410] "Class preparation" refers to the preparatory work required to smoothly carry out educational activities, such as creating teaching materials and documents to be used in class and drawing up lesson plans.

[0411] "Input means" refers to devices and software that allow teachers to use terminals to input information related to lesson content and administrative work.

[0412] "Server means" refers to a device or software that receives input information, stores it in a database, and manages and processes it.

[0413] A "database" is a system for systematically storing received information so that it can be searched and used later.

[0414] "Generation means" refers to devices or software that automatically generate documents or materials using a generative AI model based on analyzed information.

[0415] A "generative AI model" is an artificial intelligence algorithm that performs natural language processing based on input information and generates appropriate documents and materials.

[0416] "Transmission means" refers to devices and software for transferring the generated documents and materials to the teacher's terminal and displaying them.

[0417] "Correction means" refers to devices or software that allow teachers to check the generated results and make corrections as necessary.

[0418] "Results" are documents and materials created by the generating means.

[0419] A "presentation template" is a template for slide-format materials used in classes, etc.

[0420] "Lecture notes" are materials in the form of notes that contain the content necessary for the progress of a class.

[0421] "Notification templates" are standardized email and letter templates used when contacting parents and other concerned parties.

[0422] A "terminal" is a computer or other device that allows a teacher to input information and view generated results.

[0423] "Information" refers to all data related to lesson content and administrative work entered by teachers.

[0424] This invention is a system that automates and streamlines administrative work and lesson preparation for teachers. This system includes a terminal for teachers to input information, a server that receives, analyzes, and generates information, and a means for presenting and modifying the generated results to teachers.

[0425] Users (teachers) log in to the system from terminals used at educational institutions. Using the input means of the terminal, teachers input information such as the content of the next lesson, related materials, and self-study assignments. For example, they input information such as "The next lesson is 'Fundamentals of Biology', and related materials are Chapter 3 of the textbook, and self-study assignments."

[0426] When the terminal receives the input information, it sends it to the server, which verifies the received information and stores it in a database. The server manages the information using a relational database management system (e.g., an SQL database).

[0427] The server then analyzes the stored information and generates optimal lesson materials and documents using a generative AI model (e.g., OpenAI's GPT-4). The server analyzes past lesson data and related materials and generates documents based on them. For example, it generates presentation templates, lecture notes, and parent notification templates for "Fundamentals of Biology."

[0428] The generated results are sent from the server to the terminal. The terminal displays them on the user interface. The user (teacher) can check the generated results and make corrections as necessary. Corrections are made using the terminal's editing tools, and the final material is re-saved on the server.

[0429] With this system, teachers simply input information and the system automatically generates the most suitable lesson materials and documents. In addition, the generated materials can be easily edited, allowing for efficient administrative work and lesson preparation.

[0430] Specific examples

[0431] To enter the next week's lesson schedule, Teacher A logs in to the terminal and enters the following information: "The next lesson is 'Fundamentals of Biology', and the related materials are Chapter 3 of the textbook and the self-study assignment." The terminal then sends this information to the server.

[0432] The server receives the data and stores it in a database. A generative AI model analyzes past lesson data and related materials to generate presentation templates, lecture notes, and notification templates for parents that are optimal for "Fundamentals of Biology."

[0433] The generated materials are sent from the server to the terminal and displayed on Teacher A's terminal. Teacher A reviews these materials and makes corrections as necessary, for example, by inserting additional slides into the presentation template to emphasize specific content.

[0434] Prompt Sentence Examples

[0435] Here are some examples of input prompts for a generative AI model:

[0436] "I'm teaching 'Basic Biology' for next week's class. Based on past lesson data and the content of Chapter 3 of the textbook, please generate a presentation template, lecture notes, and parent notification template."

[0437] In this way, teachers can efficiently carry out administrative tasks and prepare for lessons. This invention reduces the burden on teachers and provides practical support for providing high-quality education.

[0438] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0439] Step 1:

[0440] Logging in to a teacher's device

[0441] The user (teacher) logs in to the terminal. The teacher enters their user ID and password for authentication. The terminal sends the entered authentication information to the server, which then compares it with the user information in the database. If authentication is successful, the teacher is allowed to access the system.

[0442] Input: User ID, Password

[0443] Output: Authentication result (success / failure)

[0444] Specific behavior:

[0445] Teachers enter their ID and password into the login screen.

[0446] The terminal transmits the authentication information to the server.

[0447] The server checks the credentials against a database and returns the result.

[0448] The authentication result will be displayed on the device.

[0449] Step 2:

[0450] Data entry of lesson contents

[0451] The user (teacher) inputs information such as the content of the next class, related materials, and self-study assignments into the terminal. For example, the user might input "The next class is 'Fundamentals of Biology', related materials are Chapter 3 of the textbook, and self-study assignments." The terminal then converts this input data into a structured format (e.g., JSON).

[0452] Input: Course content, related materials, self-study assignments

[0453] Output: Structured data (JSON format)

[0454] Specific behavior:

[0455] Teachers fill out the input form with the lesson content and related materials.

[0456] The terminal converts the input data into JSON format.

[0457] Step 3:

[0458] Sending data

[0459] The device transmits the structured data to the server using a secure communication protocol (e.g., HTTPS).

[0460] Input: Structured data (JSON format)

[0461] Output: Sending to server completed

[0462] Specific behavior:

[0463] The terminal generates JSON data.

[0464] The terminal transmits the data to the server through secure communication.

[0465] The server acknowledges receipt of the data.

[0466] Step 4:

[0467] Receiving and storing data on the server side

[0468] The server receives the data sent from the terminal and verifies its contents. If the verification is successful, the server saves the data in a database, such as an SQL database.

[0469] Input: Structured data (JSON format)

[0470] Output: Saved to database

[0471] Specific behavior:

[0472] The server validates the received JSON data (schema checking and data integrity checking).

[0473] The server stores the data in a database.

[0474] The database notifies the server of the successful save.

[0475] Step 5:

[0476] Data analysis and documentation generation

[0477] The server analyzes the stored data and generates optimal lesson materials and documents using a generative AI model (such as OpenAI's GPT-4). In this process, it generates prompt sentences and inputs them into the AI ​​model.

[0478] Input: saved data, prompt

[0479] Output: Generated documents (presentation templates, lecture notes, announcement templates, etc.)

[0480] Specific behavior:

[0481] The server retrieves the relevant information from a database.

[0482] The server generates a prompt for the generative AI model.

[0483] The AI ​​model generates a document based on the prompt.

[0484] The generated document is saved in temporary storage.

[0485] Step 6:

[0486] Sending generated documents

[0487] The server sends the generated documents to the terminal, which displays these documents in its user interface.

[0488] Input: Generated document

[0489] Output: Sent to terminal

[0490] Specific behavior:

[0491] The server retrieves the generated document from temporary storage.

[0492] The server sends the document to the terminal.

[0493] The terminal displays the received document.

[0494] Step 7:

[0495] Check and correct the document

[0496] The user (teacher) checks the received document and makes any necessary corrections. The corrected document is then saved back to the server and becomes available as the final version.

[0497] Input: Generated document, corrections

[0498] Output: Final document

[0499] Specific behavior:

[0500] The teacher checks the generated document on the terminal.

[0501] The teacher will make any necessary corrections.

[0502] The terminal sends the modified document to the server.

[0503] The server stores the final document in a database.

[0504] These are the specific processing steps of the system. This flow allows teachers to efficiently generate and edit lesson materials simply by inputting information.

[0505] (Application example 1)

[0506] 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."

[0507] Traditionally, teachers' administrative work and lesson preparation requires a lot of time and effort, making it inefficient. Creating lesson materials and related documents in particular requires a great deal of time and effort, preventing teachers from concentrating on their teaching activities. Furthermore, there is a lack of convenient ways to easily check and revise lesson plans and related materials on smart devices. Therefore, a system is needed that allows teachers to perform administrative work and lesson preparation more efficiently and focus on their teaching activities.

[0508] 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.

[0509] In this invention, the server includes an input means for teachers to input data for administrative work and lesson preparation, a server means for receiving the data and storing it in a database, a generation means for analyzing the data and generating documents and materials using an AI algorithm, a transmission means for sending the generated output to the teacher's terminal and displaying it, and a means for the teacher to check and modify the generated materials using a smart device. This allows teachers to efficiently create and modify materials, significantly reducing the time spent on lesson preparation and administrative work. Furthermore, checking and modifying data on a smart device improves convenience and helps teachers focus on their teaching activities.

[0510] A "teacher" is a person who teaches classes at an educational institution and is engaged in the task of imparting knowledge and skills to students.

[0511] "Administrative work" refers to work outside of teaching, including administrative tasks, document preparation, and student evaluations at educational institutions.

[0512] "Lesson preparation" refers to the process of planning a lesson, creating necessary materials and documents, and preparing the content of the lesson in advance.

[0513] "Input means" refers to devices or interfaces that teachers use to input data, including keyboards, touchscreens, etc.

[0514] "Server means" refers to a computing system responsible for storing and analyzing received data.

[0515] "Generation means" refers to a system that automatically generates documents and materials based on input data using AI algorithms.

[0516] "Transmission means" refers to a system that has the function of transmitting the generated output to the teacher's terminal and displaying it.

[0517] "Smart device" refers to an advanced digital device that can connect to the Internet and install and run applications, including smartphones and tablets.

[0518] A "PowerPoint template" refers to a basic format for creating presentations, a file with a pre-determined slide design and layout.

[0519] "Lecture notes" refer to materials that contain the content and progress plan of a class, and are used by teachers as a guide when teaching a class.

[0520] An "email template" refers to a pre-created email template based on specific content and format, intended for efficient communication.

[0521] "Correction tools" refer to tools and interfaces that allow teachers to review the generated output and make changes or additions to content as needed.

[0522] "Output" includes results, materials, and documents generated by AI algorithms based on input data.

[0523] MODE FOR CARRYING OUT THE INVENTION

[0524] As an embodiment of the present invention, a system that enables teachers to efficiently prepare for lessons and perform administrative tasks using smart devices will be described. The system includes the following elements.

[0525] 1. Input Method

[0526] Users (teachers) log in to their smart devices (smartphones, tablets, etc.) and enter data related to class content and administrative tasks, such as the next week's class content, related materials, and self-study assignments.

[0527] 2. Server Means

[0528] The entered data is sent to a cloud server and stored in a database. The server then analyzes the stored data using AI algorithms to automatically generate lesson materials and documents (PowerPoint templates, lecture notes, email templates, etc.).

[0529] 3. Generation means

[0530] The AI ​​algorithm uses past lesson data and related materials to generate optimal lesson materials based on the input data, such as PowerPoint templates, lecture notes, and email templates for parents for the next week's lesson.

[0531] 4. Transmission Method

[0532] The generated documents are sent from the server to the user's smart device and displayed on the device, where the user can review them and make corrections as necessary.

[0533] 5. Corrective measures

[0534] Users can view the generated materials on their smart devices, add specific information, or modify the content, allowing instructors to efficiently create, review, and modify course materials and documents.

[0535] Specific examples

[0536] To prepare for next week's class, "Basic Chemistry," Teacher B logs into his smart device and enters the following lesson content: "Next class will be 'Basic Chemistry,' with related materials from Chapter 4 of the textbook and self-study assignments." This data is sent to a server and stored in a database. On the server, an AI algorithm analyzes past lesson data and related materials to generate PowerPoint templates, lecture notes, and even email templates for parents that are optimal for next week's class.

[0537] The generated materials are sent from the cloud server to Teacher B's smart device and displayed on the device. Teacher B reviews these materials and, if necessary, adds additional information to specific slides or modifies the content to emphasize key points.

[0538] Prompt Sentence Examples

[0539] "The next class is on basic chemistry, and the related materials are Chapter 4 of the textbook and a self-study assignment. Generate the best PowerPoint templates, lecture notes, and email templates for parents."

[0540] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0541] Step 1:

[0542] User login and data entry

[0543] The user (teacher) logs in to the smart device and inputs the content of the next lesson and related materials. The input fields include the lesson title, textbook chapter, self-study assignment, etc. This information is collected through the user interface of the smart device and sent to the server as JSON format data. An example of input data is "The next lesson is 'Basic Chemistry', related materials are textbook chapter 4, and self-study assignment." As output, the input data is sent to the server.

[0544] Step 2:

[0545] Data reception and storage by the server

[0546] The server receives data sent from the smart device. The received data includes information such as lesson content, textbook chapters, and self-study assignments. This data is then temporarily stored in the server's database. The input is the received JSON data, and the output is the stored database entries.

[0547] Step 3:

[0548] Data analysis and generation using AI algorithms

[0549] The server inputs the saved data into an AI algorithm for analysis. The AI ​​algorithm references past lesson data and related materials to generate documents (PowerPoint templates, lecture notes, email templates, etc.) that are most suitable for the next lesson. This generation process collects highly relevant information and places it appropriately in each document. The inputs are saved data and past lesson data, and the output is the generated document.

[0550] Step 4:

[0551] Sending and viewing generated materials

[0552] The server sends the generated lesson materials to the user's smart device. The data is sent in the form of PowerPoint templates, lecture notes, email templates, etc. The user's smart device receives and displays these materials. The input is the generated document, and the output is the display screen of the smart device.

[0553] Step 5:

[0554] Review and correct the materials

[0555] The user (teacher) reviews the generated materials on the smart device and makes corrections as necessary, adding additional slides, highlighting content, and making corrections through the smart device interface. The input is the user's feedback and corrections, and the output is the final revised document.

