system

Abstract

システムを提供する。【解決手段】地域内の教育施設から情報を収集し、それを統合して中央データ管理装置に保存する手段と、収集した情報をもとに、利用者からの質問に対してリアルタイムで最適なリソースを提示する人工知能エージェント手段と、教育従事者の予定を自動的に調整し、教育活動を効率化する予定調整手段と、学習者の進捗状況を評価し、個別にカスタマイズされた学習教材を提供する手段と、地域の高齢者と教育活動を希望する利用者をマッチングする手段と、利用者間での情報共有と連絡を促進する通信機能を提供する手段と、地域における学習機会をリアルタイムで提供する手段と、携帯型情報端末を介して地域の教育情報を提供する手段と、を含むシステム。

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Due to the dispersion of regional educational resources, there is a problem that it is difficult for parents and students to obtain necessary information quickly and appropriately. In addition, the schedule management of educators is complicated, which hinders efficient educational activities. Furthermore, there is also a problem that there is a lack of a mechanism for providing customized educational content for individual learners and utilizing local elderly people as educational resources. In addition, there is a problem that the sharing and communication of important information related to education are insufficient, and the communication among relevant parties is not smooth.

Means for Solving the Problems

[0005] This invention features the ability to collect and integrate information from educational institutions within a region and store it in a central database. It utilizes an AI agent to enable the presentation of optimal resources in response to user inquiries. Furthermore, it includes means for automatically adjusting educators' schedules and providing customized educational content to students. These challenges are addressed by including communication functions that support matching local seniors with those seeking education and facilitate efficient information sharing and communication among users.

[0006] "Educational institutions" refer to all facilities used for learning and educational activities, such as schools, cram schools, libraries, and community centers.

[0007] "Collecting and integrating information" refers to the process of obtaining data from multiple sources and organizing and unifying it.

[0008] A "central database" refers to a central data storage system where collected information is stored.

[0009] An "AI agent" refers to a program that uses artificial intelligence to interact with users and provide appropriate answers and information in response to their questions.

[0010] "Automatically adjusting schedules" refers to optimizing appointments and timetables and managing them efficiently without human intervention.

[0011] "Learner" refers to an individual user who receives educational content and engages in learning activities.

[0012] "Customized educational content" refers to educational materials and teaching aids that are specially tailored to the progress and interests of individual learners.

[0013] "Local elderly" refers to older people who live in a specific area and are willing to participate in educational activities.

[0014] "Supporting matching" refers to the process of finding and connecting partners or opportunities that meet needs and conditions.

[0015] "Communication function" refers to the function used to exchange information between users and achieve communication of intentions.

Brief Explanation of Drawings

[0016] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13]It is a sequence diagram showing the processing flow of the data processing system in Embodiment 2 when the emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when the emotion engine is combined.

Mode for Carrying Out the Invention

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

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

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

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

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

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

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

[0024] [First Embodiment]

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

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

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

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

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

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

[0031] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

[0033] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

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

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

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

[0037] This invention provides an integrated platform for effectively supporting local education. Specifically, it describes a system that collects information from educational institutions and uses AI technology to provide each user with the most suitable educational resources based on that information.

[0038] The server collects information from various educational institutions within the region (schools, libraries, cram schools, etc.). Specifically, it collects data on facility schedules, event information, and available resources, and organizes and stores this information in a central database.

[0039] When a user searches for specific information or enters a question through their device, an AI agent quickly extracts relevant information from its database based on the request and presents it to the user in the most optimal format. This response may include a list of facilities or suggestions for specific services that meet detailed criteria.

[0040] Furthermore, the server has a function to automatically manage educators' schedules. When educators teach at different schools or online platforms, it efficiently adjusts their schedules to avoid overlapping class times. This function maximizes the efficiency of educational activities.

[0041] For learners, the server monitors their progress and learning history, and provides individually customized educational content. This includes video materials, sets of exercises, or materials related to new learning topics. This customization ensures that each learner can continue learning in the most optimal way possible.

[0042] Furthermore, the system incorporates a matching function to effectively utilize elderly individuals within local communities as educational resources. The server matches registered elderly individuals with educational activity needs based on their skills and experience, encouraging them to participate, for example, as workshop instructors. This mechanism improves the overall quality of education in the community.

[0043] Ultimately, it includes chat and notification features to facilitate smooth communication between users. This allows teachers, parents, and learners to share necessary information and collaborate in a timely manner.

[0044] Thus, the present invention provides a typical embodiment of a system that achieves improved efficiency and quality in local education through the coordinated operation of its various functions.

[0045] The following describes the processing flow.

[0046] Step 1:

[0047] The server collects information from the websites and public databases of various educational institutions within the region. This information includes the institutions' schedules, events, and available resources, and is stored as structured data in a central database.

[0048] Step 2:

[0049] Users can input questions about education-related information and resources into the system via their devices. User questions are in natural language, and the interface is designed to be intuitive.

[0050] Step 3:

[0051] The server receives the input question, and an AI agent analyzes its content. Using natural language processing technology, it understands the intent of the question and searches for relevant information in the database.

[0052] Step 4:

[0053] The server generates the best possible answer to the user's question and sends it to the user's terminal. The answer includes information about the relevant educational institution's facilities, available resources, and other information that matches the user's specified criteria.

[0054] Step 5:

[0055] The server automatically retrieves educators' current schedules and manages them to avoid overlaps and conflicts. Schedules are coordinated across multiple educational institutions and online platforms.

[0056] Step 6:

[0057] The server analyzes learner progress data and generates personalized educational content. Based on progress reports and past learning content, a process is performed to recommend appropriate learning resources.

[0058] Step 7:

[0059] The server implements a process to match the skills of local seniors with the educational activity needs. Based on registered profiles, it matches seniors with appropriate educational projects, enabling them to participate.

[0060] Step 8:

[0061] To facilitate information sharing among users, the server provides chat and notification functions. This ensures that relevant information is delivered to stakeholders in real time, facilitating smooth communication.

[0062] (Example 1)

[0063] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0064] To improve and streamline local education, it is necessary to collect information from educational institutions, coordinate educators' schedules, provide individualized support to learners, utilize the elderly as educational resources, and facilitate smooth communication among users. However, there are limited systems that can effectively integrate these challenges and respond in real time. Therefore, there is a need to provide a comprehensive platform that enables efficient information management and communication in local education.

[0065] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0066] In this invention, the server includes means for collecting data from an information provision structure, synthesizing it, and storing it in a management data structure; intelligent agent means for immediately presenting appropriate information sources in response to user inquiries based on the collected data; and planning means for automatically scheduling and adjusting the schedules of educators to streamline educational activities. This enables the integration and efficient management of information in local education, allowing users to receive personalized educational services and educators to enjoy non-duplicate scheduling. Furthermore, it facilitates the effective utilization of the elderly and effective information sharing.

[0067] An "information provision structure" is a collection of various data, such as schedules, events, and resources, provided by educational institutions and organizations.

[0068] A "management data structure" is a database system that systematically stores, organizes, and makes accessible collected information.

[0069] An "intelligent agent" is a software program that uses artificial intelligence to analyze collected data and provide appropriate information in response to user inquiries.

[0070] "Planning tools" are tools and algorithms that automatically analyze the schedules of educators and optimize them to eliminate duplication and waste.

[0071] "Users" refers to individuals or organizations that collect information, receive, or provide educational services through this system.

[0072] "Educational professionals" is a general term for professionals involved in educational activities, including teachers and instructors.

[0073] "Elderly people" refers to older members of the community who may have the potential to provide knowledge and experience to learners and other users.

[0074] "Multifunctional communication" refers to communication methods, including chat and notification systems, that facilitate efficient and smooth information exchange among users.

[0075] This invention provides an integrated information management system to support local education. The system aims to collect and analyze data from information provision structures and to effectively provide information to users. The server collects data such as schedules, event information, and resources from local educational institutions and organizations. This includes school class times and library event announcements. The server stores this data in a managed data structure and uses natural language processing techniques and machine learning algorithms to present information effectively. Specifically, database management systems based on Python or Java (registered trademark) are commonly used.

[0076] Users of the device can search for the information they need in real time through the system. For example, when a parent searches for nearby workshops for their child, the AI ​​agent instantly provides a list of events in response to their request. The platform supporting this process utilizes a generative AI model that analyzes prompt sentences in response to user inquiries and generates the optimal answer.

[0077] Educators can have their schedules managed by the server, avoiding overlaps in class timetables and enabling efficient teaching activities. For example, when educators teach at multiple schools or online platforms, the server coordinates their schedules and generates adjustment plans as needed.

[0078] Furthermore, this system includes a model for utilizing the knowledge and experience of older adults as educational resources. The server matches older adults' profiles with their educational needs and facilitates their participation as instructors in local workshops and courses. For example, by entering a prompt such as, "Please provide information on children's science events taking place in the following area. Also, please check if there are any older adult candidates who can participate as instructors at these events," information that facilitates older adult participation can be obtained quickly.

[0079] With the above configuration, the system will improve the quality and efficiency of local education, and provide users with personalized information and opportunities for effective communication.

[0080] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0081] Step 1:

[0082] The server collects data from the information provision structure. Specifically, it uses API access and scraping techniques to obtain schedules and event information from the websites and data feeds of educational institutions within the region.

[0083] The input is the web pages or systems of educational institutions, and the output is a list of structured schedule data and event information.

[0084] Specific operation: The server executes an automated crawling script to periodically collect specified information.

[0085] Step 2:

[0086] The server organizes and stores the collected data in a managed data structure. This process involves data cleaning and normalization, and checks for errors and duplicates.

[0087] The input is schedule and event information in raw data format, and the output is a dataset stored in a consistent database.

[0088] Specific operation: Use the database injection API to add normalized data as an entry.

[0089] Step 3:

[0090] The user uses the device to search for specific information or enter a question. Search keywords or question sentences are entered via the user interface.

[0091] The input is the user's search query, and the output is a list of search results related to the relevant information.

[0092] Specific operation: The user enters a keyword in the terminal's GUI and clicks the "Search" button.

[0093] Step 4:

[0094] The AI ​​agent instantly extracts relevant data from the managed data structure based on user questions and searches. A natural language processing model is used in this process.

[0095] The input is the user's search query, and the output is an optimized dataset or list of information presented to the user.

[0096] Specific operation: The AI ​​agent interprets queries and accesses the database using SQL or similar query languages.

[0097] Step 5:

[0098] The server analyzes and automatically adjusts the schedules of educators. Duplicate tasks and classes are detected, and an optimal time schedule is suggested.

[0099] The input is the educator's existing schedule data, and the output is an adjusted schedule proposal.

[0100] Specific operation: The server applies a scheduling algorithm to generate the adjusted schedule.

[0101] Step 6:

[0102] The server generates personalized educational support based on the learner's progress and history data. This support includes videos, exercises, and supplementary materials.

[0103] The input consists of learner history data points, and the output is a customized set of educational content.

[0104] Specific operation: The server analyzes course registration data and uses AI inference to map the most suitable content.

[0105] Step 7:

[0106] The server matches the needs of seniors with those of educational events. User-provided prompts are processed, and suitable instructors and eligible seniors are assigned.

[0107] The input is a prompt from the user, and the output is a list of matched elderly individuals.

[0108] Specific operation: Recommendations are made using a matching algorithm with a profile database.

[0109] Step 8:

[0110] The system uses devices to facilitate communication between users. Chat functions and push notifications are used to exchange necessary information and messages.

[0111] The input is the trigger for a message or contact initiated by the user, and the output is the notification or message forwarding to the recipient.

[0112] Specific operation: Messages are sent and received in real time via the chat application on the device.

[0113] (Application Example 1)

[0114] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0115] Modern communities lack systems for efficiently collecting and providing educational resources. Comprehensively managing information on local educational institutions such as schools, libraries, and cram schools, and providing it promptly as needed, is crucial for ensuring optimal learning for each student. However, various challenges exist, including information fragmentation, scheduling difficulties for educators, and underutilization of senior citizens as local educational resources. Furthermore, providing this information to learners in real time and creating an optimal learning environment remains challenging.

[0116] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0117] This invention includes a server that collects information from educational facilities within a region, integrates it, and stores it in a central data management device; a server that uses an artificial intelligence agent to present the most suitable resources in real time in response to user inquiries; and a server that automatically adjusts the schedules of educators to improve the efficiency of educational activities. This enables centralized management of educational resources within a region and provides learners with the most suitable educational information in real time.

[0118] "Educational facilities within a region" refers to various institutions and organizations located in a specific area that are dedicated to education, such as schools, libraries, and cram schools.

[0119] "Means for collecting information, integrating it, and storing it in a central data management system" refers to a mechanism for collecting information provided by educational institutions in digital format, compiling and organizing it, and storing it on a server.

[0120] "A means of presenting the most suitable resources in real time using an artificial intelligence agent" refers to a function that utilizes AI technology to instantly provide appropriate educational resources in response to questions entered by users.

[0121] "Methods for automatically adjusting the schedules of educators and improving the efficiency of educational activities" refers to methods for automatically managing and adjusting the work schedules of teachers, lecturers, and other people involved in education, thereby achieving efficient educational activities without duplication.

[0122] "Learners" refer to individuals who acquire knowledge through local educational facilities or online platforms.

[0123] "Providing information to learners in real time" means processing information quickly in response to user requests and delivering the necessary educational information to learners immediately.

[0124] The system to realize this application will be built around cloud-based data collection and artificial intelligence. The server will collect information regularly provided by various educational facilities within the region using APIs or web scraping techniques, integrate it, and store it in a database. High-performance servers are required as hardware, and cloud services such as Amazon Web Services (AWS®) and Google Cloud Platform are suitable.

