system

Abstract

We provide the system. [Solution] A means for receiving identification information entered by a user and authenticating the user based on said identification information, A means of providing users with educational content on automation upon successful authentication, A means for collecting questions entered by a user and sending those questions to a generative artificial intelligence engine, A means of displaying the response received from the generative artificial intelligence engine to the user, It provides a bulletin board function, a means for users to share information with other users, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, 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] As the importance of modern automation technology increases, it is particularly necessary to improve the skills of robotic process automation (RPA). However, for many users, learning and practicing RPA require high learning costs, and there is also a problem that it is difficult to receive specialized support in real time. Furthermore, there is a lack of effective communication means for sharing practical knowledge. Therefore, there is a demand for a system that enables users to efficiently acquire skills from the basics of automation to practice and share knowledge with other users.

Means for Solving the Problems

[0005] To solve the aforementioned problems, the present invention provides the following means. First, a means is provided to receive identification information entered by the user and to authenticate the user based on said identification information. This allows the user to access the system safely and reliably. If authentication is successful, a means is provided to provide the user with educational content related to automation. This educational content includes material useful for the user to learn from the basics to the practical application of automation. Furthermore, a means is provided to collect questions entered by the user and send them to a generative artificial intelligence engine, allowing the user to receive expert support in real time. A means is provided to display the answers received from the generative artificial intelligence engine to the user, allowing the user to quickly obtain the necessary information. In addition, a bulletin board function is provided, allowing the user to share information with other users, thereby promoting knowledge sharing and communication. Through these means, the present invention provides a system that enables users to efficiently improve their RPA skills and facilitates efficient information sharing.

[0006] "Identification information" refers to information used to identify a user personally, and typically includes a username and password.

[0007] "Educational content related to automation" refers to educational materials and resources for users to learn automation technologies, particularly robotic process automation (RPA).

[0008] A "question" refers to the information or questions that a user inputs into a generative artificial intelligence engine.

[0009] A "generative artificial intelligence engine" is an artificial intelligence system that analyzes user questions and generates appropriate answers.

[0010] "Answer" refers to information and guidelines generated by a generative artificial intelligence engine in response to a user's question.

[0011] The "bulletin board function" is a feature that allows users to post, view, and comment on information with each other.

[0012] A "session" is a temporary unit of conversation and data exchange created after successful user authentication.

[0013] A "database" is an electronic data storage device used to systematically store and manage user information, educational content, submitted data, and other similar information.

[0014] A "terminal" is a device used by a user to access and operate a system, and usually refers to a personal computer or smartphone. [Brief explanation of the drawing]

[0015] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10]Shows an emotion map to which multiple emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Embodiment 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Embodiment 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

Modes for Carrying Out the Invention

[0016] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0017] First, the terms used in the following description will be described.

[0018] In the following embodiments, a processor with a reference numeral (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single 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), and the like.

[0019] In the following embodiments, a RAM (Random Access Memory) with a reference numeral is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0020] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0021] 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).

[0022] 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."

[0023] [First Embodiment]

[0024] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0025] 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.

[0026] 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).

[0027] 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.

[0028] 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.

[0029] 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.

[0030] 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.

[0031] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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".

[0036] This invention is a system for users to efficiently improve their skills in automation technologies, particularly robotic process automation (RPA). The system includes user authentication, provision of automation training content, question answering using generative artificial intelligence, and a bulletin board function that enables information sharing with other users.

[0037] User login and authentication

[0038] First, the user enters their identification information, specifically their username and password. The device receives this information and sends it to the server. The server accesses the database and searches for a user record that matches the entered information. If a matching record exists, the server creates a new session and notifies the device. The device displays the username and opens the dashboard. If authentication fails, the server sends an error message to the device, which then displays this to the user.

[0039] Provision of automation education content

[0040] Once authentication is successful, the user selects educational content, such as the "Automation Fundamentals" course, from the dashboard. The device sends this selection information to the server, which retrieves the corresponding educational content from its database. The retrieved content is then displayed to the user through the device.

[0041] Question answering by generative artificial intelligence

[0042] Users can ask generative artificial intelligence questions about points that arise during the learning process of educational content. The user inputs a question, the device collects it, and sends it to the server. The server passes the question to the generative AI engine, which analyzes the question and generates an appropriate answer. This answer is then sent to the device via the server and displayed to the user.

[0043] Information sharing via bulletin board function

[0044] The system also provides a bulletin board function for users to share information. Users create new posts on the bulletin board, and the terminal sends the content of the post to the server. The server saves the post to a database, and if the save is successful, it retrieves a list of the latest posts and sends it to the terminal. The terminal displays this list, allowing other users to view and comment on it. If the save fails, an error message is sent to the terminal and displayed to the user.

[0045] Specific example

[0046] For example, if a user wants to ask a question about how to use an RPA tool, they might input the question, "How do I extract data from a specific webpage using an RPA tool?" The terminal sends this to the server, which then passes it to a generative artificial intelligence engine. The engine generates an answer such as, "To extract data from a webpage, you first need to set the appropriate selector, and then use a data scraping activity. You can find detailed guidelines below: [link]," and sends it to the terminal via the server. This allows the user to learn specific techniques.

[0047] In this way, by using the system of the present invention, users can efficiently improve their automation skills and receive support to solve practical problems. Furthermore, knowledge deepening can be expected as information sharing with other users is promoted.

[0048] The following describes the processing flow.

[0049] User login and authentication

[0050] Step 1:

[0051] The user enters their username and password into the login form.

[0052] Step 2:

[0053] The device collects the login form data, encrypts it, and sends it to the server.

[0054] Step 3:

[0055] The server executes a query against the database to search for records that match the entered username and password.

[0056] Step 4:

[0057] The database returns the corresponding user record.

[0058] Step 5:

[0059] The server checks the user record, and if a matching record exists, it creates a new session.

[0060] Step 6:

[0061] The server sends session information to the terminal.

[0062] Step 7:

[0063] The device receives session information, displays the username, and opens the dashboard.

[0064] Step 8:

[0065] If authentication fails, the server sends an error message to the terminal, which then displays it to the user.

[0066] Provision of automation education content

[0067] Step 1:

[0068] The user selects the "Automation Fundamentals" course from the dashboard.

[0069] Step 2:

[0070] The device collects user selection information and sends it to the server.

[0071] Step 3:

[0072] The server retrieves the educational content corresponding to the selected course from the database.

[0073] Step 4:

[0074] The database returns the corresponding course content.

[0075] Step 5:

[0076] The server sends the acquired course information to the terminal.

[0077] Step 6:

[0078] The device displays the course content to the user.

[0079] Question answering by generative artificial intelligence

[0080] Step 1:

[0081] The user inputs questions to the generative artificial intelligence to ask questions about points they are unsure of during the learning process.

[0082] Step 2:

[0083] The device collects user questions and sends them to the server.

[0084] Step 3:

[0085] The server sends the question to a generative artificial intelligence engine.

[0086] Step 4:

[0087] A generative artificial intelligence engine analyzes the question and generates an appropriate answer.

[0088] Step 5:

[0089] The generative artificial intelligence engine generates the answer and sends it to the server.

[0090] Step 6:

[0091] The server sends the response to the terminal.

[0092] Step 7:

[0093] The device displays the answer to the user.

[0094] Information sharing via bulletin board function

[0095] Step 1:

[0096] The user enters new content for the bulletin board.

[0097] Step 2:

[0098] The device collects the posted content and sends it to the server.

[0099] Step 3:

[0100] The server saves the posted content to the database.

[0101] Step 4:

[0102] The database returns the save status to the server.

[0103] Step 5:

[0104] If the server successfully saves the data, it will execute a query to retrieve the latest list of posts from the database.

[0105] Step 6:

[0106] The database returns a list of the most recent posts to the server.

[0107] Step 7:

[0108] The server sends a list of posts to the device.

[0109] Step 8:

[0110] The device displays a list of posts to the user, allowing other users to view and comment on them.

[0111] Step 9:

[0112] If saving fails, the server sends an error message to the terminal, which then displays it to the user.

[0113] Specific example

[0114] Step 1:

[0115] The user inputs a question to the generative artificial intelligence: "How can I extract data from a specific webpage using an RPA tool?"

[0116] Step 2:

[0117] The device collects questions and sends them to the server.

[0118] Step 3:

[0119] The server sends the question to a generative artificial intelligence engine.

[0120] Step 4:

[0121] The generative artificial intelligence engine generates the response: "To extract data from a webpage, first set the appropriate selector, then use a data scraping activity. You can find detailed guidelines below: [link]".

[0122] Step 5:

[0123] The generative artificial intelligence engine sends the answer to the server.

[0124] Step 6:

[0125] The server sends the response to the terminal.

[0126] Step 7:

[0127] The device displays the answer to the user.

[0128] The above is a description of the specific operation of each processing step in the present invention.

[0129] (Example 1)

[0130] 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."

[0131] In today's business environment, there is a growing need to quickly and efficiently acquire skills in automation technologies, particularly robotic process automation (RPA). However, users are often overwhelmed by the vast amount of information and technology available, making it difficult to learn smoothly. Furthermore, support for obtaining appropriate answers when questions arise is insufficient, and information sharing with other users is limited. To address these problems, an effective learning support system is necessary.

[0132] 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.

[0133] In this invention, the server includes means for receiving identification information entered by the user and accessing a database based on said identification information to authenticate the user; means for creating a new session and notifying the terminal if authentication is successful; and means for providing educational content related to automation to the authenticated user. This enables users to be authenticated smoothly and to be provided with a consistent learning experience.

[0134] Furthermore, the server is equipped with means to send user-inputted questions to a generative artificial intelligence model, generate appropriate answers, and display them to the user, as well as a bulletin board function that allows users to share information with other users. This enables users to get immediate answers to their questions and continue learning effectively. It also facilitates information sharing with other users, promoting the deepening of knowledge.

[0135] "User authentication" is the process of verifying a user's identity by referencing a database based on the identification information (username and password) entered by the user.

[0136] "Educational content" refers to learning materials provided to users to improve their skills and knowledge, specifically including courses and materials related to automation technology and RPA.

[0137] A "generative artificial intelligence model" is a type of artificial intelligence that has the ability to analyze questions entered by a user and generate appropriate answers.

[0138] A "question answering system" is a system that has the function of passing questions entered by the user to a generative artificial intelligence model, collecting the generated answers, and displaying them to the user.

[0139] The "bulletin board function" is a platform for users to share information with other users, and includes features that allow users to post questions and opinions and leave comments.

[0140] A "session" refers to a series of operations performed by a user from the time they log in to the system until they log out, and is used to manage the user's operation history and authentication status.

[0141] A "device" refers to a device that a user uses to access a system, and includes personal computers, smartphones, tablets, and other similar devices.

[0142] A "server" is a centralized computing system that receives requests from users, processes them, accesses databases, and returns appropriate responses.

[0143] The present invention is a system for users to efficiently improve their skills in automation technology, particularly robotic process automation (RPA), and is implemented in the following specific forms.

[0144] User login and authentication

[0145] The user enters their identification information, specifically their username and password. The terminal receives this information and sends it to the server. The server accesses the database (e.g., a MySQL database) and searches for a user record that matches the entered information. If a matching record exists, the server creates a new session and notifies the terminal. The terminal displays the username and opens the dashboard. If authentication fails, the server sends an error message to the terminal, which the terminal displays to the user.

[0146] Provision of automation education content

[0147] After successful authentication, users select educational content such as "Fundamentals of Automation" from the dashboard. The device sends this selection information to the server, which retrieves the corresponding educational content from its database. The retrieved content is then displayed to the user through the device. The educational content is provided in various formats, including videos, text, and interactive exercises.

[0148] Question answering by generative artificial intelligence

[0149] Users can ask questions to a generative artificial intelligence (e.g., GPT-4®) about anything that arises while learning educational content. The user inputs a question, the device collects it, and sends it to the server. The server passes the question to the generative AI model, which analyzes the question and generates an appropriate answer. That answer is sent to the device via the server and displayed to the user.