[0556] Step 6:

[0557] Save and share the final document

[0558] Once the corrections are complete, the document is sent back to the server and saved as the final version in the database. If necessary, the document can be shared with other faculty members or other stakeholders. The input is the corrected document, and the output is the saved document and a shared link.

[0559] Example prompt: "The next lesson will be on Basic Chemistry, and related materials will be Chapter 4 of the textbook, as well as a self-study assignment. Please generate the appropriate PowerPoint template, lecture notes, and email template for parents."

[0560] 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.

[0561] As an embodiment of the present invention, a system for automating and streamlining a teacher's administrative work and lesson preparation, and taking into account the teacher's emotional state, is described below. This system includes a terminal for the teacher to input data, a server for receiving, analyzing, and generating data, a means for presenting and correcting the generated materials to the teacher, and an emotion engine for recognizing the teacher's emotions.

[0562] System Overview

[0563] 1. Data entry by the teacher (terminal side)

[0564] The user (teacher) logs in to the device and inputs data related to the required lesson content and administrative work. For example, a teacher inputs related materials and assignments for the next lesson, "Fundamentals of Biology," into the device. The device also sends the teacher's input data and behavioral data during operation to the emotion engine.

[0565] 2. Data processing and storage (server side)

[0566] The device sends input data and emotional data to the server, which receives it and stores it in a database. The server analyzes the received data and uses AI algorithms to automatically generate documents and materials. It also takes into account the emotional state of the teacher, as analyzed by the emotion engine.

[0567] 3. Document Generation (Server Side)

[0568] The server uses AI algorithms to generate optimal lesson materials and documents based on the input data. It also adjusts the content and format of the materials based on the teacher's emotional state based on the analysis results of the emotion engine. For example, if a teacher is feeling stressed, the server will reduce the amount of material provided and soften their tone.

[0569] 4. Sending and displaying the results (terminal side)

[0570] The server sends the generated materials to the terminal, which displays them to the user, who can then use them to prepare for classes or perform administrative tasks.

[0571] 5. Checking and correcting materials (user side)

[0572] The user can review the submitted materials and make any necessary modifications, for example adding specific information to the generated PowerPoint template or modifying the content.

[0573] Specific examples

[0574] Teacher A logs in to the device to enter the next week's lesson schedule and enters the following: "The next lesson is 'Fundamentals of Biology', and the related materials are Chapter 3 of the textbook and the self-study assignment." The device sends this data, along with the teacher's input operation data, to the emotion engine.

[0575] The server receives the data and stores it in a database. An AI algorithm analyzes past lesson data and related materials to generate PowerPoint templates and lecture notes optimal for the next week's lesson, as well as email templates for parents. At the same time, an emotion engine analyzes Teacher A's emotional state and, if it determines that he is feeling stressed, makes adjustments such as reducing the amount of material or simplifying the content.

[0576] The generated materials are sent from the server to the terminal and displayed on Teacher A's terminal. Teacher A reviews these materials and makes corrections as necessary, for example, by inserting additional slides into the PowerPoint template to emphasize specific content.

[0577] This system allows teachers to save time by manually creating materials, enabling them to prepare lessons and perform administrative tasks more efficiently. Furthermore, the introduction of an emotion engine provides a system that takes into account the teacher's emotional state, improving the user experience. This invention reduces the workload of teachers and provides sufficient support for them to focus on their teaching activities.

[0578] The processing flow will be explained below.

[0579] Step 1:

[0580] Users log in to the terminal and enter data related to the required lesson content and administrative tasks. For example, a teacher may enter "Fundamentals of Biology" as the lesson content for next week, and enter related materials and assignments. At the same time, the terminal collects operation data such as the teacher's keystroke time and click frequency.

[0581] Step 2:

[0582] The terminal sends input data and operation data to the server using an encryption protocol that takes security into consideration.

[0583] Step 3:

[0584] The server receives the data sent from the device and stores it in a database. The stored data includes lesson content, related materials, assignments, and teacher operation data.

[0585] Step 4:

[0586] The server reads the incoming data from the database and begins analyzing it, using AI algorithms to analyze the content of the input data.

[0587] Step 5:

[0588] The server uses an emotion engine to analyze the teacher's operation data and estimate the teacher's emotional state. Specifically, it determines whether the teacher is feeling stressed based on data such as keystroke speed and click intervals.

[0589] Step 6:

[0590] Based on the analysis results, the server uses AI algorithms to generate optimal documents and materials. These include PowerPoint templates for lessons, lecture notes, and email templates for parents. Based on the analysis results of the emotion engine, if a teacher is feeling stressed, the server will adjust the amount of materials provided, such as reducing the content or making it more concise.

[0591] Step 7:

[0592] The server sends the generated documents and materials to the terminal, using a real-time communication protocol to quickly deliver the data to the user.

[0593] Step 8:

[0594] The terminal displays the sent documents and materials to the user, who can then use them to prepare for classes or perform administrative tasks.

[0595] Step 9:

[0596] The user can review the displayed document or material and make any necessary edits. The edited document is then saved back to the device. For example, the user can add specific information to the generated PowerPoint template to highlight the content.

[0597] This system will enable teachers to save time by manually creating materials, allowing them to prepare lessons and perform administrative tasks more efficiently. It will also improve the user experience by taking into account the emotional state of teachers, providing a less stressful work environment.

[0598] Example 2

[0599] 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."

[0600] Traditionally, administrative work and lesson preparation required a lot of time and effort, reducing productivity. These tasks can also affect teachers' emotional state and increase stress. This can reduce the time teachers have to concentrate on teaching activities, potentially resulting in a decline in the quality of education. Given this background, there was a need for a system that could streamline teachers' work and also take into account their emotional state.

[0601] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes an input means through which a teacher inputs data for administrative work and lesson preparation, a server means for receiving the data and storing it in a database, a generation means for analyzing the data and generating documents and materials using an AI algorithm, a transmission means for transmitting the generated output to the teacher's terminal and displaying it, an emotion recognition means for recognizing the teacher's emotional state based on the data, and an adjustment means for adjusting the document content based on the analysis results of the emotion recognition means. This automates the teacher's work and makes it possible to provide materials customized according to the teacher's emotional state. This reduces the teacher's workload and provides sufficient support for them to concentrate on their teaching activities.

[0602] "Input means" refers to the means by which teachers input data necessary for administrative work and lesson preparation into the system.

[0603] "Server means" refers to means having a server function for receiving data entered by a teacher and storing it in a database.

[0604] "Generation means" refers to the means for analyzing received data and generating documents or materials using AI algorithms.

[0605] The "transmission means" is a means for transmitting the generated output to the teacher's terminal and displaying it.

[0606] The "emotion recognition means" is a means for recognizing the emotional state of the teacher based on the input data and operation data.

[0607] The "adjustment means" is a means for adjusting the document contents based on the analysis results of the emotion recognition means.

[0608] "Documents" refers to all documents used by teachers, including course materials.

[0609] "Materials" refers to various documents used by faculty for classes and administrative work, including PowerPoint templates, lecture notes, and email templates.

[0610] "Teacher" refers to anyone engaged in educational activities.

[0611] This invention relates to a system that automates and streamlines the administrative work and lesson preparation of teachers and takes into account the emotional state of the teacher. This system includes a terminal for teachers to input data, a server that receives, analyzes, and generates data, a means for presenting and correcting the generated materials to the teacher, and an emotion engine that recognizes the teacher's emotions.

[0612] Teachers log in to the terminal and input data related to the next class content and administrative work. For example, a teacher can input related materials and assignments for next week's class content, "Fundamentals of Biology," into the terminal. At this time, the teacher's input data and behavioral data during operation are sent to the emotion engine.

[0613] The device sends input data and emotional data to a server, which receives the data and stores it in a database. The server then analyzes the data and uses an AI algorithm to automatically generate documents and materials. One example of the algorithm used is OpenAI's GPT-3. The emotional state of the teacher, as analyzed by the emotion engine, is also taken into account.

[0614] The server uses an AI algorithm to generate optimal lesson materials and documents based on the input data. For example, if a teacher is feeling stressed, the server will adjust the amount of material provided, soften the tone, and make other adjustments. An example of a specific prompt could be, "The next class will be on 'Fundamentals of Biology,' and the related materials will be Chapter 3 of the textbook and self-study assignments. Please simplify the materials for teachers who are feeling stressed."

[0615] The generated materials are sent from the server to the terminal and displayed on the teacher's terminal. Teachers can use these materials to efficiently prepare for classes and perform administrative tasks. Teachers can also review the sent materials and make corrections as necessary. For example, they can add specific information to the generated PowerPoint template or modify the content.

[0616] This system reduces the workload of teachers and provides sufficient support for them to concentrate on teaching activities. In addition, by using an emotion engine, services are provided that take into account the emotional state of teachers, improving the user experience.

[0617] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0618] Step 1:

[0619] The user (teacher) logs into the terminal and inputs the data necessary for lesson preparation and administrative work. Specifically, they input the next lesson content, "Fundamentals of Biology," related materials, "Textbook Chapter 3," and assignment content, "Self-Study Assignment." This input data is acquired through the terminal's interface. The terminal also simultaneously collects operation data such as the teacher's keystroke speed and mouse operation, and sends this data to the emotion engine. The input data is text data related to the lesson content and administrative work, while the operation data is behavioral data used to determine the teacher's emotional state.

[0620] Step 2:

[0621] The terminal uses a communication module to send input data and operation data to the server in real time. The server temporarily stores the received data and then stores it in a database. Specifically, the server receives input data and operation data in a standard format such as JSON and temporarily stores it in a buffer area. This data is then stored in a structured or relational database. The input is the data stream from the terminal, and the output is the data stored in the database.

[0622] Step 3:

[0623] The server uses AI algorithms to analyze the data stored in the database. First, it analyzes the lesson content data and extracts the information necessary to generate related materials and documents. Next, the emotion engine analyzes the operation data and determines the teacher's emotional state. For example, it can identify whether the teacher is feeling stressed based on the speed of keystrokes and frequency of mouse operations. The input is lesson content data and operation data obtained from the database, and the output is lesson information and emotional state data as the analytical results.

[0624] Step 4:

[0625] Based on the analysis results, the server uses an AI algorithm to automatically generate lesson materials and documents. For example, it uses a generative AI model such as OpenAI GPT-3 to generate relevant materials (e.g., PowerPoint templates, lecture notes, email templates). At this time, the content and amount of the materials are adjusted based on the analysis results of the emotion engine, taking into account the teacher's emotional state. The input is the analysis results and emotional state data obtained from Step 3, and the output is the generated lesson materials and documents. The generated materials are created according to a prompt. For example, a prompt might be used: "The next class is 'Fundamentals of Biology,' and the related materials are Chapter 3 of the textbook and self-study assignments. Please keep the materials concise for teachers who are feeling stressed."

[0626] Step 5:

[0627] The server sends the generated lesson materials and documents to the terminal. This transmission process uses a secure communication protocol (e.g., HTTPS). The terminal displays the received materials on the teacher's screen. The input is the generated materials sent from the server, and the output is the visual information displayed through the terminal's interface.

[0628] Step 6:

[0629] The user (teacher) checks the materials displayed on the terminal and edits or modifies them as necessary. For example, they can insert additional slides into the generated PowerPoint template to emphasize specific content. They can also customize the content of their lecture notes. The input is the generated material displayed on the terminal, and the output is the final material to which the teacher has made modifications. The results of these modifications are saved back in the database and used to prepare for future lessons.

[0630] (Application example 2)

[0631] 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."

[0632] In brick-and-mortar stores, it takes a lot of time and effort for staff to efficiently perform their daily tasks and respond to customers. Furthermore, performing tasks without considering the emotional state of staff can cause stress and fatigue, resulting in a decline in the quality of work and customer satisfaction. This invention aims to provide a system that automates and streamlines work management and customer response in brick-and-mortar stores, while also taking into account the emotional state of staff.

[0633] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes an input means through which a teacher inputs data for clerical work and lesson preparation, a server means for receiving the data and storing it in a database, a generation means for analyzing the data and generating documents and materials using an AI algorithm, a transmission means for sending the generated output to the teacher's terminal and displaying it, an input means through which staff input customer service and work content based on the input data, a generation means for generating procedure manuals and scripts based on the work content, and an emotion analysis means for analyzing the emotional state of staff and optimizing information based on this. This not only efficiently automates work and customer service in physical stores, but also enables appropriate support that takes the emotional state of staff into consideration.

[0634] A "teacher" is a person whose job is to provide education to pupils or students at an educational institution.

[0635] "Office work" is a general term for everyday work tasks such as creating documents, processing data, and organizing information necessary for general business operations.

[0636] "Class preparation" refers to a series of preparatory activities that teachers at educational institutions undertake, such as preparing teaching materials, formulating lesson plans, and creating materials, in order to teach a class.

[0637] "Data" is a collective term for information and records that are input into a system for processing.

[0638] "Input means" is a general term for interfaces and devices that allow a user to input data into the system.

[0639] "Server means" is a general term for a computer system that receives data, stores it in a database, and performs processing such as analysis.

[0640] "Generation means" is a general term for functions and devices that automatically generate documents and materials using AI algorithms based on input data.

[0641] "Transmission means" is a general term for functions and devices for transmitting the generated output to the user's terminal and displaying it.

[0642] "Customer service" refers to a series of actions and activities that store staff take to provide service in response to customer requests and inquiries and improve customer satisfaction.

[0643] "Work content" refers to the details and content of the work and tasks that staff perform on a daily basis.

