system

Abstract

Provide a system. 【Solution means】 Means for analyzing information received from an educational institution and generating a schedule for notifying a guardian at an appropriate timing; Means for automatically distributing notifications based on the schedule; Means for obtaining the progress information of a learner and generating a report in an easy-to-understand format; Means for periodically sending the report to a guardian; Means for receiving an inquiry from a guardian and appropriately generating a response using natural language processing; Means for sending the response to a guardian; Means for organizing event and itinerary information and distributing notifications in multiple languages; A system including the above.

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, the method 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] In modern educational institutions, insufficient information transmission and poor communication often occur between educational institutions and parents, resulting in insufficient sharing of the progress of learners and causing anxiety among parents. In addition, for busy educators, information transmission and individual inquiry responses may be burdensome, which may lead to a decline in the quality of education. Furthermore, there is a language barrier for foreign parents, and important information may not be accurately conveyed. Due to these problems, there is a problem that smooth communication between educational institutions and families is hindered.

Means for Solving the Problems

[0005] This invention is a system for automating information transmission between educational institutions and parents, thereby facilitating communication. Specifically, it includes means for analyzing information received from educational institutions and generating a schedule for notifying parents at the appropriate time. It also includes means for acquiring learner progress information and generating reports in an easy-to-understand format, which can be sent to parents periodically. Furthermore, it can receive inquiries from parents, generate appropriate responses using natural language processing, and send them, and can also distribute information about events and activities in multiple languages. This aims to improve the efficiency of communication and increase parental satisfaction.

[0006] An "educational institution" refers to an organization or facility that provides education, such as a school or a cram school.

[0007] A "guardian" is a parent or legal guardian who is responsible for the student's life and education.

[0008] "Information analysis" is the process of analyzing received data, extracting necessary information, and presenting it in an understandable format.

[0009] "Creating a schedule" is the act of planning and setting the timing for things to be done based on a specific purpose.

[0010] "Automatically sending notifications" refers to a function where the system sends information based on pre-configured conditions without requiring manual intervention.

[0011] "Learner progress information" refers to data that shows the extent to which learners have acquired knowledge and skills during the educational process.

[0012] "Generating a report" refers to organizing specific information or data and outputting it in an easy-to-understand format.

[0013] "Receiving inquiries and generating responses" refers to the process of automatically creating appropriate answers to questions and requests received from external sources.

[0014] "Natural language processing" is a technology for a computer to understand, interpret, and process human language.

[0015] "Delivering notifications in multiple languages" refers to the function of translating information in multiple languages and delivering the information to recipients in each language.

Brief Description of the 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 Example 2 when combined with an emotion engine. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when combined with an emotion engine.

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 multiple arithmetic units. Also, the processor may be one type of arithmetic unit or a combination of multiple 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), etc.

[0020] In the following embodiments, the numbered RAM (Random Access Memory) is a memory where 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 is an advanced information processing system designed to support smooth communication between educational institutions and parents. Built around a server, this system automates information distribution from educational institutions, learner progress reporting, parental inquiries, and multilingual information provision through multiple functions.

[0038] The server analyzes information received from educational institutions and schedules timely notifications for parents. Following this notification schedule, the server automatically delivers information to parents' devices, ensuring that important communications reach them.

[0039] Furthermore, the server integrates with educational institutions' performance management systems to retrieve learner progress data. Based on this data, it creates learning reports in an easy-to-understand format and sends them regularly to parents' devices. This allows parents to always stay informed about their child's current learning progress.

[0040] When a user (a parent or guardian) submits an inquiry, the inquiry is sent to the server via their device. The server receives this information, uses its built-in AI module to perform natural language processing, and generates an appropriate response. This response is then sent from the server to the user's device, ensuring prompt and accurate information delivery.

[0041] Furthermore, the server organizes information on educational institutions' events and activities from a database and notifies parents in multiple languages. It is designed to ensure that information is communicated to foreign parents as well, overcoming language barriers.

[0042] As a concrete example, if an educational institution wants to send a notification to parents about a parent-child observation day scheduled for Saturday, the server first analyzes the information. Next, it calculates the appropriate timing for sending the notification and schedules it to the parents' devices. If a parent asks a question about the details of the observation day, the user's device sends a query to the server, and the server's AI module analyzes the question and quickly provides detailed information about the observation day.

[0043] Thus, the system of the present invention aims to streamline complex communication between educational institutions and parents, thereby improving the quality of education and reducing the burden on parents.

[0044] The following describes the processing flow.

[0045] Step 1:

[0046] The server receives communications from educational institutions. These communications are digital data, including event information, schedules, and emergency announcements.

[0047] Step 2:

[0048] The server analyzes the received messages and generates a schedule to determine delivery priority and appropriate sending timing. This process takes into account past delivery history and optimal notification times.

[0049] Step 3:

[0050] Based on a schedule generated by the server, notifications are sent to the parents' devices. The information is then automatically translated into multiple languages ​​according to each device's language settings and delivered in the appropriate format.

[0051] Step 4:

[0052] The server automatically retrieves learner performance information from the educational institution's management system. This allows for the collection of the latest performance data and learning progress information.

[0053] Step 5:

[0054] The server generates a learning report for parents based on the data it acquires. This report includes a summary of academic progress and learning status.

[0055] Step 6:

[0056] The server sends learning reports to the parent's device. This is also done according to a regular schedule and delivered at pre-set intervals.

[0057] Step 7:

[0058] Users send questions and inquiries to the server via their devices. The questions arrive at the server as forms or messages.

[0059] Step 8:

[0060] The server receives inquiries from users and analyzes the content of those inquiries using its built-in AI. It utilizes natural language processing to understand appropriate keywords and context.

[0061] Step 9:

[0062] The server generates an appropriate response based on the analysis results. The generated response is automatically translated as needed and provided in the user's preferred language.

[0063] Step 10:

[0064] The server sends the generated response to the user's device. The user can then ask additional questions or follow up if they wish.

[0065] (Example 1)

[0066] 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."

[0067] In communication between educational institutions and parents, there are sometimes delays in receiving information and providing progress reports, or insufficient notifications. Furthermore, responding to inquiries quickly and accurately is challenging. There are also problems with inadequate information dissemination to parents who speak different languages. These challenges raise concerns that the quality of education may decline and parents' sense of security may be undermined.

[0068] 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.

[0069] This invention includes a server that includes means for analyzing information received from educational organizations and generating a plan to notify customers at an appropriate time; means for acquiring learner progress information and generating reports in an easy-to-understand format; and means for processing natural language queries using a generative AI model and creating responses. This enables information from educational institutions to be communicated to parents quickly and accurately. Furthermore, it enables rapid responses to inquiries from parents and smooth information provision to parents who use different languages.

[0070] "Educational organizations" is a general term for institutions that provide educational services, such as schools, universities, and vocational schools.

[0071] "Customers" are recipients of information, such as parents and students who have a relationship with an educational organization.

[0072] A "plan" is a document or data that outlines a schedule for automatically distributing information at the appropriate time.

[0073] A "report" is a document that visually displays a learner's progress and is provided in a format that facilitates understanding.

[0074] A "generative AI model" refers to an algorithm or system that uses artificial intelligence technology to process inquiries and generate responses.

[0075] A "natural language query" is a question or request that a customer makes to a system using everyday language and sentences.

[0076] A "response" is the information or answer that a server generates and sends in response to a customer inquiry.

[0077] "Push communication technology" is a communication method in which a server proactively sends information to a customer's terminal.

[0078] "Multilingual translation" is a technology that converts information between different languages ​​and facilitates its transmission to those who speak those languages.

[0079] In this invention, the server receives information from educational organizations and uses a secure data transfer protocol for analysis. Furthermore, natural language processing software is utilized for data analysis, and efficient data management is performed using a database management system. Specific software used includes spaCy and MySQL®.

[0080] The server retrieves learner progress data from the educational organization's management system and generates reports using data visualization tools. Power BI is one such tool. These reports are periodically delivered directly to the customer's device using push notification technology.

[0081] Furthermore, the server uses a generative AI model to process customer inquiries in natural language. The AI ​​model utilizes generative AI technology to generate quick and appropriate responses. These responses are also sent as push notifications to the customer's device.

[0082] As a concrete example, suppose an educational organization wants to notify customers of the details of a parent-child observation day. The server first analyzes the information and creates an optimal notification plan. If a customer asks for details about the location of the observation day, the server will quickly provide the information via an AI model using the prompt "Where is the observation day being held?". In this way, the flow of information between educational organizations and customers is streamlined, enabling the delivery of high-quality information that transcends language barriers.

[0083] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0084] Step 1:

[0085] The server receives information from educational organizations. The input consists of event information and notification information sent by these organizations. The server uses secure data transfer protocols to store the received data in a database for analysis. Specifically, it receives data via various protocols and saves it to the database using SQL queries.

[0086] Step 2:

[0087] The server analyzes the information stored in the database using natural language processing software. The input is the raw data stored in step 1, and the output is the extraction of keywords and important event information. The spaCy library is used in this process to perform tokenization and entity analysis. Specifically, it automatically extracts important information such as event names, dates and times, and locations, and organizes them into a format suitable for the next processing step.

[0088] Step 3:

[0089] The server generates a notification schedule based on the analysis results. The input is the analysis results from step 2, and the output is a plan that optimizes the timing of notifications. This plan is calculated by an algorithm based on past notification history and user access patterns, and is stored in the form of a CRON job. In its specific operation, the server automatically calculates the appropriate notification timing for the analyzed event information and registers that schedule in the system calendar.

[0090] Step 4:

[0091] The server delivers notifications to the customer's device based on the configured schedule. The input is the notification plan generated in step 3, and the output is a notification message that is displayed on the customer's device. A push notification service (e.g., Firebase) is used for this. Specifically, when the scheduled time arrives, the server automatically generates a message and sends it to the customer's device. The device displays the received notification on the screen to inform the customer.

[0092] Step 5:

[0093] The user, a parent or guardian, initiates the inquiry from their device. The input consists of natural language questions and requests sent by the parent or guardian to the server. The server processes this inquiry using a generative AI model and generates an appropriate response. The output is the information or answer the parent or guardian is seeking. Specifically, the inquiry from the device is sent to the server, and the server uses an AI model to analyze the text and generate a response message.

[0094] Step 6:

[0095] The server sends a response to the query to the user's terminal. The input is the response generated in step 5, and the output is the message displayed on the terminal. In this process, data is sent from the server, and the terminal immediately presents the received information to the user. Specifically, as soon as the server generates a response, it converts it into the appropriate message format and transfers it to the terminal using push communication technology.

[0096] (Application Example 1)

[0097] 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."

[0098] A key challenge is to improve the efficiency of information exchange between care facilities and the families of residents. Specifically, this requires timely delivery of daily status reports from care facilities to families, and prompt, multilingual responses to inquiries. Furthermore, the aim is to reduce the burden and improve communication quality through clear translation of information and automated responses.

[0099] 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.

[0100] In this invention, the server includes means for analyzing information received from educational facilities and generating a plan to notify users at an appropriate time; means for automatically distributing notifications based on the plan; and means for acquiring progress information and generating reports in an easy-to-understand format. This makes it possible to exchange information quickly and accurately between care facilities and families.

[0101] An "educational institution" is a place or organization that provides educational activities, and includes schools and vocational schools.

[0102] "Users" refers to individuals or families who receive information through this system.

[0103] A "plan" is a set of settings and schedules for notifying information at the appropriate time and frequency.

[0104] "Notification" refers to the transmission of information or messaging from a system to a user.

[0105] "Progress information" refers to data or results related to the activities and learning process of the subject.

[0106] A "report" is a summary of progress information in document or data format.

[0107] "Natural language processing" is a technology that uses AI to analyze, understand, and generate human language.

[0108] A "response" is a message generated by a system as a reply or answer to an inquiry.

[0109] "Events" refer to planned activities and events within the nursing care facility.

[0110] "Event information" refers to detailed information about a specific event or activity.

[0111] "Multilingual translation" is the process of accurately converting information between different languages.

[0112] "Information sharing" is the activity of transmitting information among different stakeholders and promoting a common understanding.

[0113] To realize this invention, the server plays a central role in collecting information from care facilities and transmitting it to users in a timely manner. First, the server receives and analyzes daily status and event information from care facilities. A plan is generated from the received information for automatic distribution to users at the appropriate time. Based on this plan, notifications are sent to designated terminals.

[0114] If necessary, the server organizes progress information and generates it as a user-friendly report. This allows users to regularly receive up-to-date information about the care facility. Furthermore, the server receives inquiries from users and responds using natural language processing through its built-in AI module. Responses are generated in real time and returned to users quickly.

[0115] Furthermore, the server has a multilingual translation function that translates received information and notifications into the target language. This facilitates smooth information sharing for users who speak different languages. Specifically, the server organizes information in multiple languages ​​and enables notifications in a language suitable for each household.

[0116] For example, if a nursing home wants to inform residents about "today's care status" or "information about tomorrow's events," the server receives this information, translates it into the necessary language, and notifies the residents at the specified time. Furthermore, if a resident asks a question such as "Can I participate in tomorrow's event?", the server generates a quick and accurate response using a generative AI model. An example of a prompt would be, "Please provide details about tomorrow's facility event."