[0150] Specific example:

[0151] For example, a user might input the question, "How can I extract data from a specific webpage using an RPA tool?" The terminal sends this to a server, which then passes it to a generative artificial intelligence model. The model generates the answer, "To extract data from a webpage, you first need to set the appropriate selector, and then use a data scraping activity. You can find detailed guidelines below: [link]," and sends this answer back to the terminal via the server. This allows the user to learn specific techniques.

[0152] Information sharing via bulletin board function

[0153] The system also provides a bulletin board function for users to share information. Users create new posts on the bulletin board, and the terminal sends the content of the post to the server. The server saves the post to a database, and if the save is successful, it retrieves a list of the latest posts and sends it to the terminal. The terminal displays this list, allowing other users to view and comment on it. If the save fails, an error message is sent to the terminal and displayed to the user.

[0154] In this way, by using the system of the present invention, users can efficiently improve their automation skills and receive support to solve practical problems. Furthermore, knowledge deepening can be expected as information sharing with other users is promoted.

[0155] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0156] User login and authentication

[0157] Step 1:

[0158] The user enters their username and password.

[0159] Input: Username and password

[0160] Specific action: The user enters their username and password into the form on the login screen and clicks the login button.

[0161] Output: Authentication information

[0162] Step 2:

[0163] The device sends authentication information to the server.

[0164] Input: Authentication information

[0165] Specific operation: The terminal sends the username and password to the server as an HTTP request in JSON format.

[0166] Output: Request to the server

[0167] Step 3:

[0168] The server accesses the database and verifies the user information.

[0169] Input: Request to the server

[0170] Specific operation: The server issues a SELECT query to the MySQL database and searches for records where the username and password match.

[0171] Output: Authentication result (success / failure)

[0172] Step 4:

[0173] The server notifies the terminal of the authentication result.

[0174] Input: Authentication result

[0175] Specific operation: If authentication is successful, the server generates a new session ID and sends it to the terminal in the HTTP response. If authentication fails, it sends a response containing an error message.

[0176] Output: Session ID or error message

[0177] Step 5:

[0178] The device displays the username and opens the dashboard screen.

[0179] Input: Session ID or error message

[0180] Specific actions: If authentication is successful, the device will display the username on the dashboard screen; if authentication fails, an error message will be displayed on the login screen.

[0181] Output: Dashboard screen or error message

[0182] Provision of automation education content

[0183] Step 1:

[0184] The user selects educational content.

[0185] Input: Selection of educational content

[0186] Specific operation: The user selects educational content such as "Fundamentals of Automation" from the list of educational courses provided on the dashboard screen.

[0187] Output: Selections

[0188] Step 2:

[0189] The device sends the selection information to the server.

[0190] Input: Selection

[0191] Specific operation: The device sends the selected course ID to the server as an HTTP request in JSON format.

[0192] Output: Request to the server

[0193] Step 3:

[0194] The server retrieves educational content from the database.

[0195] Input: Request to the server

[0196] Specific operation: The server issues a SELECT query to the database and retrieves the relevant content information.

[0197] Output: Educational content data

[0198] Step 4:

[0199] The device displays educational content to the user.

[0200] Input: Educational content data

[0201] Specific operation: The terminal renders the educational content received from the server and displays it to the user.

[0202] Output: Display of educational content

[0203] Question answering by generative artificial intelligence

[0204] Step 1:

[0205] The user enters their question.

[0206] Input: Questions about points of doubt

[0207] Specific operation: If a user has a question while viewing educational content, they enter their question into a question form and submit it.

[0208] Output: Question content

[0209] Step 2:

[0210] The terminal sends the question to the server.

[0211] Input: Question content

[0212] Specific operation: The terminal sends the user's question to the server in JSON format.

[0213] Output: Request to the server

[0214] Step 3:

[0215] The server sends a question to the generative artificial intelligence model.

[0216] Input: Request to the server

[0217] Specific operation: The server sends a question as an API request to a generative artificial intelligence (e.g., GPT-4).

[0218] Output: Request to generative artificial intelligence

[0219] Step 4:

[0220] A generative artificial intelligence model generates the appropriate answer.

[0221] Input: Request to generative artificial intelligence

[0222] Specific operation: Generative artificial intelligence analyzes the question and generates an appropriate answer.

[0223] Output: Answer content

[0224] Step 5:

[0225] The server sends the response to the terminal.

[0226] Input: Answer content

[0227] Specific operation: The server sends the response received from the generative artificial intelligence to the terminal.

[0228] Output: Response to terminal

[0229] Step 6:

[0230] The device displays the answer to the user.

[0231] Input: Response to the terminal

[0232] Specific operation: The device renders the answer in a way that is easy for the user to read.

[0233] Output: Display of answers

[0234] Information sharing via bulletin board function

[0235] Step 1:

[0236] A user creates a new post on the bulletin board.

[0237] Input: Post content

[0238] Specific action: The user accesses the bulletin board screen, enters a new message, and presses the post button.

[0239] Output: Submission Request

[0240] Step 2:

[0241] The device sends the posted content to the server.

[0242] Input: Post request

[0243] Specific operation: The terminal sends the posted content to the server in JSON format.

[0244] Output: Request to the server

[0245] Step 3:

[0246] The server saves the post to the database.

[0247] Input: Request to the server

[0248] Specific operation: The server issues an INSERT query to the database and saves the posted content.

[0249] Output: Saved result

[0250] Step 4:

[0251] If saving is successful, the server retrieves the latest list of posts and sends it to the device.

[0252] Input: Saved result

[0253] Specific operation: If the save is successful, the server issues a SELECT query to retrieve the latest list of posts from the database.

[0254] Output: List of latest posts

[0255] Step 5:

[0256] The device displays a list of the latest posts to the user.

[0257] Input: Latest posts list

[0258] Specific operation: The device displays a list of the latest posts to the user, allowing other users to view and comment on them.

[0259] Output: Display of the latest posts

[0260] Based on the above process, this system efficiently supports the improvement of automation skills and information sharing.

[0261] (Application Example 1)

[0262] 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."

[0263] For users to efficiently acquire Robotic Process Automation (RPA) skills, it is crucial not only to provide appropriate educational content but also to receive prompt answers to questions and share information with other users. However, conventional systems have been unable to provide these in a centralized manner, making training particularly difficult in remote environments. Furthermore, the lack of learning environments utilizing advanced interfaces such as voice input and smart glasses has reduced user convenience.

[0264] 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.

[0265] In this invention, the server includes means for receiving identification information entered by a user and authenticating the user based on said identification information; means for providing the user with automation-related educational content if authentication is successful; means for collecting questions entered by the user and sending said questions to a generative artificial intelligence engine; means for displaying the answers received from the generative artificial intelligence engine to the user; means for providing a bulletin board function so that the user can share information with other users; means for the user to remotely access automation educational content via smart glasses; means for streaming the educational content in real time via a remote interface; and means for receiving voice input or text input and sending questions to the generative artificial intelligence engine in real time. This enables the user to learn advanced RPA skills regardless of location, get quick answers to their questions, and share information with other users.

[0266] User authentication is the process of verifying that a user is a legitimate user based on the identification information (username and password) that the user has entered.

[0267] "Automation education content" refers to educational materials such as learning materials and video tutorials provided to users to acquire robotic process automation (RPA) skills.

[0268] "Generative artificial intelligence" is an artificial intelligence technology that uses natural language processing and machine learning techniques to generate appropriate answers to user questions.

[0269] A "bulletin board function" is an online communication platform that allows users to share information and exchange opinions with other users.

[0270] "Smart glasses" are wearable devices that users wear and that have a display function to enhance visual information.

[0271] A "remote interface" is a system interface that allows users to access and operate a system from a remote location.

[0272] "Voice input" is the process by which a user inputs voice information into a system through a microphone.

[0273] "Real-time streaming display" is a technology that delivers educational content and other information to users in real time and displays it instantly.

[0274] This invention provides a system for users to efficiently improve their Robotic Process Automation (RPA) skills. The system includes user authentication, provision of automated training content, generative artificial intelligence-based question answering, and a bulletin board function enabling information sharing with other users. Furthermore, this invention enables remote training using smart glasses.

[0275] 1. User Authentication

[0276] The user wears smart glasses and enters their username and password via voice or text. The smart glasses send this information to the server. The server accesses the database and verifies the entered identification information. If authentication is successful, the server creates a new session and notifies the smart glasses. If authentication fails, the server sends an error message to the smart glasses and displays it to the user.

[0277] Example: The user says "Log in" by voice and enters their username and password. The smart glasses display shows "Welcome, [Username]".

[0278] 2. Provision of automation education content

[0279] Once authenticated, users select educational content using a remote interface via smart glasses. The smart glasses send this selection information to a server, which retrieves the corresponding educational content from its database. The retrieved educational content is then streamed in real time on the smart glasses' display.

[0280] Example: The "Fundamentals of Automation" course is played on the smart glasses' display. The user controls playback using voice commands.

[0281] 3. Question answering using generative artificial intelligence

[0282] If a user has questions while learning educational content, they can submit their questions via voice or text input. The smart glasses send the questions to a server, which then forwards them to a generative artificial intelligence engine. The generative AI engine analyzes the questions and generates appropriate answers. The generated answers are sent back to the smart glasses via the server and displayed to the user.

[0283] Example: When a user asks, "How can I extract data from a specific web page using an RPA tool?", the generative artificial intelligence answers, "To extract data from a web page, first set up an appropriate selector and then use a data scraping activity."

[0284] 4. Information Sharing via Bulletin Board Function

[0285] The system provides a bulletin board function for sharing information among users. Users can create new posts through smart glasses, and the smart glasses send the post content to the server. The server saves the post in the database and, if the saving is successful, retrieves the latest list of posts and sends it to the smart glasses. Other users can view this and make comments.

[0286] Example: When a user posts on the bulletin board, "Please teach me how to solve errors in a new RPA script", other users provide answers and advice.

[0287] Hardware and Software Used

[0288] Smart Glasses (wearable display, microphone, camera): Used by users to view and input educational content and question answers.

[0289] Server (authentication server, content distribution server): Provides user authentication, educational content provision, question answering, and bulletin board function.

[0290] Generative Artificial Intelligence Engine (natural language processing engine): Generates answers to users' questions.

[0291] Database: Saves user information, educational content, and bulletin board posts.

[0292] Example prompt: When the user types "How do I start the script?", the generative AI responds "To get started, first create a new project, then click the 'Run Script' button."

[0293] This allows users to efficiently acquire RPA skills even in a remote environment, obtain information in real time, and share information with other users.

[0294] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0295] Step 1:

[0296] The user puts on the smart glasses, says "login" by voice, and enters their username and password. The smart glasses send this information to the server. The server compares the entered identification information with a database and searches for a matching record. If a matching record exists, the server creates a new session and sends the session information to the smart glasses. If authentication is successful, the smart glasses display "Welcome, [Username]".

[0297] Input: Username, Password

[0298] Data processing: Database search

[0299] Output: Session information, authentication message

[0300] Step 2:

[0301] Users who successfully authenticate select automated educational content through the control panel on their smart glasses. The selection information is sent to the server, which accesses the database to retrieve the corresponding educational content. The retrieved educational content is then streamed in real time on the smart glasses' display.

[0302] Input: Selection information of educational content

[0303] Data processing: Obtain content from the database and perform streaming distribution

[0304] Output: Streaming display of educational content

[0305] Step 3:

[0306] When a user has questions during learning educational content, the user makes a question by voice input or text input. The smart glasses send the question to the server. The server passes the question to the generative artificial intelligence engine, and the engine analyzes the question and generates an appropriate answer. The answer is sent to the smart glasses via the server and displayed to the user.

[0307] Input: User's question

[0308] Data calculation: Question analysis and answer generation by the generative artificial intelligence engine

[0309] Output: Answer to the question

[0310] Step 4:

[0311] The user accesses the bulletin board via the smart glasses and creates a new post. The smart glasses send the content of the post to the server, and the server saves it in the database. If the saving is successful, the server obtains the latest list of posts and sends it to the smart glasses. Other users can view this and make comments.