[0644] "Emotion analysis means" is a general term for functions and devices that analyze the user's emotional state and generate optimized information based on the results.

[0645] A "procedure manual" is a document that contains detailed instructions and procedures for carrying out a specific task or work.

[0646] A "script" is a document that contains standard phrases and conversational guidelines used in specific tasks or customer interactions.

[0647] "Output" refers to documents and materials that are the result of a system's generation.

[0648] As an embodiment of the present invention, a system that improves the efficiency of staff work management and customer service and also takes into account the emotional state of staff is described below. This system includes a terminal for staff to input data, a server that receives, analyzes, and stores the data, a means for presenting and correcting the generated materials to staff, and an emotion analysis engine that recognizes the emotions of staff.

[0649] System Overview

[0650] 1. Data entry by staff (terminal side)

[0651] Users (staff) log in to a smartphone app and input their daily work and customer service details. The input method sends the work details and behavioral data to the emotion analysis engine. Specifically, data such as "New product A has arrived" or "Customer B has an inquiry about a product" is entered into the app.

[0652] 2. Data processing and storage (server side)

[0653] The terminal sends input data and emotional data to the server, which receives it and stores it in a database. The server then uses AI algorithms to analyze the input data and generate appropriate work procedures and customer service scripts. It also takes into account the emotional state of the staff analyzed by the emotion analysis engine.

[0654] 3. Document generation and display (server side and terminal side)

[0655] The server uses an AI algorithm to generate optimal procedures and scripts based on the input data. Furthermore, based on the analysis results of the emotion analysis engine, if a staff member is feeling stressed, the server will adjust the procedure by simplifying it or softening the tone of the script. The generated materials are sent from the server to the terminal, where they are displayed to the staff member.

[0656] 4. Checking and correcting materials (staff side)

[0657] Staff can review the submitted materials and make corrections as needed, for example by adding additional information to the generated customer response script or by amending the content.

[0658] Program processing explanation

[0659] The server runs on the Flask framework and stores data in a SQLite database. Task details and emotional data entered by users through a smartphone app are sent to the server and analyzed by an AI algorithm. The AI ​​algorithm generates optimal procedures and scripts based on a database containing past data and related information. The emotion analysis engine also analyzes the emotional state of staff and adjusts the content and format of the generated materials.

[0660] Specifically, if a staff member inputs "New product A has arrived" or "Customer B has an inquiry about a product," the server will generate the optimal receiving procedure manual and customer response script based on this data. Also, if a staff member is feeling stressed, the server will simplify the procedure or generate a script using a gentler tone.

[0661] Prompt Sentence Examples

[0662] Task: New product A has arrived, and customer B has inquired about the product.

[0663] Emotional data: tired, stressed

[0664] The above is a detailed description of the embodiment of the present invention. This system not only efficiently automates operations and customer service in brick-and-mortar stores, but also enables appropriate support that takes into account the emotional state of staff. Implementing the system in accordance with this embodiment will improve work efficiency and reduce staff stress.

[0665] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0666] Step 1:

[0667] The user logs into the smartphone app and inputs details of their daily work and customer service. For example, this data might include "New product A has arrived" or "Customer B has an inquiry about a product." The device then sends this input data and behavioral data during operation to the emotion analysis engine.

[0668] Step 2:

[0669] The device sends input data and emotion data to the server, which receives it and stores it in a database. The SQLite database ensures data persistence and efficient management.

[0670] Step 3:

[0671] The server analyzes the received data and uses an AI algorithm to generate optimal procedures and scripts based on the input work content, while referring to related past data and materials. The AI ​​model uses a pre-trained generative AI model.

[0672] Step 4:

[0673] The emotion analysis engine analyzes the emotional data sent from the device, evaluating the emotional state of the staff member and determining whether they are feeling stressed or fatigued. Emotion analysis is performed using behavioral data during operation and facial expression recognition technology.

[0674] Step 5:

[0675] The server adjusts the generated procedures and scripts based on the results of the emotion analysis engine. For example, if a staff member is feeling stressed, it will simplify the work procedures or soften the tone of the script.

[0676] Step 6:

[0677] The server sends the generated optimized procedures and scripts to the terminal, which displays them to the staff, who can then view them through the app.

[0678] Step 7:

[0679] Staff members can review the displayed procedures and scripts and make any necessary corrections. For example, they can add additional information to a customer support script or modify its content. The corrected materials are then sent back to the server and updated in the database.

[0680] 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.

[0681] 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.

[0682] 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.

[0683] [Third embodiment]

[0684] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0685] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0686] 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).

[0687] 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.

[0688] 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.

[0689] 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).

[0690] 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.

[0691] 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.

[0692] 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.

[0693] 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.

[0694] 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.

[0695] 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."

[0696] As an embodiment of the present invention, a system for automating and streamlining administrative work and lesson preparation for teachers is described below. This system includes a terminal for teachers to input data, a server that receives, analyzes, and generates data, and a means for presenting and modifying the generated materials to teachers.

[0697] System Overview

[0698] 1. Data entry by the teacher (terminal side)

[0699] The user (teacher) logs in to the terminal and inputs data related to the required lesson content and administrative work. For example, a teacher inputs related materials and assignments for the next lesson, "Fundamentals of Biology," into the terminal.

[0700] 2. Data processing and storage (server side)

[0701] The device sends the input data to a server, which receives it and stores it in a database. The server then analyzes the data and uses AI algorithms to automatically generate documents and materials.

[0702] 3. Document Generation (Server Side)

[0703] The server uses AI algorithms to generate optimal lesson materials and documents based on the input data, such as PowerPoint templates, lecture notes, and email templates for parents on "Fundamentals of Biology."

[0704] 4. Sending and displaying the results (terminal side)

[0705] The server sends the generated materials to the terminal, which displays them to the user, who can then use them to prepare for classes or perform administrative tasks.

[0706] 5. Checking and correcting materials (user side)

[0707] The user can review the submitted materials and make any necessary modifications, for example adding specific information to the generated PowerPoint template or modifying the content.

[0708] Specific examples

[0709] To enter the next week's lesson schedule, Teacher A logs in to the terminal and enters the following information: "The next lesson is 'Fundamentals of Biology', and the related materials are Chapter 3 of the textbook and the self-study assignment." The terminal then sends this data to the server.

[0710] The server receives the data and stores it in a database. AI algorithms analyze past lesson data and related materials to generate PowerPoint templates, lecture notes, and email templates for parents that are optimal for the next week's lesson.

[0711] The generated materials are sent from the server to the terminal and displayed on Teacher A's terminal. Teacher A reviews these materials and makes corrections as necessary, for example, by inserting additional slides into the PowerPoint template to emphasize specific content.

[0712] This system allows teachers to save time by manually creating materials, and to carry out lesson preparation and administrative work more efficiently. The present invention reduces the workload of teachers and provides sufficient support for them to concentrate on teaching activities.

[0713] The processing flow will be explained below.

[0714] Step 1:

[0715] Users log in to the terminal and enter the necessary data related to the course content and administrative work, such as the class schedule, student list, and past class materials.

[0716] Step 2:

[0717] The device sends the input data to the server using an encryption protocol that takes security into consideration.

[0718] Step 3:

[0719] The server receives the data sent from the terminal and stores it in a database using a database management system (DBMS).

[0720] Step 4:

[0721] The server reads the incoming data from the database and begins analyzing it, using AI algorithms to analyze the content of the input data.

[0722] Step 5:

[0723] The server generates specific documents and materials based on the analysis results, including PowerPoint templates for lessons, lecture notes, and email templates for parents.

[0724] Step 6:

[0725] The server sends the generated documents and materials to the terminal, using a real-time communication protocol to quickly deliver the data to the user.

[0726] Step 7:

[0727] The terminal displays the transmitted documents and materials to the user, who then checks the displayed materials.

[0728] Step 8:

[0729] The user can check the displayed document or material and make any necessary corrections. Once the corrections are complete, the document is saved back to the device.

[0730] This system allows teachers to prepare for classes and carry out administrative tasks quickly and efficiently. The specific processes performed at each step are explained in detail, making the operation of each step clear.

[0731] Example 1

[0732] 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."

[0733] Because administrative work and lesson preparation for teachers requires a great deal of time and effort, there is a need for greater efficiency. However, the traditional method of manually creating documents and generating materials is time-consuming and has limited effectiveness in reducing the burden on teachers. The present invention aims to solve these issues and significantly reduce the burden on teachers by automating and streamlining administrative work and lesson preparation for teachers.

[0734] 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.

[0735] In this invention, the server includes an input means for teachers to input information for administrative work and lesson preparation, a server means for receiving the information and storing it in a database, a generation means for analyzing the information and generating documents and materials using a generative AI model, a transmission means for sending the generated results to the teacher's terminal and displaying them, and a correction means for the teacher to check the results and correct them as necessary. This allows teachers to automatically generate optimal lesson materials and documents by simply inputting information, enabling them to efficiently perform administrative work and lesson preparation.

[0736] A "teacher" is a person who provides educational activities to students at an educational institution.

[0737] "Administrative work" refers to non-educational tasks performed by teachers, such as preparing for classes, managing student grades, and communicating with parents.

[0738] "Class preparation" refers to the preparatory work required to smoothly carry out educational activities, such as creating teaching materials and documents to be used in class and drawing up lesson plans.

[0739] "Input means" refers to devices and software that allow teachers to use terminals to input information related to lesson content and administrative work.

[0740] "Server means" refers to a device or software that receives input information, stores it in a database, and manages and processes it.

[0741] A "database" is a system for systematically storing received information so that it can be searched and used later.

[0742] "Generation means" refers to devices or software that automatically generate documents or materials using a generative AI model based on analyzed information.

[0743] A "generative AI model" is an artificial intelligence algorithm that performs natural language processing based on input information and generates appropriate documents and materials.

[0744] "Transmission means" refers to devices and software for transferring the generated documents and materials to the teacher's terminal and displaying them.

[0745] "Correction means" refers to devices or software that allow teachers to check the generated results and make corrections as necessary.

[0746] "Results" are documents and materials created by the generating means.

[0747] A "presentation template" is a template for slide-format materials used in classes, etc.

[0748] "Lecture notes" are materials in the form of notes that contain the content necessary for the progress of a class.

[0749] "Notification templates" are standardized email and letter templates used when contacting parents and other concerned parties.

[0750] A "terminal" is a computer or other device that allows a teacher to input information and view generated results.

[0751] "Information" refers to all data related to lesson content and administrative work entered by teachers.

[0752] This invention is a system that automates and streamlines administrative work and lesson preparation for teachers. This system includes a terminal for teachers to input information, a server that receives, analyzes, and generates information, and a means for presenting and modifying the generated results to teachers.

[0753] Users (teachers) log in to the system from terminals used at educational institutions. Using the input means of the terminal, teachers input information such as the content of the next lesson, related materials, and self-study assignments. For example, they input information such as "The next lesson is 'Fundamentals of Biology', and related materials are Chapter 3 of the textbook, and self-study assignments."

[0754] When the terminal receives the input information, it sends it to the server, which verifies the received information and stores it in a database. The server manages the information using a relational database management system (e.g., an SQL database).

[0755] The server then analyzes the stored information and generates optimal lesson materials and documents using a generative AI model (e.g., OpenAI's GPT-4). The server analyzes past lesson data and related materials and generates documents based on them. For example, it generates presentation templates, lecture notes, and parent notification templates for "Fundamentals of Biology."

[0756] The generated results are sent from the server to the terminal. The terminal displays them on the user interface. The user (teacher) can check the generated results and make corrections as necessary. Corrections are made using the terminal's editing tools, and the final material is re-saved on the server.

[0757] With this system, teachers simply input information and the system automatically generates the most suitable lesson materials and documents. In addition, the generated materials can be easily edited, allowing for efficient administrative work and lesson preparation.

[0758] Specific examples

[0759] To enter the next week's lesson schedule, Teacher A logs in to the terminal and enters the following information: "The next lesson is 'Fundamentals of Biology', and the related materials are Chapter 3 of the textbook and the self-study assignment." The terminal then sends this information to the server.

[0760] The server receives the data and stores it in a database. A generative AI model analyzes past lesson data and related materials to generate presentation templates, lecture notes, and notification templates for parents that are optimal for "Fundamentals of Biology."

[0761] The generated materials are sent from the server to the terminal and displayed on Teacher A's terminal. Teacher A reviews these materials and makes corrections as necessary, for example, by inserting additional slides into the presentation template to emphasize specific content.

[0762] Prompt Sentence Examples

[0763] Here are some examples of input prompts for a generative AI model:

[0764] "I'm teaching 'Basic Biology' for next week's class. Based on past lesson data and the content of Chapter 3 of the textbook, please generate a presentation template, lecture notes, and parent notification template."

[0765] In this way, teachers can efficiently carry out administrative tasks and prepare for lessons. This invention reduces the burden on teachers and provides practical support for providing high-quality education.

[0766] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0767] Step 1:

[0768] Logging in to a teacher's device

[0769] The user (teacher) logs in to the terminal. The teacher enters their user ID and password for authentication. The terminal sends the entered authentication information to the server, which then compares it with the user information in the database. If authentication is successful, the teacher is allowed to access the system.

[0770] Input: User ID, Password

[0771] Output: Authentication result (success / failure)

[0772] Specific behavior:

[0773] Teachers enter their ID and password into the login screen.

[0774] The terminal transmits the authentication information to the server.

[0775] The server checks the credentials against a database and returns the result.

[0776] The authentication result will be displayed on the device.