[0117] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0118] Step 1:

[0119] The server receives daily status and event information from nursing care facilities. This information is sent to the server via the facility's data management system or as direct feedback. Initial input involves verifying the information format and extracting necessary data fields. The output is data formatted for analysis.

[0120] Step 2:

[0121] The server analyzes the received information and generates a plan to send notifications to users at the optimal time. AI algorithms are used to take into account the importance of the information and the priority of notifications. The input is formatted data, and the output is a notification plan including scheduling information.

[0122] Step 3:

[0123] The server automatically delivers notifications to the user's device based on the generated notification plan. Each notification is sent to the device as a text message or in-app notification. The input is the notification plan, and the output is the notification message delivered to the user's device.

[0124] Step 4:

[0125] The server organizes progress information and generates reports in a user-friendly format. Progress data is converted into graphs and tables using visualization tools, ready to be sent to users. The input is progress data, and the output is a formatted report.

[0126] Step 5:

[0127] The server receives inquiries from users and applies AI-powered natural language processing to generate appropriate responses. Inquiries are parsed as textual information, and the AI ​​model generates responses. This output is immediately sent to the user, enabling rapid information provision.

[0128] Step 6:

[0129] The server performs multilingual translation, translating received information and sent notifications into the target language. This is essential for providing accurate and easily understandable information to multilingual users. The input is the original text, and the output is the translated information.

[0130] Step 7:

[0131] The server appropriately delivers translated notifications to the user's device. This ensures that all users receive information in their specified language. The input is translated information, and the output is the delivery of multilingual notifications.

[0132] 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.

[0133] This invention is an information processing system incorporating an emotion engine to improve communication between educational institutions and parents. The system includes functions for information distribution, automated responses, multilingual support, and user emotion recognition. Servers, terminals, and users each play their respective roles, forming the overall flow of the system.

[0134] The server receives information from educational institutions, analyzes it, and generates a schedule for notifying parents at the appropriate time. The received information includes event information and learner progress data, which are automatically distributed according to the schedule. The server also retrieves learner performance data and generates easy-to-understand learning reports based on this data, which are sent to parents periodically.

[0135] When a user submits a question through their device, the inquiry is forwarded to a server. The server uses its built-in AI and emotion engine to analyze the inquiry using natural language processing and recognize the user's emotional state. Based on this, an appropriate response is generated, and the interaction with the parent is customized as needed. The emotion engine can generate a more reassuring response if the user is showing signs of anxiety or dissatisfaction.

[0136] Furthermore, the server can organize event and activity information and notify parents in multiple languages. This allows for smoother information provision to parents of foreign nationality.

[0137] For example, if a parent inquires, "I'm worried about my son's academic performance," the server uses an emotion engine to recognize the parent's anxiety. The server then generates a detailed learning report and prepares a reassuring response, which is sent to the user's device. In this way, parental anxiety is reduced, and good communication can be maintained.

[0138] This system is effective in supporting the educational environment by improving the efficiency of information processing and enhancing individualized support. By combining it with an emotion engine, it becomes possible to provide added value beyond mere information provision and improve the user experience.

[0139] The following describes the processing flow.

[0140] Step 1:

[0141] The server receives communications and event information from educational institutions. The received data is managed in a digital format and is ready for analysis.

[0142] Step 2:

[0143] The server analyzes the received information and generates an appropriate notification schedule, taking into account the importance of the information, the timing of transmission, and the priority of the recipients.

[0144] Step 3:

[0145] The server translates notification content into multiple languages, taking into account the user's (parent's) language settings, and automatically delivers it to the parent's device.

[0146] Step 4:

[0147] The server retrieves learners' grades and progress data from the educational institution's grade management system. This allows users to check the latest learning status.

[0148] Step 5:

[0149] Based on the data acquired by the server, a learning report for parents is created. The report is created in an easy-to-read format that summarizes the key points.

[0150] Step 6:

[0151] The server periodically sends learning reports to parents' devices. These are typically sent monthly or semesterly, according to a set schedule.

[0152] Step 7:

[0153] Users send questions and concerns to the server via their devices. These messages may include questions or anxieties related to education.

[0154] Step 8:

[0155] The server receives a user inquiry and analyzes the input using an emotion engine. Here, the server recognizes the user's emotions (e.g., anxiety, joy, confusion, etc.).

[0156] Step 9:

[0157] The server generates a response using natural language processing techniques based on the analysis results. Here, a more personalized response is prepared, taking into account the user's emotions.

[0158] Step 10:

[0159] The server sends the generated response to the user's terminal. The response includes appropriate advice and support information, with the aim of reducing user anxiety and improving satisfaction.

[0160] (Example 2)

[0161] 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".

[0162] In recent years, there has been a growing demand for prompt and appropriate information sharing between educational institutions and parents. However, insufficient individualized support and multilingual assistance can lead to a decline in the quality of communication, causing anxiety and confusion among parents. Furthermore, a lack of responses that consider parents' feelings often results in one-way information sharing. This creates a problem where the relationship between educational institutions and parents is damaged.

[0163] 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.

[0164] In this invention, the server includes means for analyzing information received from an information provider and generating a schedule for notifying parents at an appropriate time; means for recognizing the parents' emotions based on the content of their inquiries and generating an appropriate response; and means for translating the notification content into different languages ​​using multilingual translation technology. This enables the rapid and accurate provision of information, reduces parental anxiety, and facilitates smooth intercultural communication.

[0165] An "information provider" is an organization or group that generates and manages information related to education and learning.

[0166] A "parent" is a person who supports the education and growth of a learner and is interested in their progress and academic performance.

[0167] A "schedule" is a systematically organized and planned timeline of when specific events or information will be provided.

[0168] "Natural language processing technology" is a technology that enables computers to understand and process human language.

[0169] "Recognizing emotions" means analyzing a user's emotional state from their words and actions and understanding specific emotions.

[0170] "Multilingual translation technology" is a technology that converts information written in one language into another language, accurately conveying its meaning.

[0171] A "notification" is a message or alarm used to convey information to a specific recipient.

[0172] A "report" is a document or statement that compiles facts and data for a specific target audience.

[0173] An "educational leader" is a professional who has the role of teaching and guiding learners in an educational setting.

[0174] This invention is an information processing system for facilitating communication between educational institutions and parents. The system incorporates information reception and analysis, automatic response, multilingual support, and emotion recognition functions.

[0175] The server receives information provided by educational institutions via the internet. This information includes learner progress and event information, and the data is stored using a database management system that conforms to the sender's data format. Specifically, data management and analysis are performed using SQL databases and Python.

[0176] The server further analyzes user inquiries using natural language processing (NLP) techniques and recognizes user emotions through an emotion engine. The NLP library utilizes open-source machine learning models to accurately determine the user's intent and emotions contained in the question. Based on these results, the server generates an appropriate automated response. For example, if a parent inquires, "I'm worried about my son's academic performance," the server recognizes the emotion as "anxiety" and immediately generates and sends a corresponding learning report.

[0177] Furthermore, the server enables multilingual support and translates information for parents in each country. A machine translation API is used for translation and dissemination, ensuring accurate communication to parents who speak different languages.

[0178] The device communicates with a server via the internet and displays questions from parents and received information on its interface. The device's user interface is designed to be intuitive and easy to understand, making it easy for parents to operate.

[0179] The server utilizes a generative AI model to streamline inquiry handling and data analysis. An example of a prompt message is, "Generate a student's performance report and consider an appropriate response to alleviate parental concerns." This system enables rapid and accurate information dissemination, contributing to improved relationships between parents and educational institutions.

[0180] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0181] Step 1:

[0182] The server receives event information and learner progress data from information providers. Input is digital data sent via email or API. The server analyzes the received data and stores it in a database. The database, for example, uses an SQL database, and the storage process is performed while verifying data integrity. Output is an integrated dataset.

[0183] Step 2:

[0184] The server analyzes the received data to generate a notification schedule. The input is the data saved in step 1. A Python program is used for the analysis to create a schedule based on the specified timings. A time management library is used for this scheduling. The output is the notification schedule sent to the parents.

[0185] Step 3:

[0186] When a user submits a question through their device, the server receives the information and begins analysis. The input is the user's inquiry message. The server uses NLP techniques to analyze the text and recognizes emotions using an emotion engine. The analysis is enhanced by a generative AI model. The output is an appropriate response that takes emotions into account.

[0187] Step 4:

[0188] The server retrieves learner performance data from a database and generates an easy-to-understand report. The input consists of performance data and progress information. The Pandas library is used for data processing, including aggregation and analysis. Matplotlib is then used to create a graphed report. The output is a visually organized learning report.

[0189] Step 5:

[0190] The server sends automatically generated responses and learning reports to the parent's device in the appropriate format. The input consists of the responses and reports generated in steps 3 and 4. The transmission utilizes a network communication protocol and sends encrypted data. The output is the information displayed on the parent's device.

[0191] Step 6:

[0192] The server translates event information into multiple languages ​​and delivers notifications to parents who speak different languages. The input is untranslated event information. A machine translation API is used for translation, ensuring the content is translated appropriately. The output is the translated multilingual notification.

[0193] This system allows parents to receive information at the appropriate time and communicate with educational institutions with peace of mind.

[0194] (Application Example 2)

[0195] 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".

[0196] Lack of communication between educational institutions and parents can hinder the smooth sharing of learning progress and event information. Furthermore, there is a lack of information provision for foreign parents and inadequate support for parents experiencing anxiety. This necessitates individualized approaches to receiving education-related information, which traditional systems struggle to address. Moreover, with technological advancements, new forms of communication support utilizing home devices are needed.

[0197] 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.

[0198] In this invention, the server includes means for analyzing information received from educational organizations and generating time plans for notifying individuals at appropriate times; means for acquiring learner progress information and generating reports in an easy-to-understand format; and means for recognizing and analyzing emotions. This facilitates smooth communication between educational institutions and parents and enables flexible information distribution, including personalized learning progress information, multilingual information provision, and anxiety reduction.

[0199] "Education-related organizations" is a general term for schools, learning facilities, and other organizations that provide educational services.

[0200] "Individuals" refers to parents or guardians who communicate with educational institutions, or those responsible for education within the home.

[0201] A "time plan" is a schedule created to notify individuals of information at the appropriate time.

[0202] A "report" refers to a document or data that summarizes learners' progress in an easy-to-understand format.

[0203] "Methods for converting speech into text" refers to technologies that analyze an individual's voice and convert it into text data.

[0204] "Means for recognizing and analyzing emotions" refers to a system or function that judges an individual's emotions and outputs analysis results according to the situation.

[0205] "Speech synthesis technology" refers to the technology that converts text data into speech and outputs it.

[0206] "Information processing devices installed in the home" refers to devices or equipment used to process and provide information within a home environment.

[0207] This invention provides a system for facilitating information exchange between educational organizations and individuals. The server first receives information from educational organizations, analyzes its content, and generates a time plan for notifying individuals at appropriate times. The server translates this information into multiple languages ​​and notifies individuals via in-home information processing devices. It also acquires learner progress information, generates reports, and periodically sends these reports to individuals.

[0208] By using speech recognition technology, the information processing device converts an individual's speech into text and sends it to a server. The server uses generative AI models and natural language processing to analyze the text data from the individual and recognize their emotions. Based on the results of the emotion analysis, speech synthesis technology is used to generate a natural and appropriate response, which can then be output from the information processing device within the home.

[0209] For example, if an individual speaks to an information processing device saying, "I'm worried about my child's school progress," the server can recognize this concern and prepare a reassuring response by generating a detailed learning report. In this way, accurate and personalized responses to education-related information can be achieved, providing support tailored to individual needs.

[0210] An example of a prompt when using a generative AI model is, "If a parent is concerned about school information, use the emotion engine to come up with a reassuring response." In this way, the system utilizes natural language processing and speech technology to improve how information is received and provide a more enriching communication experience.

[0211] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0212] Step 1:

[0213] The server receives information from education-related organizations. Input data includes event information and learner progress data. This data is analyzed to generate a time plan that determines which individuals should be notified and when. The output is an individual time plan.

[0214] Step 2:

[0215] The server translates information into multiple languages ​​based on the generated time plan and prepares it for distribution. The input is each individual's time plan and the corresponding information. The output is a set of translated notification messages.

[0216] Step 3:

[0217] The server sends individual notification messages to the home information processing devices via the terminals. The input consists of a set of multilingual translated notification messages and their delivery schedule. The output consists of the notification messages sent to each information processing device.

[0218] Step 4:

[0219] The device converts an individual's voice into text data using speech recognition technology. The input is the individual's voice data. The output is the text data sent to the server.

[0220] Step 5:

[0221] The server analyzes text data from individuals through generative AI models and natural language processing. The input is text data sent from the terminal. It uses an emotion engine to recognize emotions and generates responses based on them. The output is the response message.

[0222] Step 6:

[0223] The server converts the response message, generated using speech synthesis technology, into speech and sends it to the information processing device in the home. The input is the response message. The output is the speech data.