[0125] The collected data is processed using Python and delivered as a web application using the Flask framework. The server utilizes TENSORFLOW® and PyTorch as artificial intelligence models to provide users with the most suitable educational resources in real time. The AI ​​agent uses natural language processing technology to quickly respond to user questions and select and display the necessary information.

[0126] Furthermore, to enable educators to manage their schedules, it integrates with the Google Calendar API and Microsoft® Graph API to automatically adjust appointments. This improves the efficiency of educators' time management.

[0127] As a concrete example, when a user enters the prompt "Please tell me which workshops are available next week" into a smartphone app, the server searches its database for relevant information, and the AI ​​agent presents the most suitable resources. The generative AI model used in this process is an advanced natural language processing model such as BERT.

[0128] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0129] Step 1:

[0130] The server retrieves information from educational facilities within the region via APIs. Inputs include schedules and resource information from each facility, and output is a unified dataset in CSV or JSON format. This data is stored in a database for subsequent processing.

[0131] Step 2:

[0132] The server receives a prompt from the user. The input is a question in natural language, which is parsed by the AI ​​agent. A generative AI model (e.g., BERT) processes this prompt and understands the user's intent. The output is the user's intent, organized as a query.

[0133] Step 3:

[0134] The AI ​​agent retrieves relevant information from a database based on user intent. The input is organized user intent, which generates database queries and executes requests. The output is a list of relevant educational resource information.

[0135] Step 4:

[0136] The server organizes the retrieved resource information for return to the user. The input is a list of educational resources, to which prioritization and formatting are applied. The output is the final response format for presentation to the user (e.g., HTML content in list format).

[0137] Step 5:

[0138] The terminal receives responses from the server and displays them on the user's screen. The input is the final response from the server, and the output is the information visually displayed on the user interface. Based on this information, the user can decide which workshops to participate in and which services to use.

[0139] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0140] This invention provides users with a more personalized educational experience by combining an emotion recognition engine with a local educational support system. This enables interaction that responds to the user's emotions, thereby improving the quality of education. Specific embodiments are described below.

[0141] The server collects data from educational institutions within the region and stores it in a central database. This information includes schedules, events, and resource information for each facility. This ensures that users always have access to the most up-to-date information.

[0142] Users can inquire about educational resources and information through the device. The device is equipped with an emotion recognition engine that uses voice and text data as input. This engine analyzes the user's emotions from the tone and speed of their voice and the content of their text to determine how the user is feeling when seeking information.

[0143] The server uses an AI agent to comprehensively analyze the user's questions and emotional state. For example, if the user is feeling anxious, the server adjusts its approach to provide more detailed and reassuring information. For instance, if the user inputs "I'm anxious about the next test," the server will suggest a learning plan and various learning support content to alleviate that anxiety.

[0144] The scheduling system efficiently manages educators' schedules, automatically updating them based on new information. It also generates customized educational content that takes learners' progress and emotional states into account. The emotional engine suggests content that adjusts difficulty levels or includes encouraging words if learners are experiencing stress.

[0145] Furthermore, it includes a matching function to utilize local seniors as educational resources. The emotional engine also evaluates the attitude of seniors towards the educational activities they wish to participate in, ensuring appropriate matching. Communication functions are also integrated, supporting smooth information sharing among users and delivering important notifications in real time.

[0146] Thus, by combining an emotion recognition engine, the present invention provides a system that enables more flexible and effective educational support for users, allowing all participants to enjoy a more fulfilling educational environment.

[0147] The following describes the processing flow.

[0148] Step 1:

[0149] The server collects important educational resource information from websites and databases published by educational institutions within the region. This includes opening hours, event information, and lists of available facilities for each institution. This information is updated in real time and integrated into a central database.

[0150] Step 2:

[0151] Users access the system using a terminal and enter questions about specific educational information or resources. This input can be done using voice commands or text input.

[0152] Step 3:

[0153] The device sends the user's voice and text data to an emotion recognition engine. The engine analyzes the tone of voice, speaking speed, and keywords in the text to determine the user's emotional state. For example, if a user says "Teach me about this long homework" in a tired tone, the engine might estimate that the user is feeling frustrated or stressed.

[0154] Step 4:

[0155] The server uses an AI agent to process user questions and sentiment data. Considering the sentiment data, the server gains a deeper understanding of the intent behind the questions and selects the appropriate level of information. If the user is feeling anxious, the server presents more detailed and reassuring information.

[0156] Step 5:

[0157] The server generates user-specific educational content based on emotional data, including stress-reducing elements where necessary. This content is presented to the user in the form of surveys and activities.

[0158] Step 6:

[0159] When a user views suggested information or content on their device and enters further questions, their responses are also analyzed again by the emotion recognition engine and fed back to the server. This enables more personalized responses.

[0160] Step 7:

[0161] The server matches data on the skills and desired activities of older adults as educational resources, finding the optimal match with users who wish to engage in educational activities. Emotional data is also considered in this process to assess whether older adults are motivated to participate in the activities.

[0162] Step 8:

[0163] The communication function activates, and the server delivers notifications and messages in real time to facilitate information sharing among users. This function strengthens collaboration among educators.

[0164] (Example 2)

[0165] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0166] In today's educational environment, providing education that meets the individual needs and emotional states of learners is a challenge. Furthermore, there is a need for the effective utilization of educational resources through interaction with local elderly residents, and for efficient information sharing among learners. A flexible and effective educational support system that addresses these needs has yet to be established.

[0167] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0168] This invention includes a server that collects information from educational institutions within a region, integrates it, and stores it in a central database; an emotion recognition means that analyzes the user's voice and text input and estimates their emotional state; and a schedule management means that automatically adjusts the educator's activity schedule and streamlines educational activities. This enables the presentation of optimal educational information tailored to the user's emotions and individual learning needs, the effective provision of educational resources, and comprehensive educational support through collaboration with local communities.

[0169] "Information processing means" refers to a function that, in response to user inquiries, presents the most suitable educational resources in real time based on collected information.

[0170] "Emotion recognition means" refers to technology that analyzes a user's voice or text input to estimate their emotional state and use that information to provide appropriate information.

[0171] A "correction mechanism" is a function that optimizes the information provided based on the user's emotional state and suggests content that is appropriate to the user's situation.

[0172] A "schedule management system" is a management function that automatically adjusts the activity schedules of educators and improves the efficiency of educational activities.

[0173] "Mediation means" refers to functions that connect elderly people in the community with users who want to participate in educational activities, and support the effective use of local resources.

[0174] "Communication functions" are features that enable smooth information sharing and communication among users within the system.

[0175] Embodiments of the present invention are described below.

[0176] The server is responsible for collecting data from educational institutions within the region and storing it in a central database. Data collection is performed using API communication over the internet, retrieving schedules, event information, and resource data provided by educational institutions. The server filters this data, removing duplicates and incorrect information, and then efficiently stores it in the database, making it easy for users to access the latest information.

[0177] The device analyzes voice and text input from the user using an emotion recognition engine. This engine employs a machine learning model to analyze input data in order to recognize the user's emotional state. Specifically, it estimates emotions from the tone and speed of voice data and the content of text. For example, if a user enters the prompt "Please tell me my schedule for next week," the device is designed to take into account not only the acquisition of static information but also the user's current emotional state.

[0178] The server uses an AI agent to analyze the user's emotional state and questions, optimizing the information it provides. This AI agent incorporates natural language processing (NLP) technology, meticulously analyzing user input to select the most relevant information and resources. If the user is feeling anxious, the server prioritizes presenting resources that provide reassurance.

[0179] Furthermore, the server is equipped with a schedule management function to automatically adjust educators' activity schedules, thereby improving the efficiency of educational activities. It also has the ability to evaluate learners' progress and provide personalized educational resources. To achieve this, it utilizes a generative AI model to generate learning plans and practice problems tailored to the learners' progress.

[0180] Ultimately, the system connects local seniors with users who wish to engage in educational activities, providing opportunities to effectively utilize their knowledge and experience. The server manages this process comprehensively and provides example inputs as prompts to ensure an efficient learning environment and support users in smoothly using the system.

[0181] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0182] Step 1:

[0183] The server collects schedules, event information, and resource data from educational institutions within the region. Input consists of data submitted by each educational institution, which the server stores in a central database. The server processes the data to check for duplicates and standardize its format, storing it in an organized manner.

[0184] Step 2:

[0185] Users make inquiries via text or voice through the device. The input is a prompt statement uttered by the user (e.g., "Please tell me the schedule for next week"), and the device uses an emotion recognition engine to analyze the input data. The emotion recognition engine analyzes the tone and speed of the voice and the content of the text to estimate the user's emotional state.

[0186] Step 3:

[0187] The server, upon receiving data transmitted from the terminal, performs analysis using an AI agent. The input consists of the user's question and sentiment data, while the output is optimized information and resources. The server uses natural language processing technology to deeply analyze the user's intent and provide information tailored to their emotional state.

[0188] Step 4:

[0189] The server automatically adjusts educators' schedules to improve the efficiency of educational activities. Input is the latest schedule and resource information, and output is automatically updated schedules. The server dynamically manages this updated information and notifies educators and learners.

[0190] Step 5:

[0191] The server evaluates the learner's progress and generates personalized educational resources. The input is the learner's historical data, and the output is a customized learning plan and practice problems. A generative AI model is used to suggest appropriate learning content based on the learner's progress.

[0192] Step 6:

[0193] The server acts as an intermediary between local seniors and those seeking educational activities. Inputs include the seniors' registration information and the users' preferences; output is a personalized matching list. The server analyzes the registration data to derive appropriate pairings.

[0194] Step 7:

[0195] To facilitate information sharing among users, the server provides real-time communication capabilities. Inputs include new event information and announcements, while outputs include push notifications and messages. The server immediately sends this information to user terminals, supporting smooth communication.

[0196] (Application Example 2)

[0197] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0198] In modern families, there is a demand for individualized and efficient learning, but traditional educational methods make it difficult to flexibly provide learning content according to the emotions and progress of individual learners. Furthermore, there is a lack of means to deepen understanding of learners when providing educational support within the home. In addition, there is a need for means to enhance educational support throughout the community by utilizing the knowledge and experience of the elderly as educational resources.

[0199] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0200] This invention includes a server that collects information from local educational institutions, integrates it, and stores it in a central database; a server that analyzes the user's emotional state using an emotion recognition engine and adjusts educational resources based on the analysis results; and an implementation method that uses a consumer robot to provide educational support to the user in the home. This makes it possible to provide education tailored to each learner and to provide personalized learning support that takes emotions into consideration. Furthermore, it is expected to promote interactive learning that utilizes the knowledge and experience of the elderly and enhance the educational effect throughout the community.

[0201] "Educational institutions within a region" refers to educational organizations and facilities such as schools, libraries, and learning centers that are located within a specific region.

[0202] A "central database" is a database system used to centrally store and manage various types of information.

[0203] An "intelligent agent" is a program that uses artificial intelligence technology to autonomously process and judge information, and to provide the user with the most appropriate answers and suggestions.

[0204] "Planning tools" refer to functions or methods for efficiently combining and coordinating the schedules and plans of educators.

[0205] "Educational content" refers to learning plans and materials created according to the progress and individual needs of specific learners.

[0206] "Communication functions" refer to features that allow users to share information and communicate with each other.

[0207] An "emotion recognition engine" is a system that analyzes and identifies emotions from the user's voice, facial expressions, etc., and provides the results.

[0208] A "consumer robot" is a robot intended for use within the home and capable of providing educational support, household assistance, and other similar functions.

[0209] This invention provides a system for collecting information from local educational institutions, integrating it, and storing it in a central database. The server collects schedule and event information from each educational institution and stores it in the central database. This allows users to always access the latest information.

[0210] Users inquire about educational resources and information through consumer robots. The robots use an emotion recognition engine to analyze the user's emotional state and adjust educational resources based on the analysis results. The emotion recognition engine uses the user's voice and facial expressions as input data, converts the voice into text data using Google Cloud Speech-to-Text, and analyzes the emotions.

[0211] This system utilizes intelligent agents to comprehensively assess the user's questions and emotional state. For example, if it determines that the user is feeling anxious, it adjusts its approach to provide more detailed and reassuring information. Specifically, if the user inputs "I'm anxious about the next test," the server will provide a learning plan and support materials through a robot to alleviate that anxiety.

[0212] To enhance educational support within the home, consumer robots will be used. This will allow learners to have a consistent educational experience even at home. For example, if a child is having trouble with math homework, they can consult the robot. In this case, the robot will analyze the child's emotions and provide easy-to-understand learning materials along with reassuring words.

[0213] By utilizing generative AI models, highly personalized educational support becomes possible, providing a learning experience tailored to each individual learner. Furthermore, the knowledge and experience of the elderly can be used as educational resources, promoting two-way learning exchange.

[0214] As an example of a prompt, the AI ​​will be input with a message like, "When a child is stressed about math homework, please suggest how to encourage them and what learning materials to provide," and a method will be built to provide appropriate learning support.

[0215] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0216] Step 1:

[0217] A user asks educational questions to a consumer robot. Voice data is provided as input. A voice input device captures the voice and sends it to a server.

[0218] Step 2:

[0219] The server receives the audio data and uses an emotion recognition engine to convert the speech to text. The Google Cloud Speech-to-Text service is used for this conversion from speech to text data. The output is text data.

[0220] Step 3:

[0221] The server analyzes text data to recognize the user's emotions. This analysis applies an emotion recognition algorithm, which analyzes the types and tone of words the user uses. As a result, the server identifies the user's emotional state and outputs emotion state data.