[0312] Input: Content of the post to the bulletin board

[0313] Data processing: Saving the content of the post to the database and obtaining the latest posts

[0314] Output: Updated bulletin board list

[0315] This system supports users in efficiently acquiring RPA skills even in remote environments, enabling quick answers to questions and information sharing with other users.

[0316] 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.

[0317] This invention is a system for users to efficiently improve their skills in automation technologies, particularly robotic process automation (RPA). The system includes user authentication, provision of automation training content, question answering using generative artificial intelligence, a bulletin board function that enables information sharing with other users, and an emotion engine that recognizes the user's emotions.

[0318] User login and authentication

[0319] First, the user enters their identification information, specifically their username and password. The device receives this information and sends it to the server. The server accesses the database and searches for a user record that matches the entered information. If a matching record exists, the server creates a new session and notifies the device. The device displays the username and opens the dashboard. If authentication fails, the server sends an error message to the device, which then displays this to the user.

[0320] Provision of automation education content

[0321] Once authentication is successful, the user selects educational content, such as the "Automation Fundamentals" course, from the dashboard. The device sends this selection information to the server, which retrieves the corresponding educational content from its database. The retrieved content is then displayed to the user through the device.

[0322] Question answering by generative artificial intelligence

[0323] When a user encounters a question while learning educational content, they input the question into a generative artificial intelligence (AI). The device collects the question and sends it to an emotion engine. The emotion engine analyzes the user's emotions and sends that emotional state as additional information to the server. The server passes the question and emotion information back to the generative AI engine, which analyzes it and generates an appropriate answer. The tone and content of the answer are adjusted according to the user's emotions. The generated answer is sent to the device via the server and displayed to the user.

[0324] Information sharing via bulletin board function

[0325] The system also provides a bulletin board function for users to share information. Users create new posts on the bulletin board, and the terminal sends the content of the post to the server. The server saves the content of the post to a database, and if the save is successful, it retrieves a list of the latest posts and sends it to the terminal. The terminal displays this list, allowing other users to view and comment on it. If the save fails, an error message is sent to the terminal and displayed to the user.

[0326] Specific examples of combinations of emotional engines

[0327] For example, if a user wants to ask a question about how to use an RPA tool, they might input the question, "How do I extract data from a specific webpage using an RPA tool?" The terminal sends this to the server, which then sends it to the emotion engine. The emotion engine analyzes the user's emotional state, and if it determines that the user is feeling anxious, it sends the result to the server. The server passes this emotional information along with the question to a generative artificial intelligence engine, which, based on the emotional state, generates a message such as, "To extract data from a webpage, you first need to set the appropriate selector, and then use a data scraping activity. If this is your first time, please refer to the link below. There is also a video with detailed guidelines, so don't worry." This answer is sent to the terminal via the server and displayed to the user.

[0328] Utilizing user sentiment data

[0329] Furthermore, user sentiment data is stored in a database, allowing a generative artificial intelligence engine to provide personalized answers based on past sentiment data the next time a question is asked. For example, when asking similar questions, it can provide more relaxing language and reference materials.

[0330] In this way, the system of the present invention not only allows users to efficiently improve their RPA skills but also provides a more personalized learning experience by offering support tailored to their emotional state. This allows users to engage in learning with peace of mind, and as a result, skill acquisition is accelerated.

[0331] The following describes the processing flow.

[0332] User login and authentication

[0333] Step 1:

[0334] The user enters their username and password into the login form.

[0335] Step 2:

[0336] The device collects the login form data, encrypts it, and sends it to the server.

[0337] Step 3:

[0338] The server executes a query against the database to search for records that match the entered username and password.

[0339] Step 4:

[0340] The database returns the corresponding user record.

[0341] Step 5:

[0342] The server checks the user record, and if a matching record exists, it creates a new session.

[0343] Step 6:

[0344] The server sends session information to the terminal.

[0345] Step 7:

[0346] The device receives session information, displays the username, and opens the dashboard.

[0347] Step 8:

[0348] If authentication fails, the server sends an error message to the terminal, which then displays it to the user.

[0349] Provision of automation education content

[0350] Step 1:

[0351] The user selects the "Automation Fundamentals" course from the dashboard.

[0352] Step 2:

[0353] The device collects user selection information and sends it to the server.

[0354] Step 3:

[0355] The server retrieves the educational content corresponding to the selected course from the database.

[0356] Step 4:

[0357] The database returns the corresponding course content.

[0358] Step 5:

[0359] The server sends the acquired course information to the terminal.

[0360] Step 6:

[0361] The device displays the course content to the user.

[0362] Question answering by generative artificial intelligence

[0363] Step 1:

[0364] The user inputs questions to the generative artificial intelligence to ask questions about points they are unsure of during the learning process.

[0365] Step 2:

[0366] The device collects user questions and sends them to the sentiment engine.

[0367] Step 3:

[0368] The emotion engine analyzes the user's emotions and generates emotion data.

[0369] Step 4:

[0370] The emotion engine sends emotion data to the server.

[0371] Step 5:

[0372] The server sends the question and sentiment data to a generative artificial intelligence engine.

[0373] Step 6:

[0374] A generative artificial intelligence engine analyzes questions and emotion data to generate responses that are appropriate to the emotions.

[0375] Step 7:

[0376] The generative artificial intelligence engine generates the answer and sends it to the server.

[0377] Step 8:

[0378] The server sends the response to the terminal.

[0379] Step 9:

[0380] The device displays the answer to the user.

[0381] Information sharing via bulletin board function

[0382] Step 1:

[0383] The user enters new content for the bulletin board.

[0384] Step 2:

[0385] The device collects the posted content and sends it to the server.

[0386] Step 3:

[0387] The server saves the posted content to the database.

[0388] Step 4:

[0389] The database returns the save status to the server.

[0390] Step 5:

[0391] If the server successfully saves the data, it will execute a query to retrieve the latest list of posts from the database.

[0392] Step 6:

[0393] The database returns a list of the most recent posts to the server.

[0394] Step 7:

[0395] The server sends a list of posts to the device.

[0396] Step 8:

[0397] The device displays a list of posts to the user, allowing other users to view and comment on them.

[0398] Step 9:

[0399] If saving fails, the server sends an error message to the terminal, which then displays it to the user.

[0400] Specific example: Questions about how to use RPA tools

[0401] Step 1:

[0402] The user inputs a question to the generative artificial intelligence: "How can I extract data from a specific webpage using an RPA tool?"

[0403] Step 2:

[0404] The device collects questions and sends them to the server, which then also sends them to the emotion engine.

[0405] Step 3:

[0406] The emotion engine analyzes the user's emotional state from their questions, determines it to be "anxious," and sends the result to the server.

[0407] Step 4:

[0408] The server sends the question and "anxiety" emotion data to a generative artificial intelligence engine.

[0409] Step 5:

[0410] A generative artificial intelligence engine analyzes questions and sentiment data to generate sentiment-sensitive responses. For example, it might create a response like, "To extract data from a webpage, you first need to set the appropriate selectors, and then use a data scraping activity. If this is your first time, please refer to the link below. There is also a video with detailed guidelines, so don't worry."

[0411] Step 6:

[0412] The generative artificial intelligence engine generates the answer and sends it to the server.

[0413] Step 7:

[0414] The server sends the response to the terminal.

[0415] Step 8:

[0416] The device displays the response to the user. This allows the user to receive a response that has been adjusted based on sentiment data.

[0417] Utilizing user sentiment data

[0418] Step 1:

[0419] The questions submitted by users, along with their sentiment data, and their corresponding answers are stored in a database.

[0420] Step 2:

[0421] The next time the same user asks a question, the generative artificial intelligence engine can provide a personalized answer based on past sentiment data. For example, if a user was previously identified as "anxious," the engine will provide an answer carefully designed to make them feel "reassured" again.

[0422] In this way, the system of the present invention not only allows users to efficiently improve their automation skills, but also provides a more personalized learning experience by offering detailed support tailored to their emotional state. As a result, users can engage in learning with peace of mind, and consequently, skill acquisition is accelerated.

[0423] (Example 2)

[0424] 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".

[0425] Traditional robotic process automation (RPA) training systems lack personalized responses to user questions and fail to provide support that takes into account the user's emotional state. Furthermore, information sharing among users is often limited, posing challenges to improving learning efficiency and maintaining sustained motivation.

[0426] 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.

[0427] In this invention, the server includes means for receiving identification information entered by the user and authenticating the user based on said identification information; means for providing the user with educational content related to automation if authentication is successful; means for collecting questions entered by the user and sending said questions to a generative artificial intelligence engine; means for displaying the answers received from the generative artificial intelligence engine to the user; means for providing a bulletin board function so that the user can share information with other users; means for analyzing the user's emotional state, adding that information, and sending it to the generative artificial intelligence engine; and means for storing the user's emotional data in a database and generating personalized answers for the next time a question is asked. This enables personalized support based on the user's emotional state, allowing for efficient learning and the maintenance of continuous motivation.

[0428] "Identification information" refers to information used by a user when accessing the system, including, for example, usernames and passwords.

[0429] "Authentication" is the process of verifying whether the identification information entered by the user is correct.

[0430] "Educational content related to automation" refers to educational materials and training resources related to robotic process automation (RPA).

[0431] A "question" refers to any doubts or inquiries that a user may have while learning educational content.

[0432] A "generative artificial intelligence engine" refers to an artificial intelligence model that analyzes user questions and generates corresponding answers.

[0433] A "bulletin board function" refers to an online platform for users to share information and communicate with each other.

[0434] "Emotional state" refers to the user's current psychological state and emotions, and is the subject of analysis by the system.

[0435] A "personalized response" refers to a response that is tailored based on the user's individual circumstances and past data.

[0436] This invention is a system for users to efficiently improve their skills in automation technology, particularly robotic process automation (RPA). The system includes user authentication, provision of automation training content, question answering using generative artificial intelligence, a bulletin board function that enables information sharing with other users, and an emotion engine that recognizes the user's emotions.

[0437] User login and authentication

[0438] First, the user enters their identification information, specifically their username and password. The device receives this information and sends it to the server. The server accesses the database and searches for a user record that matches the entered information. If a matching record exists, the server creates a new session and notifies the device. The device displays the username and opens the dashboard. If authentication fails, the server sends an error message to the device, which then displays this to the user.

[0439] Provision of automation education content

[0440] Once authentication is successful, the user selects educational content, such as the "Automation Fundamentals" course, from the dashboard. The device sends this selection information to the server, which retrieves the corresponding educational content from its database. The retrieved content is then displayed to the user through the device.

[0441] Question answering by generative artificial intelligence

[0442] When a user encounters a question while learning educational content, they input the question into a generative artificial intelligence (AI). The device collects the question and sends it to an emotion engine. The emotion engine analyzes the user's emotions and sends that emotional state as additional information to the server. The server passes the question and emotion information back to the generative AI engine, which analyzes it and generates an appropriate answer. The tone and content of the answer are adjusted according to the user's emotions. The generated answer is sent to the device via the server and displayed to the user.

[0443] Specific example:

[0444] A user can input a question such as, "How can I extract data from a specific webpage using an RPA tool?" The terminal sends this to the server, which then sends it to the emotion engine. The emotion engine analyzes the user's emotional state, and if it determines that the user is feeling anxious, it sends the result to the server. The server then passes the question, based on the emotional information, to a generative artificial intelligence engine, which generates an answer such as, "To extract data from a webpage, you must first set the appropriate selector, and then use a data scraping activity. If this is your first time, please refer to the link below. There is also a video with detailed guidelines, so please don't worry." This answer is then sent to the terminal via the server and displayed to the user.

[0445] Information sharing via bulletin board function

[0446] The system also provides a bulletin board function for users to share information. Users create new posts on the bulletin board, and the terminal sends the content of the post to the server. The server saves the content of the post to a database, and if the save is successful, it retrieves a list of the latest posts and sends it to the terminal. The terminal displays this list, allowing other users to view and comment on it. If the save fails, an error message is sent to the terminal and displayed to the user.