[0224] Step 7:

[0225] A home information processing device receives audio data from a server and plays it back appropriately for the individual. The input is audio data. The output is audio output for the individual to hear.

[0226] This series of steps enables a system where information is personalized and communicated to individuals, and appropriate feedback is provided.

[0227] 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.

[0228] 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.

[0229] 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.

[0230] [Second Embodiment]

[0231] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0232] 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.

[0233] 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).

[0234] 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.

[0235] 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.

[0236] 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).

[0237] 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.

[0238] 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.

[0239] 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.

[0240] 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.

[0241] 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.

[0242] 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".

[0243] This invention is an advanced information processing system designed to support smooth communication between educational institutions and parents. Built around a server, this system automates information distribution from educational institutions, learner progress reporting, parental inquiries, and multilingual information provision through multiple functions.

[0244] The server analyzes information received from educational institutions and schedules timely notifications for parents. Following this notification schedule, the server automatically delivers information to parents' devices, ensuring that important communications reach them.

[0245] Furthermore, the server integrates with educational institutions' performance management systems to retrieve learner progress data. Based on this data, it creates learning reports in an easy-to-understand format and sends them regularly to parents' devices. This allows parents to always stay informed about their child's current learning progress.

[0246] When a user (a parent or guardian) submits an inquiry, the inquiry is sent to the server via their device. The server receives this information, uses its built-in AI module to perform natural language processing, and generates an appropriate response. This response is then sent from the server to the user's device, ensuring prompt and accurate information delivery.

[0247] Furthermore, the server organizes information on educational institutions' events and activities from a database and notifies parents in multiple languages. It is designed to ensure that information is communicated to foreign parents as well, overcoming language barriers.

[0248] As a concrete example, if an educational institution wants to send a notification to parents about a parent-child observation day scheduled for Saturday, the server first analyzes the information. Next, it calculates the appropriate timing for sending the notification and schedules it to the parents' devices. If a parent asks a question about the details of the observation day, the user's device sends a query to the server, and the server's AI module analyzes the question and quickly provides detailed information about the observation day.

[0249] Thus, the system of the present invention aims to streamline complex communication between educational institutions and parents, thereby improving the quality of education and reducing the burden on parents.

[0250] The following describes the processing flow.

[0251] Step 1:

[0252] The server receives communications from educational institutions. These communications are digital data, including event information, schedules, and emergency announcements.

[0253] Step 2:

[0254] The server analyzes the received messages and generates a schedule to determine delivery priority and appropriate sending timing. This process takes into account past delivery history and optimal notification times.

[0255] Step 3:

[0256] Based on a schedule generated by the server, notifications are sent to the parents' devices. The information is then automatically translated into multiple languages ​​according to each device's language settings and delivered in the appropriate format.

[0257] Step 4:

[0258] The server automatically retrieves learner performance information from the educational institution's management system. This allows for the collection of the latest performance data and learning progress information.

[0259] Step 5:

[0260] The server generates a learning report for parents based on the data it acquires. This report includes a summary of academic progress and learning status.

[0261] Step 6:

[0262] The server sends learning reports to the parent's device. This is also done according to a regular schedule and delivered at pre-set intervals.

[0263] Step 7:

[0264] Users send questions and inquiries to the server via their devices. The questions arrive at the server as forms or messages.

[0265] Step 8:

[0266] The server receives inquiries from users and analyzes the content of those inquiries using its built-in AI. It utilizes natural language processing to understand appropriate keywords and context.

[0267] Step 9:

[0268] The server generates an appropriate response based on the analysis results. The generated response is automatically translated as needed and provided in the user's preferred language.

[0269] Step 10:

[0270] The server sends the generated response to the user's device. The user can then ask additional questions or follow up if they wish.

[0271] (Example 1)

[0272] 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."

[0273] In communication between educational institutions and parents, there are sometimes delays in receiving information and providing progress reports, or insufficient notifications. Furthermore, responding to inquiries quickly and accurately is challenging. There are also problems with inadequate information dissemination to parents who speak different languages. These challenges raise concerns that the quality of education may decline and parents' sense of security may be undermined.

[0274] 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.

[0275] This invention includes a server that includes means for analyzing information received from educational organizations and generating a plan to notify customers at an appropriate time; means for acquiring learner progress information and generating reports in an easy-to-understand format; and means for processing natural language queries using a generative AI model and creating responses. This enables information from educational institutions to be communicated to parents quickly and accurately. Furthermore, it enables rapid responses to inquiries from parents and smooth information provision to parents who use different languages.

[0276] "Educational organizations" is a general term for institutions that provide educational services, such as schools, universities, and vocational schools.

[0277] "Customers" are recipients of information, such as parents and students who have a relationship with an educational organization.

[0278] A "plan" is a document or data that outlines a schedule for automatically distributing information at the appropriate time.

[0279] A "report" is a document that visually displays a learner's progress and is provided in a format that facilitates understanding.

[0280] A "generative AI model" refers to an algorithm or system that uses artificial intelligence technology to process inquiries and generate responses.

[0281] A "natural language query" is a question or request that a customer makes to a system using everyday language and sentences.

[0282] A "response" is the information or answer that a server generates and sends in response to a customer inquiry.

[0283] "Push communication technology" is a communication method in which a server proactively sends information to a customer's terminal.

[0284] "Multilingual translation" is a technology for converting information between different languages and facilitating its transmission to users who speak different languages.

[0285] In this invention, the server receives information from an educational organization and uses a secure data transfer protocol to analyze it. Additionally, natural language processing software is utilized for data analysis, and efficient data management is carried out by a database management system. Specific software such as spaCy and MySQL is used.

[0286] The server obtains the progress data of learners from the management system of the educational organization and creates a report using a data visualization tool. One of the tools used is Power BI. This report is regularly delivered directly to the customer's terminal using push communication technology.

[0287] Furthermore, the server uses a generative AI model to process inquiries from customers made in natural language. As the AI model, generative AI technology is utilized to generate quick and appropriate responses. This response is also push-notified to the customer's terminal.

[0288] As a specific example, assume that an educational organization wants to notify customers of the details of a parent-child visitation day. The server first analyzes the information and formulates an optimal notification plan. When a customer asks for details about the location of the visitation day, by using a prompt sentence such as "Where is the location of the visitation day?", the server quickly provides information via the AI model. In this way, the flow of information between the educational organization and the customer can be smoothed, and high-quality information provision can be achieved across language barriers.

[0289] The flow of specific processing in Example 1 will be described using FIG. 11.

[0290] Step 1:

[0291] The server receives information from educational organizations. The input consists of event information and notification information sent by these organizations. The server uses secure data transfer protocols to store the received data in a database for analysis. Specifically, it receives data via various protocols and saves it to the database using SQL queries.

[0292] Step 2:

[0293] The server analyzes the information stored in the database using natural language processing software. The input is the raw data stored in step 1, and the output is the extraction of keywords and important event information. The spaCy library is used in this process to perform tokenization and entity analysis. Specifically, it automatically extracts important information such as event names, dates and times, and locations, and organizes them into a format suitable for the next processing step.

[0294] Step 3:

[0295] The server generates a notification schedule based on the analysis results. The input is the analysis results from step 2, and the output is a plan that optimizes the timing of notifications. This plan is calculated by an algorithm based on past notification history and user access patterns, and is stored in the form of a CRON job. In its specific operation, the server automatically calculates the appropriate notification timing for the analyzed event information and registers that schedule in the system calendar.

[0296] Step 4:

[0297] The server delivers notifications to the customer's device based on the configured schedule. The input is the notification plan generated in step 3, and the output is a notification message that is displayed on the customer's device. A push notification service (e.g., Firebase) is used for this. Specifically, when the scheduled time arrives, the server automatically generates a message and sends it to the customer's device. The device displays the received notification on the screen to inform the customer.

[0298] Step 5:

[0299] The user, a parent or guardian, initiates the inquiry from their device. The input consists of natural language questions and requests sent by the parent or guardian to the server. The server processes this inquiry using a generative AI model and generates an appropriate response. The output is the information or answer the parent or guardian is seeking. Specifically, the inquiry from the device is sent to the server, and the server uses an AI model to analyze the text and generate a response message.

[0300] Step 6:

[0301] The server sends a response to the query to the user's terminal. The input is the response generated in step 5, and the output is the message displayed on the terminal. In this process, data is sent from the server, and the terminal immediately presents the received information to the user. Specifically, as soon as the server generates a response, it converts it into the appropriate message format and transfers it to the terminal using push communication technology.

[0302] (Application Example 1)

[0303] 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."

[0304] A key challenge is to improve the efficiency of information exchange between care facilities and the families of residents. Specifically, this requires timely delivery of daily status reports from care facilities to families, and prompt, multilingual responses to inquiries. Furthermore, the aim is to reduce the burden and improve communication quality through clear translation of information and automated responses.

[0305] 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.

[0306] In this invention, the server includes means for generating a plan to analyze the information received from an educational institution and notify the user at an appropriate timing, means for automatically distributing the notification based on the plan, and means for acquiring progress information and generating a report in an easy-to-understand format. This enables quick and accurate information exchange between the nursing facility and the family.

[0307] An "educational institution" is a place or organization that provides educational activities, including schools and vocational schools.

[0308] A "user" refers to an individual or family that receives information through this system.

[0309] A "plan" is a setting or schedule for notifying information at an appropriate timing and frequency.

[0310] A "notification" is information transmission or messaging from the system to the user.

[0311] "Progress information" is data or results regarding the activities and learning processes of the target person.

[0312] A "report" is a document or summary report in data format that summarizes progress information.

[0313] "Natural language processing" is a technology that analyzes, understands, and generates human language using AI technology.

[0314] A "response" is a message generated by the system as a reply or answer to an inquiry.

[0315] An "event" refers to a planned event or activity within the nursing facility.

[0316] "Event information" is detailed information regarding a specific event or activity.

[0317] "Multilingual translation" is a process of accurately converting information between different languages.

[0318] "Information sharing" is the activity of transmitting information among different stakeholders and promoting a common understanding.

[0319] To realize this invention, the server plays a central role in collecting information from care facilities and transmitting it to users in a timely manner. First, the server receives and analyzes daily status and event information from care facilities. A plan is generated from the received information for automatic distribution to users at the appropriate time. Based on this plan, notifications are sent to designated terminals.

[0320] If necessary, the server organizes progress information and generates it as a user-friendly report. This allows users to regularly receive up-to-date information about the care facility. Furthermore, the server receives inquiries from users and responds using natural language processing through its built-in AI module. Responses are generated in real time and returned to users quickly.

[0321] Furthermore, the server has a multilingual translation function that translates received information and notifications into the target language. This facilitates smooth information sharing for users who speak different languages. Specifically, the server organizes information in multiple languages ​​and enables notifications in a language suitable for each household.

[0322] For example, if a nursing home wants to inform residents about "today's care status" or "information about tomorrow's events," the server receives this information, translates it into the necessary language, and notifies the residents at the specified time. Furthermore, if a resident asks a question such as "Can I participate in tomorrow's event?", the server generates a quick and accurate response using a generative AI model. An example of a prompt would be, "Please provide details about tomorrow's facility event."

[0323] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0324] Step 1:

[0325] The server receives daily status and event information from nursing care facilities. This information is sent to the server via the facility's data management system or as direct feedback. Initial input involves verifying the information format and extracting necessary data fields. The output is data formatted for analysis.

[0326] Step 2:

[0327] The server analyzes the received information and generates a plan to send notifications to users at the optimal time. AI algorithms are used to take into account the importance of the information and the priority of notifications. The input is formatted data, and the output is a notification plan including scheduling information.

[0328] Step 3:

[0329] The server automatically delivers notifications to the user's device based on the generated notification plan. Each notification is sent to the device as a text message or in-app notification. The input is the notification plan, and the output is the notification message delivered to the user's device.

[0330] Step 4:

[0331] The server organizes progress information and generates reports in a user-friendly format. Progress data is converted into graphs and tables using visualization tools, ready to be sent to users. The input is progress data, and the output is a formatted report.

[0332] Step 5:

[0333] The server receives inquiries from users and applies AI-powered natural language processing to generate appropriate responses. Inquiries are parsed as textual information, and the AI ​​model generates responses. This output is immediately sent to the user, enabling rapid information provision.

[0334] Step 6:

[0335] The server performs multilingual translation, translating received information and sent notifications into the target language. This is essential for providing accurate and easily understandable information to multilingual users. The input is the original text, and the output is the translated information.

[0336] Step 7:

[0337] The server appropriately delivers translated notifications to the user's device. This ensures that all users receive information in their specified language. The input is translated information, and the output is the delivery of multilingual notifications.

[0338] 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.

[0339] This invention is an information processing system incorporating an emotion engine to improve communication between educational institutions and parents. The system includes functions for information distribution, automated responses, multilingual support, and user emotion recognition. Servers, terminals, and users each play their respective roles, forming the overall flow of the system.

[0340] The server receives information from educational institutions, analyzes it, and generates a schedule for notifying parents at the appropriate time. The received information includes event information and learner progress data, which are automatically distributed according to the schedule. The server also retrieves learner performance data and generates easy-to-understand learning reports based on this data, which are sent to parents periodically.