[0222] Step 4:

[0223] The server uses intelligent agents to comprehensively evaluate the user's questions and emotional state. Here, the server combines the questions and emotional state to select the most appropriate educational resources and support methods. This process involves database access, referencing past data and learning resources.

[0224] Step 5:

[0225] The server transmits selected educational resources and support content to the consumer robot. The robot provides feedback and advice to the user as voice data. The output is the educational advice and resource information transmitted to the user.

[0226] Step 6:

[0227] Users receive information from the robot and use it in their learning activities. Specifically, they can learn based on the presented materials, and can repeat the learning process or ask further questions as needed.

[0228] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0229] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0230] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0231] [Second Embodiment]

[0232] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0233] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0234] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0235] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0236] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0237] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0238] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0239] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0240] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0241] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0242] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0243] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0244] This invention provides an integrated platform for effectively supporting local education. Specifically, it describes a system that collects information from educational institutions and uses AI technology to provide each user with the most suitable educational resources based on that information.

[0245] The server collects information from various educational institutions within the region (schools, libraries, cram schools, etc.). Specifically, it collects data on facility schedules, event information, and available resources, and organizes and stores this information in a central database.

[0246] When a user searches for specific information or enters a question through their device, an AI agent quickly extracts relevant information from its database based on the request and presents it to the user in the most optimal format. This response may include a list of facilities or suggestions for specific services that meet detailed criteria.

[0247] Furthermore, the server has a function to automatically manage educators' schedules. When educators teach at different schools or online platforms, it efficiently adjusts their schedules to avoid overlapping class times. This function maximizes the efficiency of educational activities.

[0248] For learners, the server monitors their progress and learning history, and provides individually customized educational content. This includes video materials, sets of exercises, or materials related to new learning topics. This customization ensures that each learner can continue learning in the most optimal way possible.

[0249] Furthermore, the system incorporates a matching function to effectively utilize elderly individuals within local communities as educational resources. The server matches registered elderly individuals with educational activity needs based on their skills and experience, encouraging them to participate, for example, as workshop instructors. This mechanism improves the overall quality of education in the community.

[0250] Ultimately, it includes chat and notification features to facilitate smooth communication between users. This allows teachers, parents, and learners to share necessary information and collaborate in a timely manner.

[0251] Thus, the present invention provides a typical embodiment of a system that achieves improved efficiency and quality in local education through the coordinated operation of its various functions.

[0252] The following describes the processing flow.

[0253] Step 1:

[0254] The server collects information from the websites and public databases of various educational institutions within the region. This information includes the institutions' schedules, events, and available resources, and is stored as structured data in a central database.

[0255] Step 2:

[0256] Users can input questions about education-related information and resources into the system via their devices. User questions are in natural language, and the interface is designed to be intuitive.

[0257] Step 3:

[0258] The server receives the input question, and an AI agent analyzes its content. Using natural language processing technology, it understands the intent of the question and searches for relevant information in the database.

[0259] Step 4:

[0260] The server generates the best possible answer to the user's question and sends it to the user's terminal. The answer includes information about the relevant educational institution's facilities, available resources, and other information that matches the user's specified criteria.

[0261] Step 5:

[0262] The server automatically retrieves educators' current schedules and manages them to avoid overlaps and conflicts. Schedules are coordinated across multiple educational institutions and online platforms.

[0263] Step 6:

[0264] The server analyzes learner progress data and generates personalized educational content. Based on progress reports and past learning content, a process is performed to recommend appropriate learning resources.

[0265] Step 7:

[0266] The server implements a process to match the skills of local seniors with the educational activity needs. Based on registered profiles, it matches seniors with appropriate educational projects, enabling them to participate.

[0267] Step 8:

[0268] To facilitate information sharing among users, the server provides chat and notification functions. This ensures that relevant information is delivered to stakeholders in real time, facilitating smooth communication.

[0269] (Example 1)

[0270] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0271] To improve and streamline local education, it is necessary to collect information from educational institutions, coordinate educators' schedules, provide individualized support to learners, utilize the elderly as educational resources, and facilitate smooth communication among users. However, there are limited systems that can effectively integrate these challenges and respond in real time. Therefore, there is a need to provide a comprehensive platform that enables efficient information management and communication in local education.

[0272] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0273] In this invention, the server includes means for collecting data from an information provision structure, synthesizing it, and storing it in a management data structure; intelligent agent means for immediately presenting appropriate information sources in response to user inquiries based on the collected data; and planning means for automatically scheduling and adjusting the schedules of educators to streamline educational activities. This enables the integration and efficient management of information in local education, allowing users to receive personalized educational services and educators to enjoy non-duplicate scheduling. Furthermore, it facilitates the effective utilization of the elderly and effective information sharing.

[0274] An "information provision structure" is a collection of various data, such as schedules, events, and resources, provided by educational institutions and organizations.

[0275] A "management data structure" is a database system that systematically stores, organizes, and makes accessible collected information.

[0276] An "intelligent agent" is a software program that uses artificial intelligence to analyze collected data and provide appropriate information in response to user inquiries.

[0277] "Planning tools" are tools and algorithms that automatically analyze the schedules of educators and optimize them to eliminate duplication and waste.

[0278] "Users" refers to individuals or organizations that collect information, receive, or provide educational services through this system.

[0279] "Educational professionals" is a general term for professionals involved in educational activities, including teachers and instructors.

[0280] "Elderly people" refers to older members of the community who may have the potential to provide knowledge and experience to learners and other users.

[0281] "Multifunctional communication" refers to communication means including chat and notification systems that facilitate efficient and smooth information exchange among users.

[0282] This invention provides an integrated information management system for supporting regional education. This system aims at data collection from information-providing structures, analysis, and effective information provision to users. The server collects data such as schedules, event information, resources, etc. from educational institutions and organizations within the region. This includes school class schedules and event notices at libraries. The server stores these data in a management data structure and uses natural language processing technology and machine learning algorithms to present effective information. As specific technologies, database management systems based on Python and Java are generally utilized.

[0283] Users using the terminal can search for the information they need in real time through the system. For example, when a parent is looking for a workshop held in the neighborhood for their child, the AI agent immediately provides a list of events in response to that request. A generative AI model is utilized in the platform that supports this process to analyze prompt sentences in response to inquiries from users and generate optimal answers.

[0284] Educational staff members' schedules are managed by the server, avoiding duplication of class timetables and enabling efficient educational activities. For example, when an educator teaches at multiple schools or online platforms, the server coordinates their schedules and generates adjustment plans as needed.

[0285] Furthermore, this system includes a form of utilizing the knowledge and experience of the elderly as educational resources. The server matches the profiles of the elderly with their educational needs and promotes their participation as lecturers in local workshops and lectures. As a specific example, by inputting a prompt sentence such as "Please provide information on the upcoming children's science event in the local area. Also, check if there are any elderly candidates who can participate as lecturers in that event.", information that promotes the participation of the elderly can be obtained quickly.

[0286] With the above configuration, the system realizes an improvement in the quality and efficiency of local education, and provides users with individualized information and opportunities for effective communication.

[0287] The flow of the specific process in Example 1 will be described using FIG. 11.

[0288] Step 1:

[0289] The server collects data from the information provision structure. Specifically, it uses API access and scraping techniques to obtain schedule and event information from the websites and data feeds of educational institutions within the region.

[0290] The input is the website or system of an educational institution, and the output is a list of structured schedule data and event information.

[0291] Specific operation: The server executes an automated crawling script to periodically collect the specified information.

[0292] Step 2:

[0293] The server organizes and stores the collected data in a management data structure. In this process, data cleaning and normalization are performed, and errors and duplicates are checked.

[0294] The input is schedule and event information in raw data format, and the output is a dataset stored in a consistent database.

[0295] Specific operation: Use the database injection API to add normalized data as an entry.

[0296] Step 3:

[0297] The user uses the device to search for specific information or enter a question. Search keywords or question sentences are entered via the user interface.

[0298] The input is the user's search query, and the output is a list of search results related to the relevant information.

[0299] Specific operation: The user enters a keyword in the terminal's GUI and clicks the "Search" button.

[0300] Step 4:

[0301] The AI ​​agent instantly extracts relevant data from the managed data structure based on user questions and searches. A natural language processing model is used in this process.

[0302] The input is the user's search query, and the output is an optimized dataset or list of information presented to the user.

[0303] Specific operation: The AI ​​agent interprets queries and accesses the database using SQL or similar query languages.

[0304] Step 5:

[0305] The server analyzes and automatically adjusts the schedules of educators. Duplicate tasks and classes are detected, and an optimal time schedule is suggested.

[0306] The input is the existing schedule data of the educator, and the output is the adjusted schedule plan.

[0307] Specific operation: The server applies a scheduling algorithm to generate an adjusted schedule.

[0308] Step 6:

[0309] The server generates individualized educational support content based on the learner's progress and historical data. The content targeted includes videos, exercise questions, and additional materials.

[0310] The input is the learner's historical data points, and the output is a group of customized educational content.

[0311] Specific operation: The server analyzes the enrollment data and uses AI inference to map the optimal content.

[0312] Step 7:

[0313] The server matches the needs of the elderly with educational events. The prompt text provided by the user is processed, and appropriate lecturers and eligible elderly people are assigned.

[0314] The input is the prompt text from the user, and the output is a list of matched elderly people.

[0315] Specific operation: Recommendations are made using a matching algorithm with the profile database.

[0316] Step 8:

[0317] Use the terminal to enable communication between users. Chat functions and push notifications are used to exchange necessary information and messages.

[0318] The input is the trigger for a message or contact initiated by the user, and the output is the notification or message forwarding to the recipient.

[0319] Specific operation: Messages are sent and received in real time via the chat application on the device.

[0320] (Application Example 1)

[0321] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0322] Modern communities lack systems for efficiently collecting and providing educational resources. Comprehensively managing information on local educational institutions such as schools, libraries, and cram schools, and providing it promptly as needed, is crucial for ensuring optimal learning for each student. However, various challenges exist, including information fragmentation, scheduling difficulties for educators, and underutilization of senior citizens as local educational resources. Furthermore, providing this information to learners in real time and creating an optimal learning environment remains challenging.

[0323] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0324] This invention includes a server that collects information from educational facilities within a region, integrates it, and stores it in a central data management device; a server that uses an artificial intelligence agent to present the most suitable resources in real time in response to user inquiries; and a server that automatically adjusts the schedules of educators to improve the efficiency of educational activities. This enables centralized management of educational resources within a region and provides learners with the most suitable educational information in real time.

[0325] "Educational facilities within a region" refers to various institutions and organizations located in a specific area that are dedicated to education, such as schools, libraries, and cram schools.

[0326] "Means for collecting information, integrating it, and storing it in a central data management system" refers to a mechanism for collecting information provided by educational institutions in digital format, compiling and organizing it, and storing it on a server.

[0327] "A means of presenting the most suitable resources in real time using an artificial intelligence agent" refers to a function that utilizes AI technology to instantly provide appropriate educational resources in response to questions entered by users.

[0328] "Methods for automatically adjusting the schedules of educators and improving the efficiency of educational activities" refers to methods for automatically managing and adjusting the work schedules of teachers, lecturers, and other people involved in education, thereby achieving efficient educational activities without duplication.

[0329] "Learners" refer to individuals who acquire knowledge through local educational facilities or online platforms.

[0330] "Providing information to learners in real time" means processing information quickly in response to user requests and delivering the necessary educational information to learners immediately.

[0331] The system to realize this application will be built around cloud-based data collection and artificial intelligence. The server will collect information regularly provided by various educational facilities within the region using APIs or web scraping techniques, integrate it, and store it in a database. High-performance servers are required as hardware, and cloud services such as Amazon Web Services (AWS) and Google Cloud Platform are suitable.

[0332] The collected data is processed using Python and delivered as a web application using the Flask framework. The server utilizes TensorFlow and PyTorch as artificial intelligence models to provide users with the most suitable educational resources in real time. The AI ​​agent uses natural language processing techniques to quickly respond to user questions and select and display the necessary information.

[0333] Furthermore, to enable educators to manage their schedules, it integrates with the Google Calendar API and Microsoft Graph API, and includes a function to automatically adjust appointments. This will improve the efficiency of educators' time management.

[0334] As a concrete example, when a user enters the prompt "Please tell me which workshops are available next week" into a smartphone app, the server searches its database for relevant information, and the AI ​​agent presents the most suitable resources. The generative AI model used in this process is an advanced natural language processing model such as BERT.

[0335] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0336] Step 1:

[0337] The server retrieves information from educational facilities within the region via APIs. Inputs include schedules and resource information from each facility, and output is a unified dataset in CSV or JSON format. This data is stored in a database for subsequent processing.

[0338] Step 2:

[0339] The server receives a prompt from the user. The input is a question in natural language, which is parsed by the AI ​​agent. A generative AI model (e.g., BERT) processes this prompt and understands the user's intent. The output is the user's intent, organized as a query.

[0340] Step 3:

[0341] The AI ​​agent retrieves relevant information from a database based on user intent. The input is organized user intent, which generates database queries and executes requests. The output is a list of relevant educational resource information.

[0342] Step 4:

[0343] The server organizes the retrieved resource information for return to the user. The input is a list of educational resources, to which prioritization and formatting are applied. The output is the final response format for presentation to the user (e.g., HTML content in list format).

[0344] Step 5:

[0345] The terminal receives responses from the server and displays them on the user's screen. The input is the final response from the server, and the output is the information visually displayed on the user interface. Based on this information, the user can decide which workshops to participate in and which services to use.

[0346] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0347] This invention provides users with a more personalized educational experience by combining an emotion recognition engine with a local educational support system. This enables interaction that responds to the user's emotions, thereby improving the quality of education. Specific embodiments are described below.