[0447] Utilizing user sentiment data

[0448] Furthermore, user sentiment data is stored in a database, allowing a generative artificial intelligence engine to provide personalized answers based on past sentiment data the next time a question is asked. For example, when asking similar questions, it can provide expressions and reference materials that help the user relax.

[0449] Hardware and software to use

[0450] The operation of this system requires servers, terminals (PCs, tablets, smartphones, etc.), a database management system (DBMS), a generative artificial intelligence engine (e.g., ChatGPT®, BERT), and an emotion recognition engine. These elements work together to create a system that supports the improvement of users' RPA skills.

[0451] As a result, the system of the present invention can not only enable users to efficiently improve their RPA skills, but also provide a more personalized learning experience by offering support tailored to their emotional state.

[0452] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0453] Step 1:

[0454] The user enters their username and password on the login screen.

[0455] Input: User's username and password.

[0456] Operation: The user enters their identification information into the system.

[0457] Output: The entered authentication information is sent to the terminal.

[0458] Step 2:

[0459] The terminal sends the user's input information to the server.

[0460] Input: User's username and password.

[0461] Operation: The terminal receives user input and sends it to the server.

[0462] Output: Authentication information sent to the server.

[0463] Step 3:

[0464] The server accesses the database and searches for records that match the entered information.

[0465] Input: Username and password sent to the server.

[0466] Operation: The server queries the database and evaluates the authentication information.

[0467] Output: Authentication result (success or failure).

[0468] Step 4:

[0469] The server sends the authentication result to the terminal and notifies the user.

[0470] Input: Authentication result.

[0471] Operation: If authentication is successful, the server creates a new session and sends the information to the terminal. If authentication fails, it generates an error message.

[0472] Output: Session information or error messages are sent to the terminal.

[0473] Step 5:

[0474] The device displays the authentication result to the user.

[0475] Input: Session information or error message.

[0476] Operation: The terminal displays information received from the server to the user.

[0477] Output: The user will be able to access the dashboard (on success) or an error message will be displayed (on failure).

[0478] Step 6:

[0479] Users who successfully authenticate can select educational content from the dashboard.

[0480] Input: User's content selection.

[0481] Operation: Users select educational content of interest on the dashboard.

[0482] Output: Selected content information is sent to the device.

[0483] Step 7:

[0484] The device sends the selection information to the server.

[0485] Input: Selected educational content information.

[0486] Operation: The terminal receives the user's selection information and sends it to the server.

[0487] Output: Content selection information sent to the server.

[0488] Step 8:

[0489] The server retrieves the relevant educational content from the database.

[0490] Input: Content selection information sent to the server.

[0491] Operation: The server accesses the database and retrieves the relevant educational content.

[0492] Output: Acquired educational content.

[0493] Step 9:

[0494] The device displays educational content to the user.

[0495] Input: Acquired educational content.

[0496] Operation: The terminal displays educational content received from the server to the user.

[0497] Output: The user becomes able to view the educational content.

[0498] Step 10:

[0499] Users input questions as points of confusion during their learning process.

[0500] Input: User's question.

[0501] Operation: The user enters questions that arise while learning educational content into the device.

[0502] Output: The entered question is sent to the terminal.

[0503] Step 11:

[0504] The device sends the question to the emotion engine.

[0505] Input: The question that was entered.

[0506] Operation: The terminal sends the user's question to the sentiment engine.

[0507] Output: The question sent to the emotion engine.

[0508] Step 12:

[0509] The emotion engine analyzes the user's emotions and sends the results to the server.

[0510] Input: User's question.

[0511] Operation: The emotion engine analyzes the user's emotional state based on the content of the question.

[0512] Output: The analyzed emotion information is sent to the server.

[0513] Step 13:

[0514] The server sends the question and sentiment information to a generative artificial intelligence engine.

[0515] Input: User's question and sentiment information.

[0516] Operation: The server sends the question and sentiment information to a generative artificial intelligence engine.

[0517] Output: Questions and sentiment information sent to the generative artificial intelligence engine.

[0518] Step 14:

[0519] A generative artificial intelligence engine generates answers to questions.

[0520] Input: Question and sentiment information.

[0521] Operation: The generative artificial intelligence engine generates appropriate answers based on the question and sentiment information.

[0522] Output: Generated answer.

[0523] Step 15:

[0524] The server sends the generated response to the terminal.

[0525] Input: Generated response.

[0526] Operation: The server receives the generated response and sends it to the terminal.

[0527] Output: The response sent to the terminal.

[0528] Step 16:

[0529] The terminal displays the generated response to the user.

[0530] Input: Response sent from the server.

[0531] Operation: The terminal displays the generated response to the user.

[0532] Output: The user will be able to view the answer.

[0533] Step 17:

[0534] A user creates a new post on the bulletin board.

[0535] Input: Post content.

[0536] Action: The user enters a new post on the bulletin board.

[0537] Output: The entered post content is sent to the device.

[0538] Step 18:

[0539] The device sends the posted content to the server.

[0540] Input: Post content.

[0541] Operation: The terminal receives user input and sends it to the server.

[0542] Output: The content of the post sent to the server.

[0543] Step 19:

[0544] The server saves the posted content to a database and sends the saved result to the terminal.

[0545] Input: Post content.

[0546] Operation: The server saves the posted content to the database and determines whether the save was successful or unsuccessful.

[0547] Output: The saved result is sent to the terminal.

[0548] Step 20:

[0549] The device displays the saved results to the user and updates the list of posts.

[0550] Input: Saved results and a list of the latest posts.

[0551] Operation: The terminal displays a message to the user depending on the save result, and if the save is successful, it displays a list of the latest posts.

[0552] Output: The user will be able to view the latest posts.

[0553] Step 21:

[0554] The emotion engine stores the user's emotional data in a database.

[0555] Input: User sentiment data.

[0556] Operation: The emotion engine saves the analyzed emotion data to a database.

[0557] Output: Emotional data stored in the database.

[0558] Step 22:

[0559] The next time a question is asked, the server sends past sentiment data to a generative artificial intelligence engine to generate a personalized response.

[0560] Input: Past sentiment data and a new question.

[0561] Operation: The server sends questions to a generative artificial intelligence engine based on past sentiment data, which then generates personalized answers.

[0562] Output: Personalized response.

[0563] (Application Example 2)

[0564] 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".

[0565] In modern factories and businesses, improving skills in efficient automation technologies, particularly robotic process automation (RPA), requires employees to acquire a broad range of knowledge and practical skills individually. However, providing appropriate education and support tailored to each employee's individual skill level and emotional state is extremely difficult. Furthermore, a lack of information sharing raises concerns about decreased productivity and the occurrence of problems.

[0566] 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.

[0567] In this invention, the server includes means for receiving identification information entered by a user and authenticating the user based on said identification information; means for providing the user with educational content related to automation if authentication is successful; means for providing content related to automated work in the factory as educational content; means for collecting questions entered by the user and sending said questions to a generative artificial intelligence engine; means for displaying the answers received from the generative artificial intelligence engine to the user; means for providing a bulletin board function so that the user can share information with other users; and means for analyzing the user's emotional state using an emotion engine, and for the generative artificial intelligence engine to provide the user with personalized answers based on the results. This enables personalized education and support tailored to the skills and emotional state of employees, and also promotes information sharing.

[0568] "User-entered identification information" refers to information that a user enters to identify themselves, specifically including usernames and passwords.

[0569] "Means of authentication" refers to a function that performs a process to verify that a user is a legitimate user based on the identification information entered by the user.

[0570] "Educational content related to automation" refers to educational materials and content that provide users with knowledge and skills related to automation technologies and robotic process automation (RPA).

[0571] A "generative artificial intelligence engine" refers to a machine learning model or algorithm that generates appropriate answers to input questions.

[0572] The term "bulletin board function" refers to online forums or bulletin boards where users can share information and engage in discussions with other users.

[0573] An "emotion engine" refers to software or algorithms that analyze a user's emotional state and adjust the output of other functions based on that information.

[0574] "Content related to automation work within the factory" refers to information and educational content regarding specific procedures and methods related to automation processes and machine operation in a factory.

[0575] "Means of collecting questions" refers to a function that receives questions entered by users and stores or processes them for analysis and answer generation.

[0576] "Means of displaying to the user" refers to functions that visually present generated information or answers to the user.

[0577] "Means of sharing information" refers to platforms and functions that allow multiple users to exchange and share information with one another.

[0578] A "personalized response" refers to a response that is customized according to the user's individual circumstances and needs.

[0579] Modes for carrying out the invention

[0580] The embodiments for carrying out the present invention are shown below.

[0581] System Overview

[0582] This invention is a system for efficiently improving the skills of factory employees in Robotic Process Automation (RPA). The system includes user authentication, provision of automated training content, question answering using generative artificial intelligence, a bulletin board function, and an emotion engine.

[0583] Hardware and software to be used

[0584] Hardware: Smartphones, factory robot panels

[0585] Software: Flask (Python framework), Emotion Engine library, RPAContentAPI, generative artificial intelligence model

[0586] User Authentication

[0587] The server receives identification information (username and password) entered by the user using a smartphone or a panel on a factory robot. Based on this, the server searches the database for the corresponding user record and performs authentication. If authentication is successful, the server creates a new session and notifies the terminal. If authentication fails, an error message is sent to the terminal and displayed to the user.

[0588] Provision of automation education content

[0589] Users who successfully authenticate select educational content related to automated tasks within the factory from the dashboard. The terminal sends this selection information to the server, which uses the RPAContentAPI to retrieve the corresponding educational content from the database and display it to the user. This allows users to learn the basics of automated tasks and RPA.

[0590] Question answering by generative artificial intelligence

[0591] If a user has questions about how to learn educational content, they enter their question. The device sends this question to an emotion engine, which analyzes the user's emotional state. The analysis results are sent to a server, where a generative artificial intelligence engine generates an appropriate answer based on the analyzed question and emotional information. The generated answer is adjusted in content and tone according to the user's emotional state, and is sent to the device via the server and displayed to the user.

[0592] Information sharing via bulletin board function

[0593] The system also provides a bulletin board function for users to share information. Users create new posts on the bulletin board, and their devices send the content of those posts to the server. The server stores this content in a database, making it available for other users to view and comment on. If saving fails, an error message is sent to the device and displayed to the user.

[0594] The use of the emotion engine and specific examples.

[0595] The emotion engine is used when a user has a question about how to use the RPA tool. For example, if the user enters the question, "How do I extract data from a specific webpage using the RPA tool?", the terminal sends this to the server, and the emotion engine analyzes the user's emotional state. Depending on the analysis results, if it is determined that the user is feeling anxious, that information is passed to the generative artificial intelligence engine, and the response will include a tone such as "Don't worry." The generated response is sent to the terminal via the server and displayed to the user.

[0596] Example of a prompt

[0597] "How can I extract data from a specific webpage using an RPA tool?"

[0598] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0599] Step 1:

[0600] The user enters identification information (username and password) using a smartphone or a panel on a factory robot. The terminal receives the entered identification information and sends it to the server. At this stage, the input is the username and password, and the output is the data sent to the server.

[0601] Step 2:

[0602] The server searches the database based on the received user identification information to find the corresponding user record. The input for the database search is the identification information, and the output is either the user record (if it exists) or an error message (if it does not exist).

[0603] Step 3:

[0604] When the server finds a user record, it creates a new session and notifies the terminal. The input is the user record, and the output is the new session information. Based on this session information, the terminal displays a login success message to the user.

[0605] Step 4:

[0606] If authentication is successful, the user selects educational content related to automated factory operations from the dashboard. The terminal sends the selected content information to the server. The input is the selected content information, and the output is the data sent to the server.

[0607] Step 5:

[0608] The server uses the RPAContentAPI to retrieve the relevant educational content from the database. The input is content selection information, and the output is the retrieved educational content. The server sends the retrieved educational content to the terminal, which then displays it to the user.

[0609] Step 6:

[0610] When a user encounters a question while learning educational content, they input the question, and the device sends this question to the emotion engine. The input is the user's question, and the output is the data sent to the emotion engine.