[0341] When a user submits a question through their device, the inquiry is forwarded to a server. The server uses its built-in AI and emotion engine to analyze the inquiry using natural language processing and recognize the user's emotional state. Based on this, an appropriate response is generated, and the interaction with the parent is customized as needed. The emotion engine can generate a more reassuring response if the user is showing signs of anxiety or dissatisfaction.

[0342] Furthermore, the server can organize event and activity information and notify parents in multiple languages. This allows for smoother information provision to parents of foreign nationality.

[0343] For example, if a parent inquires, "I'm worried about my son's academic performance," the server uses an emotion engine to recognize the parent's anxiety. The server then generates a detailed learning report and prepares a reassuring response, which is sent to the user's device. In this way, parental anxiety is reduced, and good communication can be maintained.

[0344] This system is effective in supporting the educational environment by improving the efficiency of information processing and enhancing individualized support. By combining it with an emotion engine, it becomes possible to provide added value beyond mere information provision and improve the user experience.

[0345] The following describes the processing flow.

[0346] Step 1:

[0347] The server receives communications and event information from educational institutions. The received data is managed in a digital format and is ready for analysis.

[0348] Step 2:

[0349] The server analyzes the received information and generates an appropriate notification schedule, taking into account the importance of the information, the timing of transmission, and the priority of the recipients.

[0350] Step 3:

[0351] The server translates notification content into multiple languages, taking into account the user's (parent's) language settings, and automatically delivers it to the parent's device.

[0352] Step 4:

[0353] The server retrieves learners' grades and progress data from the educational institution's grade management system. This allows users to check the latest learning status.

[0354] Step 5:

[0355] Based on the data acquired by the server, a learning report for parents is created. The report is created in an easy-to-read format that summarizes the key points.

[0356] Step 6:

[0357] The server periodically sends learning reports to parents' devices. These are typically sent monthly or semesterly, according to a set schedule.

[0358] Step 7:

[0359] Users send questions and concerns to the server via their devices. These messages may include questions or anxieties related to education.

[0360] Step 8:

[0361] The server receives a user inquiry and analyzes the input using an emotion engine. Here, the server recognizes the user's emotions (e.g., anxiety, joy, confusion, etc.).

[0362] Step 9:

[0363] The server generates a response using natural language processing techniques based on the analysis results. Here, a more personalized response is prepared, taking into account the user's emotions.

[0364] Step 10:

[0365] The server sends the generated response to the user's terminal. The response includes appropriate advice and support information, with the aim of reducing user anxiety and improving satisfaction.

[0366] (Example 2)

[0367] 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".

[0368] In recent years, there has been a growing demand for prompt and appropriate information sharing between educational institutions and parents. However, insufficient individualized support and multilingual assistance can lead to a decline in the quality of communication, causing anxiety and confusion among parents. Furthermore, a lack of responses that consider parents' feelings often results in one-way information sharing. This creates a problem where the relationship between educational institutions and parents is damaged.

[0369] 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.

[0370] In this invention, the server includes means for analyzing information received from an information provider and generating a schedule for notifying parents at an appropriate time; means for recognizing the parents' emotions based on the content of their inquiries and generating an appropriate response; and means for translating the notification content into different languages ​​using multilingual translation technology. This enables the rapid and accurate provision of information, reduces parental anxiety, and facilitates smooth intercultural communication.

[0371] An "information provider" is an organization or group that generates and manages information related to education and learning.

[0372] A "parent" is a person who supports the education and growth of a learner and is interested in their progress and academic performance.

[0373] A "schedule" is a systematically organized and planned timeline of when specific events or information will be provided.

[0374] "Natural language processing technology" is a technology that enables computers to understand and process human language.

[0375] "Recognizing emotions" means analyzing a user's emotional state from their words and actions and understanding specific emotions.

[0376] "Multilingual translation technology" is a technology that converts information written in one language into another language, accurately conveying its meaning.

[0377] A "notification" is a message or alarm used to convey information to a specific recipient.

[0378] A "report" is a document or statement that compiles facts and data for a specific target audience.

[0379] An "educational leader" is a professional who has the role of teaching and guiding learners in an educational setting.

[0380] This invention is an information processing system for facilitating communication between educational institutions and parents. The system incorporates information reception and analysis, automatic response, multilingual support, and emotion recognition functions.

[0381] The server receives information provided by educational institutions via the internet. This information includes learner progress and event information, and the data is stored using a database management system that conforms to the sender's data format. Specifically, data management and analysis are performed using SQL databases and Python.

[0382] The server further analyzes user inquiries using natural language processing (NLP) techniques and recognizes user emotions through an emotion engine. The NLP library utilizes open-source machine learning models to accurately determine the user's intent and emotions contained in the question. Based on these results, the server generates an appropriate automated response. For example, if a parent inquires, "I'm worried about my son's academic performance," the server recognizes the emotion as "anxiety" and immediately generates and sends a corresponding learning report.

[0383] Furthermore, the server enables multilingual support and translates information for parents in each country. A machine translation API is used for translation and dissemination, ensuring accurate communication to parents who speak different languages.

[0384] The device communicates with a server via the internet and displays questions from parents and received information on its interface. The device's user interface is designed to be intuitive and easy to understand, making it easy for parents to operate.

[0385] The server utilizes a generative AI model to streamline inquiry handling and data analysis. An example of a prompt message is, "Generate a student's performance report and consider an appropriate response to alleviate parental concerns." This system enables rapid and accurate information dissemination, contributing to improved relationships between parents and educational institutions.

[0386] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0387] Step 1:

[0388] The server receives event information and learner progress data from information providers. Input is digital data sent via email or API. The server analyzes the received data and stores it in a database. The database, for example, uses an SQL database, and the storage process is performed while verifying data integrity. Output is an integrated dataset.

[0389] Step 2:

[0390] The server analyzes the received data to generate a notification schedule. The input is the data saved in step 1. A Python program is used for the analysis to create a schedule based on the specified timings. A time management library is used for this scheduling. The output is the notification schedule sent to the parents.

[0391] Step 3:

[0392] When a user submits a question through their device, the server receives the information and begins analysis. The input is the user's inquiry message. The server uses NLP techniques to analyze the text and recognizes emotions using an emotion engine. The analysis is enhanced by a generative AI model. The output is an appropriate response that takes emotions into account.

[0393] Step 4:

[0394] The server retrieves learner performance data from a database and generates an easy-to-understand report. The input consists of performance data and progress information. The Pandas library is used for data processing, including aggregation and analysis. Matplotlib is then used to create a graphed report. The output is a visually organized learning report.

[0395] Step 5:

[0396] The server sends automatically generated responses and learning reports to the parent's device in the appropriate format. The input consists of the responses and reports generated in steps 3 and 4. The transmission utilizes a network communication protocol and sends encrypted data. The output is the information displayed on the parent's device.

[0397] Step 6:

[0398] The server translates event information into multiple languages ​​and delivers notifications to parents who speak different languages. The input is untranslated event information. A machine translation API is used for translation, ensuring the content is translated appropriately. The output is the translated multilingual notification.

[0399] This system allows parents to receive information at the appropriate time and communicate with educational institutions with peace of mind.

[0400] (Application Example 2)

[0401] 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."

[0402] Lack of communication between educational institutions and parents can hinder the smooth sharing of learning progress and event information. Furthermore, there is a lack of information provision for foreign parents and inadequate support for parents experiencing anxiety. This necessitates individualized approaches to receiving education-related information, which traditional systems struggle to address. Moreover, with technological advancements, new forms of communication support utilizing home devices are needed.

[0403] 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.

[0404] In this invention, the server includes means for analyzing information received from educational organizations and generating time plans for notifying individuals at appropriate times; means for acquiring learner progress information and generating reports in an easy-to-understand format; and means for recognizing and analyzing emotions. This facilitates smooth communication between educational institutions and parents and enables flexible information distribution, including personalized learning progress information, multilingual information provision, and anxiety reduction.

[0405] "Education-related organizations" is a general term for schools, learning facilities, and other organizations that provide educational services.

[0406] "Individuals" refers to parents or guardians who communicate with educational institutions, or those responsible for education within the home.

[0407] A "time plan" is a schedule created to notify individuals of information at the appropriate time.

[0408] A "report" refers to a document or data that summarizes learners' progress in an easy-to-understand format.

[0409] "Methods for converting speech into text" refers to technologies that analyze an individual's voice and convert it into text data.

[0410] "Means for recognizing and analyzing emotions" refers to a system or function that judges an individual's emotions and outputs analysis results according to the situation.

[0411] "Speech synthesis technology" refers to the technology that converts text data into speech and outputs it.

[0412] "Information processing devices installed in the home" refers to devices or equipment used to process and provide information within a home environment.

[0413] This invention provides a system for facilitating information exchange between educational organizations and individuals. The server first receives information from educational organizations, analyzes its content, and generates a time plan for notifying individuals at appropriate times. The server translates this information into multiple languages ​​and notifies individuals via in-home information processing devices. It also acquires learner progress information, generates reports, and periodically sends these reports to individuals.

[0414] By using speech recognition technology, the information processing device converts an individual's speech into text and sends it to a server. The server uses generative AI models and natural language processing to analyze the text data from the individual and recognize their emotions. Based on the results of the emotion analysis, speech synthesis technology is used to generate a natural and appropriate response, which can then be output from the information processing device within the home.

[0415] For example, if an individual speaks to an information processing device saying, "I'm worried about my child's school progress," the server can recognize this concern and prepare a reassuring response by generating a detailed learning report. In this way, accurate and personalized responses to education-related information can be achieved, providing support tailored to individual needs.

[0416] An example of a prompt when using a generative AI model is, "If a parent is concerned about school information, use the emotion engine to come up with a reassuring response." In this way, the system utilizes natural language processing and speech technology to improve how information is received and provide a more enriching communication experience.

[0417] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0418] Step 1:

[0419] The server receives information from education-related organizations. Input data includes event information and learner progress data. This data is analyzed to generate a time plan that determines which individuals should be notified and when. The output is an individual time plan.

[0420] Step 2:

[0421] The server translates information into multiple languages ​​based on the generated time plan and prepares it for distribution. The input is each individual's time plan and the corresponding information. The output is a set of translated notification messages.

[0422] Step 3:

[0423] The server sends individual notification messages to the home information processing devices via the terminals. The input consists of a set of multilingual translated notification messages and their delivery schedule. The output consists of the notification messages sent to each information processing device.

[0424] Step 4:

[0425] The device converts an individual's voice into text data using speech recognition technology. The input is the individual's voice data. The output is the text data sent to the server.

[0426] Step 5:

[0427] The server analyzes text data from individuals through generative AI models and natural language processing. The input is text data sent from the terminal. It uses an emotion engine to recognize emotions and generates responses based on them. The output is the response message.

[0428] Step 6:

[0429] The server converts the response message, generated using speech synthesis technology, into speech and sends it to the information processing device in the home. The input is the response message. The output is the speech data.

[0430] Step 7:

[0431] A home information processing device receives audio data from a server and plays it back appropriately for the individual. The input is audio data. The output is audio output for the individual to hear.

[0432] This series of steps enables a system where information is personalized and communicated to individuals, and appropriate feedback is provided.

[0433] 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.

[0434] 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.

[0435] 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.

[0436] [Third Embodiment]

[0437] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0438] 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.

[0439] 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).

[0440] 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.

[0441] 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.

[0442] 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).

[0443] 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.

[0444] 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.

[0445] 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.

[0446] 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.

[0447] 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.

[0448] 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".

[0449] This invention is an advanced information processing system designed to support smooth communication between educational institutions and parents. Built around a server, this system automates information distribution from educational institutions, learner progress reporting, parental inquiries, and multilingual information provision through multiple functions.

[0450] The server analyzes information received from educational institutions and schedules timely notifications for parents. Following this notification schedule, the server automatically delivers information to parents' devices, ensuring that important communications reach them.

[0451] Furthermore, the server integrates with educational institutions' performance management systems to retrieve learner progress data. Based on this data, it creates learning reports in an easy-to-understand format and sends them regularly to parents' devices. This allows parents to always stay informed about their child's current learning progress.

[0452] When a user (a parent or guardian) submits an inquiry, the inquiry is sent to the server via their device. The server receives this information, uses its built-in AI module to perform natural language processing, and generates an appropriate response. This response is then sent from the server to the user's device, ensuring prompt and accurate information delivery.

[0453] Furthermore, the server organizes information on educational institutions' events and activities from a database and notifies parents in multiple languages. It is designed to ensure that information is communicated to foreign parents as well, overcoming language barriers.

[0454] As a concrete example, if an educational institution wants to send a notification to parents about a parent-child observation day scheduled for Saturday, the server first analyzes the information. Next, it calculates the appropriate timing for sending the notification and schedules it to the parents' devices. If a parent asks a question about the details of the observation day, the user's device sends a query to the server, and the server's AI module analyzes the question and quickly provides detailed information about the observation day.

[0455] Thus, the system of the present invention aims to streamline complex communication between educational institutions and parents, thereby improving the quality of education and reducing the burden on parents.