[0777] Step 2:

[0778] Data entry of lesson contents

[0779] The user (teacher) inputs information such as the content of the next class, related materials, and self-study assignments into the terminal. For example, the user might input "The next class is 'Fundamentals of Biology', related materials are Chapter 3 of the textbook, and self-study assignments." The terminal then converts this input data into a structured format (e.g., JSON).

[0780] Input: Course content, related materials, self-study assignments

[0781] Output: Structured data (JSON format)

[0782] Specific behavior:

[0783] Teachers fill out the input form with the lesson content and related materials.

[0784] The terminal converts the input data into JSON format.

[0785] Step 3:

[0786] Sending data

[0787] The device transmits the structured data to the server using a secure communication protocol (e.g., HTTPS).

[0788] Input: Structured data (JSON format)

[0789] Output: Sending to server completed

[0790] Specific behavior:

[0791] The terminal generates JSON data.

[0792] The terminal transmits the data to the server through secure communication.

[0793] The server acknowledges receipt of the data.

[0794] Step 4:

[0795] Receiving and storing data on the server side

[0796] The server receives the data sent from the terminal and verifies its contents. If the verification is successful, the server saves the data in a database, such as an SQL database.

[0797] Input: Structured data (JSON format)

[0798] Output: Saved to database

[0799] Specific behavior:

[0800] The server validates the received JSON data (schema checking and data integrity checking).

[0801] The server stores the data in a database.

[0802] The database notifies the server of the successful save.

[0803] Step 5:

[0804] Data analysis and documentation generation

[0805] The server analyzes the stored data and generates optimal lesson materials and documents using a generative AI model (such as OpenAI's GPT-4). In this process, it generates prompt sentences and inputs them into the AI ​​model.

[0806] Input: saved data, prompt

[0807] Output: Generated documents (presentation templates, lecture notes, announcement templates, etc.)

[0808] Specific behavior:

[0809] The server retrieves the relevant information from a database.

[0810] The server generates a prompt for the generative AI model.

[0811] The AI ​​model generates a document based on the prompt.

[0812] The generated document is saved in temporary storage.

[0813] Step 6:

[0814] Sending generated documents

[0815] The server sends the generated documents to the terminal, which displays these documents in its user interface.

[0816] Input: Generated document

[0817] Output: Sent to terminal

[0818] Specific behavior:

[0819] The server retrieves the generated document from temporary storage.

[0820] The server sends the document to the terminal.

[0821] The terminal displays the received document.

[0822] Step 7:

[0823] Check and correct the document

[0824] The user (teacher) checks the received document and makes any necessary corrections. The corrected document is then saved back to the server and becomes available as the final version.

[0825] Input: Generated document, corrections

[0826] Output: Final document

[0827] Specific behavior:

[0828] The teacher checks the generated document on the terminal.

[0829] The teacher will make any necessary corrections.

[0830] The terminal sends the modified document to the server.

[0831] The server stores the final document in a database.

[0832] These are the specific processing steps of the system. This flow allows teachers to efficiently generate and edit lesson materials simply by inputting information.

[0833] (Application example 1)

[0834] 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."

[0835] Traditionally, teachers' administrative work and lesson preparation requires a lot of time and effort, making it inefficient. Creating lesson materials and related documents in particular requires a great deal of time and effort, preventing teachers from concentrating on their teaching activities. Furthermore, there is a lack of convenient ways to easily check and revise lesson plans and related materials on smart devices. Therefore, a system is needed that allows teachers to perform administrative work and lesson preparation more efficiently and focus on their teaching activities.

[0836] 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.

[0837] In this invention, the server includes an input means for teachers to input data for administrative work and lesson preparation, a server means for receiving the data and storing it in a database, a generation means for analyzing the data and generating documents and materials using an AI algorithm, a transmission means for sending the generated output to the teacher's terminal and displaying it, and a means for the teacher to check and modify the generated materials using a smart device. This allows teachers to efficiently create and modify materials, significantly reducing the time spent on lesson preparation and administrative work. Furthermore, checking and modifying data on a smart device improves convenience and helps teachers focus on their teaching activities.

[0838] A "teacher" is a person who teaches classes at an educational institution and is engaged in the task of imparting knowledge and skills to students.

[0839] "Administrative work" refers to work outside of teaching, including administrative tasks, document preparation, and student evaluations at educational institutions.

[0840] "Lesson preparation" refers to the process of planning a lesson, creating necessary materials and documents, and preparing the content of the lesson in advance.

[0841] "Input means" refers to devices or interfaces that teachers use to input data, including keyboards, touchscreens, etc.

[0842] "Server means" refers to a computing system responsible for storing and analyzing received data.

[0843] "Generation means" refers to a system that automatically generates documents and materials based on input data using AI algorithms.

[0844] "Transmission means" refers to a system that has the function of transmitting the generated output to the teacher's terminal and displaying it.

[0845] "Smart device" refers to an advanced digital device that can connect to the Internet and install and run applications, including smartphones and tablets.

[0846] A "PowerPoint template" refers to a basic format for creating presentations, a file with a pre-determined slide design and layout.

[0847] "Lecture notes" refer to materials that contain the content and progress plan of a class, and are used by teachers as a guide when teaching a class.

[0848] An "email template" refers to a pre-created email template based on specific content and format, intended for efficient communication.

[0849] "Correction tools" refer to tools and interfaces that allow teachers to review the generated output and make changes or additions to content as needed.

[0850] "Output" includes results, materials, and documents generated by AI algorithms based on input data.

[0851] MODE FOR CARRYING OUT THE INVENTION

[0852] As an embodiment of the present invention, a system that enables teachers to efficiently prepare for lessons and perform administrative tasks using smart devices will be described. The system includes the following elements.

[0853] 1. Input Method

[0854] Users (teachers) log in to their smart devices (smartphones, tablets, etc.) and enter data related to class content and administrative tasks, such as the next week's class content, related materials, and self-study assignments.

[0855] 2. Server Means

[0856] The entered data is sent to a cloud server and stored in a database. The server then analyzes the stored data using AI algorithms to automatically generate lesson materials and documents (PowerPoint templates, lecture notes, email templates, etc.).

[0857] 3. Generation means

[0858] The AI ​​algorithm uses past lesson data and related materials to generate optimal lesson materials based on the input data, such as PowerPoint templates, lecture notes, and email templates for parents for the next week's lesson.

[0859] 4. Transmission Method

[0860] The generated documents are sent from the server to the user's smart device and displayed on the device, where the user can review them and make corrections as necessary.

[0861] 5. Corrective measures

[0862] Users can view the generated materials on their smart devices, add specific information, or modify the content, allowing instructors to efficiently create, review, and modify course materials and documents.

[0863] Specific examples

[0864] To prepare for next week's class, "Basic Chemistry," Teacher B logs into his smart device and enters the following lesson content: "Next class will be 'Basic Chemistry,' with related materials from Chapter 4 of the textbook and self-study assignments." This data is sent to a server and stored in a database. On the server, an AI algorithm analyzes past lesson data and related materials to generate PowerPoint templates, lecture notes, and even email templates for parents that are optimal for next week's class.

[0865] The generated materials are sent from the cloud server to Teacher B's smart device and displayed on the device. Teacher B reviews these materials and, if necessary, adds additional information to specific slides or modifies the content to emphasize key points.

[0866] Prompt Sentence Examples

[0867] "The next class is on basic chemistry, and the related materials are Chapter 4 of the textbook and a self-study assignment. Generate the best PowerPoint templates, lecture notes, and email templates for parents."

[0868] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0869] Step 1:

[0870] User login and data entry

[0871] The user (teacher) logs in to the smart device and inputs the content of the next lesson and related materials. The input fields include the lesson title, textbook chapter, self-study assignment, etc. This information is collected through the user interface of the smart device and sent to the server as JSON format data. An example of input data is "The next lesson is 'Basic Chemistry', related materials are textbook chapter 4, and self-study assignment." As output, the input data is sent to the server.

[0872] Step 2:

[0873] Data reception and storage by the server

[0874] The server receives data sent from the smart device. The received data includes information such as lesson content, textbook chapters, and self-study assignments. This data is then temporarily stored in the server's database. The input is the received JSON data, and the output is the stored database entries.

[0875] Step 3:

[0876] Data analysis and generation using AI algorithms

[0877] The server inputs the saved data into an AI algorithm for analysis. The AI ​​algorithm references past lesson data and related materials to generate documents (PowerPoint templates, lecture notes, email templates, etc.) that are most suitable for the next lesson. This generation process collects highly relevant information and places it appropriately in each document. The inputs are saved data and past lesson data, and the output is the generated document.

[0878] Step 4:

[0879] Sending and viewing generated materials

[0880] The server sends the generated lesson materials to the user's smart device. The data is sent in the form of PowerPoint templates, lecture notes, email templates, etc. The user's smart device receives and displays these materials. The input is the generated document, and the output is the display screen of the smart device.

[0881] Step 5:

[0882] Review and correct the materials

[0883] The user (teacher) reviews the generated materials on the smart device and makes corrections as necessary, adding additional slides, highlighting content, and making corrections through the smart device interface. The input is the user's feedback and corrections, and the output is the final revised document.

[0884] Step 6:

[0885] Save and share the final document

[0886] Once the corrections are complete, the document is sent back to the server and saved as the final version in the database. If necessary, the document can be shared with other faculty members or other stakeholders. The input is the corrected document, and the output is the saved document and a shared link.

[0887] Example prompt: "The next lesson will be on Basic Chemistry, and related materials will be Chapter 4 of the textbook, as well as a self-study assignment. Please generate the appropriate PowerPoint template, lecture notes, and email template for parents."

[0888] 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.

[0889] As an embodiment of the present invention, a system for automating and streamlining a teacher's administrative work and lesson preparation, and taking into account the teacher's emotional state, is described below. This system includes a terminal for the teacher to input data, a server for receiving, analyzing, and generating data, a means for presenting and correcting the generated materials to the teacher, and an emotion engine for recognizing the teacher's emotions.

[0890] System Overview

[0891] 1. Data entry by the teacher (terminal side)

[0892] The user (teacher) logs in to the device and inputs data related to the required lesson content and administrative work. For example, a teacher inputs related materials and assignments for the next lesson, "Fundamentals of Biology," into the device. The device also sends the teacher's input data and behavioral data during operation to the emotion engine.

[0893] 2. Data processing and storage (server side)

[0894] The device sends input data and emotional data to the server, which receives it and stores it in a database. The server analyzes the received data and uses AI algorithms to automatically generate documents and materials. It also takes into account the emotional state of the teacher, as analyzed by the emotion engine.

[0895] 3. Document Generation (Server Side)

[0896] The server uses AI algorithms to generate optimal lesson materials and documents based on the input data. It also adjusts the content and format of the materials based on the teacher's emotional state based on the analysis results of the emotion engine. For example, if a teacher is feeling stressed, the server will reduce the amount of material provided and soften their tone.

[0897] 4. Sending and displaying the results (terminal side)

[0898] The server sends the generated materials to the terminal, which displays them to the user, who can then use them to prepare for classes or perform administrative tasks.

[0899] 5. Checking and correcting materials (user side)

[0900] The user can review the submitted materials and make any necessary modifications, for example adding specific information to the generated PowerPoint template or modifying the content.

[0901] Specific examples

[0902] Teacher A logs in to the device to enter the next week's lesson schedule and enters the following: "The next lesson is 'Fundamentals of Biology', and the related materials are Chapter 3 of the textbook and the self-study assignment." The device sends this data, along with the teacher's input operation data, to the emotion engine.

[0903] The server receives the data and stores it in a database. An AI algorithm analyzes past lesson data and related materials to generate PowerPoint templates and lecture notes optimal for the next week's lesson, as well as email templates for parents. At the same time, an emotion engine analyzes Teacher A's emotional state and, if it determines that he is feeling stressed, makes adjustments such as reducing the amount of material or simplifying the content.

[0904] The generated materials are sent from the server to the terminal and displayed on Teacher A's terminal. Teacher A reviews these materials and makes corrections as necessary, for example, by inserting additional slides into the PowerPoint template to emphasize specific content.

[0905] This system allows teachers to save time by manually creating materials, enabling them to prepare lessons and perform administrative tasks more efficiently. Furthermore, the introduction of an emotion engine provides a system that takes into account the teacher's emotional state, improving the user experience. This invention reduces the workload of teachers and provides sufficient support for them to focus on their teaching activities.

[0906] The processing flow will be explained below.

[0907] Step 1:

[0908] Users log in to the terminal and enter data related to the required lesson content and administrative tasks. For example, a teacher may enter "Fundamentals of Biology" as the lesson content for next week, and enter related materials and assignments. At the same time, the terminal collects operation data such as the teacher's keystroke time and click frequency.

[0909] Step 2:

[0910] The terminal sends input data and operation data to the server using an encryption protocol that takes security into consideration.

[0911] Step 3:

[0912] The server receives the data sent from the device and stores it in a database. The stored data includes lesson content, related materials, assignments, and teacher operation data.

[0913] Step 4:

[0914] The server reads the incoming data from the database and begins analyzing it, using AI algorithms to analyze the content of the input data.

[0915] Step 5:

[0916] The server uses an emotion engine to analyze the teacher's operation data and estimate the teacher's emotional state. Specifically, it determines whether the teacher is feeling stressed based on data such as keystroke speed and click intervals.

[0917] Step 6:

[0918] Based on the analysis results, the server uses AI algorithms to generate optimal documents and materials. These include PowerPoint templates for lessons, lecture notes, and email templates for parents. Based on the analysis results of the emotion engine, if a teacher is feeling stressed, the server will adjust the amount of materials provided, such as reducing the content or making it more concise.