[0611] Step 7:

[0612] The emotion engine analyzes the user's emotional state along with their question. The input is the user's question and emotional data, and the output is the analyzed emotional information. This analyzed information is then sent to the server.

[0613] Step 8:

[0614] The server passes the analyzed question and sentiment information to a generative artificial intelligence engine, which then generates an appropriate answer. The input is the analyzed question and sentiment information, and the output is the generated answer. This answer is sent to the terminal via the server, and the terminal displays the answer to the user.

[0615] Step 9:

[0616] The user creates a new post using the bulletin board function. The terminal sends the content entered by the user to the server. The input is the post content, and the output is the data sent to the server.

[0617] Step 10:

[0618] The server saves the posted content to the database. If the save is successful, it retrieves the latest list of posts and sends it to the terminal for display to the user. The input is the posted content, and the output is the updated list of posts. If the save fails, an error message is sent to the terminal and displayed to the user.

[0619] In this way, a system is realized that allows users to efficiently improve their RPA skills through each processing step.

[0620] 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.

[0621] 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 (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.

[0622] 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.

[0623] [Second Embodiment]

[0624] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0625] 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.

[0626] 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).

[0627] 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.

[0628] 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.

[0629] 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).

[0630] 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.

[0631] 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.

[0632] 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.

[0633] 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.

[0634] 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.

[0635] 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".

[0636] This invention is a system for users to efficiently improve their skills in automation technologies, particularly robotic process automation (RPA). The system includes user authentication, provision of automation training content, question answering using generative artificial intelligence, and a bulletin board function that enables information sharing with other users.

[0637] User login and authentication

[0638] First, the user enters their identification information, specifically their username and password. The device receives this information and sends it to the server. The server accesses the database and searches for a user record that matches the entered information. If a matching record exists, the server creates a new session and notifies the device. The device displays the username and opens the dashboard. If authentication fails, the server sends an error message to the device, which then displays this to the user.

[0639] Provision of automation education content

[0640] Once authentication is successful, the user selects educational content, such as the "Automation Fundamentals" course, from the dashboard. The device sends this selection information to the server, which retrieves the corresponding educational content from its database. The retrieved content is then displayed to the user through the device.

[0641] Question answering by generative artificial intelligence

[0642] Users can ask generative artificial intelligence questions about points that arise during the learning process of educational content. The user inputs a question, the device collects it, and sends it to the server. The server passes the question to the generative AI engine, which analyzes the question and generates an appropriate answer. This answer is then sent to the device via the server and displayed to the user.

[0643] Information sharing via bulletin board function

[0644] The system also provides a bulletin board function for users to share information. Users create new posts on the bulletin board, and the terminal sends the content of the post to the server. The server saves the post to a database, and if the save is successful, it retrieves a list of the latest posts and sends it to the terminal. The terminal displays this list, allowing other users to view and comment on it. If the save fails, an error message is sent to the terminal and displayed to the user.

[0645] Specific example

[0646] For example, if a user wants to ask a question about how to use an RPA tool, they might input the question, "How do I extract data from a specific webpage using an RPA tool?" The terminal sends this to the server, which then passes it to a generative artificial intelligence engine. The engine generates an answer such as, "To extract data from a webpage, you first need to set the appropriate selector, and then use a data scraping activity. You can find detailed guidelines below: [link]," and sends it to the terminal via the server. This allows the user to learn specific techniques.

[0647] In this way, by using the system of the present invention, users can efficiently improve their automation skills and receive support to solve practical problems. Furthermore, knowledge deepening can be expected as information sharing with other users is promoted.

[0648] The following describes the processing flow.

[0649] User login and authentication

[0650] Step 1:

[0651] The user enters their username and password into the login form.

[0652] Step 2:

[0653] The device collects the login form data, encrypts it, and sends it to the server.

[0654] Step 3:

[0655] The server executes a query against the database to search for records that match the entered username and password.

[0656] Step 4:

[0657] The database returns the corresponding user record.

[0658] Step 5:

[0659] The server checks the user record, and if a matching record exists, it creates a new session.

[0660] Step 6:

[0661] The server sends session information to the terminal.

[0662] Step 7:

[0663] The device receives session information, displays the username, and opens the dashboard.

[0664] Step 8:

[0665] If authentication fails, the server sends an error message to the terminal, which then displays it to the user.

[0666] Provision of automation education content

[0667] Step 1:

[0668] The user selects the "Automation Fundamentals" course from the dashboard.

[0669] Step 2:

[0670] The device collects user selection information and sends it to the server.

[0671] Step 3:

[0672] The server retrieves the educational content corresponding to the selected course from the database.

[0673] Step 4:

[0674] The database returns the corresponding course content.

[0675] Step 5:

[0676] The server sends the acquired course information to the terminal.

[0677] Step 6:

[0678] The device displays the course content to the user.

[0679] Question answering by generative artificial intelligence

[0680] Step 1:

[0681] The user inputs questions to the generative artificial intelligence to ask questions about points they are unsure of during the learning process.

[0682] Step 2:

[0683] The device collects user questions and sends them to the server.

[0684] Step 3:

[0685] The server sends the question to a generative artificial intelligence engine.

[0686] Step 4:

[0687] A generative artificial intelligence engine analyzes the question and generates an appropriate answer.

[0688] Step 5:

[0689] The generative artificial intelligence engine generates the answer and sends it to the server.

[0690] Step 6:

[0691] The server sends the response to the terminal.

[0692] Step 7:

[0693] The device displays the answer to the user.

[0694] Information sharing via bulletin board function

[0695] Step 1:

[0696] The user enters new content for the bulletin board.

[0697] Step 2:

[0698] The device collects the posted content and sends it to the server.

[0699] Step 3:

[0700] The server saves the posted content to the database.

[0701] Step 4:

[0702] The database returns the save status to the server.

[0703] Step 5:

[0704] If the server successfully saves the data, it will execute a query to retrieve the latest list of posts from the database.

[0705] Step 6:

[0706] The database returns a list of the most recent posts to the server.

[0707] Step 7:

[0708] The server sends a list of posts to the device.

[0709] Step 8:

[0710] The device displays a list of posts to the user, allowing other users to view and comment on them.

[0711] Step 9:

[0712] If saving fails, the server sends an error message to the terminal, which then displays it to the user.

[0713] Specific example

[0714] Step 1:

[0715] The user inputs a question to the generative artificial intelligence: "How can I extract data from a specific webpage using an RPA tool?"

[0716] Step 2:

[0717] The device collects questions and sends them to the server.

[0718] Step 3:

[0719] The server sends the question to a generative artificial intelligence engine.

[0720] Step 4:

[0721] The generative artificial intelligence engine generates the response: "To extract data from a webpage, first set the appropriate selector, then use a data scraping activity. You can find detailed guidelines below: [link]".

[0722] Step 5:

[0723] The generative artificial intelligence engine sends the answer to the server.

[0724] Step 6:

[0725] The server sends the response to the terminal.

[0726] Step 7:

[0727] The device displays the answer to the user.

[0728] The above is a description of the specific operation of each processing step in the present invention.

[0729] (Example 1)

[0730] 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."

[0731] In today's business environment, there is a growing need to quickly and efficiently acquire skills in automation technologies, particularly robotic process automation (RPA). However, users are often overwhelmed by the vast amount of information and technology available, making it difficult to learn smoothly. Furthermore, support for obtaining appropriate answers when questions arise is insufficient, and information sharing with other users is limited. To address these problems, an effective learning support system is necessary.

[0732] 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.

[0733] In this invention, the server includes means for receiving identification information entered by the user and accessing a database based on said identification information to authenticate the user; means for creating a new session and notifying the terminal if authentication is successful; and means for providing educational content related to automation to the authenticated user. This enables users to be authenticated smoothly and to be provided with a consistent learning experience.

[0734] Furthermore, the server is equipped with means to send user-inputted questions to a generative artificial intelligence model, generate appropriate answers, and display them to the user, as well as a bulletin board function that allows users to share information with other users. This enables users to get immediate answers to their questions and continue learning effectively. It also facilitates information sharing with other users, promoting the deepening of knowledge.

[0735] "User authentication" is the process of verifying a user's identity by referencing a database based on the identification information (username and password) entered by the user.

[0736] "Educational content" refers to learning materials provided to users to improve their skills and knowledge, specifically including courses and materials related to automation technology and RPA.

[0737] A "generative artificial intelligence model" is a type of artificial intelligence that has the ability to analyze questions entered by a user and generate appropriate answers.

[0738] A "question answering system" is a system that has the function of passing questions entered by the user to a generative artificial intelligence model, collecting the generated answers, and displaying them to the user.

[0739] The "bulletin board function" is a platform for users to share information with other users, and includes features that allow users to post questions and opinions and leave comments.

[0740] A "session" refers to a series of operations performed by a user from the time they log in to the system until they log out, and is used to manage the user's operation history and authentication status.

[0741] A "device" refers to a device that a user uses to access a system, and includes personal computers, smartphones, tablets, and other similar devices.

[0742] A "server" is a centralized computing system that receives requests from users, processes them, accesses databases, and returns appropriate responses.

[0743] The present invention is a system for users to efficiently improve their skills in automation technology, particularly robotic process automation (RPA), and is implemented in the following specific forms.

[0744] User login and authentication

[0745] The user enters their identification information, specifically their username and password. The terminal receives this information and sends it to the server. The server accesses the database (e.g., a MySQL database) and searches for a user record that matches the entered information. If a matching record exists, the server creates a new session and notifies the terminal. The terminal displays the username and opens the dashboard. If authentication fails, the server sends an error message to the terminal, which the terminal displays to the user.

[0746] Provision of automation education content

[0747] After successful authentication, users select educational content such as "Fundamentals of Automation" from the dashboard. The device sends this selection information to the server, which retrieves the corresponding educational content from its database. The retrieved content is then displayed to the user through the device. The educational content is provided in various formats, including videos, text, and interactive exercises.

[0748] Question answering by generative artificial intelligence

[0749] Users can ask generative artificial intelligence (e.g., GPT-4) questions that arise during the learning process of educational content. The user inputs the question, the device collects it, and sends it to the server. The server passes the question to the generative AI model, which analyzes the question and generates an appropriate answer. This answer is then sent to the device via the server and displayed to the user.

[0750] Specific example:

[0751] For example, a user might input the question, "How can I extract data from a specific webpage using an RPA tool?" The terminal sends this to a server, which then passes it to a generative artificial intelligence model. The model generates the answer, "To extract data from a webpage, you first need to set the appropriate selector, and then use a data scraping activity. You can find detailed guidelines below: [link]," and sends this answer back to the terminal via the server. This allows the user to learn specific techniques.

[0752] Information sharing via bulletin board function

[0753] The system also provides a bulletin board function for users to share information. Users create new posts on the bulletin board, and the terminal sends the content of the post to the server. The server saves the post to a database, and if the save is successful, it retrieves a list of the latest posts and sends it to the terminal. The terminal displays this list, allowing other users to view and comment on it. If the save fails, an error message is sent to the terminal and displayed to the user.

[0754] In this way, by using the system of the present invention, users can efficiently improve their automation skills and receive support to solve practical problems. Furthermore, knowledge deepening can be expected as information sharing with other users is promoted.

[0755] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0756] User login and authentication

[0757] Step 1:

[0758] The user enters their username and password.

[0759] Input: Username and password

[0760] Specific action: The user enters their username and password into the form on the login screen and clicks the login button.

[0761] Output: Authentication information

[0762] Step 2:

[0763] The device sends authentication information to the server.

[0764] Input: Authentication information

[0765] Specific operation: The terminal sends the username and password to the server as an HTTP request in JSON format.

[0766] Output: Request to the server

[0767] Step 3:

[0768] The server accesses the database and verifies the user information.

[0769] Input: Request to the server

[0770] Specific operation: The server issues a SELECT query to the MySQL database and searches for records where the username and password match.

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

[0772] Step 4:

[0773] The server notifies the terminal of the authentication result.