[0456] The following describes the processing flow.

[0457] Step 1:

[0458] The server receives communications from educational institutions. These communications are digital data, including event information, schedules, and emergency announcements.

[0459] Step 2:

[0460] The server analyzes the received messages and generates a schedule to determine delivery priority and appropriate sending timing. This process takes into account past delivery history and optimal notification times.

[0461] Step 3:

[0462] Based on a schedule generated by the server, notifications are sent to the parents' devices. The information is then automatically translated into multiple languages ​​according to each device's language settings and delivered in the appropriate format.

[0463] Step 4:

[0464] The server automatically retrieves learner performance information from the educational institution's management system. This allows for the collection of the latest performance data and learning progress information.

[0465] Step 5:

[0466] The server generates a learning report for parents based on the data it acquires. This report includes a summary of academic progress and learning status.

[0467] Step 6:

[0468] The server sends learning reports to the parent's device. This is also done according to a regular schedule and delivered at pre-set intervals.

[0469] Step 7:

[0470] Users send questions and inquiries to the server via their devices. The questions arrive at the server as forms or messages.

[0471] Step 8:

[0472] The server receives inquiries from users and analyzes the content of those inquiries using its built-in AI. It utilizes natural language processing to understand appropriate keywords and context.

[0473] Step 9:

[0474] The server generates an appropriate response based on the analysis results. The generated response is automatically translated as needed and provided in the user's preferred language.

[0475] Step 10:

[0476] The server sends the generated response to the user's device. The user can then ask additional questions or follow up if they wish.

[0477] (Example 1)

[0478] 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."

[0479] In communication between educational institutions and parents, there are sometimes delays in receiving information and providing progress reports, or insufficient notifications. Furthermore, responding to inquiries quickly and accurately is challenging. There are also problems with inadequate information dissemination to parents who speak different languages. These challenges raise concerns that the quality of education may decline and parents' sense of security may be undermined.

[0480] 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.

[0481] This invention includes a server that includes means for analyzing information received from educational organizations and generating a plan to notify customers at an appropriate time; means for acquiring learner progress information and generating reports in an easy-to-understand format; and means for processing natural language queries using a generative AI model and creating responses. This enables information from educational institutions to be communicated to parents quickly and accurately. Furthermore, it enables rapid responses to inquiries from parents and smooth information provision to parents who use different languages.

[0482] "Educational organizations" is a general term for institutions that provide educational services, such as schools, universities, and vocational schools.

[0483] "Customers" are recipients of information, such as parents and students who have a relationship with an educational organization.

[0484] A "plan" is a document or data that outlines a schedule for automatically distributing information at the appropriate time.

[0485] A "report" is a document that visually displays a learner's progress and is provided in a format that facilitates understanding.

[0486] A "generative AI model" refers to an algorithm or system that uses artificial intelligence technology to process inquiries and generate responses.

[0487] A "natural language query" is a question or request that a customer makes to a system using everyday language and sentences.

[0488] A "response" is the information or answer that a server generates and sends in response to a customer inquiry.

[0489] "Push communication technology" is a communication method in which a server proactively sends information to a customer's terminal.

[0490] "Multilingual translation" is a technology that converts information between different languages ​​and facilitates its transmission to those who speak those languages.

[0491] In this invention, the server receives information from educational organizations and uses a secure data transfer protocol for analysis. Furthermore, natural language processing software is utilized for data analysis, and efficient data management is performed using a database management system. Specific software used includes spaCy and MySQL.

[0492] The server retrieves learner progress data from the educational organization's management system and generates reports using data visualization tools. Power BI is one such tool. These reports are periodically delivered directly to the customer's device using push notification technology.

[0493] Furthermore, the server uses a generative AI model to process customer inquiries in natural language. The AI ​​model utilizes generative AI technology to generate quick and appropriate responses. These responses are also sent as push notifications to the customer's device.

[0494] As a concrete example, suppose an educational organization wants to notify customers of the details of a parent-child observation day. The server first analyzes the information and creates an optimal notification plan. If a customer asks for details about the location of the observation day, the server will quickly provide the information via an AI model using the prompt "Where is the observation day being held?". In this way, the flow of information between educational organizations and customers is streamlined, enabling the delivery of high-quality information that transcends language barriers.

[0495] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0496] Step 1:

[0497] The server receives information from educational organizations. The input consists of event information and notification information sent by these organizations. The server uses secure data transfer protocols to store the received data in a database for analysis. Specifically, it receives data via various protocols and saves it to the database using SQL queries.

[0498] Step 2:

[0499] The server analyzes the information stored in the database using natural language processing software. The input is the raw data stored in step 1, and the output is the extraction of keywords and important event information. The spaCy library is used in this process to perform tokenization and entity analysis. Specifically, it automatically extracts important information such as event names, dates and times, and locations, and organizes them into a format suitable for the next processing step.

[0500] Step 3:

[0501] The server generates a notification schedule based on the analysis results. The input is the analysis results from step 2, and the output is a plan that optimizes the timing of notifications. This plan is calculated by an algorithm based on past notification history and user access patterns, and is stored in the form of a CRON job. In its specific operation, the server automatically calculates the appropriate notification timing for the analyzed event information and registers that schedule in the system calendar.

[0502] Step 4:

[0503] The server delivers notifications to the customer's device based on the configured schedule. The input is the notification plan generated in step 3, and the output is a notification message that is displayed on the customer's device. A push notification service (e.g., Firebase) is used for this. Specifically, when the scheduled time arrives, the server automatically generates a message and sends it to the customer's device. The device displays the received notification on the screen to inform the customer.

[0504] Step 5:

[0505] The user, a parent or guardian, initiates the inquiry from their device. The input consists of natural language questions and requests sent by the parent or guardian to the server. The server processes this inquiry using a generative AI model and generates an appropriate response. The output is the information or answer the parent or guardian is seeking. Specifically, the inquiry from the device is sent to the server, and the server uses an AI model to analyze the text and generate a response message.

[0506] Step 6:

[0507] The server sends a response to the query to the user's terminal. The input is the response generated in step 5, and the output is the message displayed on the terminal. In this process, data is sent from the server, and the terminal immediately presents the received information to the user. Specifically, as soon as the server generates a response, it converts it into the appropriate message format and transfers it to the terminal using push communication technology.

[0508] (Application Example 1)

[0509] 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."

[0510] A key challenge is to improve the efficiency of information exchange between care facilities and the families of residents. Specifically, this requires timely delivery of daily status reports from care facilities to families, and prompt, multilingual responses to inquiries. Furthermore, the aim is to reduce the burden and improve communication quality through clear translation of information and automated responses.

[0511] 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.

[0512] In this invention, the server includes means for analyzing information received from educational facilities and generating a plan to notify users at an appropriate time; means for automatically distributing notifications based on the plan; and means for acquiring progress information and generating reports in an easy-to-understand format. This makes it possible to exchange information quickly and accurately between care facilities and families.

[0513] An "educational institution" is a place or organization that provides educational activities, and includes schools and vocational schools.

[0514] "Users" refers to individuals or families who receive information through this system.

[0515] A "plan" is a set of settings and schedules for notifying information at the appropriate time and frequency.

[0516] "Notification" refers to the transmission of information or messaging from a system to a user.

[0517] "Progress information" refers to data or results related to the activities and learning process of the subject.

[0518] A "report" is a summary of progress information in document or data format.

[0519] "Natural language processing" is a technology that uses AI to analyze, understand, and generate human language.

[0520] A "response" is a message generated by a system as a reply or answer to an inquiry.

[0521] "Events" refer to planned activities and events within the nursing care facility.

[0522] "Event information" refers to detailed information about a specific event or activity.

[0523] "Multilingual translation" is the process of accurately converting information between different languages.

[0524] "Information sharing" is the activity of transmitting information among different stakeholders and promoting a common understanding.

[0525] To realize this invention, the server plays a central role in collecting information from care facilities and transmitting it to users in a timely manner. First, the server receives and analyzes daily status and event information from care facilities. A plan is generated from the received information for automatic distribution to users at the appropriate time. Based on this plan, notifications are sent to designated terminals.

[0526] If necessary, the server organizes progress information and generates it as a user-friendly report. This allows users to regularly receive up-to-date information about the care facility. Furthermore, the server receives inquiries from users and responds using natural language processing through its built-in AI module. Responses are generated in real time and returned to users quickly.

[0527] Furthermore, the server has a multilingual translation function that translates received information and notifications into the target language. This facilitates smooth information sharing for users who speak different languages. Specifically, the server organizes information in multiple languages ​​and enables notifications in a language suitable for each household.

[0528] For example, if a nursing home wants to inform residents about "today's care status" or "information about tomorrow's events," the server receives this information, translates it into the necessary language, and notifies the residents at the specified time. Furthermore, if a resident asks a question such as "Can I participate in tomorrow's event?", the server generates a quick and accurate response using a generative AI model. An example of a prompt would be, "Please provide details about tomorrow's facility event."

[0529] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0530] Step 1:

[0531] The server receives daily status and event information from nursing care facilities. This information is sent to the server via the facility's data management system or as direct feedback. Initial input involves verifying the information format and extracting necessary data fields. The output is data formatted for analysis.

[0532] Step 2:

[0533] The server analyzes the received information and generates a plan to send notifications to users at the optimal time. AI algorithms are used to take into account the importance of the information and the priority of notifications. The input is formatted data, and the output is a notification plan including scheduling information.

[0534] Step 3:

[0535] The server automatically delivers notifications to the user's device based on the generated notification plan. Each notification is sent to the device as a text message or in-app notification. The input is the notification plan, and the output is the notification message delivered to the user's device.

[0536] Step 4:

[0537] The server organizes progress information and generates reports in a user-friendly format. Progress data is converted into graphs and tables using visualization tools, ready to be sent to users. The input is progress data, and the output is a formatted report.

[0538] Step 5:

[0539] The server receives inquiries from users and applies AI-powered natural language processing to generate appropriate responses. Inquiries are parsed as textual information, and the AI ​​model generates responses. This output is immediately sent to the user, enabling rapid information provision.

[0540] Step 6:

[0541] The server performs multilingual translation, translating received information and sent notifications into the target language. This is essential for providing accurate and easily understandable information to multilingual users. The input is the original text, and the output is the translated information.

[0542] Step 7:

[0543] The server appropriately delivers translated notifications to the user's device. This ensures that all users receive information in their specified language. The input is translated information, and the output is the delivery of multilingual notifications.

[0544] 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.

[0545] This invention is an information processing system incorporating an emotion engine to improve communication between educational institutions and parents. The system includes functions for information distribution, automated responses, multilingual support, and user emotion recognition. Servers, terminals, and users each play their respective roles, forming the overall flow of the system.

[0546] The server receives information from educational institutions, analyzes it, and generates a schedule for notifying parents at the appropriate time. The received information includes event information and learner progress data, which are automatically distributed according to the schedule. The server also retrieves learner performance data and generates easy-to-understand learning reports based on this data, which are sent to parents periodically.

[0547] When a user submits a question through their device, the inquiry is forwarded to a server. The server uses its built-in AI and emotion engine to analyze the inquiry using natural language processing and recognize the user's emotional state. Based on this, an appropriate response is generated, and the interaction with the parent is customized as needed. The emotion engine can generate a more reassuring response if the user is showing signs of anxiety or dissatisfaction.

[0548] Furthermore, the server can organize event and activity information and notify parents in multiple languages. This allows for smoother information provision to parents of foreign nationality.

[0549] For example, if a parent inquires, "I'm worried about my son's academic performance," the server uses an emotion engine to recognize the parent's anxiety. The server then generates a detailed learning report and prepares a reassuring response, which is sent to the user's device. In this way, parental anxiety is reduced, and good communication can be maintained.

[0550] This system is effective in supporting the educational environment by improving the efficiency of information processing and enhancing individualized support. By combining it with an emotion engine, it becomes possible to provide added value beyond mere information provision and improve the user experience.

[0551] The following describes the processing flow.

[0552] Step 1:

[0553] The server receives communications and event information from educational institutions. The received data is managed in a digital format and is ready for analysis.

[0554] Step 2:

[0555] The server analyzes the received information and generates an appropriate notification schedule, taking into account the importance of the information, the timing of transmission, and the priority of the recipients.

[0556] Step 3:

[0557] The server translates notification content into multiple languages, taking into account the user's (parent's) language settings, and automatically delivers it to the parent's device.

[0558] Step 4:

[0559] The server retrieves learners' grades and progress data from the educational institution's grade management system. This allows users to check the latest learning status.

[0560] Step 5:

[0561] Based on the data acquired by the server, a learning report for parents is created. The report is created in an easy-to-read format that summarizes the key points.

[0562] Step 6:

[0563] The server periodically sends learning reports to parents' devices. These are typically sent monthly or semesterly, according to a set schedule.

[0564] Step 7:

[0565] Users send questions and concerns to the server via their devices. These messages may include questions or anxieties related to education.

[0566] Step 8:

[0567] The server receives a user inquiry and analyzes the input using an emotion engine. Here, the server recognizes the user's emotions (e.g., anxiety, joy, confusion, etc.).