[0919] Step 7:

[0920] The server sends the generated documents and materials to the terminal, using a real-time communication protocol to quickly deliver the data to the user.

[0921] Step 8:

[0922] The terminal displays the sent documents and materials to the user, who can then use them to prepare for classes or perform administrative tasks.

[0923] Step 9:

[0924] The user can review the displayed document or material and make any necessary edits. The edited document is then saved back to the device. For example, the user can add specific information to the generated PowerPoint template to highlight the content.

[0925] This system will enable teachers to save time by manually creating materials, allowing them to prepare lessons and perform administrative tasks more efficiently. It will also improve the user experience by taking into account the emotional state of teachers, providing a less stressful work environment.

[0926] Example 2

[0927] 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."

[0928] Traditionally, administrative work and lesson preparation required a lot of time and effort, reducing productivity. These tasks can also affect teachers' emotional state and increase stress. This can reduce the time teachers have to concentrate on teaching activities, potentially resulting in a decline in the quality of education. Given this background, there was a need for a system that could streamline teachers' work and also take into account their emotional state.

[0929] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes an input means through which a teacher inputs data for administrative work and lesson preparation, a server means for receiving the data and storing it in a database, a generation means for analyzing the data and generating documents and materials using an AI algorithm, a transmission means for transmitting the generated output to the teacher's terminal and displaying it, an emotion recognition means for recognizing the teacher's emotional state based on the data, and an adjustment means for adjusting the document content based on the analysis results of the emotion recognition means. This automates the teacher's work and makes it possible to provide materials customized according to the teacher's emotional state. This reduces the teacher's workload and provides sufficient support for them to concentrate on their teaching activities.

[0930] "Input means" refers to the means by which teachers input data necessary for administrative work and lesson preparation into the system.

[0931] "Server means" refers to means having a server function for receiving data entered by a teacher and storing it in a database.

[0932] "Generation means" refers to the means for analyzing received data and generating documents or materials using AI algorithms.

[0933] The "transmission means" is a means for transmitting the generated output to the teacher's terminal and displaying it.

[0934] The "emotion recognition means" is a means for recognizing the emotional state of the teacher based on the input data and operation data.

[0935] The "adjustment means" is a means for adjusting the document contents based on the analysis results of the emotion recognition means.

[0936] "Documents" refers to all documents used by teachers, including course materials.

[0937] "Materials" refers to various documents used by faculty for classes and administrative work, including PowerPoint templates, lecture notes, and email templates.

[0938] "Teacher" refers to anyone engaged in educational activities.

[0939] This invention relates to a system that automates and streamlines the administrative work and lesson preparation of teachers and takes into account the emotional state of the teacher. This system includes a terminal for teachers to input data, a server that receives, analyzes, and generates data, a means for presenting and correcting the generated materials to the teacher, and an emotion engine that recognizes the teacher's emotions.

[0940] Teachers log in to the terminal and input data related to the next class content and administrative work. For example, a teacher can input related materials and assignments for next week's class content, "Fundamentals of Biology," into the terminal. At this time, the teacher's input data and behavioral data during operation are sent to the emotion engine.

[0941] The device sends input data and emotional data to a server, which receives the data and stores it in a database. The server then analyzes the data and uses an AI algorithm to automatically generate documents and materials. One example of the algorithm used is OpenAI's GPT-3. The emotional state of the teacher, as analyzed by the emotion engine, is also taken into account.

[0942] The server uses an AI algorithm to generate optimal lesson materials and documents based on the input data. For example, if a teacher is feeling stressed, the server will adjust the amount of material provided, soften the tone, and make other adjustments. An example of a specific prompt could be, "The next class will be on 'Fundamentals of Biology,' and the related materials will be Chapter 3 of the textbook and self-study assignments. Please simplify the materials for teachers who are feeling stressed."

[0943] The generated materials are sent from the server to the terminal and displayed on the teacher's terminal. Teachers can use these materials to efficiently prepare for classes and perform administrative tasks. Teachers can also review the sent materials and make corrections as necessary. For example, they can add specific information to the generated PowerPoint template or modify the content.

[0944] This system reduces the workload of teachers and provides sufficient support for them to concentrate on teaching activities. In addition, by using an emotion engine, services are provided that take into account the emotional state of teachers, improving the user experience.

[0945] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0946] Step 1:

[0947] The user (teacher) logs into the terminal and inputs the data necessary for lesson preparation and administrative work. Specifically, they input the next lesson content, "Fundamentals of Biology," related materials, "Textbook Chapter 3," and assignment content, "Self-Study Assignment." This input data is acquired through the terminal's interface. The terminal also simultaneously collects operation data such as the teacher's keystroke speed and mouse operation, and sends this data to the emotion engine. The input data is text data related to the lesson content and administrative work, while the operation data is behavioral data used to determine the teacher's emotional state.

[0948] Step 2:

[0949] The terminal uses a communication module to send input data and operation data to the server in real time. The server temporarily stores the received data and then stores it in a database. Specifically, the server receives input data and operation data in a standard format such as JSON and temporarily stores it in a buffer area. This data is then stored in a structured or relational database. The input is the data stream from the terminal, and the output is the data stored in the database.

[0950] Step 3:

[0951] The server uses AI algorithms to analyze the data stored in the database. First, it analyzes the lesson content data and extracts the information necessary to generate related materials and documents. Next, the emotion engine analyzes the operation data and determines the teacher's emotional state. For example, it can identify whether the teacher is feeling stressed based on the speed of keystrokes and frequency of mouse operations. The input is lesson content data and operation data obtained from the database, and the output is lesson information and emotional state data as the analytical results.

[0952] Step 4:

[0953] Based on the analysis results, the server uses an AI algorithm to automatically generate lesson materials and documents. For example, it uses a generative AI model such as OpenAI GPT-3 to generate relevant materials (e.g., PowerPoint templates, lecture notes, email templates). At this time, the content and amount of the materials are adjusted based on the analysis results of the emotion engine, taking into account the teacher's emotional state. The input is the analysis results and emotional state data obtained from Step 3, and the output is the generated lesson materials and documents. The generated materials are created according to a prompt. For example, a prompt might be used: "The next class is 'Fundamentals of Biology,' and the related materials are Chapter 3 of the textbook and self-study assignments. Please keep the materials concise for teachers who are feeling stressed."

[0954] Step 5:

[0955] The server sends the generated lesson materials and documents to the terminal. This transmission process uses a secure communication protocol (e.g., HTTPS). The terminal displays the received materials on the teacher's screen. The input is the generated materials sent from the server, and the output is the visual information displayed through the terminal's interface.

[0956] Step 6:

[0957] The user (teacher) checks the materials displayed on the terminal and edits or modifies them as necessary. For example, they can insert additional slides into the generated PowerPoint template to emphasize specific content. They can also customize the content of their lecture notes. The input is the generated material displayed on the terminal, and the output is the final material to which the teacher has made modifications. The results of these modifications are saved back in the database and used to prepare for future lessons.

[0958] (Application example 2)

[0959] 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."

[0960] In brick-and-mortar stores, it takes a lot of time and effort for staff to efficiently perform their daily tasks and respond to customers. Furthermore, performing tasks without considering the emotional state of staff can cause stress and fatigue, resulting in a decline in the quality of work and customer satisfaction. This invention aims to provide a system that automates and streamlines work management and customer response in brick-and-mortar stores, while also taking into account the emotional state of staff.

[0961] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes an input means through which a teacher inputs data for clerical work and lesson preparation, a server means for receiving the data and storing it in a database, a generation means for analyzing the data and generating documents and materials using an AI algorithm, a transmission means for sending the generated output to the teacher's terminal and displaying it, an input means through which staff input customer service and work content based on the input data, a generation means for generating procedure manuals and scripts based on the work content, and an emotion analysis means for analyzing the emotional state of staff and optimizing information based on this. This not only efficiently automates work and customer service in physical stores, but also enables appropriate support that takes the emotional state of staff into consideration.

[0962] A "teacher" is a person whose job is to provide education to pupils or students at an educational institution.

[0963] "Office work" is a general term for everyday work tasks such as creating documents, processing data, and organizing information necessary for general business operations.

[0964] "Class preparation" refers to a series of preparatory activities that teachers at educational institutions undertake, such as preparing teaching materials, formulating lesson plans, and creating materials, in order to teach a class.

[0965] "Data" is a collective term for information and records that are input into a system for processing.

[0966] "Input means" is a general term for interfaces and devices that allow a user to input data into the system.

[0967] "Server means" is a general term for a computer system that receives data, stores it in a database, and performs processing such as analysis.

[0968] "Generation means" is a general term for functions and devices that automatically generate documents and materials using AI algorithms based on input data.

[0969] "Transmission means" is a general term for functions and devices for transmitting the generated output to the user's terminal and displaying it.

[0970] "Customer service" refers to a series of actions and activities that store staff take to provide service in response to customer requests and inquiries and improve customer satisfaction.

[0971] "Work content" refers to the details and content of the work and tasks that staff perform on a daily basis.

[0972] "Emotion analysis means" is a general term for functions and devices that analyze the user's emotional state and generate optimized information based on the results.

[0973] A "procedure manual" is a document that contains detailed instructions and procedures for carrying out a specific task or work.

[0974] A "script" is a document that contains standard phrases and conversational guidelines used in specific tasks or customer interactions.

[0975] "Output" refers to documents and materials that are the result of a system's generation.

[0976] As an embodiment of the present invention, a system that improves the efficiency of staff work management and customer service and also takes into account the emotional state of staff is described below. This system includes a terminal for staff to input data, a server that receives, analyzes, and stores the data, a means for presenting and correcting the generated materials to staff, and an emotion analysis engine that recognizes the emotions of staff.

[0977] System Overview

[0978] 1. Data entry by staff (terminal side)

[0979] Users (staff) log in to a smartphone app and input their daily work and customer service details. The input method sends the work details and behavioral data to the emotion analysis engine. Specifically, data such as "New product A has arrived" or "Customer B has an inquiry about a product" is entered into the app.

[0980] 2. Data processing and storage (server side)

[0981] The terminal sends input data and emotional data to the server, which receives it and stores it in a database. The server then uses AI algorithms to analyze the input data and generate appropriate work procedures and customer service scripts. It also takes into account the emotional state of the staff analyzed by the emotion analysis engine.

[0982] 3. Document generation and display (server side and terminal side)

[0983] The server uses an AI algorithm to generate optimal procedures and scripts based on the input data. Furthermore, based on the analysis results of the emotion analysis engine, if a staff member is feeling stressed, the server will adjust the procedure by simplifying it or softening the tone of the script. The generated materials are sent from the server to the terminal, where they are displayed to the staff member.

[0984] 4. Checking and correcting materials (staff side)

[0985] Staff can review the submitted materials and make corrections as needed, for example by adding additional information to the generated customer response script or by amending the content.

[0986] Program processing explanation

[0987] The server runs on the Flask framework and stores data in a SQLite database. Task details and emotional data entered by users through a smartphone app are sent to the server and analyzed by an AI algorithm. The AI ​​algorithm generates optimal procedures and scripts based on a database containing past data and related information. The emotion analysis engine also analyzes the emotional state of staff and adjusts the content and format of the generated materials.

[0988] Specifically, if a staff member inputs "New product A has arrived" or "Customer B has an inquiry about a product," the server will generate the optimal receiving procedure manual and customer response script based on this data. Also, if a staff member is feeling stressed, the server will simplify the procedure or generate a script using a gentler tone.

[0989] Prompt Sentence Examples

[0990] Task: New product A has arrived, and customer B has inquired about the product.

[0991] Emotional data: tired, stressed

[0992] The above is a detailed description of the embodiment of the present invention. This system not only efficiently automates operations and customer service in brick-and-mortar stores, but also enables appropriate support that takes into account the emotional state of staff. Implementing the system in accordance with this embodiment will improve work efficiency and reduce staff stress.

[0993] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0994] Step 1:

[0995] The user logs into the smartphone app and inputs details of their daily work and customer service. For example, this data might include "New product A has arrived" or "Customer B has an inquiry about a product." The device then sends this input data and behavioral data during operation to the emotion analysis engine.

[0996] Step 2:

[0997] The device sends input data and emotion data to the server, which receives it and stores it in a database. The SQLite database ensures data persistence and efficient management.

[0998] Step 3:

[0999] The server analyzes the received data and uses an AI algorithm to generate optimal procedures and scripts based on the input work content, while referring to related past data and materials. The AI ​​model uses a pre-trained generative AI model.

[1000] Step 4:

[1001] The emotion analysis engine analyzes the emotional data sent from the device, evaluating the emotional state of the staff member and determining whether they are feeling stressed or fatigued. Emotion analysis is performed using behavioral data during operation and facial expression recognition technology.

[1002] Step 5:

[1003] The server adjusts the generated procedures and scripts based on the results of the emotion analysis engine. For example, if a staff member is feeling stressed, it will simplify the work procedures or soften the tone of the script.

[1004] Step 6:

[1005] The server sends the generated optimized procedures and scripts to the terminal, which displays them to the staff, who can then view them through the app.

[1006] Step 7:

[1007] Staff members can review the displayed procedures and scripts and make any necessary corrections. For example, they can add additional information to a customer support script or modify its content. The corrected materials are then sent back to the server and updated in the database.

[1008] 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.

[1009] 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.

[1010] 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.

[1011] [Fourth embodiment]

[1012] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1013] 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.