[0774] Input: Authentication result

[0775] Specific operation: If authentication is successful, the server generates a new session ID and sends it to the terminal in the HTTP response. If authentication fails, it sends a response containing an error message.

[0776] Output: Session ID or error message

[0777] Step 5:

[0778] The device displays the username and opens the dashboard screen.

[0779] Input: Session ID or error message

[0780] Specific actions: If authentication is successful, the device will display the username on the dashboard screen; if authentication fails, an error message will be displayed on the login screen.

[0781] Output: Dashboard screen or error message

[0782] Provision of automation education content

[0783] Step 1:

[0784] The user selects educational content.

[0785] Input: Selection of educational content

[0786] Specific operation: The user selects educational content such as "Fundamentals of Automation" from the list of educational courses provided on the dashboard screen.

[0787] Output: Selections

[0788] Step 2:

[0789] The device sends the selection information to the server.

[0790] Input: Selection

[0791] Specific operation: The device sends the selected course ID to the server as an HTTP request in JSON format.

[0792] Output: Request to the server

[0793] Step 3:

[0794] The server retrieves educational content from the database.

[0795] Input: Request to the server

[0796] Specific operation: The server issues a SELECT query to the database and retrieves the relevant content information.

[0797] Output: Educational content data

[0798] Step 4:

[0799] The device displays educational content to the user.

[0800] Input: Educational content data

[0801] Specific operation: The terminal renders the educational content received from the server and displays it to the user.

[0802] Output: Display of educational content

[0803] Question answering by generative artificial intelligence

[0804] Step 1:

[0805] The user enters their question.

[0806] Input: Questions about points of doubt

[0807] Specific operation: If a user has a question while viewing educational content, they enter their question into a question form and submit it.

[0808] Output: Question content

[0809] Step 2:

[0810] The terminal sends the question to the server.

[0811] Input: Question content

[0812] Specific operation: The terminal sends the user's question to the server in JSON format.

[0813] Output: Request to the server

[0814] Step 3:

[0815] The server sends a question to the generative artificial intelligence model.

[0816] Input: Request to the server

[0817] Specific operation: The server sends a question as an API request to a generative artificial intelligence (e.g., GPT-4).

[0818] Output: Request to generative artificial intelligence

[0819] Step 4:

[0820] A generative artificial intelligence model generates the appropriate answer.

[0821] Input: Request to generative artificial intelligence

[0822] Specific operation: Generative artificial intelligence analyzes the question and generates an appropriate answer.

[0823] Output: Answer content

[0824] Step 5:

[0825] The server sends the response to the terminal.

[0826] Input: Answer content

[0827] Specific operation: The server sends the response received from the generative artificial intelligence to the terminal.

[0828] Output: Response to terminal

[0829] Step 6:

[0830] The device displays the answer to the user.

[0831] Input: Response to the terminal

[0832] Specific operation: The device renders the answer in a way that is easy for the user to read.

[0833] Output: Display of answers

[0834] Information sharing via bulletin board function

[0835] Step 1:

[0836] A user creates a new post on the bulletin board.

[0837] Input: Post content

[0838] Specific action: The user accesses the bulletin board screen, enters a new message, and presses the post button.

[0839] Output: Submission Request

[0840] Step 2:

[0841] The device sends the posted content to the server.

[0842] Input: Post request

[0843] Specific operation: The terminal sends the posted content to the server in JSON format.

[0844] Output: Request to the server

[0845] Step 3:

[0846] The server saves the post to the database.

[0847] Input: Request to the server

[0848] Specific operation: The server issues an INSERT query to the database and saves the posted content.

[0849] Output: Saved result

[0850] Step 4:

[0851] If saving is successful, the server retrieves the latest list of posts and sends it to the device.

[0852] Input: Saved result

[0853] Specific operation: If the save is successful, the server issues a SELECT query to retrieve the latest list of posts from the database.

[0854] Output: List of latest posts

[0855] Step 5:

[0856] The device displays a list of the latest posts to the user.

[0857] Input: Latest posts list

[0858] Specific operation: The device displays a list of the latest posts to the user, allowing other users to view and comment on them.

[0859] Output: Display of the latest posts

[0860] Based on the above process, this system efficiently supports the improvement of automation skills and information sharing.

[0861] (Application Example 1)

[0862] 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."

[0863] For users to efficiently acquire Robotic Process Automation (RPA) skills, it is crucial not only to provide appropriate educational content but also to receive prompt answers to questions and share information with other users. However, conventional systems have been unable to provide these in a centralized manner, making training particularly difficult in remote environments. Furthermore, the lack of learning environments utilizing advanced interfaces such as voice input and smart glasses has reduced user convenience.

[0864] 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.

[0865] In this invention, the server includes means for receiving identification information entered by a user and authenticating the user based on said identification information; means for providing the user with automation-related educational content if authentication is successful; means for collecting questions entered by the user and sending said questions to a generative artificial intelligence engine; means for displaying the answers received from the generative artificial intelligence engine to the user; means for providing a bulletin board function so that the user can share information with other users; means for the user to remotely access automation educational content via smart glasses; means for streaming the educational content in real time via a remote interface; and means for receiving voice input or text input and sending questions to the generative artificial intelligence engine in real time. This enables the user to learn advanced RPA skills regardless of location, get quick answers to their questions, and share information with other users.

[0866] User authentication is the process of verifying that a user is a legitimate user based on the identification information (username and password) that the user has entered.

[0867] "Automation education content" refers to educational materials such as learning materials and video tutorials provided to users to acquire robotic process automation (RPA) skills.

[0868] "Generative artificial intelligence" is an artificial intelligence technology that uses natural language processing and machine learning techniques to generate appropriate answers to user questions.

[0869] A "bulletin board function" is an online communication platform that allows users to share information and exchange opinions with other users.

[0870] "Smart glasses" are wearable devices that users wear and that have a display function to enhance visual information.

[0871] A "remote interface" is a system interface that allows users to access and operate a system from a remote location.

[0872] "Voice input" is the process by which a user inputs voice information into a system through a microphone.

[0873] "Real-time streaming display" is a technology that delivers educational content and other information to users in real time and displays it instantly.

[0874] This invention provides a system for users to efficiently improve their Robotic Process Automation (RPA) skills. The system includes user authentication, provision of automated training content, generative artificial intelligence-based question answering, and a bulletin board function enabling information sharing with other users. Furthermore, this invention enables remote training using smart glasses.

[0875] 1. User Authentication

[0876] The user wears smart glasses and enters their username and password via voice or text. The smart glasses send this information to the server. The server accesses the database and verifies the entered identification information. If authentication is successful, the server creates a new session and notifies the smart glasses. If authentication fails, the server sends an error message to the smart glasses and displays it to the user.

[0877] Example: The user says "Log in" by voice and enters their username and password. The smart glasses display shows "Welcome, [Username]".

[0878] 2. Provision of automation education content

[0879] Once authenticated, users select educational content using a remote interface via smart glasses. The smart glasses send this selection information to a server, which retrieves the corresponding educational content from its database. The retrieved educational content is then streamed in real time on the smart glasses' display.

[0880] Example: The "Fundamentals of Automation" course is played on the smart glasses' display. The user controls playback using voice commands.

[0881] 3. Question answering using generative artificial intelligence

[0882] If a user has questions while learning educational content, they can submit their questions via voice or text input. The smart glasses send the questions to a server, which then forwards them to a generative artificial intelligence engine. The generative AI engine analyzes the questions and generates appropriate answers. The generated answers are sent back to the smart glasses via the server and displayed to the user.

[0883] For example, if a user asks, "How can I extract data from a specific webpage using an RPA tool?", the generative artificial intelligence will respond, "To extract data from a webpage, first set the appropriate selector, and then use a data scraping activity."

[0884] 4. Information sharing via bulletin board function

[0885] The system provides a bulletin board function for users to share information. Users create new posts through their smart glasses, which then send the content of the post to the server. The server saves the post to a database, and if successful, retrieves a list of the latest posts and sends it to the smart glasses. Other users can view and comment on these posts.

[0886] Example: If a user posts on a message board asking "How do I fix the error in my new RPA script?", other users will provide answers and advice.

[0887] Hardware and software to be used

[0888] Smart glasses (wearable display, microphone, camera): Used by users to view and input educational content and answer questions.

[0889] Servers (authentication server, content delivery server): Provide user authentication, educational content delivery, question answering, and bulletin board functionality.

[0890] Generative artificial intelligence engine (natural language processing engine): Generates answers to user questions.

[0891] Database: Stores user information, educational content, and forum posts.

[0892] Example prompt: When the user types "How do I start the script?", the generative AI responds "To get started, first create a new project, then click the 'Run Script' button."

[0893] This allows users to efficiently acquire RPA skills even in a remote environment, obtain information in real time, and share information with other users.

[0894] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0895] Step 1:

[0896] The user puts on the smart glasses, says "login" by voice, and enters their username and password. The smart glasses send this information to the server. The server compares the entered identification information with a database and searches for a matching record. If a matching record exists, the server creates a new session and sends the session information to the smart glasses. If authentication is successful, the smart glasses display "Welcome, [Username]".

[0897] Input: Username, Password

[0898] Data processing: Database search

[0899] Output: Session information, authentication message

[0900] Step 2:

[0901] Users who successfully authenticate select automated educational content through the control panel on their smart glasses. The selection information is sent to the server, which accesses the database to retrieve the corresponding educational content. The retrieved educational content is then streamed in real time on the smart glasses' display.

[0902] Input: Educational content selection information

[0903] Data processing: Retrieve content from database and stream it.

[0904] Output: Streaming display of educational content

[0905] Step 3:

[0906] When a user encounters a question while learning educational content, they can ask it via voice or text input. The smart glasses send the question to a server. The server passes the question to a generative artificial intelligence engine, which analyzes the question and generates an appropriate answer. This answer is then sent back to the smart glasses via the server and displayed to the user.

[0907] Input: User's question

[0908] Data processing: Question analysis and answer generation using a generative artificial intelligence engine.

[0909] Output: Answer to the question

[0910] Step 4:

[0911] Users access the bulletin board via smart glasses and create new posts. The smart glasses send the post content to the server, which stores it in a database. If the save is successful, the server retrieves a list of the latest posts and sends it to the smart glasses. Other users can view and comment on these posts.

[0912] Input: Content to post on the bulletin board

[0913] Data processing: Saving posted content to the database and retrieving the latest posts.

[0914] Output: Updated bulletin board list

[0915] This system supports users in efficiently acquiring RPA skills even in remote environments, enabling quick answers to questions and information sharing with other users.

[0916] 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.

[0917] This invention is a system for users to efficiently improve their skills in automation technologies, particularly robotic process automation (RPA). The system includes user authentication, provision of automation training content, question answering using generative artificial intelligence, a bulletin board function that enables information sharing with other users, and an emotion engine that recognizes the user's emotions.

[0918] User login and authentication

[0919] First, the user enters their identification information, specifically their username and password. The device receives this information and sends it to the server. The server accesses the database and searches for a user record that matches the entered information. If a matching record exists, the server creates a new session and notifies the device. The device displays the username and opens the dashboard. If authentication fails, the server sends an error message to the device, which then displays this to the user.

[0920] Provision of automation education content

[0921] Once authentication is successful, the user selects educational content, such as the "Automation Fundamentals" course, from the dashboard. The device sends this selection information to the server, which retrieves the corresponding educational content from its database. The retrieved content is then displayed to the user through the device.

[0922] Question answering by generative artificial intelligence

[0923] When a user encounters a question while learning educational content, they input the question into a generative artificial intelligence (AI). The device collects the question and sends it to an emotion engine. The emotion engine analyzes the user's emotions and sends that emotional state as additional information to the server. The server passes the question and emotion information back to the generative AI engine, which analyzes it and generates an appropriate answer. The tone and content of the answer are adjusted according to the user's emotions. The generated answer is sent to the device via the server and displayed to the user.