[0568] Step 9:

[0569] The server generates a response using natural language processing techniques based on the analysis results. Here, a more personalized response is prepared, taking into account the user's emotions.

[0570] Step 10:

[0571] The server sends the generated response to the user's terminal. The response includes appropriate advice and support information, with the aim of reducing user anxiety and improving satisfaction.

[0572] (Example 2)

[0573] 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."

[0574] In recent years, there has been a growing demand for prompt and appropriate information sharing between educational institutions and parents. However, insufficient individualized support and multilingual assistance can lead to a decline in the quality of communication, causing anxiety and confusion among parents. Furthermore, a lack of responses that consider parents' feelings often results in one-way information sharing. This creates a problem where the relationship between educational institutions and parents is damaged.

[0575] 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.

[0576] In this invention, the server includes means for analyzing information received from an information provider and generating a schedule for notifying parents at an appropriate time; means for recognizing the parents' emotions based on the content of their inquiries and generating an appropriate response; and means for translating the notification content into different languages ​​using multilingual translation technology. This enables the rapid and accurate provision of information, reduces parental anxiety, and facilitates smooth intercultural communication.

[0577] An "information provider" is an organization or group that generates and manages information related to education and learning.

[0578] A "parent" is a person who supports the education and growth of a learner and is interested in their progress and academic performance.

[0579] A "schedule" is a systematically organized and planned timeline of when specific events or information will be provided.

[0580] "Natural language processing technology" is a technology that enables computers to understand and process human language.

[0581] "Recognizing emotions" means analyzing a user's emotional state from their words and actions and understanding specific emotions.

[0582] "Multilingual translation technology" is a technology that converts information written in one language into another language, accurately conveying its meaning.

[0583] A "notification" is a message or alarm used to convey information to a specific recipient.

[0584] A "report" is a document or statement that compiles facts and data for a specific target audience.

[0585] An "educational leader" is a professional who has the role of teaching and guiding learners in an educational setting.

[0586] This invention is an information processing system for facilitating communication between educational institutions and parents. The system incorporates information reception and analysis, automatic response, multilingual support, and emotion recognition functions.

[0587] The server receives information provided by educational institutions via the internet. This information includes learner progress and event information, and the data is stored using a database management system that conforms to the sender's data format. Specifically, data management and analysis are performed using SQL databases and Python.

[0588] The server further analyzes user inquiries using natural language processing (NLP) techniques and recognizes user emotions through an emotion engine. The NLP library utilizes open-source machine learning models to accurately determine the user's intent and emotions contained in the question. Based on these results, the server generates an appropriate automated response. For example, if a parent inquires, "I'm worried about my son's academic performance," the server recognizes the emotion as "anxiety" and immediately generates and sends a corresponding learning report.

[0589] Furthermore, the server enables multilingual support and translates information for parents in each country. A machine translation API is used for translation and dissemination, ensuring accurate communication to parents who speak different languages.

[0590] The device communicates with a server via the internet and displays questions from parents and received information on its interface. The device's user interface is designed to be intuitive and easy to understand, making it easy for parents to operate.

[0591] The server utilizes a generative AI model to streamline inquiry handling and data analysis. An example of a prompt message is, "Generate a student's performance report and consider an appropriate response to alleviate parental concerns." This system enables rapid and accurate information dissemination, contributing to improved relationships between parents and educational institutions.

[0592] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0593] Step 1:

[0594] The server receives event information and learner progress data from information providers. Input is digital data sent via email or API. The server analyzes the received data and stores it in a database. The database, for example, uses an SQL database, and the storage process is performed while verifying data integrity. Output is an integrated dataset.

[0595] Step 2:

[0596] The server analyzes the received data to generate a notification schedule. The input is the data saved in step 1. A Python program is used for the analysis to create a schedule based on the specified timings. A time management library is used for this scheduling. The output is the notification schedule sent to the parents.

[0597] Step 3:

[0598] When a user submits a question through their device, the server receives the information and begins analysis. The input is the user's inquiry message. The server uses NLP techniques to analyze the text and recognizes emotions using an emotion engine. The analysis is enhanced by a generative AI model. The output is an appropriate response that takes emotions into account.

[0599] Step 4:

[0600] The server retrieves learner performance data from a database and generates an easy-to-understand report. The input consists of performance data and progress information. The Pandas library is used for data processing, including aggregation and analysis. Matplotlib is then used to create a graphed report. The output is a visually organized learning report.

[0601] Step 5:

[0602] The server sends automatically generated responses and learning reports to the parent's device in the appropriate format. The input consists of the responses and reports generated in steps 3 and 4. The transmission utilizes a network communication protocol and sends encrypted data. The output is the information displayed on the parent's device.

[0603] Step 6:

[0604] The server translates event information into multiple languages ​​and delivers notifications to parents who speak different languages. The input is untranslated event information. A machine translation API is used for translation, ensuring the content is translated appropriately. The output is the translated multilingual notification.

[0605] This system allows parents to receive information at the appropriate time and communicate with educational institutions with peace of mind.

[0606] (Application Example 2)

[0607] 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."

[0608] Lack of communication between educational institutions and parents can hinder the smooth sharing of learning progress and event information. Furthermore, there is a lack of information provision for foreign parents and inadequate support for parents experiencing anxiety. This necessitates individualized approaches to receiving education-related information, which traditional systems struggle to address. Moreover, with technological advancements, new forms of communication support utilizing home devices are needed.

[0609] 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.

[0610] In this invention, the server includes means for analyzing information received from educational organizations and generating time plans for notifying individuals at appropriate times; means for acquiring learner progress information and generating reports in an easy-to-understand format; and means for recognizing and analyzing emotions. This facilitates smooth communication between educational institutions and parents and enables flexible information distribution, including personalized learning progress information, multilingual information provision, and anxiety reduction.

[0611] "Education-related organizations" is a general term for schools, learning facilities, and other organizations that provide educational services.

[0612] "Individuals" refers to parents or guardians who communicate with educational institutions, or those responsible for education within the home.

[0613] A "time plan" is a schedule created to notify individuals of information at the appropriate time.

[0614] A "report" refers to a document or data that summarizes learners' progress in an easy-to-understand format.

[0615] "Methods for converting speech into text" refers to technologies that analyze an individual's voice and convert it into text data.

[0616] "Means for recognizing and analyzing emotions" refers to a system or function that judges an individual's emotions and outputs analysis results according to the situation.

[0617] "Speech synthesis technology" refers to the technology that converts text data into speech and outputs it.

[0618] "Information processing devices installed in the home" refers to devices or equipment used to process and provide information within a home environment.

[0619] This invention provides a system for facilitating information exchange between educational organizations and individuals. The server first receives information from educational organizations, analyzes its content, and generates a time plan for notifying individuals at appropriate times. The server translates this information into multiple languages ​​and notifies individuals via in-home information processing devices. It also acquires learner progress information, generates reports, and periodically sends these reports to individuals.

[0620] By using speech recognition technology, the information processing device converts an individual's speech into text and sends it to a server. The server uses generative AI models and natural language processing to analyze the text data from the individual and recognize their emotions. Based on the results of the emotion analysis, speech synthesis technology is used to generate a natural and appropriate response, which can then be output from the information processing device within the home.

[0621] For example, if an individual speaks to an information processing device saying, "I'm worried about my child's school progress," the server can recognize this concern and prepare a reassuring response by generating a detailed learning report. In this way, accurate and personalized responses to education-related information can be achieved, providing support tailored to individual needs.

[0622] An example of a prompt when using a generative AI model is, "If a parent is concerned about school information, use the emotion engine to come up with a reassuring response." In this way, the system utilizes natural language processing and speech technology to improve how information is received and provide a more enriching communication experience.

[0623] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0624] Step 1:

[0625] The server receives information from education-related organizations. Input data includes event information and learner progress data. This data is analyzed to generate a time plan that determines which individuals should be notified and when. The output is an individual time plan.

[0626] Step 2:

[0627] The server translates information into multiple languages ​​based on the generated time plan and prepares it for distribution. The input is each individual's time plan and the corresponding information. The output is a set of translated notification messages.

[0628] Step 3:

[0629] The server sends individual notification messages to the home information processing devices via the terminals. The input consists of a set of multilingual translated notification messages and their delivery schedule. The output consists of the notification messages sent to each information processing device.

[0630] Step 4:

[0631] The device converts an individual's voice into text data using speech recognition technology. The input is the individual's voice data. The output is the text data sent to the server.

[0632] Step 5:

[0633] The server analyzes text data from individuals through generative AI models and natural language processing. The input is text data sent from the terminal. It uses an emotion engine to recognize emotions and generates responses based on them. The output is the response message.

[0634] Step 6:

[0635] The server converts the response message, generated using speech synthesis technology, into speech and sends it to the information processing device in the home. The input is the response message. The output is the speech data.

[0636] Step 7:

[0637] A home information processing device receives audio data from a server and plays it back appropriately for the individual. The input is audio data. The output is audio output for the individual to hear.

[0638] This series of steps enables a system where information is personalized and communicated to individuals, and appropriate feedback is provided.

[0639] 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.

[0640] 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.

[0641] 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.

[0642] [Fourth Embodiment]

[0643] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0644] 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.

[0645] 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).

[0646] 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.

[0647] 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.

[0648] 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).

[0649] 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.

[0650] 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.

[0651] 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.

[0652] 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.

[0653] 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.

[0654] 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.

[0655] 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".

[0656] This invention is an advanced information processing system designed to support smooth communication between educational institutions and parents. Built around a server, this system automates information distribution from educational institutions, learner progress reporting, parental inquiries, and multilingual information provision through multiple functions.

[0657] The server analyzes information received from educational institutions and schedules timely notifications for parents. Following this notification schedule, the server automatically delivers information to parents' devices, ensuring that important communications reach them.

[0658] Furthermore, the server integrates with educational institutions' performance management systems to retrieve learner progress data. Based on this data, it creates learning reports in an easy-to-understand format and sends them regularly to parents' devices. This allows parents to always stay informed about their child's current learning progress.

[0659] When a user (a parent or guardian) submits an inquiry, the inquiry is sent to the server via their device. The server receives this information, uses its built-in AI module to perform natural language processing, and generates an appropriate response. This response is then sent from the server to the user's device, ensuring prompt and accurate information delivery.

[0660] Furthermore, the server organizes information on educational institutions' events and activities from a database and notifies parents in multiple languages. It is designed to ensure that information is communicated to foreign parents as well, overcoming language barriers.

[0661] As a concrete example, if an educational institution wants to send a notification to parents about a parent-child observation day scheduled for Saturday, the server first analyzes the information. Next, it calculates the appropriate timing for sending the notification and schedules it to the parents' devices. If a parent asks a question about the details of the observation day, the user's device sends a query to the server, and the server's AI module analyzes the question and quickly provides detailed information about the observation day.

[0662] Thus, the system of the present invention aims to streamline complex communication between educational institutions and parents, thereby improving the quality of education and reducing the burden on parents.

[0663] The following describes the processing flow.

[0664] Step 1:

[0665] The server receives communications from educational institutions. These communications are digital data, including event information, schedules, and emergency announcements.

[0666] Step 2:

[0667] The server analyzes the received messages and generates a schedule to determine delivery priority and appropriate sending timing. This process takes into account past delivery history and optimal notification times.

[0668] Step 3:

[0669] Based on a schedule generated by the server, notifications are sent to the parents' devices. The information is then automatically translated into multiple languages ​​according to each device's language settings and delivered in the appropriate format.

[0670] Step 4:

[0671] The server automatically retrieves learner performance information from the educational institution's management system. This allows for the collection of the latest performance data and learning progress information.

[0672] Step 5:

[0673] The server generates a learning report for parents based on the data it acquires. This report includes a summary of academic progress and learning status.

[0674] Step 6:

[0675] The server sends learning reports to the parent's device. This is also done according to a regular schedule and delivered at pre-set intervals.

[0676] Step 7:

[0677] Users send questions and inquiries to the server via their devices. The questions arrive at the server as forms or messages.

[0678] Step 8:

[0679] The server receives inquiries from users and analyzes the content of those inquiries using its built-in AI. It utilizes natural language processing to understand appropriate keywords and context.

[0680] Step 9:

[0681] The server generates an appropriate response based on the analysis results. The generated response is automatically translated as needed and provided in the user's preferred language.

[0682] Step 10:

[0683] The server sends the generated response to the user's device. The user can then ask additional questions or follow up if they wish.

[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] In communication between educational institutions and parents, there are sometimes delays in receiving information and providing progress reports, or insufficient notifications. Furthermore, responding to inquiries quickly and accurately is challenging. There are also problems with inadequate information dissemination to parents who speak different languages. These challenges raise concerns that the quality of education may decline and parents' sense of security may be undermined.

[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] This invention includes a server that includes means for analyzing information received from educational organizations and generating a plan to notify customers at an appropriate time; means for acquiring learner progress information and generating reports in an easy-to-understand format; and means for processing natural language queries using a generative AI model and creating responses. This enables information from educational institutions to be communicated to parents quickly and accurately. Furthermore, it enables rapid responses to inquiries from parents and smooth information provision to parents who use different languages.