[1014] 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).

[1015] 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.

[1016] 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.

[1017] 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).

[1018] 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.

[1019] 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.

[1020] 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.

[1021] 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.

[1022] 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.

[1023] 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.

[1024] 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."

[1025] As an embodiment of the present invention, a system for automating and streamlining administrative work and lesson preparation for teachers is described below. This system includes a terminal for teachers to input data, a server that receives, analyzes, and generates data, and a means for presenting and modifying the generated materials to teachers.

[1026] System Overview

[1027] 1. Data entry by the teacher (terminal side)

[1028] The user (teacher) logs in to the terminal and inputs data related to the required lesson content and administrative work. For example, a teacher inputs related materials and assignments for the next lesson, "Fundamentals of Biology," into the terminal.

[1029] 2. Data processing and storage (server side)

[1030] The device sends the input data to a server, which receives it and stores it in a database. The server then analyzes the data and uses AI algorithms to automatically generate documents and materials.

[1031] 3. Document Generation (Server Side)

[1032] The server uses AI algorithms to generate optimal lesson materials and documents based on the input data, such as PowerPoint templates, lecture notes, and email templates for parents on "Fundamentals of Biology."

[1033] 4. Sending and displaying the results (terminal side)

[1034] The server sends the generated materials to the terminal, which displays them to the user, who can then use them to prepare for classes or perform administrative tasks.

[1035] 5. Checking and correcting materials (user side)

[1036] The user can review the submitted materials and make any necessary modifications, for example adding specific information to the generated PowerPoint template or modifying the content.

[1037] Specific examples

[1038] To enter the next week's lesson schedule, Teacher A logs in to the terminal and enters the following information: "The next lesson is 'Fundamentals of Biology', and the related materials are Chapter 3 of the textbook and the self-study assignment." The terminal then sends this data to the server.

[1039] The server receives the data and stores it in a database. AI algorithms analyze past lesson data and related materials to generate PowerPoint templates, lecture notes, and email templates for parents that are optimal for the next week's lesson.

[1040] The generated materials are sent from the server to the terminal and displayed on Teacher A's terminal. Teacher A reviews these materials and makes corrections as necessary, for example, by inserting additional slides into the PowerPoint template to emphasize specific content.

[1041] This system allows teachers to save time by manually creating materials, and to carry out lesson preparation and administrative work more efficiently. The present invention reduces the workload of teachers and provides sufficient support for them to concentrate on teaching activities.

[1042] The processing flow will be explained below.

[1043] Step 1:

[1044] Users log in to the terminal and enter the necessary data related to the course content and administrative work, such as the class schedule, student list, and past class materials.

[1045] Step 2:

[1046] The device sends the input data to the server using an encryption protocol that takes security into consideration.

[1047] Step 3:

[1048] The server receives the data sent from the terminal and stores it in a database using a database management system (DBMS).

[1049] Step 4:

[1050] The server reads the incoming data from the database and begins analyzing it, using AI algorithms to analyze the content of the input data.

[1051] Step 5:

[1052] The server generates specific documents and materials based on the analysis results, including PowerPoint templates for lessons, lecture notes, and email templates for parents.

[1053] Step 6:

[1054] The server sends the generated documents and materials to the terminal, using a real-time communication protocol to quickly deliver the data to the user.

[1055] Step 7:

[1056] The terminal displays the transmitted documents and materials to the user, who then checks the displayed materials.

[1057] Step 8:

[1058] The user can check the displayed document or material and make any necessary corrections. Once the corrections are complete, the document is saved back to the device.

[1059] This system allows teachers to prepare for classes and carry out administrative tasks quickly and efficiently. The specific processes performed at each step are explained in detail, making the operation of each step clear.

[1060] Example 1

[1061] 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."

[1062] Because administrative work and lesson preparation for teachers requires a great deal of time and effort, there is a need for greater efficiency. However, the traditional method of manually creating documents and generating materials is time-consuming and has limited effectiveness in reducing the burden on teachers. The present invention aims to solve these issues and significantly reduce the burden on teachers by automating and streamlining administrative work and lesson preparation for teachers.

[1063] 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.

[1064] In this invention, the server includes an input means for teachers to input information for administrative work and lesson preparation, a server means for receiving the information and storing it in a database, a generation means for analyzing the information and generating documents and materials using a generative AI model, a transmission means for sending the generated results to the teacher's terminal and displaying them, and a correction means for the teacher to check the results and correct them as necessary. This allows teachers to automatically generate optimal lesson materials and documents by simply inputting information, enabling them to efficiently perform administrative work and lesson preparation.

[1065] A "teacher" is a person who provides educational activities to students at an educational institution.

[1066] "Administrative work" refers to non-educational tasks performed by teachers, such as preparing for classes, managing student grades, and communicating with parents.

[1067] "Class preparation" refers to the preparatory work required to smoothly carry out educational activities, such as creating teaching materials and documents to be used in class and drawing up lesson plans.

[1068] "Input means" refers to devices and software that allow teachers to use terminals to input information related to lesson content and administrative work.

[1069] "Server means" refers to a device or software that receives input information, stores it in a database, and manages and processes it.

[1070] A "database" is a system for systematically storing received information so that it can be searched and used later.

[1071] "Generation means" refers to devices or software that automatically generate documents or materials using a generative AI model based on analyzed information.

[1072] A "generative AI model" is an artificial intelligence algorithm that performs natural language processing based on input information and generates appropriate documents and materials.

[1073] "Transmission means" refers to devices and software for transferring the generated documents and materials to the teacher's terminal and displaying them.

[1074] "Correction means" refers to devices or software that allow teachers to check the generated results and make corrections as necessary.

[1075] "Results" are documents and materials created by the generating means.

[1076] A "presentation template" is a template for slide-format materials used in classes, etc.

[1077] "Lecture notes" are materials in the form of notes that contain the content necessary for the progress of a class.

[1078] "Notification templates" are standardized email and letter templates used when contacting parents and other concerned parties.

[1079] A "terminal" is a computer or other device that allows a teacher to input information and view generated results.

[1080] "Information" refers to all data related to lesson content and administrative work entered by teachers.

[1081] This invention is a system that automates and streamlines administrative work and lesson preparation for teachers. This system includes a terminal for teachers to input information, a server that receives, analyzes, and generates information, and a means for presenting and modifying the generated results to teachers.

[1082] Users (teachers) log in to the system from terminals used at educational institutions. Using the input means of the terminal, teachers input information such as the content of the next lesson, related materials, and self-study assignments. For example, they input information such as "The next lesson is 'Fundamentals of Biology', and related materials are Chapter 3 of the textbook, and self-study assignments."

[1083] When the terminal receives the input information, it sends it to the server, which verifies the received information and stores it in a database. The server manages the information using a relational database management system (e.g., an SQL database).

[1084] The server then analyzes the stored information and generates optimal lesson materials and documents using a generative AI model (e.g., OpenAI's GPT-4). The server analyzes past lesson data and related materials and generates documents based on them. For example, it generates presentation templates, lecture notes, and parent notification templates for "Fundamentals of Biology."

[1085] The generated results are sent from the server to the terminal. The terminal displays them on the user interface. The user (teacher) can check the generated results and make corrections as necessary. Corrections are made using the terminal's editing tools, and the final material is re-saved on the server.

[1086] With this system, teachers simply input information and the system automatically generates the most suitable lesson materials and documents. In addition, the generated materials can be easily edited, allowing for efficient administrative work and lesson preparation.

[1087] Specific examples

[1088] To enter the next week's lesson schedule, Teacher A logs in to the terminal and enters the following information: "The next lesson is 'Fundamentals of Biology', and the related materials are Chapter 3 of the textbook and the self-study assignment." The terminal then sends this information to the server.

[1089] The server receives the data and stores it in a database. A generative AI model analyzes past lesson data and related materials to generate presentation templates, lecture notes, and notification templates for parents that are optimal for "Fundamentals of Biology."

[1090] The generated materials are sent from the server to the terminal and displayed on Teacher A's terminal. Teacher A reviews these materials and makes corrections as necessary, for example, by inserting additional slides into the presentation template to emphasize specific content.

[1091] Prompt Sentence Examples

[1092] Here are some examples of input prompts for a generative AI model:

[1093] "I'm teaching 'Basic Biology' for next week's class. Based on past lesson data and the content of Chapter 3 of the textbook, please generate a presentation template, lecture notes, and parent notification template."

[1094] In this way, teachers can efficiently carry out administrative tasks and prepare for lessons. This invention reduces the burden on teachers and provides practical support for providing high-quality education.

[1095] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1096] Step 1:

[1097] Logging in to a teacher's device

[1098] The user (teacher) logs in to the terminal. The teacher enters their user ID and password for authentication. The terminal sends the entered authentication information to the server, which then compares it with the user information in the database. If authentication is successful, the teacher is allowed to access the system.

[1099] Input: User ID, Password

[1100] Output: Authentication result (success / failure)

[1101] Specific behavior:

[1102] Teachers enter their ID and password into the login screen.

[1103] The terminal transmits the authentication information to the server.

[1104] The server checks the credentials against a database and returns the result.

[1105] The authentication result will be displayed on the device.

[1106] Step 2:

[1107] Data entry of lesson contents

[1108] The user (teacher) inputs information such as the content of the next class, related materials, and self-study assignments into the terminal. For example, the user might input "The next class is 'Fundamentals of Biology', related materials are Chapter 3 of the textbook, and self-study assignments." The terminal then converts this input data into a structured format (e.g., JSON).

[1109] Input: Course content, related materials, self-study assignments

[1110] Output: Structured data (JSON format)

[1111] Specific behavior:

[1112] Teachers fill out the input form with the lesson content and related materials.

[1113] The terminal converts the input data into JSON format.

[1114] Step 3:

[1115] Sending data

[1116] The device transmits the structured data to the server using a secure communication protocol (e.g., HTTPS).

[1117] Input: Structured data (JSON format)

[1118] Output: Sending to server completed

[1119] Specific behavior:

[1120] The terminal generates JSON data.

[1121] The terminal transmits the data to the server through secure communication.

[1122] The server acknowledges receipt of the data.

[1123] Step 4:

[1124] Receiving and storing data on the server side

[1125] The server receives the data sent from the terminal and verifies its contents. If the verification is successful, the server saves the data in a database, such as an SQL database.

[1126] Input: Structured data (JSON format)

[1127] Output: Saved to database

[1128] Specific behavior:

[1129] The server validates the received JSON data (schema checking and data integrity checking).

[1130] The server stores the data in a database.

[1131] The database notifies the server of the successful save.

[1132] Step 5:

[1133] Data analysis and documentation generation

[1134] The server analyzes the stored data and generates optimal lesson materials and documents using a generative AI model (such as OpenAI's GPT-4). In this process, it generates prompt sentences and inputs them into the AI ​​model.

[1135] Input: saved data, prompt

[1136] Output: Generated documents (presentation templates, lecture notes, announcement templates, etc.)

[1137] Specific behavior:

[1138] The server retrieves the relevant information from a database.

[1139] The server generates a prompt for the generative AI model.

[1140] The AI ​​model generates a document based on the prompt.

[1141] The generated document is saved in temporary storage.

[1142] Step 6:

[1143] Sending generated documents

[1144] The server sends the generated documents to the terminal, which displays these documents in its user interface.

[1145] Input: Generated document

[1146] Output: Sent to terminal

[1147] Specific behavior:

[1148] The server retrieves the generated document from temporary storage.

[1149] The server sends the document to the terminal.

[1150] The terminal displays the received document.

[1151] Step 7:

[1152] Check and correct the document

[1153] The user (teacher) checks the received document and makes any necessary corrections. The corrected document is then saved back to the server and becomes available as the final version.

[1154] Input: Generated document, corrections

[1155] Output: Final document

[1156] Specific behavior:

[1157] The teacher checks the generated document on the terminal.

[1158] The teacher will make any necessary corrections.

[1159] The terminal sends the modified document to the server.

[1160] The server stores the final document in a database.

[1161] These are the specific processing steps of the system. This flow allows teachers to efficiently generate and edit lesson materials simply by inputting information.

[1162] (Application example 1)

[1163] 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."

[1164] Traditionally, teachers' administrative work and lesson preparation requires a lot of time and effort, making it inefficient. Creating lesson materials and related documents in particular requires a great deal of time and effort, preventing teachers from concentrating on their teaching activities. Furthermore, there is a lack of convenient ways to easily check and revise lesson plans and related materials on smart devices. Therefore, a system is needed that allows teachers to perform administrative work and lesson preparation more efficiently and focus on their teaching activities.

[1165] 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.

[1166] In this invention, the server includes an input means for teachers to input data for administrative work and lesson preparation, a server means for receiving the data and storing it in a database, a generation means for analyzing the data and generating documents and materials using an AI algorithm, a transmission means for sending the generated output to the teacher's terminal and displaying it, and a means for the teacher to check and modify the generated materials using a smart device. This allows teachers to efficiently create and modify materials, significantly reducing the time spent on lesson preparation and administrative work. Furthermore, checking and modifying data on a smart device improves convenience and helps teachers focus on their teaching activities.

[1167] A "teacher" is a person who teaches classes at an educational institution and is engaged in the task of imparting knowledge and skills to students.

[1168] "Administrative work" refers to work outside of teaching, including administrative tasks, document preparation, and student evaluations at educational institutions.

[1169] "Lesson preparation" refers to the process of planning a lesson, creating necessary materials and documents, and preparing the content of the lesson in advance.

[1170] "Input means" refers to devices or interfaces that teachers use to input data, including keyboards, touchscreens, etc.