[0348] The server collects data from educational institutions within the region and stores it in a central database. This information includes schedules, events, and resource information for each facility. This ensures that users always have access to the most up-to-date information.

[0349] Users can inquire about educational resources and information through the device. The device is equipped with an emotion recognition engine that uses voice and text data as input. This engine analyzes the user's emotions from the tone and speed of their voice and the content of their text to determine how the user is feeling when seeking information.

[0350] The server uses an AI agent to comprehensively analyze the user's questions and emotional state. For example, if the user is feeling anxious, the server adjusts its approach to provide more detailed and reassuring information. For instance, if the user inputs "I'm anxious about the next test," the server will suggest a learning plan and various learning support content to alleviate that anxiety.

[0351] The scheduling system efficiently manages educators' schedules, automatically updating them based on new information. It also generates customized educational content that takes learners' progress and emotional states into account. The emotional engine suggests content that adjusts difficulty levels or includes encouraging words if learners are experiencing stress.

[0352] Furthermore, it includes a matching function to utilize local seniors as educational resources. The emotional engine also evaluates the attitude of seniors towards the educational activities they wish to participate in, ensuring appropriate matching. Communication functions are also integrated, supporting smooth information sharing among users and delivering important notifications in real time.

[0353] Thus, by combining an emotion recognition engine, the present invention provides a system that enables more flexible and effective educational support for users, allowing all participants to enjoy a more fulfilling educational environment.

[0354] The following describes the processing flow.

[0355] Step 1:

[0356] The server collects important educational resource information from websites and databases published by educational institutions within the region. This includes opening hours, event information, and lists of available facilities for each institution. This information is updated in real time and integrated into a central database.

[0357] Step 2:

[0358] Users access the system using a terminal and enter questions about specific educational information or resources. This input can be done using voice commands or text input.

[0359] Step 3:

[0360] The device sends the user's voice and text data to an emotion recognition engine. The engine analyzes the tone of voice, speaking speed, and keywords in the text to determine the user's emotional state. For example, if a user says "Teach me about this long homework" in a tired tone, the engine might estimate that the user is feeling frustrated or stressed.

[0361] Step 4:

[0362] The server uses an AI agent to process user questions and sentiment data. Considering the sentiment data, the server gains a deeper understanding of the intent behind the questions and selects the appropriate level of information. If the user is feeling anxious, the server presents more detailed and reassuring information.

[0363] Step 5:

[0364] The server generates user-specific educational content based on emotional data, including stress-reducing elements where necessary. This content is presented to the user in the form of surveys and activities.

[0365] Step 6:

[0366] When a user views suggested information or content on their device and enters further questions, their responses are also analyzed again by the emotion recognition engine and fed back to the server. This enables more personalized responses.

[0367] Step 7:

[0368] The server matches data on the skills and desired activities of older adults as educational resources, finding the optimal match with users who wish to engage in educational activities. Emotional data is also considered in this process to assess whether older adults are motivated to participate in the activities.

[0369] Step 8:

[0370] The communication function activates, and the server delivers notifications and messages in real time to facilitate information sharing among users. This function strengthens collaboration among educators.

[0371] (Example 2)

[0372] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0373] In today's educational environment, providing education that meets the individual needs and emotional states of learners is a challenge. Furthermore, there is a need for the effective utilization of educational resources through interaction with local elderly residents, and for efficient information sharing among learners. A flexible and effective educational support system that addresses these needs has yet to be established.

[0374] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0375] This invention includes a server that collects information from educational institutions within a region, integrates it, and stores it in a central database; an emotion recognition means that analyzes the user's voice and text input and estimates their emotional state; and a schedule management means that automatically adjusts the educator's activity schedule and streamlines educational activities. This enables the presentation of optimal educational information tailored to the user's emotions and individual learning needs, the effective provision of educational resources, and comprehensive educational support through collaboration with local communities.

[0376] "Information processing means" refers to a function that, in response to user inquiries, presents the most suitable educational resources in real time based on collected information.

[0377] "Emotion recognition means" refers to technology that analyzes a user's voice or text input to estimate their emotional state and use that information to provide appropriate information.

[0378] A "correction mechanism" is a function that optimizes the information provided based on the user's emotional state and suggests content that is appropriate to the user's situation.

[0379] A "schedule management system" is a management function that automatically adjusts the activity schedules of educators and improves the efficiency of educational activities.

[0380] "Mediation means" refers to functions that connect elderly people in the community with users who want to participate in educational activities, and support the effective use of local resources.

[0381] "Communication functions" are features that enable smooth information sharing and communication among users within the system.

[0382] Embodiments of the present invention are described below.

[0383] The server is responsible for collecting data from educational institutions within the region and storing it in a central database. Data collection is performed using API communication over the internet, retrieving schedules, event information, and resource data provided by educational institutions. The server filters this data, removing duplicates and incorrect information, and then efficiently stores it in the database, making it easy for users to access the latest information.

[0384] The device analyzes voice and text input from the user using an emotion recognition engine. This engine employs a machine learning model to analyze input data in order to recognize the user's emotional state. Specifically, it estimates emotions from the tone and speed of voice data and the content of text. For example, if a user enters the prompt "Please tell me my schedule for next week," the device is designed to take into account not only the acquisition of static information but also the user's current emotional state.

[0385] The server uses an AI agent to analyze the user's emotional state and questions, optimizing the information it provides. This AI agent incorporates natural language processing (NLP) technology, meticulously analyzing user input to select the most relevant information and resources. If the user is feeling anxious, the server prioritizes presenting resources that provide reassurance.

[0386] Furthermore, the server is equipped with a schedule management function to automatically adjust educators' activity schedules, thereby improving the efficiency of educational activities. It also has the ability to evaluate learners' progress and provide personalized educational resources. To achieve this, it utilizes a generative AI model to generate learning plans and practice problems tailored to the learners' progress.

[0387] Ultimately, the system connects local seniors with users who wish to engage in educational activities, providing opportunities to effectively utilize their knowledge and experience. The server manages this process comprehensively and provides example inputs as prompts to ensure an efficient learning environment and support users in smoothly using the system.

[0388] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0389] Step 1:

[0390] The server collects schedules, event information, and resource data from educational institutions within the region. Input consists of data submitted by each educational institution, which the server stores in a central database. The server processes the data to check for duplicates and standardize its format, storing it in an organized manner.

[0391] Step 2:

[0392] Users make inquiries via text or voice through the device. The input is a prompt statement uttered by the user (e.g., "Please tell me the schedule for next week"), and the device uses an emotion recognition engine to analyze the input data. The emotion recognition engine analyzes the tone and speed of the voice and the content of the text to estimate the user's emotional state.

[0393] Step 3:

[0394] The server, upon receiving data transmitted from the terminal, performs analysis using an AI agent. The input consists of the user's question and sentiment data, while the output is optimized information and resources. The server uses natural language processing technology to deeply analyze the user's intent and provide information tailored to their emotional state.

[0395] Step 4:

[0396] The server automatically adjusts educators' schedules to improve the efficiency of educational activities. Input is the latest schedule and resource information, and output is automatically updated schedules. The server dynamically manages this updated information and notifies educators and learners.

[0397] Step 5:

[0398] The server evaluates the learner's progress and generates personalized educational resources. The input is the learner's historical data, and the output is a customized learning plan and practice problems. A generative AI model is used to suggest appropriate learning content based on the learner's progress.

[0399] Step 6:

[0400] The server acts as an intermediary between local seniors and those seeking educational activities. Inputs include the seniors' registration information and the users' preferences; output is a personalized matching list. The server analyzes the registration data to derive appropriate pairings.

[0401] Step 7:

[0402] To facilitate information sharing among users, the server provides real-time communication capabilities. Inputs include new event information and announcements, while outputs include push notifications and messages. The server immediately sends this information to user terminals, supporting smooth communication.

[0403] (Application Example 2)

[0404] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0405] In modern families, there is a demand for individualized and efficient learning, but traditional educational methods make it difficult to flexibly provide learning content according to the emotions and progress of individual learners. Furthermore, there is a lack of means to deepen understanding of learners when providing educational support within the home. In addition, there is a need for means to enhance educational support throughout the community by utilizing the knowledge and experience of the elderly as educational resources.

[0406] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0407] This invention includes a server that collects information from local educational institutions, integrates it, and stores it in a central database; a server that analyzes the user's emotional state using an emotion recognition engine and adjusts educational resources based on the analysis results; and an implementation method that uses a consumer robot to provide educational support to the user in the home. This makes it possible to provide education tailored to each learner and to provide personalized learning support that takes emotions into consideration. Furthermore, it is expected to promote interactive learning that utilizes the knowledge and experience of the elderly and enhance the educational effect throughout the community.

[0408] "Educational institutions within a region" refers to educational organizations and facilities such as schools, libraries, and learning centers that are located within a specific region.

[0409] A "central database" is a database system used to centrally store and manage various types of information.

[0410] An "intelligent agent" is a program that uses artificial intelligence technology to autonomously process and judge information, and to provide the user with the most appropriate answers and suggestions.

[0411] "Planning tools" refer to functions or methods for efficiently combining and coordinating the schedules and plans of educators.

[0412] "Educational content" refers to learning plans and materials created according to the progress and individual needs of specific learners.

[0413] "Communication functions" refer to features that allow users to share information and communicate with each other.

[0414] An "emotion recognition engine" is a system that analyzes and identifies emotions from the user's voice, facial expressions, etc., and provides the results.

[0415] A "consumer robot" is a robot intended for use within the home and capable of providing educational support, household assistance, and other similar functions.

[0416] This invention provides a system for collecting information from local educational institutions, integrating it, and storing it in a central database. The server collects schedule and event information from each educational institution and stores it in the central database. This allows users to always access the latest information.

[0417] Users inquire about educational resources and information through consumer robots. The robots use an emotion recognition engine to analyze the user's emotional state and adjust educational resources based on the analysis results. The emotion recognition engine uses the user's voice and facial expressions as input data, converts the voice into text data using Google Cloud Speech-to-Text, and analyzes the emotions.

[0418] This system utilizes intelligent agents to comprehensively assess the user's questions and emotional state. For example, if it determines that the user is feeling anxious, it adjusts its approach to provide more detailed and reassuring information. Specifically, if the user inputs "I'm anxious about the next test," the server will provide a learning plan and support materials through a robot to alleviate that anxiety.

[0419] To enhance educational support within the home, consumer robots will be used. This will allow learners to have a consistent educational experience even at home. For example, if a child is having trouble with math homework, they can consult the robot. In this case, the robot will analyze the child's emotions and provide easy-to-understand learning materials along with reassuring words.

[0420] By utilizing generative AI models, highly personalized educational support becomes possible, providing a learning experience tailored to each individual learner. Furthermore, the knowledge and experience of the elderly can be used as educational resources, promoting two-way learning exchange.

[0421] As an example of a prompt, the AI ​​will be input with a message like, "When a child is stressed about math homework, please suggest how to encourage them and what learning materials to provide," and a method will be built to provide appropriate learning support.

[0422] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0423] Step 1:

[0424] A user asks educational questions to a consumer robot. Voice data is provided as input. A voice input device captures the voice and sends it to a server.

[0425] Step 2:

[0426] The server receives the audio data and uses an emotion recognition engine to convert the speech to text. The Google Cloud Speech-to-Text service is used for this conversion from speech to text data. The output is text data.

[0427] Step 3:

[0428] The server analyzes text data to recognize the user's emotions. This analysis applies an emotion recognition algorithm, which analyzes the types and tone of words the user uses. As a result, the server identifies the user's emotional state and outputs emotion state data.

[0429] Step 4:

[0430] The server uses intelligent agents to comprehensively evaluate the user's questions and emotional state. Here, the server combines the questions and emotional state to select the most appropriate educational resources and support methods. This process involves database access, referencing past data and learning resources.

[0431] Step 5:

[0432] The server transmits selected educational resources and support content to the consumer robot. The robot provides feedback and advice to the user as voice data. The output is the educational advice and resource information transmitted to the user.

[0433] Step 6:

[0434] Users receive information from the robot and use it in their learning activities. Specifically, they can learn based on the presented materials, and can repeat the learning process or ask further questions as needed.

[0435] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0436] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0437] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0438] [Third Embodiment]

[0439] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0440] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0441] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0442] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0443] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0444] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0445] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0446] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0447] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0448] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0449] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0450] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0451] This invention provides an integrated platform for effectively supporting local education. Specifically, it describes a system that collects information from educational institutions and uses AI technology to provide each user with the most suitable educational resources based on that information.

[0452] The server collects information from various educational institutions within the region (schools, libraries, cram schools, etc.). Specifically, it collects data on facility schedules, event information, and available resources, and organizes and stores this information in a central database.

[0453] When a user searches for specific information or enters a question through their device, an AI agent quickly extracts relevant information from its database based on the request and presents it to the user in the most optimal format. This response may include a list of facilities or suggestions for specific services that meet detailed criteria.

[0454] Furthermore, the server has a function to automatically manage educators' schedules. When educators teach at different schools or online platforms, it efficiently adjusts their schedules to avoid overlapping class times. This function maximizes the efficiency of educational activities.

[0455] For learners, the server monitors their progress and learning history, and provides individually customized educational content. This includes video materials, sets of exercises, or materials related to new learning topics. This customization ensures that each learner can continue learning in the most optimal way possible.

[0456] Furthermore, the system incorporates a matching function to effectively utilize elderly individuals within local communities as educational resources. The server matches registered elderly individuals with educational activity needs based on their skills and experience, encouraging them to participate, for example, as workshop instructors. This mechanism improves the overall quality of education in the community.