[0689] "Educational organizations" is a general term for institutions that provide educational services, such as schools, universities, and vocational schools.

[0690] "Customers" are recipients of information, such as parents and students who have a relationship with an educational organization.

[0691] A "plan" is a document or data that outlines a schedule for automatically distributing information at the appropriate time.

[0692] A "report" is a document that visually displays a learner's progress and is provided in a format that facilitates understanding.

[0693] A "generative AI model" refers to an algorithm or system that uses artificial intelligence technology to process inquiries and generate responses.

[0694] A "natural language query" is a question or request that a customer makes to a system using everyday language and sentences.

[0695] A "response" is the information or answer that a server generates and sends in response to a customer inquiry.

[0696] "Push communication technology" is a communication method in which a server proactively sends information to a customer's terminal.

[0697] "Multilingual translation" is a technology that converts information between different languages ​​and facilitates its transmission to those who speak those languages.

[0698] In this invention, the server receives information from educational organizations and uses a secure data transfer protocol for analysis. Furthermore, natural language processing software is utilized for data analysis, and efficient data management is performed using a database management system. Specific software used includes spaCy and MySQL.

[0699] The server retrieves learner progress data from the educational organization's management system and generates reports using data visualization tools. Power BI is one such tool. These reports are periodically delivered directly to the customer's device using push notification technology.

[0700] Furthermore, the server uses a generative AI model to process customer inquiries in natural language. The AI ​​model utilizes generative AI technology to generate quick and appropriate responses. These responses are also sent as push notifications to the customer's device.

[0701] As a concrete example, suppose an educational organization wants to notify customers of the details of a parent-child observation day. The server first analyzes the information and creates an optimal notification plan. If a customer asks for details about the location of the observation day, the server will quickly provide the information via an AI model using the prompt "Where is the observation day being held?". In this way, the flow of information between educational organizations and customers is streamlined, enabling the delivery of high-quality information that transcends language barriers.

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

[0703] Step 1:

[0704] The server receives information from educational organizations. The input consists of event information and notification information sent by these organizations. The server uses secure data transfer protocols to store the received data in a database for analysis. Specifically, it receives data via various protocols and saves it to the database using SQL queries.

[0705] Step 2:

[0706] The server analyzes the information stored in the database using natural language processing software. The input is the raw data stored in step 1, and the output is the extraction of keywords and important event information. The spaCy library is used in this process to perform tokenization and entity analysis. Specifically, it automatically extracts important information such as event names, dates and times, and locations, and organizes them into a format suitable for the next processing step.

[0707] Step 3:

[0708] The server generates a notification schedule based on the analysis results. The input is the analysis results from step 2, and the output is a plan that optimizes the timing of notifications. This plan is calculated by an algorithm based on past notification history and user access patterns, and is stored in the form of a CRON job. In its specific operation, the server automatically calculates the appropriate notification timing for the analyzed event information and registers that schedule in the system calendar.

[0709] Step 4:

[0710] The server delivers notifications to the customer's device based on the configured schedule. The input is the notification plan generated in step 3, and the output is a notification message that is displayed on the customer's device. A push notification service (e.g., Firebase) is used for this. Specifically, when the scheduled time arrives, the server automatically generates a message and sends it to the customer's device. The device displays the received notification on the screen to inform the customer.

[0711] Step 5:

[0712] The user, a parent or guardian, initiates the inquiry from their device. The input consists of natural language questions and requests sent by the parent or guardian to the server. The server processes this inquiry using a generative AI model and generates an appropriate response. The output is the information or answer the parent or guardian is seeking. Specifically, the inquiry from the device is sent to the server, and the server uses an AI model to analyze the text and generate a response message.

[0713] Step 6:

[0714] The server sends a response to the query to the user's terminal. The input is the response generated in step 5, and the output is the message displayed on the terminal. In this process, data is sent from the server, and the terminal immediately presents the received information to the user. Specifically, as soon as the server generates a response, it converts it into the appropriate message format and transfers it to the terminal using push communication technology.

[0715] (Application Example 1)

[0716] 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".

[0717] A key challenge is to improve the efficiency of information exchange between care facilities and the families of residents. Specifically, this requires timely delivery of daily status reports from care facilities to families, and prompt, multilingual responses to inquiries. Furthermore, the aim is to reduce the burden and improve communication quality through clear translation of information and automated responses.

[0718] 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.

[0719] In this invention, the server includes means for analyzing information received from educational facilities and generating a plan to notify users at an appropriate time; means for automatically distributing notifications based on the plan; and means for acquiring progress information and generating reports in an easy-to-understand format. This makes it possible to exchange information quickly and accurately between care facilities and families.

[0720] An "educational institution" is a place or organization that provides educational activities, and includes schools and vocational schools.

[0721] "Users" refers to individuals or families who receive information through this system.

[0722] A "plan" is a set of settings and schedules for notifying information at the appropriate time and frequency.

[0723] "Notification" refers to the transmission of information or messaging from a system to a user.

[0724] "Progress information" refers to data or results related to the activities and learning process of the subject.

[0725] A "report" is a summary of progress information in document or data format.

[0726] "Natural language processing" is a technology that uses AI to analyze, understand, and generate human language.

[0727] A "response" is a message generated by a system as a reply or answer to an inquiry.

[0728] "Events" refer to planned activities and events within the nursing care facility.

[0729] "Event information" refers to detailed information about a specific event or activity.

[0730] "Multilingual translation" is the process of accurately converting information between different languages.

[0731] "Information sharing" is the activity of transmitting information among different stakeholders and promoting a common understanding.

[0732] To realize this invention, the server plays a central role in collecting information from care facilities and transmitting it to users in a timely manner. First, the server receives and analyzes daily status and event information from care facilities. A plan is generated from the received information for automatic distribution to users at the appropriate time. Based on this plan, notifications are sent to designated terminals.

[0733] If necessary, the server organizes progress information and generates it as a user-friendly report. This allows users to regularly receive up-to-date information about the care facility. Furthermore, the server receives inquiries from users and responds using natural language processing through its built-in AI module. Responses are generated in real time and returned to users quickly.

[0734] Furthermore, the server has a multilingual translation function that translates received information and notifications into the target language. This facilitates smooth information sharing for users who speak different languages. Specifically, the server organizes information in multiple languages ​​and enables notifications in a language suitable for each household.

[0735] For example, if a nursing home wants to inform residents about "today's care status" or "information about tomorrow's events," the server receives this information, translates it into the necessary language, and notifies the residents at the specified time. Furthermore, if a resident asks a question such as "Can I participate in tomorrow's event?", the server generates a quick and accurate response using a generative AI model. An example of a prompt would be, "Please provide details about tomorrow's facility event."

[0736] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0737] Step 1:

[0738] The server receives daily status and event information from nursing care facilities. This information is sent to the server via the facility's data management system or as direct feedback. Initial input involves verifying the information format and extracting necessary data fields. The output is data formatted for analysis.

[0739] Step 2:

[0740] The server analyzes the received information and generates a plan to send notifications to users at the optimal time. AI algorithms are used to take into account the importance of the information and the priority of notifications. The input is formatted data, and the output is a notification plan including scheduling information.

[0741] Step 3:

[0742] The server automatically delivers notifications to the user's device based on the generated notification plan. Each notification is sent to the device as a text message or in-app notification. The input is the notification plan, and the output is the notification message delivered to the user's device.

[0743] Step 4:

[0744] The server organizes progress information and generates reports in a user-friendly format. Progress data is converted into graphs and tables using visualization tools, ready to be sent to users. The input is progress data, and the output is a formatted report.

[0745] Step 5:

[0746] The server receives inquiries from users and applies AI-powered natural language processing to generate appropriate responses. Inquiries are parsed as textual information, and the AI ​​model generates responses. This output is immediately sent to the user, enabling rapid information provision.

[0747] Step 6:

[0748] The server performs multilingual translation, translating received information and sent notifications into the target language. This is essential for providing accurate and easily understandable information to multilingual users. The input is the original text, and the output is the translated information.

[0749] Step 7:

[0750] The server appropriately delivers translated notifications to the user's device. This ensures that all users receive information in their specified language. The input is translated information, and the output is the delivery of multilingual notifications.

[0751] 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.

[0752] This invention is an information processing system incorporating an emotion engine to improve communication between educational institutions and parents. The system includes functions for information distribution, automated responses, multilingual support, and user emotion recognition. Servers, terminals, and users each play their respective roles, forming the overall flow of the system.

[0753] The server receives information from educational institutions, analyzes it, and generates a schedule for notifying parents at the appropriate time. The received information includes event information and learner progress data, which are automatically distributed according to the schedule. The server also retrieves learner performance data and generates easy-to-understand learning reports based on this data, which are sent to parents periodically.

[0754] When a user submits a question through their device, the inquiry is forwarded to a server. The server uses its built-in AI and emotion engine to analyze the inquiry using natural language processing and recognize the user's emotional state. Based on this, an appropriate response is generated, and the interaction with the parent is customized as needed. The emotion engine can generate a more reassuring response if the user is showing signs of anxiety or dissatisfaction.

[0755] Furthermore, the server can organize event and activity information and notify parents in multiple languages. This allows for smoother information provision to parents of foreign nationality.

[0756] For example, if a parent inquires, "I'm worried about my son's academic performance," the server uses an emotion engine to recognize the parent's anxiety. The server then generates a detailed learning report and prepares a reassuring response, which is sent to the user's device. In this way, parental anxiety is reduced, and good communication can be maintained.

[0757] This system is effective in supporting the educational environment by improving the efficiency of information processing and enhancing individualized support. By combining it with an emotion engine, it becomes possible to provide added value beyond mere information provision and improve the user experience.

[0758] The following describes the processing flow.

[0759] Step 1:

[0760] The server receives communications and event information from educational institutions. The received data is managed in a digital format and is ready for analysis.

[0761] Step 2:

[0762] The server analyzes the received information and generates an appropriate notification schedule, taking into account the importance of the information, the timing of transmission, and the priority of the recipients.

[0763] Step 3:

[0764] The server translates notification content into multiple languages, taking into account the user's (parent's) language settings, and automatically delivers it to the parent's device.

[0765] Step 4:

[0766] The server retrieves learners' grades and progress data from the educational institution's grade management system. This allows users to check the latest learning status.

[0767] Step 5:

[0768] Based on the data acquired by the server, a learning report for parents is created. The report is created in an easy-to-read format that summarizes the key points.

[0769] Step 6:

[0770] The server periodically sends learning reports to parents' devices. These are typically sent monthly or semesterly, according to a set schedule.

[0771] Step 7:

[0772] Users send questions and concerns to the server via their devices. These messages may include questions or anxieties related to education.

[0773] Step 8:

[0774] The server receives a user inquiry and analyzes the input using an emotion engine. Here, the server recognizes the user's emotions (e.g., anxiety, joy, confusion, etc.).

[0775] Step 9:

[0776] The server generates a response using natural language processing techniques based on the analysis results. Here, a more personalized response is prepared, taking into account the user's emotions.

[0777] Step 10:

[0778] The server sends the generated response to the user's terminal. The response includes appropriate advice and support information, with the aim of reducing user anxiety and improving satisfaction.

[0779] (Example 2)

[0780] 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".

[0781] In recent years, there has been a growing demand for prompt and appropriate information sharing between educational institutions and parents. However, insufficient individualized support and multilingual assistance can lead to a decline in the quality of communication, causing anxiety and confusion among parents. Furthermore, a lack of responses that consider parents' feelings often results in one-way information sharing. This creates a problem where the relationship between educational institutions and parents is damaged.

[0782] 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.

[0783] In this invention, the server includes means for analyzing information received from an information provider and generating a schedule for notifying parents at an appropriate time; means for recognizing the parents' emotions based on the content of their inquiries and generating an appropriate response; and means for translating the notification content into different languages ​​using multilingual translation technology. This enables the rapid and accurate provision of information, reduces parental anxiety, and facilitates smooth intercultural communication.

[0784] An "information provider" is an organization or group that generates and manages information related to education and learning.

[0785] A "parent" is a person who supports the education and growth of a learner and is interested in their progress and academic performance.

[0786] A "schedule" is a systematically organized and planned timeline of when specific events or information will be provided.

[0787] "Natural language processing technology" is a technology that enables computers to understand and process human language.

[0788] "Recognizing emotions" means analyzing a user's emotional state from their words and actions and understanding specific emotions.

[0789] "Multilingual translation technology" is a technology that converts information written in one language into another language, accurately conveying its meaning.

[0790] A "notification" is a message or alarm used to convey information to a specific recipient.

[0791] A "report" is a document or statement that compiles facts and data for a specific target audience.

[0792] An "educational leader" is a professional who has the role of teaching and guiding learners in an educational setting.

[0793] This invention is an information processing system for facilitating communication between educational institutions and parents. The system incorporates information reception and analysis, automatic response, multilingual support, and emotion recognition functions.

[0794] The server receives information provided by educational institutions via the internet. This information includes learner progress and event information, and the data is stored using a database management system that conforms to the sender's data format. Specifically, data management and analysis are performed using SQL databases and Python.