[1171] "Server means" refers to a computing system responsible for storing and analyzing received data.

[1172] "Generation means" refers to a system that automatically generates documents and materials based on input data using AI algorithms.

[1173] "Transmission means" refers to a system that has the function of transmitting the generated output to the teacher's terminal and displaying it.

[1174] "Smart device" refers to an advanced digital device that can connect to the Internet and install and run applications, including smartphones and tablets.

[1175] A "PowerPoint template" refers to a basic format for creating presentations, a file with a pre-determined slide design and layout.

[1176] "Lecture notes" refer to materials that contain the content and progress plan of a class, and are used by teachers as a guide when teaching a class.

[1177] An "email template" refers to a pre-created email template based on specific content and format, intended for efficient communication.

[1178] "Correction tools" refer to tools and interfaces that allow teachers to review the generated output and make changes or additions to content as needed.

[1179] "Output" includes results, materials, and documents generated by AI algorithms based on input data.

[1180] MODE FOR CARRYING OUT THE INVENTION

[1181] As an embodiment of the present invention, a system that enables teachers to efficiently prepare for lessons and perform administrative tasks using smart devices will be described. The system includes the following elements.

[1182] 1. Input Method

[1183] Users (teachers) log in to their smart devices (smartphones, tablets, etc.) and enter data related to class content and administrative tasks, such as the next week's class content, related materials, and self-study assignments.

[1184] 2. Server Means

[1185] The entered data is sent to a cloud server and stored in a database. The server then analyzes the stored data using AI algorithms to automatically generate lesson materials and documents (PowerPoint templates, lecture notes, email templates, etc.).

[1186] 3. Generation means

[1187] The AI ​​algorithm uses past lesson data and related materials to generate optimal lesson materials based on the input data, such as PowerPoint templates, lecture notes, and email templates for parents for the next week's lesson.

[1188] 4. Transmission Method

[1189] The generated documents are sent from the server to the user's smart device and displayed on the device, where the user can review them and make corrections as necessary.

[1190] 5. Corrective measures

[1191] Users can view the generated materials on their smart devices, add specific information, or modify the content, allowing instructors to efficiently create, review, and modify course materials and documents.

[1192] Specific examples

[1193] To prepare for next week's class, "Basic Chemistry," Teacher B logs into his smart device and enters the following lesson content: "Next class will be 'Basic Chemistry,' with related materials from Chapter 4 of the textbook and self-study assignments." This data is sent to a server and stored in a database. On the server, an AI algorithm analyzes past lesson data and related materials to generate PowerPoint templates, lecture notes, and even email templates for parents that are optimal for next week's class.

[1194] The generated materials are sent from the cloud server to Teacher B's smart device and displayed on the device. Teacher B reviews these materials and, if necessary, adds additional information to specific slides or modifies the content to emphasize key points.

[1195] Prompt Sentence Examples

[1196] "The next class is on basic chemistry, and the related materials are Chapter 4 of the textbook and a self-study assignment. Generate the best PowerPoint templates, lecture notes, and email templates for parents."

[1197] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1198] Step 1:

[1199] User login and data entry

[1200] The user (teacher) logs in to the smart device and inputs the content of the next lesson and related materials. The input fields include the lesson title, textbook chapter, self-study assignment, etc. This information is collected through the user interface of the smart device and sent to the server as JSON format data. An example of input data is "The next lesson is 'Basic Chemistry', related materials are textbook chapter 4, and self-study assignment." As output, the input data is sent to the server.

[1201] Step 2:

[1202] Data reception and storage by the server

[1203] The server receives data sent from the smart device. The received data includes information such as lesson content, textbook chapters, and self-study assignments. This data is then temporarily stored in the server's database. The input is the received JSON data, and the output is the stored database entries.

[1204] Step 3:

[1205] Data analysis and generation using AI algorithms

[1206] The server inputs the saved data into an AI algorithm for analysis. The AI ​​algorithm references past lesson data and related materials to generate documents (PowerPoint templates, lecture notes, email templates, etc.) that are most suitable for the next lesson. This generation process collects highly relevant information and places it appropriately in each document. The inputs are saved data and past lesson data, and the output is the generated document.

[1207] Step 4:

[1208] Sending and viewing generated materials

[1209] The server sends the generated lesson materials to the user's smart device. The data is sent in the form of PowerPoint templates, lecture notes, email templates, etc. The user's smart device receives and displays these materials. The input is the generated document, and the output is the display screen of the smart device.

[1210] Step 5:

[1211] Review and correct the materials

[1212] The user (teacher) reviews the generated materials on the smart device and makes corrections as necessary, adding additional slides, highlighting content, and making corrections through the smart device interface. The input is the user's feedback and corrections, and the output is the final revised document.

[1213] Step 6:

[1214] Save and share the final document

[1215] Once the corrections are complete, the document is sent back to the server and saved as the final version in the database. If necessary, the document can be shared with other faculty members or other stakeholders. The input is the corrected document, and the output is the saved document and a shared link.

[1216] Example prompt: "The next lesson will be on Basic Chemistry, and related materials will be Chapter 4 of the textbook, as well as a self-study assignment. Please generate the appropriate PowerPoint template, lecture notes, and email template for parents."

[1217] 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.

[1218] As an embodiment of the present invention, a system for automating and streamlining a teacher's administrative work and lesson preparation, and taking into account the teacher's emotional state, is described below. This system includes a terminal for the teacher to input data, a server for receiving, analyzing, and generating data, a means for presenting and correcting the generated materials to the teacher, and an emotion engine for recognizing the teacher's emotions.

[1219] System Overview

[1220] 1. Data entry by the teacher (terminal side)

[1221] The user (teacher) logs in to the device and inputs data related to the required lesson content and administrative work. For example, a teacher inputs related materials and assignments for the next lesson, "Fundamentals of Biology," into the device. The device also sends the teacher's input data and behavioral data during operation to the emotion engine.

[1222] 2. Data processing and storage (server side)

[1223] The device sends input data and emotional data to the server, which receives it and stores it in a database. The server analyzes the received data and uses AI algorithms to automatically generate documents and materials. It also takes into account the emotional state of the teacher, as analyzed by the emotion engine.

[1224] 3. Document Generation (Server Side)

[1225] The server uses AI algorithms to generate optimal lesson materials and documents based on the input data. It also adjusts the content and format of the materials based on the teacher's emotional state based on the analysis results of the emotion engine. For example, if a teacher is feeling stressed, the server will reduce the amount of material provided and soften their tone.

[1226] 4. Sending and displaying the results (terminal side)

[1227] The server sends the generated materials to the terminal, which displays them to the user, who can then use them to prepare for classes or perform administrative tasks.

[1228] 5. Checking and correcting materials (user side)

[1229] The user can review the submitted materials and make any necessary modifications, for example adding specific information to the generated PowerPoint template or modifying the content.

[1230] Specific examples

[1231] Teacher A logs in to the device to enter the next week's lesson schedule and enters the following: "The next lesson is 'Fundamentals of Biology', and the related materials are Chapter 3 of the textbook and the self-study assignment." The device sends this data, along with the teacher's input operation data, to the emotion engine.

[1232] The server receives the data and stores it in a database. An AI algorithm analyzes past lesson data and related materials to generate PowerPoint templates and lecture notes optimal for the next week's lesson, as well as email templates for parents. At the same time, an emotion engine analyzes Teacher A's emotional state and, if it determines that he is feeling stressed, makes adjustments such as reducing the amount of material or simplifying the content.

[1233] The generated materials are sent from the server to the terminal and displayed on Teacher A's terminal. Teacher A reviews these materials and makes corrections as necessary, for example, by inserting additional slides into the PowerPoint template to emphasize specific content.

[1234] This system allows teachers to save time by manually creating materials, enabling them to prepare lessons and perform administrative tasks more efficiently. Furthermore, the introduction of an emotion engine provides a system that takes into account the teacher's emotional state, improving the user experience. This invention reduces the workload of teachers and provides sufficient support for them to focus on their teaching activities.

[1235] The processing flow will be explained below.

[1236] Step 1:

[1237] Users log in to the terminal and enter data related to the required lesson content and administrative tasks. For example, a teacher may enter "Fundamentals of Biology" as the lesson content for next week, and enter related materials and assignments. At the same time, the terminal collects operation data such as the teacher's keystroke time and click frequency.

[1238] Step 2:

[1239] The terminal sends input data and operation data to the server using an encryption protocol that takes security into consideration.

[1240] Step 3:

[1241] The server receives the data sent from the device and stores it in a database. The stored data includes lesson content, related materials, assignments, and teacher operation data.

[1242] Step 4:

[1243] The server reads the incoming data from the database and begins analyzing it, using AI algorithms to analyze the content of the input data.

[1244] Step 5:

[1245] The server uses an emotion engine to analyze the teacher's operation data and estimate the teacher's emotional state. Specifically, it determines whether the teacher is feeling stressed based on data such as keystroke speed and click intervals.

[1246] Step 6:

[1247] Based on the analysis results, the server uses AI algorithms to generate optimal documents and materials. These include PowerPoint templates for lessons, lecture notes, and email templates for parents. Based on the analysis results of the emotion engine, if a teacher is feeling stressed, the server will adjust the amount of materials provided, such as reducing the content or making it more concise.

[1248] Step 7:

[1249] The server sends the generated documents and materials to the terminal, using a real-time communication protocol to quickly deliver the data to the user.

[1250] Step 8:

[1251] The terminal displays the sent documents and materials to the user, who can then use them to prepare for classes or perform administrative tasks.

[1252] Step 9:

[1253] The user can review the displayed document or material and make any necessary edits. The edited document is then saved back to the device. For example, the user can add specific information to the generated PowerPoint template to highlight the content.

[1254] This system will enable teachers to save time by manually creating materials, allowing them to prepare lessons and perform administrative tasks more efficiently. It will also improve the user experience by taking into account the emotional state of teachers, providing a less stressful work environment.

[1255] Example 2

[1256] 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."

[1257] Traditionally, administrative work and lesson preparation required a lot of time and effort, reducing productivity. These tasks can also affect teachers' emotional state and increase stress. This can reduce the time teachers have to concentrate on teaching activities, potentially resulting in a decline in the quality of education. Given this background, there was a need for a system that could streamline teachers' work and also take into account their emotional state.

[1258] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes an input means through which a teacher inputs data for administrative work and lesson preparation, a server means for receiving the data and storing it in a database, a generation means for analyzing the data and generating documents and materials using an AI algorithm, a transmission means for transmitting the generated output to the teacher's terminal and displaying it, an emotion recognition means for recognizing the teacher's emotional state based on the data, and an adjustment means for adjusting the document content based on the analysis results of the emotion recognition means. This automates the teacher's work and makes it possible to provide materials customized according to the teacher's emotional state. This reduces the teacher's workload and provides sufficient support for them to concentrate on their teaching activities.

[1259] "Input means" refers to the means by which teachers input data necessary for administrative work and lesson preparation into the system.

[1260] "Server means" refers to means having a server function for receiving data entered by a teacher and storing it in a database.

[1261] "Generation means" refers to the means for analyzing received data and generating documents or materials using AI algorithms.

[1262] The "transmission means" is a means for transmitting the generated output to the teacher's terminal and displaying it.

[1263] The "emotion recognition means" is a means for recognizing the emotional state of the teacher based on the input data and operation data.

[1264] The "adjustment means" is a means for adjusting the document contents based on the analysis results of the emotion recognition means.

[1265] "Documents" refers to all documents used by teachers, including course materials.

[1266] "Materials" refers to various documents used by faculty for classes and administrative work, including PowerPoint templates, lecture notes, and email templates.

[1267] "Teacher" refers to anyone engaged in educational activities.

[1268] This invention relates to a system that automates and streamlines the administrative work and lesson preparation of teachers and takes into account the emotional state of the teacher. This system includes a terminal for teachers to input data, a server that receives, analyzes, and generates data, a means for presenting and correcting the generated materials to the teacher, and an emotion engine that recognizes the teacher's emotions.

[1269] Teachers log in to the terminal and input data related to the next class content and administrative work. For example, a teacher can input related materials and assignments for next week's class content, "Fundamentals of Biology," into the terminal. At this time, the teacher's input data and behavioral data during operation are sent to the emotion engine.

[1270] The device sends input data and emotional data to a server, which receives the data and stores it in a database. The server then analyzes the data and uses an AI algorithm to automatically generate documents and materials. One example of the algorithm used is OpenAI's GPT-3. The emotional state of the teacher, as analyzed by the emotion engine, is also taken into account.

[1271] The server uses an AI algorithm to generate optimal lesson materials and documents based on the input data. For example, if a teacher is feeling stressed, the server will adjust the amount of material provided, soften the tone, and make other adjustments. An example of a specific prompt could be, "The next class will be on 'Fundamentals of Biology,' and the related materials will be Chapter 3 of the textbook and self-study assignments. Please simplify the materials for teachers who are feeling stressed."

[1272] The generated materials are sent from the server to the terminal and displayed on the teacher's terminal. Teachers can use these materials to efficiently prepare for classes and perform administrative tasks. Teachers can also review the sent materials and make corrections as necessary. For example, they can add specific information to the generated PowerPoint template or modify the content.

[1273] This system reduces the workload of teachers and provides sufficient support for them to concentrate on teaching activities. In addition, by using an emotion engine, services are provided that take into account the emotional state of teachers, improving the user experience.