[0924] Information sharing via bulletin board function

[0925] The system also provides a bulletin board function for users to share information. Users create new posts on the bulletin board, and the terminal sends the content of the post to the server. The server saves the content of the post to a database, and if the save is successful, it retrieves a list of the latest posts and sends it to the terminal. The terminal displays this list, allowing other users to view and comment on it. If the save fails, an error message is sent to the terminal and displayed to the user.

[0926] Specific examples of combinations of emotional engines

[0927] For example, if a user wants to ask a question about how to use an RPA tool, they might input the question, "How do I extract data from a specific webpage using an RPA tool?" The terminal sends this to the server, which then sends it to the emotion engine. The emotion engine analyzes the user's emotional state, and if it determines that the user is feeling anxious, it sends the result to the server. The server passes this emotional information along with the question to a generative artificial intelligence engine, which, based on the emotional state, generates a message such as, "To extract data from a webpage, you first need to set the appropriate selector, and then use a data scraping activity. If this is your first time, please refer to the link below. There is also a video with detailed guidelines, so don't worry." This answer is sent to the terminal via the server and displayed to the user.

[0928] Utilizing user sentiment data

[0929] Furthermore, user sentiment data is stored in a database, allowing a generative artificial intelligence engine to provide personalized answers based on past sentiment data the next time a question is asked. For example, when asking similar questions, it can provide more relaxing language and reference materials.

[0930] In this way, the system of the present invention not only allows users to efficiently improve their RPA skills but also provides a more personalized learning experience by offering support tailored to their emotional state. This allows users to engage in learning with peace of mind, and as a result, skill acquisition is accelerated.

[0931] The following describes the processing flow.

[0932] User login and authentication

[0933] Step 1:

[0934] The user enters their username and password into the login form.

[0935] Step 2:

[0936] The device collects the login form data, encrypts it, and sends it to the server.

[0937] Step 3:

[0938] The server executes a query against the database to search for records that match the entered username and password.

[0939] Step 4:

[0940] The database returns the corresponding user record.

[0941] Step 5:

[0942] The server checks the user record, and if a matching record exists, it creates a new session.

[0943] Step 6:

[0944] The server sends session information to the terminal.

[0945] Step 7:

[0946] The device receives session information, displays the username, and opens the dashboard.

[0947] Step 8:

[0948] If authentication fails, the server sends an error message to the terminal, which then displays it to the user.

[0949] Provision of automation education content

[0950] Step 1:

[0951] The user selects the "Automation Fundamentals" course from the dashboard.

[0952] Step 2:

[0953] The device collects user selection information and sends it to the server.

[0954] Step 3:

[0955] The server retrieves the educational content corresponding to the selected course from the database.

[0956] Step 4:

[0957] The database returns the corresponding course content.

[0958] Step 5:

[0959] The server sends the acquired course information to the terminal.

[0960] Step 6:

[0961] The device displays the course content to the user.

[0962] Question answering by generative artificial intelligence

[0963] Step 1:

[0964] The user inputs questions to the generative artificial intelligence to ask questions about points they are unsure of during the learning process.

[0965] Step 2:

[0966] The device collects user questions and sends them to the sentiment engine.

[0967] Step 3:

[0968] The emotion engine analyzes the user's emotions and generates emotion data.

[0969] Step 4:

[0970] The emotion engine sends emotion data to the server.

[0971] Step 5:

[0972] The server sends the question and sentiment data to a generative artificial intelligence engine.

[0973] Step 6:

[0974] A generative artificial intelligence engine analyzes questions and emotion data to generate responses that are appropriate to the emotions.

[0975] Step 7:

[0976] The generative artificial intelligence engine generates the answer and sends it to the server.

[0977] Step 8:

[0978] The server sends the response to the terminal.

[0979] Step 9:

[0980] The device displays the answer to the user.

[0981] Information sharing via bulletin board function

[0982] Step 1:

[0983] The user enters new content for the bulletin board.

[0984] Step 2:

[0985] The device collects the posted content and sends it to the server.

[0986] Step 3:

[0987] The server saves the posted content to the database.

[0988] Step 4:

[0989] The database returns the save status to the server.

[0990] Step 5:

[0991] If the server successfully saves the data, it will execute a query to retrieve the latest list of posts from the database.

[0992] Step 6:

[0993] The database returns a list of the most recent posts to the server.

[0994] Step 7:

[0995] The server sends a list of posts to the device.

[0996] Step 8:

[0997] The device displays a list of posts to the user, allowing other users to view and comment on them.

[0998] Step 9:

[0999] If saving fails, the server sends an error message to the terminal, which then displays it to the user.

[1000] Specific example: Questions about how to use RPA tools

[1001] Step 1:

[1002] The user inputs a question to the generative artificial intelligence: "How can I extract data from a specific webpage using an RPA tool?"

[1003] Step 2:

[1004] The device collects questions and sends them to the server, which then also sends them to the emotion engine.

[1005] Step 3:

[1006] The emotion engine analyzes the user's emotional state from their questions, determines it to be "anxious," and sends the result to the server.

[1007] Step 4:

[1008] The server sends the question and "anxiety" emotion data to a generative artificial intelligence engine.

[1009] Step 5:

[1010] A generative artificial intelligence engine analyzes questions and sentiment data to generate sentiment-sensitive responses. For example, it might create a response like, "To extract data from a webpage, you first need to set the appropriate selectors, and then use a data scraping activity. If this is your first time, please refer to the link below. There is also a video with detailed guidelines, so don't worry."

[1011] Step 6:

[1012] The generative artificial intelligence engine generates the answer and sends it to the server.

[1013] Step 7:

[1014] The server sends the response to the terminal.

[1015] Step 8:

[1016] The device displays the response to the user. This allows the user to receive a response that has been adjusted based on sentiment data.

[1017] Utilizing user sentiment data

[1018] Step 1:

[1019] The questions submitted by users, along with their sentiment data, and their corresponding answers are stored in a database.

[1020] Step 2:

[1021] The next time the same user asks a question, the generative artificial intelligence engine can provide a personalized answer based on past sentiment data. For example, if a user was previously identified as "anxious," the engine will provide an answer carefully designed to make them feel "reassured" again.

[1022] In this way, the system of the present invention not only allows users to efficiently improve their automation skills, but also provides a more personalized learning experience by offering detailed support tailored to their emotional state. As a result, users can engage in learning with peace of mind, and consequently, skill acquisition is accelerated.

[1023] (Example 2)

[1024] 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".

[1025] Traditional robotic process automation (RPA) training systems lack personalized responses to user questions and fail to provide support that takes into account the user's emotional state. Furthermore, information sharing among users is often limited, posing challenges to improving learning efficiency and maintaining sustained motivation.

[1026] 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.

[1027] In this invention, the server includes means for receiving identification information entered by the user and authenticating the user based on said identification information; means for providing the user with educational content related to automation if authentication is successful; means for collecting questions entered by the user and sending said questions to a generative artificial intelligence engine; means for displaying the answers received from the generative artificial intelligence engine to the user; means for providing a bulletin board function so that the user can share information with other users; means for analyzing the user's emotional state, adding that information, and sending it to the generative artificial intelligence engine; and means for storing the user's emotional data in a database and generating personalized answers for the next time a question is asked. This enables personalized support based on the user's emotional state, allowing for efficient learning and the maintenance of continuous motivation.

[1028] "Identification information" refers to information used by a user when accessing the system, including, for example, usernames and passwords.

[1029] "Authentication" is the process of verifying whether the identification information entered by the user is correct.

[1030] "Educational content related to automation" refers to educational materials and training resources related to robotic process automation (RPA).

[1031] A "question" refers to any doubts or inquiries that a user may have while learning educational content.

[1032] A "generative artificial intelligence engine" refers to an artificial intelligence model that analyzes user questions and generates corresponding answers.

[1033] A "bulletin board function" refers to an online platform for users to share information and communicate with each other.

[1034] "Emotional state" refers to the user's current psychological state and emotions, and is the subject of analysis by the system.

[1035] A "personalized response" refers to a response that is tailored based on the user's individual circumstances and past data.

[1036] This invention is a system for users to efficiently improve their skills in automation technology, particularly robotic process automation (RPA). The system includes user authentication, provision of automation training content, question answering using generative artificial intelligence, a bulletin board function that enables information sharing with other users, and an emotion engine that recognizes the user's emotions.

[1037] User login and authentication

[1038] First, the user enters their identification information, specifically their username and password. The device receives this information and sends it to the server. The server accesses the database and searches for a user record that matches the entered information. If a matching record exists, the server creates a new session and notifies the device. The device displays the username and opens the dashboard. If authentication fails, the server sends an error message to the device, which then displays this to the user.

[1039] Provision of automation education content

[1040] Once authentication is successful, the user selects educational content, such as the "Automation Fundamentals" course, from the dashboard. The device sends this selection information to the server, which retrieves the corresponding educational content from its database. The retrieved content is then displayed to the user through the device.

[1041] Question answering by generative artificial intelligence

[1042] When a user encounters a question while learning educational content, they input the question into a generative artificial intelligence (AI). The device collects the question and sends it to an emotion engine. The emotion engine analyzes the user's emotions and sends that emotional state as additional information to the server. The server passes the question and emotion information back to the generative AI engine, which analyzes it and generates an appropriate answer. The tone and content of the answer are adjusted according to the user's emotions. The generated answer is sent to the device via the server and displayed to the user.

[1043] Specific example:

[1044] A user can input a question such as, "How can I extract data from a specific webpage using an RPA tool?" The terminal sends this to the server, which then sends it to the emotion engine. The emotion engine analyzes the user's emotional state, and if it determines that the user is feeling anxious, it sends the result to the server. The server then passes the question, based on the emotional information, to a generative artificial intelligence engine, which generates an answer such as, "To extract data from a webpage, you must first set the appropriate selector, and then use a data scraping activity. If this is your first time, please refer to the link below. There is also a video with detailed guidelines, so please don't worry." This answer is then sent to the terminal via the server and displayed to the user.

[1045] Information sharing via bulletin board function

[1046] The system also provides a bulletin board function for users to share information. Users create new posts on the bulletin board, and the terminal sends the content of the post to the server. The server saves the content of the post to a database, and if the save is successful, it retrieves a list of the latest posts and sends it to the terminal. The terminal displays this list, allowing other users to view and comment on it. If the save fails, an error message is sent to the terminal and displayed to the user.

[1047] Utilizing user sentiment data

[1048] Furthermore, user sentiment data is stored in a database, allowing a generative artificial intelligence engine to provide personalized answers based on past sentiment data the next time a question is asked. For example, when asking similar questions, it can provide expressions and reference materials that help the user relax.

[1049] Hardware and software to use

[1050] The operation of this system requires servers, terminals (PCs, tablets, smartphones, etc.), a database management system (DBMS), a generative artificial intelligence engine (e.g., ChatGPT, BERT), and an emotion recognition engine. These elements work together to create a system that supports the improvement of users' RPA skills.

[1051] As a result, the system of the present invention can not only enable users to efficiently improve their RPA skills, but also provide a more personalized learning experience by offering support tailored to their emotional state.

[1052] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1053] Step 1:

[1054] The user enters their username and password on the login screen.

[1055] Input: User's username and password.

[1056] Operation: The user enters their identification information into the system.

[1057] Output: The entered authentication information is sent to the terminal.

[1058] Step 2:

[1059] The terminal sends the user's input information to the server.

[1060] Input: User's username and password.

[1061] Operation: The terminal receives user input and sends it to the server.

[1062] Output: Authentication information sent to the server.

[1063] Step 3:

[1064] The server accesses the database and searches for records that match the entered information.

[1065] Input: Username and password sent to the server.

[1066] Operation: The server queries the database and evaluates the authentication information.

[1067] Output: Authentication result (success or failure).

[1068] Step 4:

[1069] The server sends the authentication result to the terminal and notifies the user.

[1070] Input: Authentication result.

[1071] Operation: If authentication is successful, the server creates a new session and sends the information to the terminal. If authentication fails, it generates an error message.

[1072] Output: Session information or error messages are sent to the terminal.

[1073] Step 5:

[1074] The device displays the authentication result to the user.