[0457] Ultimately, it includes chat and notification features to facilitate smooth communication between users. This allows teachers, parents, and learners to share necessary information and collaborate in a timely manner.

[0458] Thus, the present invention provides a typical embodiment of a system that achieves improved efficiency and quality in local education through the coordinated operation of its various functions.

[0459] The following describes the processing flow.

[0460] Step 1:

[0461] The server collects information from the websites and public databases of various educational institutions within the region. This information includes the institutions' schedules, events, and available resources, and is stored as structured data in a central database.

[0462] Step 2:

[0463] Users can input questions about education-related information and resources into the system via their devices. User questions are in natural language, and the interface is designed to be intuitive.

[0464] Step 3:

[0465] The server receives the input question, and an AI agent analyzes its content. Using natural language processing technology, it understands the intent of the question and searches for relevant information in the database.

[0466] Step 4:

[0467] The server generates the best possible answer to the user's question and sends it to the user's terminal. The answer includes information about the relevant educational institution's facilities, available resources, and other information that matches the user's specified criteria.

[0468] Step 5:

[0469] The server automatically retrieves educators' current schedules and manages them to avoid overlaps and conflicts. Schedules are coordinated across multiple educational institutions and online platforms.

[0470] Step 6:

[0471] The server analyzes learner progress data and generates personalized educational content. Based on progress reports and past learning content, a process is performed to recommend appropriate learning resources.

[0472] Step 7:

[0473] The server implements a process to match the skills of local seniors with the educational activity needs. Based on registered profiles, it matches seniors with appropriate educational projects, enabling them to participate.

[0474] Step 8:

[0475] To facilitate information sharing among users, the server provides chat and notification functions. This ensures that relevant information is delivered to stakeholders in real time, facilitating smooth communication.

[0476] (Example 1)

[0477] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0478] To improve and streamline local education, it is necessary to collect information from educational institutions, coordinate educators' schedules, provide individualized support to learners, utilize the elderly as educational resources, and facilitate smooth communication among users. However, there are limited systems that can effectively integrate these challenges and respond in real time. Therefore, there is a need to provide a comprehensive platform that enables efficient information management and communication in local education.

[0479] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0480] In this invention, the server includes means for collecting data from an information provision structure, synthesizing it, and storing it in a management data structure; intelligent agent means for immediately presenting appropriate information sources in response to user inquiries based on the collected data; and planning means for automatically scheduling and adjusting the schedules of educators to streamline educational activities. This enables the integration and efficient management of information in local education, allowing users to receive personalized educational services and educators to enjoy non-duplicate scheduling. Furthermore, it facilitates the effective utilization of the elderly and effective information sharing.

[0481] An "information provision structure" is a collection of various data, such as schedules, events, and resources, provided by educational institutions and organizations.

[0482] A "management data structure" is a database system that systematically stores, organizes, and makes accessible collected information.

[0483] An "intelligent agent" is a software program that uses artificial intelligence to analyze collected data and provide appropriate information in response to user inquiries.

[0484] "Planning tools" are tools and algorithms that automatically analyze the schedules of educators and optimize them to eliminate duplication and waste.

[0485] "Users" refers to individuals or organizations that collect information, receive, or provide educational services through this system.

[0486] "Educational professionals" is a general term for professionals involved in educational activities, including teachers and instructors.

[0487] "Elderly people" refers to older members of the community who may have the potential to provide knowledge and experience to learners and other users.

[0488] "Multifunctional communication" refers to communication methods, including chat and notification systems, that facilitate efficient and smooth information exchange among users.

[0489] This invention provides an integrated information management system to support local education. The system aims to collect and analyze data from information provision structures and to effectively provide information to users. The server collects data such as schedules, event information, and resources from local educational institutions and organizations. This includes school class times and library event announcements. The server stores this data in a managed data structure and uses natural language processing techniques and machine learning algorithms to present information effectively. Specifically, database management systems based on Python or Java are commonly used.

[0490] Users of the device can search for the information they need in real time through the system. For example, when a parent searches for nearby workshops for their child, the AI ​​agent instantly provides a list of events in response to their request. The platform supporting this process utilizes a generative AI model that analyzes prompt sentences in response to user inquiries and generates the optimal answer.

[0491] Educators can have their schedules managed by the server, avoiding overlaps in class timetables and enabling efficient teaching activities. For example, when educators teach at multiple schools or online platforms, the server coordinates their schedules and generates adjustment plans as needed.

[0492] Furthermore, this system includes a model for utilizing the knowledge and experience of older adults as educational resources. The server matches older adults' profiles with their educational needs and facilitates their participation as instructors in local workshops and courses. For example, by entering a prompt such as, "Please provide information on children's science events taking place in the following area. Also, please check if there are any older adult candidates who can participate as instructors at these events," information that facilitates older adult participation can be obtained quickly.

[0493] With the above configuration, the system will improve the quality and efficiency of local education, and provide users with personalized information and opportunities for effective communication.

[0494] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0495] Step 1:

[0496] The server collects data from the information provision structure. Specifically, it uses API access and scraping techniques to obtain schedules and event information from the websites and data feeds of educational institutions within the region.

[0497] The input is the web pages or systems of educational institutions, and the output is a list of structured schedule data and event information.

[0498] Specific operation: The server executes an automated crawling script to periodically collect specified information.

[0499] Step 2:

[0500] The server organizes and stores the collected data in a managed data structure. This process involves data cleaning and normalization, and checks for errors and duplicates.

[0501] The input is schedule and event information in raw data format, and the output is a dataset stored in a consistent database.

[0502] Specific operation: Use the database injection API to add normalized data as an entry.

[0503] Step 3:

[0504] The user uses the device to search for specific information or enter a question. Search keywords or question sentences are entered via the user interface.

[0505] The input is the user's search query, and the output is a list of search results related to the relevant information.

[0506] Specific operation: The user enters a keyword in the terminal's GUI and clicks the "Search" button.

[0507] Step 4:

[0508] The AI ​​agent instantly extracts relevant data from the managed data structure based on user questions and searches. A natural language processing model is used in this process.

[0509] The input is the user's search query, and the output is an optimized dataset or list of information presented to the user.

[0510] Specific operation: The AI ​​agent interprets queries and accesses the database using SQL or similar query languages.

[0511] Step 5:

[0512] The server analyzes and automatically adjusts the schedules of educators. Duplicate tasks and classes are detected, and an optimal time schedule is suggested.

[0513] The input is the educator's existing schedule data, and the output is an adjusted schedule proposal.

[0514] Specific operation: The server applies a scheduling algorithm to generate the adjusted schedule.

[0515] Step 6:

[0516] The server generates personalized educational support based on the learner's progress and history data. This support includes videos, exercises, and supplementary materials.

[0517] The input consists of learner history data points, and the output is a customized set of educational content.

[0518] Specific operation: The server analyzes course registration data and uses AI inference to map the most suitable content.

[0519] Step 7:

[0520] The server matches the needs of seniors with those of educational events. User-provided prompts are processed, and suitable instructors and eligible seniors are assigned.

[0521] The input is a prompt from the user, and the output is a list of matched elderly individuals.

[0522] Specific operation: Recommendations are made using a matching algorithm with a profile database.

[0523] Step 8:

[0524] The system uses devices to facilitate communication between users. Chat functions and push notifications are used to exchange necessary information and messages.

[0525] The input is the trigger for a message or contact initiated by the user, and the output is the notification or message forwarding to the recipient.

[0526] Specific operation: Messages are sent and received in real time via the chat application on the device.

[0527] (Application Example 1)

[0528] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0529] Modern communities lack systems for efficiently collecting and providing educational resources. Comprehensively managing information on local educational institutions such as schools, libraries, and cram schools, and providing it promptly as needed, is crucial for ensuring optimal learning for each student. However, various challenges exist, including information fragmentation, scheduling difficulties for educators, and underutilization of senior citizens as local educational resources. Furthermore, providing this information to learners in real time and creating an optimal learning environment remains challenging.

[0530] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0531] This invention includes a server that collects information from educational facilities within a region, integrates it, and stores it in a central data management device; a server that uses an artificial intelligence agent to present the most suitable resources in real time in response to user inquiries; and a server that automatically adjusts the schedules of educators to improve the efficiency of educational activities. This enables centralized management of educational resources within a region and provides learners with the most suitable educational information in real time.

[0532] "Educational facilities within a region" refers to various institutions and organizations located in a specific area that are dedicated to education, such as schools, libraries, and cram schools.

[0533] "Means for collecting information, integrating it, and storing it in a central data management system" refers to a mechanism for collecting information provided by educational institutions in digital format, compiling and organizing it, and storing it on a server.

[0534] "A means of presenting the most suitable resources in real time using an artificial intelligence agent" refers to a function that utilizes AI technology to instantly provide appropriate educational resources in response to questions entered by users.

[0535] "Methods for automatically adjusting the schedules of educators and improving the efficiency of educational activities" refers to methods for automatically managing and adjusting the work schedules of teachers, lecturers, and other people involved in education, thereby achieving efficient educational activities without duplication.

[0536] "Learners" refer to individuals who acquire knowledge through local educational facilities or online platforms.

[0537] "Providing information to learners in real time" means processing information quickly in response to user requests and delivering the necessary educational information to learners immediately.

[0538] The system to realize this application will be built around cloud-based data collection and artificial intelligence. The server will collect information regularly provided by various educational facilities within the region using APIs or web scraping techniques, integrate it, and store it in a database. High-performance servers are required as hardware, and cloud services such as Amazon Web Services (AWS) and Google Cloud Platform are suitable.

[0539] The collected data is processed using Python and delivered as a web application using the Flask framework. The server utilizes TensorFlow and PyTorch as artificial intelligence models to provide users with the most suitable educational resources in real time. The AI ​​agent uses natural language processing techniques to quickly respond to user questions and select and display the necessary information.

[0540] Furthermore, to enable educators to manage their schedules, it integrates with the Google Calendar API and Microsoft Graph API, and includes a function to automatically adjust appointments. This will improve the efficiency of educators' time management.

[0541] As a concrete example, when a user enters the prompt "Please tell me which workshops are available next week" into a smartphone app, the server searches its database for relevant information, and the AI ​​agent presents the most suitable resources. The generative AI model used in this process is an advanced natural language processing model such as BERT.

[0542] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0543] Step 1:

[0544] The server retrieves information from educational facilities within the region via APIs. Inputs include schedules and resource information from each facility, and output is a unified dataset in CSV or JSON format. This data is stored in a database for subsequent processing.

[0545] Step 2:

[0546] The server receives a prompt from the user. The input is a question in natural language, which is parsed by the AI ​​agent. A generative AI model (e.g., BERT) processes this prompt and understands the user's intent. The output is the user's intent, organized as a query.

[0547] Step 3:

[0548] The AI ​​agent retrieves relevant information from a database based on user intent. The input is organized user intent, which generates database queries and executes requests. The output is a list of relevant educational resource information.

[0549] Step 4:

[0550] The server organizes the retrieved resource information for return to the user. The input is a list of educational resources, to which prioritization and formatting are applied. The output is the final response format for presentation to the user (e.g., HTML content in list format).

[0551] Step 5:

[0552] The terminal receives responses from the server and displays them on the user's screen. The input is the final response from the server, and the output is the information visually displayed on the user interface. Based on this information, the user can decide which workshops to participate in and which services to use.

[0553] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0554] This invention provides users with a more personalized educational experience by combining an emotion recognition engine with a local educational support system. This enables interaction that responds to the user's emotions, thereby improving the quality of education. Specific embodiments are described below.

[0555] The server collects data from educational institutions within the region and stores it in a central database. This information includes schedules, events, and resource information for each facility. This ensures that users always have access to the most up-to-date information.

[0556] Users can inquire about educational resources and information through the device. The device is equipped with an emotion recognition engine that uses voice and text data as input. This engine analyzes the user's emotions from the tone and speed of their voice and the content of their text to determine how the user is feeling when seeking information.

[0557] The server uses an AI agent to comprehensively analyze the user's questions and emotional state. For example, if the user is feeling anxious, the server adjusts its approach to provide more detailed and reassuring information. For instance, if the user inputs "I'm anxious about the next test," the server will suggest a learning plan and various learning support content to alleviate that anxiety.

[0558] The scheduling system efficiently manages educators' schedules, automatically updating them based on new information. It also generates customized educational content that takes learners' progress and emotional states into account. The emotional engine suggests content that adjusts difficulty levels or includes encouraging words if learners are experiencing stress.

[0559] Furthermore, it includes a matching function to utilize local seniors as educational resources. The emotional engine also evaluates the attitude of seniors towards the educational activities they wish to participate in, ensuring appropriate matching. Communication functions are also integrated, supporting smooth information sharing among users and delivering important notifications in real time.

[0560] Thus, by combining an emotion recognition engine, the present invention provides a system that enables more flexible and effective educational support for users, allowing all participants to enjoy a more fulfilling educational environment.

[0561] The following describes the processing flow.

[0562] Step 1:

[0563] The server collects important educational resource information from websites and databases published by educational institutions within the region. This includes opening hours, event information, and lists of available facilities for each institution. This information is updated in real time and integrated into a central database.

[0564] Step 2:

[0565] Users access the system using a terminal and enter questions about specific educational information or resources. This input can be done using voice commands or text input.

[0566] Step 3:

[0567] The device sends the user's voice and text data to an emotion recognition engine. The engine analyzes the tone of voice, speaking speed, and keywords in the text to determine the user's emotional state. For example, if a user says "Teach me about this long homework" in a tired tone, the engine might estimate that the user is feeling frustrated or stressed.