[0795] The server further analyzes user inquiries using natural language processing (NLP) techniques and recognizes user emotions through an emotion engine. The NLP library utilizes open-source machine learning models to accurately determine the user's intent and emotions contained in the question. Based on these results, the server generates an appropriate automated response. For example, if a parent inquires, "I'm worried about my son's academic performance," the server recognizes the emotion as "anxiety" and immediately generates and sends a corresponding learning report.

[0796] Furthermore, the server enables multilingual support and translates information for parents in each country. A machine translation API is used for translation and dissemination, ensuring accurate communication to parents who speak different languages.

[0797] The device communicates with a server via the internet and displays questions from parents and received information on its interface. The device's user interface is designed to be intuitive and easy to understand, making it easy for parents to operate.

[0798] The server utilizes a generative AI model to streamline inquiry handling and data analysis. An example of a prompt message is, "Generate a student's performance report and consider an appropriate response to alleviate parental concerns." This system enables rapid and accurate information dissemination, contributing to improved relationships between parents and educational institutions.

[0799] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0800] Step 1:

[0801] The server receives event information and learner progress data from information providers. Input is digital data sent via email or API. The server analyzes the received data and stores it in a database. The database, for example, uses an SQL database, and the storage process is performed while verifying data integrity. Output is an integrated dataset.

[0802] Step 2:

[0803] The server analyzes the received data to generate a notification schedule. The input is the data saved in step 1. A Python program is used for the analysis to create a schedule based on the specified timings. A time management library is used for this scheduling. The output is the notification schedule sent to the parents.

[0804] Step 3:

[0805] When a user submits a question through their device, the server receives the information and begins analysis. The input is the user's inquiry message. The server uses NLP techniques to analyze the text and recognizes emotions using an emotion engine. The analysis is enhanced by a generative AI model. The output is an appropriate response that takes emotions into account.

[0806] Step 4:

[0807] The server retrieves learner performance data from a database and generates an easy-to-understand report. The input consists of performance data and progress information. The Pandas library is used for data processing, including aggregation and analysis. Matplotlib is then used to create a graphed report. The output is a visually organized learning report.

[0808] Step 5:

[0809] The server sends automatically generated responses and learning reports to the parent's device in the appropriate format. The input consists of the responses and reports generated in steps 3 and 4. The transmission utilizes a network communication protocol and sends encrypted data. The output is the information displayed on the parent's device.

[0810] Step 6:

[0811] The server translates event information into multiple languages ​​and delivers notifications to parents who speak different languages. The input is untranslated event information. A machine translation API is used for translation, ensuring the content is translated appropriately. The output is the translated multilingual notification.

[0812] This system allows parents to receive information at the appropriate time and communicate with educational institutions with peace of mind.

[0813] (Application Example 2)

[0814] 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".

[0815] Lack of communication between educational institutions and parents can hinder the smooth sharing of learning progress and event information. Furthermore, there is a lack of information provision for foreign parents and inadequate support for parents experiencing anxiety. This necessitates individualized approaches to receiving education-related information, which traditional systems struggle to address. Moreover, with technological advancements, new forms of communication support utilizing home devices are needed.

[0816] 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.

[0817] In this invention, the server includes means for analyzing information received from educational organizations and generating time plans for notifying individuals at appropriate times; means for acquiring learner progress information and generating reports in an easy-to-understand format; and means for recognizing and analyzing emotions. This facilitates smooth communication between educational institutions and parents and enables flexible information distribution, including personalized learning progress information, multilingual information provision, and anxiety reduction.

[0818] "Education-related organizations" is a general term for schools, learning facilities, and other organizations that provide educational services.

[0819] "Individuals" refers to parents or guardians who communicate with educational institutions, or those responsible for education within the home.

[0820] A "time plan" is a schedule created to notify individuals of information at the appropriate time.

[0821] A "report" refers to a document or data that summarizes learners' progress in an easy-to-understand format.

[0822] "Methods for converting speech into text" refers to technologies that analyze an individual's voice and convert it into text data.

[0823] "Means for recognizing and analyzing emotions" refers to a system or function that judges an individual's emotions and outputs analysis results according to the situation.

[0824] "Speech synthesis technology" refers to the technology that converts text data into speech and outputs it.

[0825] "Information processing devices installed in the home" refers to devices or equipment used to process and provide information within a home environment.

[0826] This invention provides a system for facilitating information exchange between educational organizations and individuals. The server first receives information from educational organizations, analyzes its content, and generates a time plan for notifying individuals at appropriate times. The server translates this information into multiple languages ​​and notifies individuals via in-home information processing devices. It also acquires learner progress information, generates reports, and periodically sends these reports to individuals.

[0827] By using speech recognition technology, the information processing device converts an individual's speech into text and sends it to a server. The server uses generative AI models and natural language processing to analyze the text data from the individual and recognize their emotions. Based on the results of the emotion analysis, speech synthesis technology is used to generate a natural and appropriate response, which can then be output from the information processing device within the home.

[0828] For example, if an individual speaks to an information processing device saying, "I'm worried about my child's school progress," the server can recognize this concern and prepare a reassuring response by generating a detailed learning report. In this way, accurate and personalized responses to education-related information can be achieved, providing support tailored to individual needs.

[0829] An example of a prompt when using a generative AI model is, "If a parent is concerned about school information, use the emotion engine to come up with a reassuring response." In this way, the system utilizes natural language processing and speech technology to improve how information is received and provide a more enriching communication experience.

[0830] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0831] Step 1:

[0832] The server receives information from education-related organizations. Input data includes event information and learner progress data. This data is analyzed to generate a time plan that determines which individuals should be notified and when. The output is an individual time plan.

[0833] Step 2:

[0834] The server translates information into multiple languages ​​based on the generated time plan and prepares it for distribution. The input is each individual's time plan and the corresponding information. The output is a set of translated notification messages.

[0835] Step 3:

[0836] The server sends individual notification messages to the home information processing devices via the terminals. The input consists of a set of multilingual translated notification messages and their delivery schedule. The output consists of the notification messages sent to each information processing device.

[0837] Step 4:

[0838] The device converts an individual's voice into text data using speech recognition technology. The input is the individual's voice data. The output is the text data sent to the server.

[0839] Step 5:

[0840] The server analyzes text data from individuals through generative AI models and natural language processing. The input is text data sent from the terminal. It uses an emotion engine to recognize emotions and generates responses based on them. The output is the response message.

[0841] Step 6:

[0842] The server converts the response message, generated using speech synthesis technology, into speech and sends it to the information processing device in the home. The input is the response message. The output is the speech data.

[0843] Step 7:

[0844] A home information processing device receives audio data from a server and plays it back appropriately for the individual. The input is audio data. The output is audio output for the individual to hear.

[0845] This series of steps enables a system where information is personalized and communicated to individuals, and appropriate feedback is provided.

[0846] 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.

[0847] 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.

[0848] 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.

[0849] 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.

[0850] 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.

[0851] 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.

[0852] 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.

[0853] 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.

[0854] 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."

[0855] 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.

[0856] 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.

[0857] 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.

[0858] 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.

[0859] 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.

[0860] 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.

[0861] 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.

[0862] 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.

[0863] 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.

[0864] 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.

[0865] 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.

[0866] 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.

[0867] The following is further disclosed regarding the embodiments described above.

[0868] (Claim 1)

[0869] A means of analyzing information received from educational institutions and generating a schedule for notifying parents at the appropriate time,

[0870] A means for automatically distributing notifications based on the aforementioned schedule,

[0871] A means of obtaining learner progress information and generating reports in an easy-to-understand format,

[0872] A means of periodically sending the aforementioned report to the guardian,

[0873] A means of receiving inquiries from parents and generating appropriate responses using natural language processing,

[0874] A means for sending the aforementioned response to the guardian,

[0875] A means of organizing event and activity information and distributing notifications in multiple languages,

[0876] A system that includes this.

[0877] (Claim 2)

[0878] The system according to claim 1, further comprising means for analyzing inquiries from parents and connecting them to educators as necessary.

[0879] (Claim 3)

[0880] The system according to claim 1, further comprising means for translating the content of information and notices received from educational institutions into multiple languages.

[0881] "Example 1"

[0882] (Claim 1)

[0883] A means of analyzing information received from educational organizations and generating a plan to notify customers at the appropriate time,

[0884] A means for automatically distributing notifications based on the aforementioned plan,

[0885] A means of obtaining learner progress information and generating reports in an easy-to-understand format,

[0886] A means of periodically sending the aforementioned report to the customer,

[0887] A means for receiving customer inquiries and generating appropriate responses using natural language processing,

[0888] Means for sending the aforementioned response to the customer,

[0889] A means of organizing information about events and occasions and distributing notifications in multiple languages,

[0890] A means of obtaining progress information in conjunction with the performance management system of an educational organization and creating reports using visual tools,

[0891] A means of rapidly delivering information to customer terminals using push communication technology,

[0892] A means of processing natural language queries and generating responses using a generative AI model,

[0893] A system that includes this.

[0894] (Claim 2)

[0895] The system according to claim 1, further comprising means for analyzing customer inquiries and connecting them to educators as necessary.

[0896] (Claim 3)

[0897] The system according to claim 1, further comprising means for translating the content of information and notices received from educational organizations into multiple languages.

[0898] "Application Example 1"

[0899] (Claim 1)

[0900] A means for analyzing information received from educational institutions and generating a plan to notify users at the appropriate time,

[0901] A means for automatically distributing notifications based on the aforementioned plan,

[0902] A means of obtaining progress information and generating reports in an easy-to-understand format,

[0903] A means of periodically sending the aforementioned report to users,

[0904] A means for receiving inquiries from users and generating appropriate responses using natural language processing,

[0905] A means for sending the aforementioned response to the user,

[0906] A means of organizing event and activity information and distributing notifications in multiple languages,

[0907] Means to support information sharing,

[0908] A means of presenting information using multilingual translation,

[0909] A system that includes this.

[0910] (Claim 2)

[0911] The system according to claim 1, further comprising means for analyzing inquiries from users and connecting them to the appropriate person as needed.

[0912] (Claim 3)

[0913] The system according to claim 1, further comprising means for translating the content of information and notices.

[0914] "Example 2 of combining an emotion engine"

[0915] (Claim 1)

[0916] A means of analyzing information received from information-providing organizations and generating a schedule for notifying parents at the appropriate time,

[0917] A means of automatically distributing notifications based on the aforementioned schedule,

[0918] A means of obtaining learner progress information and generating reports in an easy-to-understand format,

[0919] A means of periodically sending the aforementioned report to the guardian,

[0920] A means for receiving inquiries from parents and generating appropriate responses using natural language processing technology,

[0921] Based on the content of the inquiry, a means to recognize the feelings of the parent and generate an appropriate response,

[0922] A means of translating notification content into different languages ​​using multilingual translation technology,

[0923] A means for sending the aforementioned response to the guardian,

[0924] A means of organizing event and activity information and distributing notifications in multiple languages,

[0925] A system that includes this.

[0926] (Claim 2)

[0927] The system according to claim 1, further comprising means for analyzing inquiries from parents and connecting them to educational instructors as necessary.

[0928] (Claim 3)

[0929] The system according to claim 1, further comprising means for translating the content of information and notifications received from information providers into different languages.

[0930] "Application example 2 when combining with an emotional engine"

[0931] (Claim 1)

[0932] A means of analyzing information received from education-related organizations and generating a time plan for notifying individuals at the appropriate time,

[0933] A means for automatically distributing notifications based on the aforementioned time plan,

[0934] A means of obtaining learner progress information and generating reports in an easy-to-understand format,

[0935] A means of periodically sending the aforementioned report to individuals,

[0936] A means for receiving inquiries from individuals and generating appropriate responses using natural language processing,

[0937] A means for sending the aforementioned response to an individual,

[0938] A means of organizing event and activity information and distributing notifications in multiple languages,

[0939] A means of converting an individual's speech into text using speech recognition technology,

[0940] Means for recognizing and analyzing emotions,

[0941] A means for generating an appropriate response using speech synthesis technology based on emotion analysis results,

[0942] A means of providing information through an information processing device installed in the home,

[0943] A system that includes this.

[0944] (Claim 2)

[0945] The system according to claim 1, further comprising means for analyzing inquiries from individuals and connecting them to educators as necessary.

[0946] (Claim 3)

[0947] The system according to claim 1, further comprising means for translating the content of information and notices received from education-related organizations into multiple languages. [Explanation of symbols]

[0948] 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 analyzing information received from educational institutions and generating a schedule for notifying parents at the appropriate time, A means for automatically distributing notifications based on the aforementioned schedule, A means of obtaining learner progress information and generating reports in an easy-to-understand format, A means of periodically sending the aforementioned report to the guardian, A means of receiving inquiries from parents and generating appropriate responses using natural language processing, A means for sending the aforementioned response to the guardian, A means of organizing event and activity information and distributing notifications in multiple languages, A system that includes this.

2. The system according to claim 1, further comprising means for analyzing inquiries from parents and connecting them to educators as necessary.

3. The system according to claim 1, further comprising means for translating the content of information and notices received from educational institutions into multiple languages.

Images