[1274] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1275] Step 1:

[1276] The user (teacher) logs into the terminal and inputs the data necessary for lesson preparation and administrative work. Specifically, they input the next lesson content, "Fundamentals of Biology," related materials, "Textbook Chapter 3," and assignment content, "Self-Study Assignment." This input data is acquired through the terminal's interface. The terminal also simultaneously collects operation data such as the teacher's keystroke speed and mouse operation, and sends this data to the emotion engine. The input data is text data related to the lesson content and administrative work, while the operation data is behavioral data used to determine the teacher's emotional state.

[1277] Step 2:

[1278] The terminal uses a communication module to send input data and operation data to the server in real time. The server temporarily stores the received data and then stores it in a database. Specifically, the server receives input data and operation data in a standard format such as JSON and temporarily stores it in a buffer area. This data is then stored in a structured or relational database. The input is the data stream from the terminal, and the output is the data stored in the database.

[1279] Step 3:

[1280] The server uses AI algorithms to analyze the data stored in the database. First, it analyzes the lesson content data and extracts the information necessary to generate related materials and documents. Next, the emotion engine analyzes the operation data and determines the teacher's emotional state. For example, it can identify whether the teacher is feeling stressed based on the speed of keystrokes and frequency of mouse operations. The input is lesson content data and operation data obtained from the database, and the output is lesson information and emotional state data as the analytical results.

[1281] Step 4:

[1282] Based on the analysis results, the server uses an AI algorithm to automatically generate lesson materials and documents. For example, it uses a generative AI model such as OpenAI GPT-3 to generate relevant materials (e.g., PowerPoint templates, lecture notes, email templates). At this time, the content and amount of the materials are adjusted based on the analysis results of the emotion engine, taking into account the teacher's emotional state. The input is the analysis results and emotional state data obtained from Step 3, and the output is the generated lesson materials and documents. The generated materials are created according to a prompt. For example, a prompt might be used: "The next class is 'Fundamentals of Biology,' and the related materials are Chapter 3 of the textbook and self-study assignments. Please keep the materials concise for teachers who are feeling stressed."

[1283] Step 5:

[1284] The server sends the generated lesson materials and documents to the terminal. This transmission process uses a secure communication protocol (e.g., HTTPS). The terminal displays the received materials on the teacher's screen. The input is the generated materials sent from the server, and the output is the visual information displayed through the terminal's interface.

[1285] Step 6:

[1286] The user (teacher) checks the materials displayed on the terminal and edits or modifies them as necessary. For example, they can insert additional slides into the generated PowerPoint template to emphasize specific content. They can also customize the content of their lecture notes. The input is the generated material displayed on the terminal, and the output is the final material to which the teacher has made modifications. The results of these modifications are saved back in the database and used to prepare for future lessons.

[1287] (Application example 2)

[1288] 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."

[1289] In brick-and-mortar stores, it takes a lot of time and effort for staff to efficiently perform their daily tasks and respond to customers. Furthermore, performing tasks without considering the emotional state of staff can cause stress and fatigue, resulting in a decline in the quality of work and customer satisfaction. This invention aims to provide a system that automates and streamlines work management and customer response in brick-and-mortar stores, while also taking into account the emotional state of staff.

[1290] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes an input means through which a teacher inputs data for clerical work and lesson preparation, a server means for receiving the data and storing it in a database, a generation means for analyzing the data and generating documents and materials using an AI algorithm, a transmission means for sending the generated output to the teacher's terminal and displaying it, an input means through which staff input customer service and work content based on the input data, a generation means for generating procedure manuals and scripts based on the work content, and an emotion analysis means for analyzing the emotional state of staff and optimizing information based on this. This not only efficiently automates work and customer service in physical stores, but also enables appropriate support that takes the emotional state of staff into consideration.

[1291] A "teacher" is a person whose job is to provide education to pupils or students at an educational institution.

[1292] "Office work" is a general term for everyday work tasks such as creating documents, processing data, and organizing information necessary for general business operations.

[1293] "Class preparation" refers to a series of preparatory activities that teachers at educational institutions undertake, such as preparing teaching materials, formulating lesson plans, and creating materials, in order to teach a class.

[1294] "Data" is a collective term for information and records that are input into a system for processing.

[1295] "Input means" is a general term for interfaces and devices that allow a user to input data into the system.

[1296] "Server means" is a general term for a computer system that receives data, stores it in a database, and performs processing such as analysis.

[1297] "Generation means" is a general term for functions and devices that automatically generate documents and materials using AI algorithms based on input data.

[1298] "Transmission means" is a general term for functions and devices for transmitting the generated output to the user's terminal and displaying it.

[1299] "Customer service" refers to a series of actions and activities that store staff take to provide service in response to customer requests and inquiries and improve customer satisfaction.

[1300] "Work content" refers to the details and content of the work and tasks that staff perform on a daily basis.

[1301] "Emotion analysis means" is a general term for functions and devices that analyze the user's emotional state and generate optimized information based on the results.

[1302] A "procedure manual" is a document that contains detailed instructions and procedures for carrying out a specific task or work.

[1303] A "script" is a document that contains standard phrases and conversational guidelines used in specific tasks or customer interactions.

[1304] "Output" refers to documents and materials that are the result of a system's generation.

[1305] As an embodiment of the present invention, a system that improves the efficiency of staff work management and customer service and also takes into account the emotional state of staff is described below. This system includes a terminal for staff to input data, a server that receives, analyzes, and stores the data, a means for presenting and correcting the generated materials to staff, and an emotion analysis engine that recognizes the emotions of staff.

[1306] System Overview

[1307] 1. Data entry by staff (terminal side)

[1308] Users (staff) log in to a smartphone app and input their daily work and customer service details. The input method sends the work details and behavioral data to the emotion analysis engine. Specifically, data such as "New product A has arrived" or "Customer B has an inquiry about a product" is entered into the app.

[1309] 2. Data processing and storage (server side)

[1310] The terminal sends input data and emotional data to the server, which receives it and stores it in a database. The server then uses AI algorithms to analyze the input data and generate appropriate work procedures and customer service scripts. It also takes into account the emotional state of the staff analyzed by the emotion analysis engine.

[1311] 3. Document generation and display (server side and terminal side)

[1312] The server uses an AI algorithm to generate optimal procedures and scripts based on the input data. Furthermore, based on the analysis results of the emotion analysis engine, if a staff member is feeling stressed, the server will adjust the procedure by simplifying it or softening the tone of the script. The generated materials are sent from the server to the terminal, where they are displayed to the staff member.

[1313] 4. Checking and correcting materials (staff side)

[1314] Staff can review the submitted materials and make corrections as needed, for example by adding additional information to the generated customer response script or by amending the content.

[1315] Program processing explanation

[1316] The server runs on the Flask framework and stores data in a SQLite database. Task details and emotional data entered by users through a smartphone app are sent to the server and analyzed by an AI algorithm. The AI ​​algorithm generates optimal procedures and scripts based on a database containing past data and related information. The emotion analysis engine also analyzes the emotional state of staff and adjusts the content and format of the generated materials.

[1317] Specifically, if a staff member inputs "New product A has arrived" or "Customer B has an inquiry about a product," the server will generate the optimal receiving procedure manual and customer response script based on this data. Also, if a staff member is feeling stressed, the server will simplify the procedure or generate a script using a gentler tone.

[1318] Prompt Sentence Examples

[1319] Task: New product A has arrived, and customer B has inquired about the product.

[1320] Emotional data: tired, stressed

[1321] The above is a detailed description of the embodiment of the present invention. This system not only efficiently automates operations and customer service in brick-and-mortar stores, but also enables appropriate support that takes into account the emotional state of staff. Implementing the system in accordance with this embodiment will improve work efficiency and reduce staff stress.

[1322] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1323] Step 1:

[1324] The user logs into the smartphone app and inputs details of their daily work and customer service. For example, this data might include "New product A has arrived" or "Customer B has an inquiry about a product." The device then sends this input data and behavioral data during operation to the emotion analysis engine.

[1325] Step 2:

[1326] The device sends input data and emotion data to the server, which receives it and stores it in a database. The SQLite database ensures data persistence and efficient management.

[1327] Step 3:

[1328] The server analyzes the received data and uses an AI algorithm to generate optimal procedures and scripts based on the input work content, while referring to related past data and materials. The AI ​​model uses a pre-trained generative AI model.

[1329] Step 4:

[1330] The emotion analysis engine analyzes the emotional data sent from the device, evaluating the emotional state of the staff member and determining whether they are feeling stressed or fatigued. Emotion analysis is performed using behavioral data during operation and facial expression recognition technology.

[1331] Step 5:

[1332] The server adjusts the generated procedures and scripts based on the results of the emotion analysis engine. For example, if a staff member is feeling stressed, it will simplify the work procedures or soften the tone of the script.

[1333] Step 6:

[1334] The server sends the generated optimized procedures and scripts to the terminal, which displays them to the staff, who can then view them through the app.

[1335] Step 7:

[1336] Staff members can review the displayed procedures and scripts and make any necessary corrections. For example, they can add additional information to a customer support script or modify its content. The corrected materials are then sent back to the server and updated in the database.

[1337] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1338] 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.

[1339] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1340] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1341] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1342] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1343] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1344] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1345] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1346] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1347] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1348] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1349] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1350] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1351] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1352] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1353] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1354] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1355] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1356] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1357] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1358] The following is further disclosed regarding the above embodiment.

[1359] (Claim 1)

[1360] an input means for teachers to input data for administrative work and lesson preparation;

[1361] a server means for receiving the data and storing it in a database;

[1362] A generating means for analyzing the data and generating documents and materials using an AI algorithm;

[1363] A transmitting means for transmitting the generated output to a teacher's terminal and displaying it.

[1364] A system including:

[1365] (Claim 2)

[1366] 10. The system of claim 1, wherein the documents and materials generated by the generating means include PowerPoint templates, lecture notes, and email templates.

[1367] (Claim 3)

[1368] The system of claim 1 , further comprising a correction means for the teacher to review and correct the output.

[1369] "Example 1"

[1370] (Claim 1)

[1371] an input means for teachers to input information for administrative work and lesson preparation;

[1372] a server means for receiving the information and storing it in a database;

[1373] A generating means for analyzing the information and generating documents and materials using a generative AI model;

[1374] a transmitting means for transmitting the generated result to a teacher's terminal and displaying the result;

[1375] A correction means for the teacher to check the results and correct them as necessary.

[1376] A system including:

[1377] (Claim 2)

[1378] 10. The system of claim 1, wherein the documents and materials generated by said generating means include presentation templates, lecture notes, and announcement templates.

[1379] (Claim 3)

[1380] The system of claim 1 further comprising a correction means for the teacher to review and correct the results.

[1381] "Application Example 1"

[1382] (Claim 1)

[1383] an input means for teachers to input data for administrative work and lesson preparation;

[1384] a server means for receiving the data and storing it in a database;

[1385] A generating means for analyzing the data and generating documents and materials using an AI algorithm;

[1386] a transmitting means for transmitting the generated output to a teacher's terminal and displaying the output; and

[1387] A means for teachers to check and correct the generated materials using a smart device

[1388] A system including:

[1389] (Claim 2)

[1390] 10. The system of claim 1, wherein the documents and materials generated by the generating means include PowerPoint templates, lecture notes, and email templates.

[1391] (Claim 3)

[1392] The system of claim 1 , further comprising a correction means for the teacher to check and correct the output on a smart device.

[1393] "Example 2: Combining Emotion Engines"

[1394] (Claim 1)

[1395] an input means for teachers to input data for administrative work and lesson preparation;

[1396] a server means for receiving the data and storing it in a database;

[1397] A generating means for analyzing the data and generating documents and materials using an AI algorithm;

[1398] a transmitting means for transmitting the generated output to a teacher's terminal and displaying the output;

[1399] emotion recognition means for recognizing the emotional state of the teacher based on the data;

[1400] An adjustment means for adjusting the document content based on the analysis result of the emotion recognition means.

[1401] A system including:

[1402] (Claim 2)

[1403] 10. The system of claim 1, wherein the documents and materials generated by said generating means include presentation templates, lecture materials, and notices.

[1404] (Claim 3)

[1405] The system of claim 1 , further comprising a correction means for the teacher to review and correct the output.

[1406] "Application example 2 when combining emotion engines"

[1407] (Claim 1)

[1408] an input means for teachers to input data for administrative work and lesson preparation;

[1409] a server means for receiving the data and storing it in a database;

[1410] A generating means for analyzing the data and generating documents and materials using an AI algorithm;

[1411] a transmitting means for transmitting the generated output to a teacher's terminal and displaying the output;

[1412] an input means for staff to input customer service and business details based on the input data;

[1413] a generating means for generating a procedure manual or script based on the business content;

[1414] Emotion analysis means to analyze the emotional state of staff and optimize information accordingly

[1415] A system including:

[1416] (Claim 2)

[1417] 10. The system of claim 1, wherein the documents and materials generated by the generating means include PowerPoint templates, lecture notes, and email templates.

[1418] (Claim 3)

[1419] The system of claim 1 , further comprising a correction means for the teacher to review and correct the output. [Explanation of symbols]

[1420] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. an input means for teachers to input data for administrative work and lesson preparation; a server means for receiving the data and storing it in a database; A generating means for analyzing the data and generating documents and materials using an AI algorithm; A transmitting means for transmitting the generated output to a teacher's terminal and displaying it. A system including:

2. The system of claim 1 , wherein the documents and materials generated by the generating means include PowerPoint templates, lecture notes, and email templates.

3. The system of claim 1 , further comprising a correction means for the teacher to review and correct the output.

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