[0568] Step 4:

[0569] The server uses an AI agent to process user questions and sentiment data. Considering the sentiment data, the server gains a deeper understanding of the intent behind the questions and selects the appropriate level of information. If the user is feeling anxious, the server presents more detailed and reassuring information.

[0570] Step 5:

[0571] The server generates user-specific educational content based on emotional data, including stress-reducing elements where necessary. This content is presented to the user in the form of surveys and activities.

[0572] Step 6:

[0573] When a user views suggested information or content on their device and enters further questions, their responses are also analyzed again by the emotion recognition engine and fed back to the server. This enables more personalized responses.

[0574] Step 7:

[0575] The server matches data on the skills and desired activities of older adults as educational resources, finding the optimal match with users who wish to engage in educational activities. Emotional data is also considered in this process to assess whether older adults are motivated to participate in the activities.

[0576] Step 8:

[0577] The communication function activates, and the server delivers notifications and messages in real time to facilitate information sharing among users. This function strengthens collaboration among educators.

[0578] (Example 2)

[0579] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0580] In today's educational environment, providing education that meets the individual needs and emotional states of learners is a challenge. Furthermore, there is a need for the effective utilization of educational resources through interaction with local elderly residents, and for efficient information sharing among learners. A flexible and effective educational support system that addresses these needs has yet to be established.

[0581] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0582] This invention includes a server that collects information from educational institutions within a region, integrates it, and stores it in a central database; an emotion recognition means that analyzes the user's voice and text input and estimates their emotional state; and a schedule management means that automatically adjusts the educator's activity schedule and streamlines educational activities. This enables the presentation of optimal educational information tailored to the user's emotions and individual learning needs, the effective provision of educational resources, and comprehensive educational support through collaboration with local communities.

[0583] "Information processing means" refers to a function that, in response to user inquiries, presents the most suitable educational resources in real time based on collected information.

[0584] "Emotion recognition means" refers to technology that analyzes a user's voice or text input to estimate their emotional state and use that information to provide appropriate information.

[0585] A "correction mechanism" is a function that optimizes the information provided based on the user's emotional state and suggests content that is appropriate to the user's situation.

[0586] A "schedule management system" is a management function that automatically adjusts the activity schedules of educators and improves the efficiency of educational activities.

[0587] "Mediation means" refers to functions that connect elderly people in the community with users who want to participate in educational activities, and support the effective use of local resources.

[0588] "Communication functions" are features that enable smooth information sharing and communication among users within the system.

[0589] Embodiments of the present invention are described below.

[0590] The server is responsible for collecting data from educational institutions within the region and storing it in a central database. Data collection is performed using API communication over the internet, retrieving schedules, event information, and resource data provided by educational institutions. The server filters this data, removing duplicates and incorrect information, and then efficiently stores it in the database, making it easy for users to access the latest information.

[0591] The device analyzes voice and text input from the user using an emotion recognition engine. This engine employs a machine learning model to analyze input data in order to recognize the user's emotional state. Specifically, it estimates emotions from the tone and speed of voice data and the content of text. For example, if a user enters the prompt "Please tell me my schedule for next week," the device is designed to take into account not only the acquisition of static information but also the user's current emotional state.

[0592] The server uses an AI agent to analyze the user's emotional state and questions, optimizing the information it provides. This AI agent incorporates natural language processing (NLP) technology, meticulously analyzing user input to select the most relevant information and resources. If the user is feeling anxious, the server prioritizes presenting resources that provide reassurance.

[0593] Furthermore, the server is equipped with a schedule management function to automatically adjust educators' activity schedules, thereby improving the efficiency of educational activities. It also has the ability to evaluate learners' progress and provide personalized educational resources. To achieve this, it utilizes a generative AI model to generate learning plans and practice problems tailored to the learners' progress.

[0594] Ultimately, the system connects local seniors with users who wish to engage in educational activities, providing opportunities to effectively utilize their knowledge and experience. The server manages this process comprehensively and provides example inputs as prompts to ensure an efficient learning environment and support users in smoothly using the system.

[0595] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0596] Step 1:

[0597] The server collects schedules, event information, and resource data from educational institutions within the region. Input consists of data submitted by each educational institution, which the server stores in a central database. The server processes the data to check for duplicates and standardize its format, storing it in an organized manner.

[0598] Step 2:

[0599] Users make inquiries via text or voice through the device. The input is a prompt statement uttered by the user (e.g., "Please tell me the schedule for next week"), and the device uses an emotion recognition engine to analyze the input data. The emotion recognition engine analyzes the tone and speed of the voice and the content of the text to estimate the user's emotional state.

[0600] Step 3:

[0601] The server, upon receiving data transmitted from the terminal, performs analysis using an AI agent. The input consists of the user's question and sentiment data, while the output is optimized information and resources. The server uses natural language processing technology to deeply analyze the user's intent and provide information tailored to their emotional state.

[0602] Step 4:

[0603] The server automatically adjusts educators' schedules to improve the efficiency of educational activities. Input is the latest schedule and resource information, and output is automatically updated schedules. The server dynamically manages this updated information and notifies educators and learners.

[0604] Step 5:

[0605] The server evaluates the learner's progress and generates personalized educational resources. The input is the learner's historical data, and the output is a customized learning plan and practice problems. A generative AI model is used to suggest appropriate learning content based on the learner's progress.

[0606] Step 6:

[0607] The server acts as an intermediary between local seniors and those seeking educational activities. Inputs include the seniors' registration information and the users' preferences; output is a personalized matching list. The server analyzes the registration data to derive appropriate pairings.

[0608] Step 7:

[0609] To facilitate information sharing among users, the server provides real-time communication capabilities. Inputs include new event information and announcements, while outputs include push notifications and messages. The server immediately sends this information to user terminals, supporting smooth communication.

[0610] (Application Example 2)

[0611] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0612] In modern families, there is a demand for individualized and efficient learning, but traditional educational methods make it difficult to flexibly provide learning content according to the emotions and progress of individual learners. Furthermore, there is a lack of means to deepen understanding of learners when providing educational support within the home. In addition, there is a need for means to enhance educational support throughout the community by utilizing the knowledge and experience of the elderly as educational resources.

[0613] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0614] This invention includes a server that collects information from local educational institutions, integrates it, and stores it in a central database; a server that analyzes the user's emotional state using an emotion recognition engine and adjusts educational resources based on the analysis results; and an implementation method that uses a consumer robot to provide educational support to the user in the home. This makes it possible to provide education tailored to each learner and to provide personalized learning support that takes emotions into consideration. Furthermore, it is expected to promote interactive learning that utilizes the knowledge and experience of the elderly and enhance the educational effect throughout the community.

[0615] "Educational institutions within a region" refers to educational organizations and facilities such as schools, libraries, and learning centers that are located within a specific region.

[0616] A "central database" is a database system used to centrally store and manage various types of information.

[0617] An "intelligent agent" is a program that uses artificial intelligence technology to autonomously process and judge information, and to provide the user with the most appropriate answers and suggestions.

[0618] "Planning tools" refer to functions or methods for efficiently combining and coordinating the schedules and plans of educators.

[0619] "Educational content" refers to learning plans and materials created according to the progress and individual needs of specific learners.

[0620] "Communication functions" refer to features that allow users to share information and communicate with each other.

[0621] An "emotion recognition engine" is a system that analyzes and identifies emotions from the user's voice, facial expressions, etc., and provides the results.

[0622] A "consumer robot" is a robot intended for use within the home and capable of providing educational support, household assistance, and other similar functions.

[0623] This invention provides a system for collecting information from local educational institutions, integrating it, and storing it in a central database. The server collects schedule and event information from each educational institution and stores it in the central database. This allows users to always access the latest information.

[0624] Users inquire about educational resources and information through consumer robots. The robots use an emotion recognition engine to analyze the user's emotional state and adjust educational resources based on the analysis results. The emotion recognition engine uses the user's voice and facial expressions as input data, converts the voice into text data using Google Cloud Speech-to-Text, and analyzes the emotions.

[0625] This system utilizes intelligent agents to comprehensively assess the user's questions and emotional state. For example, if it determines that the user is feeling anxious, it adjusts its approach to provide more detailed and reassuring information. Specifically, if the user inputs "I'm anxious about the next test," the server will provide a learning plan and support materials through a robot to alleviate that anxiety.

[0626] To enhance educational support within the home, consumer robots will be used. This will allow learners to have a consistent educational experience even at home. For example, if a child is having trouble with math homework, they can consult the robot. In this case, the robot will analyze the child's emotions and provide easy-to-understand learning materials along with reassuring words.

[0627] By utilizing generative AI models, highly personalized educational support becomes possible, providing a learning experience tailored to each individual learner. Furthermore, the knowledge and experience of the elderly can be used as educational resources, promoting two-way learning exchange.

[0628] As an example of a prompt, the AI ​​will be input with a message like, "When a child is stressed about math homework, please suggest how to encourage them and what learning materials to provide," and a method will be built to provide appropriate learning support.

[0629] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0630] Step 1:

[0631] A user asks educational questions to a consumer robot. Voice data is provided as input. A voice input device captures the voice and sends it to a server.

[0632] Step 2:

[0633] The server receives the audio data and uses an emotion recognition engine to convert the speech to text. The Google Cloud Speech-to-Text service is used for this conversion from speech to text data. The output is text data.

[0634] Step 3:

[0635] The server analyzes text data to recognize the user's emotions. This analysis applies an emotion recognition algorithm, which analyzes the types and tone of words the user uses. As a result, the server identifies the user's emotional state and outputs emotion state data.

[0636] Step 4:

[0637] The server uses intelligent agents to comprehensively evaluate the user's questions and emotional state. Here, the server combines the questions and emotional state to select the most appropriate educational resources and support methods. This process involves database access, referencing past data and learning resources.

[0638] Step 5:

[0639] The server transmits selected educational resources and support content to the consumer robot. The robot provides feedback and advice to the user as voice data. The output is the educational advice and resource information transmitted to the user.

[0640] Step 6:

[0641] Users receive information from the robot and use it in their learning activities. Specifically, they can learn based on the presented materials, and can repeat the learning process or ask further questions as needed.

[0642] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0643] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0644] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0645] [Fourth Embodiment]

[0646] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0647] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0648] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0649] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0650] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0651] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0652] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0653] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0654] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0655] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0656] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0657] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0658] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0659] This invention provides an integrated platform for effectively supporting local education. Specifically, it describes a system that collects information from educational institutions and uses AI technology to provide each user with the most suitable educational resources based on that information.

[0660] The server collects information from various educational institutions within the region (schools, libraries, cram schools, etc.). Specifically, it collects data on facility schedules, event information, and available resources, and organizes and stores this information in a central database.

[0661] When a user searches for specific information or enters a question through their device, an AI agent quickly extracts relevant information from its database based on the request and presents it to the user in the most optimal format. This response may include a list of facilities or suggestions for specific services that meet detailed criteria.

[0662] Furthermore, the server has a function to automatically manage educators' schedules. When educators teach at different schools or online platforms, it efficiently adjusts their schedules to avoid overlapping class times. This function maximizes the efficiency of educational activities.

[0663] For learners, the server monitors their progress and learning history, and provides individually customized educational content. This includes video materials, sets of exercises, or materials related to new learning topics. This customization ensures that each learner can continue learning in the most optimal way possible.

[0664] Furthermore, the system incorporates a matching function to effectively utilize elderly individuals within local communities as educational resources. The server matches registered elderly individuals with educational activity needs based on their skills and experience, encouraging them to participate, for example, as workshop instructors. This mechanism improves the overall quality of education in the community.

[0665] Ultimately, it includes chat and notification features to facilitate smooth communication between users. This allows teachers, parents, and learners to share necessary information and collaborate in a timely manner.

[0666] Thus, the present invention provides a typical embodiment of a system that achieves improved efficiency and quality in local education through the coordinated operation of its various functions.

[0667] The following describes the processing flow.

[0668] Step 1:

[0669] The server collects information from the websites and public databases of various educational institutions within the region. This information includes the institutions' schedules, events, and available resources, and is stored as structured data in a central database.

[0670] Step 2:

[0671] Users can input questions about education-related information and resources into the system via their devices. User questions are in natural language, and the interface is designed to be intuitive.

[0672] Step 3:

[0673] The server receives the input question, and an AI agent analyzes its content. Using natural language processing technology, it understands the intent of the question and searches for relevant information in the database.

[0674] Step 4:

[0675] The server generates the best possible answer to the user's question and sends it to the user's terminal. The answer includes information about the relevant educational institution's facilities, available resources, and other information that matches the user's specified criteria.

[0676] Step 5:

[0677] The server automatically retrieves educators' current schedules and manages them to avoid overlaps and conflicts. Schedules are coordinated across multiple educational institutions and online platforms.

[0678] Step 6:

[0679] The server analyzes learner progress data and generates personalized educational content. Based on progress reports and past learning content, a process is performed to recommend appropriate learning resources.

[0680] Step 7:

[0681] The server implements a process to match the skills of local seniors with the educational activity needs. Based on registered profiles, it matches seniors with appropriate educational projects, enabling them to participate.

[0682] Step 8:

[0683] To facilitate information sharing among users, the server provides chat and notification functions. This ensures that relevant information is delivered to stakeholders in real time, facilitating smooth communication.

[0684] (Example 1)

[0685] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0686] To improve and streamline local education, it is necessary to collect information from educational institutions, coordinate educators' schedules, provide individualized support to learners, utilize the elderly as educational resources, and facilitate smooth communication among users. However, there are limited systems that can effectively integrate these challenges and respond in real time. Therefore, there is a need to provide a comprehensive platform that enables efficient information management and communication in local education.

[0687] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0688] In this invention, the server includes means for collecting data from an information provision structure, synthesizing it, and storing it in a management data structure; intelligent agent means for immediately presenting appropriate information sources in response to user inquiries based on the collected data; and planning means for automatically scheduling and adjusting the schedules of educators to streamline educational activities. This enables the integration and efficient management of information in local education, allowing users to receive personalized educational services and educators to enjoy non-duplicate scheduling. Furthermore, it facilitates the effective utilization of the elderly and effective information sharing.

[0689] An "information provision structure" is a collection of various data, such as schedules, events, and resources, provided by educational institutions and organizations.

[0690] A "management data structure" is a database system that systematically stores, organizes, and makes accessible collected information.

[0691] An "intelligent agent" is a software program that uses artificial intelligence to analyze collected data and provide appropriate information in response to user inquiries.

[0692] "Planning tools" are tools and algorithms that automatically analyze the schedules of educators and optimize them to eliminate duplication and waste.

[0693] "Users" refers to individuals or organizations that collect information, receive, or provide educational services through this system.

[0694] "Educational professionals" is a general term for professionals involved in educational activities, including teachers and instructors.

[0695] "Elderly people" refers to older members of the community who may have the potential to provide knowledge and experience to learners and other users.

[0696] "Multifunctional communication" refers to communication methods, including chat and notification systems, that facilitate efficient and smooth information exchange among users.

[0697] This invention provides an integrated information management system to support local education. The system aims to collect and analyze data from information provision structures and to effectively provide information to users. The server collects data such as schedules, event information, and resources from local educational institutions and organizations. This includes school class times and library event announcements. The server stores this data in a managed data structure and uses natural language processing techniques and machine learning algorithms to present information effectively. Specifically, database management systems based on Python or Java are commonly used.

[0698] Users of the device can search for the information they need in real time through the system. For example, when a parent searches for nearby workshops for their child, the AI ​​agent instantly provides a list of events in response to their request. The platform supporting this process utilizes a generative AI model that analyzes prompt sentences in response to user inquiries and generates the optimal answer.

[0699] Educators can have their schedules managed by the server, avoiding overlaps in class timetables and enabling efficient teaching activities. For example, when educators teach at multiple schools or online platforms, the server coordinates their schedules and generates adjustment plans as needed.

[0700] Furthermore, this system includes a model for utilizing the knowledge and experience of older adults as educational resources. The server matches older adults' profiles with their educational needs and facilitates their participation as instructors in local workshops and courses. For example, by entering a prompt such as, "Please provide information on children's science events taking place in the following area. Also, please check if there are any older adult candidates who can participate as instructors at these events," information that facilitates older adult participation can be obtained quickly.

[0701] With the above configuration, the system will improve the quality and efficiency of local education, and provide users with personalized information and opportunities for effective communication.

[0702] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0703] Step 1:

[0704] The server collects data from the information provision structure. Specifically, it uses API access and scraping techniques to obtain schedules and event information from the websites and data feeds of educational institutions within the region.

[0705] The input is the web pages or systems of educational institutions, and the output is a list of structured schedule data and event information.

[0706] Specific operation: The server executes an automated crawling script to periodically collect specified information.

[0707] Step 2:

[0708] The server organizes and stores the collected data in a managed data structure. This process involves data cleaning and normalization, and checks for errors and duplicates.

[0709] The input is schedule and event information in raw data format, and the output is a dataset stored in a consistent database.

[0710] Specific operation: Use the database injection API to add normalized data as an entry.

[0711] Step 3:

[0712] The user uses the device to search for specific information or enter a question. Search keywords or question sentences are entered via the user interface.

[0713] The input is the user's search query, and the output is a list of search results related to the relevant information.

[0714] Specific operation: The user enters a keyword in the terminal's GUI and clicks the "Search" button.

[0715] Step 4:

[0716] The AI ​​agent instantly extracts relevant data from the managed data structure based on user questions and searches. A natural language processing model is used in this process.

[0717] The input is the user's search query, and the output is an optimized dataset or list of information presented to the user.

[0718] Specific operation: The AI ​​agent interprets queries and accesses the database using SQL or similar query languages.

[0719] Step 5:

[0720] The server analyzes and automatically adjusts the schedules of educators. Duplicate tasks and classes are detected, and an optimal time schedule is suggested.

[0721] The input is the educator's existing schedule data, and the output is an adjusted schedule proposal.

[0722] Specific operation: The server applies a scheduling algorithm to generate the adjusted schedule.

[0723] Step 6:

[0724] The server generates personalized educational support based on the learner's progress and history data. This support includes videos, exercises, and supplementary materials.

[0725] The input consists of learner history data points, and the output is a customized set of educational content.

[0726] Specific operation: The server analyzes course registration data and uses AI inference to map the most suitable content.

[0727] Step 7:

[0728] The server matches the needs of seniors with those of educational events. User-provided prompts are processed, and suitable instructors and eligible seniors are assigned.

[0729] The input is a prompt from the user, and the output is a list of matched elderly individuals.

[0730] Specific operation: Recommendations are made using a matching algorithm with a profile database.

[0731] Step 8:

[0732] The system uses devices to facilitate communication between users. Chat functions and push notifications are used to exchange necessary information and messages.

[0733] The input is the trigger for a message or contact initiated by the user, and the output is the notification or message forwarding to the recipient.

[0734] Specific operation: Messages are sent and received in real time via the chat application on the device.

[0735] (Application Example 1)

[0736] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0737] Modern communities lack systems for efficiently collecting and providing educational resources. Comprehensively managing information on local educational institutions such as schools, libraries, and cram schools, and providing it promptly as needed, is crucial for ensuring optimal learning for each student. However, various challenges exist, including information fragmentation, scheduling difficulties for educators, and underutilization of senior citizens as local educational resources. Furthermore, providing this information to learners in real time and creating an optimal learning environment remains challenging.

[0738] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0739] This invention includes a server that collects information from educational facilities within a region, integrates it, and stores it in a central data management device; a server that uses an artificial intelligence agent to present the most suitable resources in real time in response to user inquiries; and a server that automatically adjusts the schedules of educators to improve the efficiency of educational activities. This enables centralized management of educational resources within a region and provides learners with the most suitable educational information in real time.

[0740] "Educational facilities within a region" refers to various institutions and organizations located in a specific area that are dedicated to education, such as schools, libraries, and cram schools.

[0741] "Means for collecting information, integrating it, and storing it in a central data management system" refers to a mechanism for collecting information provided by educational institutions in digital format, compiling and organizing it, and storing it on a server.

[0742] "A means of presenting the most suitable resources in real time using an artificial intelligence agent" refers to a function that utilizes AI technology to instantly provide appropriate educational resources in response to questions entered by users.

[0743] "Methods for automatically adjusting the schedules of educators and improving the efficiency of educational activities" refers to methods for automatically managing and adjusting the work schedules of teachers, lecturers, and other people involved in education, thereby achieving efficient educational activities without duplication.

[0744] "Learners" refer to individuals who acquire knowledge through local educational facilities or online platforms.

[0745] "Providing information to learners in real time" means processing information quickly in response to user requests and delivering the necessary educational information to learners immediately.

[0746] The system to realize this application will be built around cloud-based data collection and artificial intelligence. The server will collect information regularly provided by various educational facilities within the region using APIs or web scraping techniques, integrate it, and store it in a database. High-performance servers are required as hardware, and cloud services such as Amazon Web Services (AWS) and Google Cloud Platform are suitable.

[0747] The collected data is processed using Python and delivered as a web application using the Flask framework. The server utilizes TensorFlow and PyTorch as artificial intelligence models to provide users with the most suitable educational resources in real time. The AI ​​agent uses natural language processing techniques to quickly respond to user questions and select and display the necessary information.

[0748] Furthermore, to enable educators to manage their schedules, it integrates with the Google Calendar API and Microsoft Graph API, and includes a function to automatically adjust appointments. This will improve the efficiency of educators' time management.

[0749] As a concrete example, when a user enters the prompt "Please tell me which workshops are available next week" into a smartphone app, the server searches its database for relevant information, and the AI ​​agent presents the most suitable resources. The generative AI model used in this process is an advanced natural language processing model such as BERT.

[0750] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0751] Step 1:

[0752] The server retrieves information from educational facilities within the region via APIs. Inputs include schedules and resource information from each facility, and output is a unified dataset in CSV or JSON format. This data is stored in a database for subsequent processing.

[0753] Step 2:

[0754] The server receives a prompt from the user. The input is a question in natural language, which is parsed by the AI ​​agent. A generative AI model (e.g., BERT) processes this prompt and understands the user's intent. The output is the user's intent, organized as a query.

[0755] Step 3:

[0756] The AI ​​agent retrieves relevant information from a database based on user intent. The input is organized user intent, which generates database queries and executes requests. The output is a list of relevant educational resource information.

[0757] Step 4:

[0758] The server organizes the retrieved resource information for return to the user. The input is a list of educational resources, to which prioritization and formatting are applied. The output is the final response format for presentation to the user (e.g., HTML content in list format).

[0759] Step 5:

[0760] The terminal receives responses from the server and displays them on the user's screen. The input is the final response from the server, and the output is the information visually displayed on the user interface. Based on this information, the user can decide which workshops to participate in and which services to use.

[0761] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0762] This invention provides users with a more personalized educational experience by combining an emotion recognition engine with a local educational support system. This enables interaction that responds to the user's emotions, thereby improving the quality of education. Specific embodiments are described below.

[0763] The server collects data from educational institutions within the region and stores it in a central database. This information includes schedules, events, and resource information for each facility. This ensures that users always have access to the most up-to-date information.

[0764] Users can inquire about educational resources and information through the device. The device is equipped with an emotion recognition engine that uses voice and text data as input. This engine analyzes the user's emotions from the tone and speed of their voice and the content of their text to determine how the user is feeling when seeking information.

[0765] The server uses an AI agent to comprehensively analyze the user's questions and emotional state. For example, if the user is feeling anxious, the server adjusts its approach to provide more detailed and reassuring information. For instance, if the user inputs "I'm anxious about the next test," the server will suggest a learning plan and various learning support content to alleviate that anxiety.

[0766] The scheduling system efficiently manages educators' schedules, automatically updating them based on new information. It also generates customized educational content that takes learners' progress and emotional states into account. The emotional engine suggests content that adjusts difficulty levels or includes encouraging words if learners are experiencing stress.

[0767] Furthermore, it includes a matching function to utilize local seniors as educational resources. The emotional engine also evaluates the attitude of seniors towards the educational activities they wish to participate in, ensuring appropriate matching. Communication functions are also integrated, supporting smooth information sharing among users and delivering important notifications in real time.

[0768] Thus, by combining an emotion recognition engine, the present invention provides a system that enables more flexible and effective educational support for users, allowing all participants to enjoy a more fulfilling educational environment.

[0769] The following describes the processing flow.

[0770] Step 1:

[0771] The server collects important educational resource information from websites and databases published by educational institutions within the region. This includes opening hours, event information, and lists of available facilities for each institution. This information is updated in real time and integrated into a central database.

[0772] Step 2:

[0773] Users access the system using a terminal and enter questions about specific educational information or resources. This input can be done using voice commands or text input.

[0774] Step 3:

[0775] The device sends the user's voice and text data to an emotion recognition engine. The engine analyzes the tone of voice, speaking speed, and keywords in the text to determine the user's emotional state. For example, if a user says "Teach me about this long homework" in a tired tone, the engine might estimate that the user is feeling frustrated or stressed.

[0776] Step 4:

[0777] The server uses an AI agent to process user questions and sentiment data. Considering the sentiment data, the server gains a deeper understanding of the intent behind the questions and selects the appropriate level of information. If the user is feeling anxious, the server presents more detailed and reassuring information.

[0778] Step 5:

[0779] The server generates user-specific educational content based on emotional data, including stress-reducing elements where necessary. This content is presented to the user in the form of surveys and activities.

[0780] Step 6:

[0781] When a user views suggested information or content on their device and enters further questions, their responses are also analyzed again by the emotion recognition engine and fed back to the server. This enables more personalized responses.

[0782] Step 7:

[0783] The server matches data on the skills and desired activities of older adults as educational resources, finding the optimal match with users who wish to engage in educational activities. Emotional data is also considered in this process to assess whether older adults are motivated to participate in the activities.

[0784] Step 8:

[0785] The communication function activates, and the server delivers notifications and messages in real time to facilitate information sharing among users. This function strengthens collaboration among educators.

[0786] (Example 2)

[0787] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0788] In today's educational environment, providing education that meets the individual needs and emotional states of learners is a challenge. Furthermore, there is a need for the effective utilization of educational resources through interaction with local elderly residents, and for efficient information sharing among learners. A flexible and effective educational support system that addresses these needs has yet to be established.

[0789] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0790] This invention includes a server that collects information from educational institutions within a region, integrates it, and stores it in a central database; an emotion recognition means that analyzes the user's voice and text input and estimates their emotional state; and a schedule management means that automatically adjusts the educator's activity schedule and streamlines educational activities. This enables the presentation of optimal educational information tailored to the user's emotions and individual learning needs, the effective provision of educational resources, and comprehensive educational support through collaboration with local communities.

[0791] "Information processing means" refers to a function that, in response to user inquiries, presents the most suitable educational resources in real time based on collected information.

[0792] "Emotion recognition means" refers to technology that analyzes a user's voice or text input to estimate their emotional state and use that information to provide appropriate information.

[0793] A "correction mechanism" is a function that optimizes the information provided based on the user's emotional state and suggests content that is appropriate to the user's situation.

[0794] A "schedule management system" is a management function that automatically adjusts the activity schedules of educators and improves the efficiency of educational activities.

[0795] "Mediation means" refers to functions that connect elderly people in the community with users who want to participate in educational activities, and support the effective use of local resources.

[0796] "Communication functions" are features that enable smooth information sharing and communication among users within the system.

[0797] Embodiments of the present invention are described below.

[0798] The server is responsible for collecting data from educational institutions within the region and storing it in a central database. Data collection is performed using API communication over the internet, retrieving schedules, event information, and resource data provided by educational institutions. The server filters this data, removing duplicates and incorrect information, and then efficiently stores it in the database, making it easy for users to access the latest information.

[0799] The device analyzes voice and text input from the user using an emotion recognition engine. This engine employs a machine learning model to analyze input data in order to recognize the user's emotional state. Specifically, it estimates emotions from the tone and speed of voice data and the content of text. For example, if a user enters the prompt "Please tell me my schedule for next week," the device is designed to take into account not only the acquisition of static information but also the user's current emotional state.

[0800] The server uses an AI agent to analyze the user's emotional state and questions, optimizing the information it provides. This AI agent incorporates natural language processing (NLP) technology, meticulously analyzing user input to select the most relevant information and resources. If the user is feeling anxious, the server prioritizes presenting resources that provide reassurance.

[0801] Furthermore, the server is equipped with a schedule management function to automatically adjust educators' activity schedules, thereby improving the efficiency of educational activities. It also has the ability to evaluate learners' progress and provide personalized educational resources. To achieve this, it utilizes a generative AI model to generate learning plans and practice problems tailored to the learners' progress.

[0802] Ultimately, the system connects local seniors with users who wish to engage in educational activities, providing opportunities to effectively utilize their knowledge and experience. The server manages this process comprehensively and provides example inputs as prompts to ensure an efficient learning environment and support users in smoothly using the system.

[0803] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0804] Step 1:

[0805] The server collects schedules, event information, and resource data from educational institutions within the region. Input consists of data submitted by each educational institution, which the server stores in a central database. The server processes the data to check for duplicates and standardize its format, storing it in an organized manner.

[0806] Step 2:

[0807] Users make inquiries via text or voice through the device. The input is a prompt statement uttered by the user (e.g., "Please tell me the schedule for next week"), and the device uses an emotion recognition engine to analyze the input data. The emotion recognition engine analyzes the tone and speed of the voice and the content of the text to estimate the user's emotional state.

[0808] Step 3:

[0809] The server, upon receiving data transmitted from the terminal, performs analysis using an AI agent. The input consists of the user's question and sentiment data, while the output is optimized information and resources. The server uses natural language processing technology to deeply analyze the user's intent and provide information tailored to their emotional state.

[0810] Step 4:

[0811] The server automatically adjusts educators' schedules to improve the efficiency of educational activities. Input is the latest schedule and resource information, and output is automatically updated schedules. The server dynamically manages this updated information and notifies educators and learners.

[0812] Step 5:

[0813] The server evaluates the learner's progress and generates personalized educational resources. The input is the learner's historical data, and the output is a customized learning plan and practice problems. A generative AI model is used to suggest appropriate learning content based on the learner's progress.

[0814] Step 6:

[0815] The server acts as an intermediary between local seniors and those seeking educational activities. Inputs include the seniors' registration information and the users' preferences; output is a personalized matching list. The server analyzes the registration data to derive appropriate pairings.

[0816] Step 7:

[0817] To facilitate information sharing among users, the server provides real-time communication capabilities. Inputs include new event information and announcements, while outputs include push notifications and messages. The server immediately sends this information to user terminals, supporting smooth communication.

[0818] (Application Example 2)

[0819] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0820] In modern families, there is a demand for individualized and efficient learning, but traditional educational methods make it difficult to flexibly provide learning content according to the emotions and progress of individual learners. Furthermore, there is a lack of means to deepen understanding of learners when providing educational support within the home. In addition, there is a need for means to enhance educational support throughout the community by utilizing the knowledge and experience of the elderly as educational resources.

[0821] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0822] This invention includes a server that collects information from local educational institutions, integrates it, and stores it in a central database; a server that analyzes the user's emotional state using an emotion recognition engine and adjusts educational resources based on the analysis results; and an implementation method that uses a consumer robot to provide educational support to the user in the home. This makes it possible to provide education tailored to each learner and to provide personalized learning support that takes emotions into consideration. Furthermore, it is expected to promote interactive learning that utilizes the knowledge and experience of the elderly and enhance the educational effect throughout the community.

[0823] "Educational institutions within a region" refers to educational organizations and facilities such as schools, libraries, and learning centers that are located within a specific region.

[0824] A "central database" is a database system used to centrally store and manage various types of information.

[0825] An "intelligent agent" is a program that uses artificial intelligence technology to autonomously process and judge information, and to provide the user with the most appropriate answers and suggestions.

[0826] "Planning tools" refer to functions or methods for efficiently combining and coordinating the schedules and plans of educators.

[0827] "Educational content" refers to learning plans and materials created according to the progress and individual needs of specific learners.

[0828] "Communication functions" refer to features that allow users to share information and communicate with each other.

[0829] An "emotion recognition engine" is a system that analyzes and identifies emotions from the user's voice, facial expressions, etc., and provides the results.

[0830] A "consumer robot" is a robot intended for use within the home and capable of providing educational support, household assistance, and other similar functions.

[0831] This invention provides a system for collecting information from local educational institutions, integrating it, and storing it in a central database. The server collects schedule and event information from each educational institution and stores it in the central database. This allows users to always access the latest information.

[0832] Users inquire about educational resources and information through consumer robots. The robots use an emotion recognition engine to analyze the user's emotional state and adjust educational resources based on the analysis results. The emotion recognition engine uses the user's voice and facial expressions as input data, converts the voice into text data using Google Cloud Speech-to-Text, and analyzes the emotions.

[0833] This system utilizes intelligent agents to comprehensively assess the user's questions and emotional state. For example, if it determines that the user is feeling anxious, it adjusts its approach to provide more detailed and reassuring information. Specifically, if the user inputs "I'm anxious about the next test," the server will provide a learning plan and support materials through a robot to alleviate that anxiety.

[0834] To enhance educational support within the home, consumer robots will be used. This will allow learners to have a consistent educational experience even at home. For example, if a child is having trouble with math homework, they can consult the robot. In this case, the robot will analyze the child's emotions and provide easy-to-understand learning materials along with reassuring words.

[0835] By utilizing generative AI models, highly personalized educational support becomes possible, providing a learning experience tailored to each individual learner. Furthermore, the knowledge and experience of the elderly can be used as educational resources, promoting two-way learning exchange.

[0836] As an example of a prompt, the AI ​​will be input with a message like, "When a child is stressed about math homework, please suggest how to encourage them and what learning materials to provide," and a method will be built to provide appropriate learning support.

[0837] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0838] Step 1:

[0839] A user asks educational questions to a consumer robot. Voice data is provided as input. A voice input device captures the voice and sends it to a server.

[0840] Step 2:

[0841] The server receives the audio data and uses an emotion recognition engine to convert the speech to text. The Google Cloud Speech-to-Text service is used for this conversion from speech to text data. The output is text data.

[0842] Step 3:

[0843] The server analyzes text data to recognize the user's emotions. This analysis applies an emotion recognition algorithm, which analyzes the types and tone of words the user uses. As a result, the server identifies the user's emotional state and outputs emotion state data.

[0844] Step 4:

[0845] The server uses intelligent agents to comprehensively evaluate the user's questions and emotional state. Here, the server combines the questions and emotional state to select the most appropriate educational resources and support methods. This process involves database access, referencing past data and learning resources.

[0846] Step 5:

[0847] The server transmits selected educational resources and support content to the consumer robot. The robot provides feedback and advice to the user as voice data. The output is the educational advice and resource information transmitted to the user.

[0848] Step 6:

[0849] Users receive information from the robot and use it in their learning activities. Specifically, they can learn based on the presented materials, and can repeat the learning process or ask further questions as needed.

[0850] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0851] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0852] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0853] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0854] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0855] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0856] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0857] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0858] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0859] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0860] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0861] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0862] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0863] 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.

[0864] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0865] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0866] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0867] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0868] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0869] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0870] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0871] The following is further disclosed regarding the embodiments described above.

[0872] (Claim 1)

[0873] A means of collecting information from educational institutions within the region, integrating it, and storing it in a central database,

[0874] Based on the collected information, an AI agent system presents the most suitable resources in real time in response to user questions,

[0875] A scheduling method that automatically adjusts educators' schedules and streamlines educational activities,

[0876] A means of evaluating learners' progress and providing individually customized educational content,

[0877] A means of matching local elderly people with users who wish to participate in educational activities,

[0878] A means of providing communication functions that facilitate information sharing and contact among users,

[0879] A system that includes this.

[0880] (Claim 2)

[0881] The system according to claim 1, further comprising means for automatically scraping opening hours and event information of educational institutions.

[0882] (Claim 3)

[0883] The system according to claim 1, comprising a means for creating a profile in which an elderly person can register their own experience and abilities.

[0884] "Example 1"

[0885] (Claim 1)

[0886] A means for collecting data from an information provision structure, synthesizing it, and storing it in a managed data structure,

[0887] An intelligent agent that, based on collected data, immediately presents appropriate information sources in response to user inquiries,

[0888] A planning tool that automatically adjusts the schedules of educators and streamlines educational activities,

[0889] A means of evaluating learners' progress and providing individually tailored educational materials,

[0890] A means of matching local seniors with users who desire educational activities,

[0891] A means of providing dialogue functions that facilitate information sharing and communication among users,

[0892] A system that includes this.

[0893] (Claim 2)

[0894] The system according to claim 1, further comprising means for automatically obtaining opening hours and activity information of educational institutions.

[0895] (Claim 3)

[0896] The system according to claim 1, comprising a means for creating a profile in which a middle-aged person can register their own experience and skills.

[0897] "Application Example 1"

[0898] (Claim 1)

[0899] A means of collecting information from educational facilities within the region, integrating it, and storing it in a central data management system,

[0900] An artificial intelligence agent that, based on the collected information, presents the most suitable resources in real time in response to user questions,

[0901] A scheduling tool that automatically adjusts the schedules of educators and streamlines educational activities,

[0902] A means of evaluating learners' progress and providing individually customized learning materials,

[0903] A means of matching local elderly people with users who wish to participate in educational activities,

[0904] A means of providing communication functions that facilitate information sharing and communication among users,

[0905] A means of providing learning opportunities in the local community in real time,

[0906] A means of providing local educational information via portable information terminals,

[0907] A system that includes this.

[0908] (Claim 2)

[0909] The system according to claim 1, further comprising means for automatically obtaining opening hours and event information of educational facilities.

[0910] (Claim 3)

[0911] The system according to claim 1, which has a means for creating a resume that allows older persons to register their own experience and abilities.

[0912] "Example 2 of combining an emotion engine"

[0913] (Claim 1)

[0914] A means of collecting information from educational institutions within the region, integrating it, and storing it in a central database,

[0915] An information processing system that, based on the collected information, presents the most suitable resources in real time in response to user inquiries,

[0916] An emotion recognition means that analyzes the user's voice and text input and estimates their emotional state,

[0917] Correction means to optimize the information provided according to the user's emotional state,

[0918] A scheduling management system that automatically adjusts educators' activity schedules and streamlines educational activities,

[0919] A means of evaluating learners' progress and providing individually customized educational resources,

[0920] A means of connecting local elderly people with users who wish to participate in educational activities,

[0921] A means of providing communication functions that facilitate information sharing and communication among users,

[0922] A system that includes this.

[0923] (Claim 2)

[0924] The system according to claim 1, further comprising means for automatically obtaining information on the opening hours and events of educational institutions.

[0925] (Claim 3)

[0926] The system according to claim 1, comprising a means for creating a profile in which an elderly person can register their own experience and abilities.

[0927] "Application example 2 when combining with an emotional engine"

[0928] (Claim 1)

[0929] A means of collecting information from educational institutions within the region, integrating it, and storing it in a central database,

[0930] An intelligent agent that, based on the collected information, presents the most suitable resources in real time in response to user questions,

[0931] A planning tool that automatically adjusts educators' schedules and streamlines educational activities,

[0932] A means of evaluating learners' progress and providing individually customized educational content,

[0933] A means of matching local elderly people with users who wish to participate in educational activities,

[0934] A means of providing communication functions that facilitate information sharing and communication among users,

[0935] A means for analyzing a user's emotional state using an emotion recognition engine and adjusting educational resources based on the analysis results,

[0936] Implementation methods using consumer robots that provide educational support to users within the home,

[0937] A system that includes this.

[0938] (Claim 2)

[0939] The system according to claim 1, further comprising means for automatically extracting opening hours and event information.

[0940] (Claim 3)

[0941] The system according to claim 1, comprising means for creating a personal profile in which an elderly person can register their own experiences and abilities. [Explanation of symbols]

[0942] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of collecting information from educational facilities within the region, integrating it, and storing it in a central data management system, An artificial intelligence agent that, based on the collected information, presents the most suitable resources in real time in response to user questions, A scheduling tool that automatically adjusts the schedules of educators and streamlines educational activities, A means of evaluating learners' progress and providing individually customized learning materials, A means of matching local elderly people with users who wish to participate in educational activities, A means of providing communication functions that facilitate information sharing and communication among users, A means of providing learning opportunities in the local community in real time, A means of providing local educational information via portable information terminals, A system that includes this.

2. The system according to claim 1, further comprising means for automatically obtaining opening hours and event information of educational facilities.

3. The system according to claim 1, which has a means for creating a resume that allows older persons to register their own experience and abilities.

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