[1075] Input: Session information or error message.

[1076] Operation: The terminal displays information received from the server to the user.

[1077] Output: The user will be able to access the dashboard (on success) or an error message will be displayed (on failure).

[1078] Step 6:

[1079] Users who successfully authenticate can select educational content from the dashboard.

[1080] Input: User's content selection.

[1081] Operation: Users select educational content of interest on the dashboard.

[1082] Output: Selected content information is sent to the device.

[1083] Step 7:

[1084] The device sends the selection information to the server.

[1085] Input: Selected educational content information.

[1086] Operation: The terminal receives the user's selection information and sends it to the server.

[1087] Output: Content selection information sent to the server.

[1088] Step 8:

[1089] The server retrieves the relevant educational content from the database.

[1090] Input: Content selection information sent to the server.

[1091] Operation: The server accesses the database and retrieves the relevant educational content.

[1092] Output: Acquired educational content.

[1093] Step 9:

[1094] The device displays educational content to the user.

[1095] Input: Acquired educational content.

[1096] Operation: The terminal displays educational content received from the server to the user.

[1097] Output: The user becomes able to view the educational content.

[1098] Step 10:

[1099] Users input questions as points of confusion during their learning process.

[1100] Input: User's question.

[1101] Operation: The user enters questions that arise while learning educational content into the device.

[1102] Output: The entered question is sent to the terminal.

[1103] Step 11:

[1104] The device sends the question to the emotion engine.

[1105] Input: The question that was entered.

[1106] Operation: The terminal sends the user's question to the sentiment engine.

[1107] Output: The question sent to the emotion engine.

[1108] Step 12:

[1109] The emotion engine analyzes the user's emotions and sends the results to the server.

[1110] Input: User's question.

[1111] Operation: The emotion engine analyzes the user's emotional state based on the content of the question.

[1112] Output: The analyzed emotion information is sent to the server.

[1113] Step 13:

[1114] The server sends the question and sentiment information to a generative artificial intelligence engine.

[1115] Input: User's question and sentiment information.

[1116] Operation: The server sends the question and sentiment information to a generative artificial intelligence engine.

[1117] Output: Questions and sentiment information sent to the generative artificial intelligence engine.

[1118] Step 14:

[1119] A generative artificial intelligence engine generates answers to questions.

[1120] Input: Question and sentiment information.

[1121] Operation: The generative artificial intelligence engine generates appropriate answers based on the question and sentiment information.

[1122] Output: Generated answer.

[1123] Step 15:

[1124] The server sends the generated response to the terminal.

[1125] Input: Generated response.

[1126] Operation: The server receives the generated response and sends it to the terminal.

[1127] Output: The response sent to the terminal.

[1128] Step 16:

[1129] The terminal displays the generated response to the user.

[1130] Input: Response sent from the server.

[1131] Operation: The terminal displays the generated response to the user.

[1132] Output: The user will be able to view the answer.

[1133] Step 17:

[1134] A user creates a new post on the bulletin board.

[1135] Input: Post content.

[1136] Action: The user enters a new post on the bulletin board.

[1137] Output: The entered post content is sent to the device.

[1138] Step 18:

[1139] The device sends the posted content to the server.

[1140] Input: Post content.

[1141] Operation: The terminal receives user input and sends it to the server.

[1142] Output: The content of the post sent to the server.

[1143] Step 19:

[1144] The server saves the posted content to a database and sends the saved result to the terminal.

[1145] Input: Post content.

[1146] Operation: The server saves the posted content to the database and determines whether the save was successful or unsuccessful.

[1147] Output: The saved result is sent to the terminal.

[1148] Step 20:

[1149] The device displays the saved results to the user and updates the list of posts.

[1150] Input: Saved results and a list of the latest posts.

[1151] Operation: The terminal displays a message to the user depending on the save result, and if the save is successful, it displays a list of the latest posts.

[1152] Output: The user will be able to view the latest posts.

[1153] Step 21:

[1154] The emotion engine stores the user's emotional data in a database.

[1155] Input: User sentiment data.

[1156] Operation: The emotion engine saves the analyzed emotion data to a database.

[1157] Output: Emotional data stored in the database.

[1158] Step 22:

[1159] The next time a question is asked, the server sends past sentiment data to a generative artificial intelligence engine to generate a personalized response.

[1160] Input: Past sentiment data and a new question.

[1161] Operation: The server sends questions to a generative artificial intelligence engine based on past sentiment data, which then generates personalized answers.

[1162] Output: Personalized response.

[1163] (Application Example 2)

[1164] 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."

[1165] In modern factories and businesses, improving skills in efficient automation technologies, particularly robotic process automation (RPA), requires employees to acquire a broad range of knowledge and practical skills individually. However, providing appropriate education and support tailored to each employee's individual skill level and emotional state is extremely difficult. Furthermore, a lack of information sharing raises concerns about decreased productivity and the occurrence of problems.

[1166] 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.

[1167] In this invention, the server includes means for receiving identification information entered by a user and authenticating the user based on said identification information; means for providing the user with educational content related to automation if authentication is successful; means for providing content related to automated work in the factory as educational content; means for collecting questions entered by the user and sending said questions to a generative artificial intelligence engine; means for displaying the answers received from the generative artificial intelligence engine to the user; means for providing a bulletin board function so that the user can share information with other users; and means for analyzing the user's emotional state using an emotion engine, and for the generative artificial intelligence engine to provide the user with personalized answers based on the results. This enables personalized education and support tailored to the skills and emotional state of employees, and also promotes information sharing.

[1168] "User-entered identification information" refers to information that a user enters to identify themselves, specifically including usernames and passwords.

[1169] "Means of authentication" refers to a function that performs a process to verify that a user is a legitimate user based on the identification information entered by the user.

[1170] "Educational content related to automation" refers to educational materials and content that provide users with knowledge and skills related to automation technologies and robotic process automation (RPA).

[1171] A "generative artificial intelligence engine" refers to a machine learning model or algorithm that generates appropriate answers to input questions.

[1172] The term "bulletin board function" refers to online forums or bulletin boards where users can share information and engage in discussions with other users.

[1173] An "emotion engine" refers to software or algorithms that analyze a user's emotional state and adjust the output of other functions based on that information.

[1174] "Content related to automation work within the factory" refers to information and educational content regarding specific procedures and methods related to automation processes and machine operation in a factory.

[1175] "Means of collecting questions" refers to a function that receives questions entered by users and stores or processes them for analysis and answer generation.

[1176] "Means of displaying to the user" refers to functions that visually present generated information or answers to the user.

[1177] "Means of sharing information" refers to platforms and functions that allow multiple users to exchange and share information with one another.

[1178] A "personalized response" refers to a response that is customized according to the user's individual circumstances and needs.

[1179] Modes for carrying out the invention

[1180] The embodiments for carrying out the present invention are shown below.

[1181] System Overview

[1182] This invention is a system for efficiently improving the skills of factory employees in Robotic Process Automation (RPA). The system includes user authentication, provision of automated training content, question answering using generative artificial intelligence, a bulletin board function, and an emotion engine.

[1183] Hardware and software to be used

[1184] Hardware: Smartphones, factory robot panels

[1185] Software: Flask (Python framework), Emotion Engine library, RPAContentAPI, generative artificial intelligence model

[1186] User Authentication

[1187] The server receives identification information (username and password) entered by the user using a smartphone or a panel on a factory robot. Based on this, the server searches the database for the corresponding user record and performs authentication. If authentication is successful, the server creates a new session and notifies the terminal. If authentication fails, an error message is sent to the terminal and displayed to the user.

[1188] Provision of automation education content

[1189] Users who successfully authenticate select educational content related to automated tasks within the factory from the dashboard. The terminal sends this selection information to the server, which uses the RPAContentAPI to retrieve the corresponding educational content from the database and display it to the user. This allows users to learn the basics of automated tasks and RPA.

[1190] Question answering by generative artificial intelligence

[1191] If a user has questions about how to learn educational content, they enter their question. The device sends this question to an emotion engine, which analyzes the user's emotional state. The analysis results are sent to a server, where a generative artificial intelligence engine generates an appropriate answer based on the analyzed question and emotional information. The generated answer is adjusted in content and tone according to the user's emotional state, and is sent to the device via the server and displayed to the user.

[1192] Information sharing via bulletin board function

[1193] The system also provides a bulletin board function for users to share information. Users create new posts on the bulletin board, and their devices send the content of those posts to the server. The server stores this content in a database, making it available for other users to view and comment on. If saving fails, an error message is sent to the device and displayed to the user.

[1194] The use of the emotion engine and specific examples.

[1195] The emotion engine is used when a user has a question about how to use the RPA tool. For example, if the user enters the question, "How do I extract data from a specific webpage using the RPA tool?", the terminal sends this to the server, and the emotion engine analyzes the user's emotional state. Depending on the analysis results, if it is determined that the user is feeling anxious, that information is passed to the generative artificial intelligence engine, and the response will include a tone such as "Don't worry." The generated response is sent to the terminal via the server and displayed to the user.

[1196] Example of a prompt

[1197] "How can I extract data from a specific webpage using an RPA tool?"

[1198] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1199] Step 1:

[1200] The user enters identification information (username and password) using a smartphone or a panel on a factory robot. The terminal receives the entered identification information and sends it to the server. At this stage, the input is the username and password, and the output is the data sent to the server.

[1201] Step 2:

[1202] The server searches the database based on the received user identification information to find the corresponding user record. The input for the database search is the identification information, and the output is either the user record (if it exists) or an error message (if it does not exist).

[1203] Step 3:

[1204] When the server finds a user record, it creates a new session and notifies the terminal. The input is the user record, and the output is the new session information. Based on this session information, the terminal displays a login success message to the user.

[1205] Step 4:

[1206] If authentication is successful, the user selects educational content related to automated factory operations from the dashboard. The terminal sends the selected content information to the server. The input is the selected content information, and the output is the data sent to the server.

[1207] Step 5:

[1208] The server uses the RPAContentAPI to retrieve the relevant educational content from the database. The input is content selection information, and the output is the retrieved educational content. The server sends the retrieved educational content to the terminal, which then displays it to the user.

[1209] Step 6:

[1210] When a user encounters a question while learning educational content, they input the question, and the device sends this question to the emotion engine. The input is the user's question, and the output is the data sent to the emotion engine.

[1211] Step 7:

[1212] The emotion engine analyzes the user's emotional state along with their question. The input is the user's question and emotional data, and the output is the analyzed emotional information. This analyzed information is then sent to the server.

[1213] Step 8:

[1214] The server passes the analyzed question and sentiment information to a generative artificial intelligence engine, which then generates an appropriate answer. The input is the analyzed question and sentiment information, and the output is the generated answer. This answer is sent to the terminal via the server, and the terminal displays the answer to the user.

[1215] Step 9:

[1216] The user creates a new post using the bulletin board function. The terminal sends the content entered by the user to the server. The input is the post content, and the output is the data sent to the server.

[1217] Step 10:

[1218] The server saves the posted content to the database. If the save is successful, it retrieves the latest list of posts and sends it to the terminal for display to the user. The input is the posted content, and the output is the updated list of posts. If the save fails, an error message is sent to the terminal and displayed to the user.

[1219] In this way, a system is realized that allows users to efficiently improve their RPA skills through each processing step.

[1220] 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.

[1221] 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.

[1222] 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.

[1223] [Third Embodiment]

[1224] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[1225] 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.

[1226] 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).

[1227] 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.

[1228] 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.

[1229] 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).

[1230] 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.

[1231] 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.

[1232] 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.

[1233] 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.

[1234] 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.

[1235] 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".

[1236] This invention is a system for users to efficiently improve their skills in automation technologies, particularly robotic process automation (RPA). The system includes user authentication, provision of automation training content, question answering using generative artificial intelligence, and a bulletin board function that enables information sharing with other users.

[1237] User login and authentication

[1238] First, the user enters their identification information, specifically their username and password. The device receives this information and sends it to the server. The server accesses the database and searches for a user record that matches the entered information. If a matching record exists, the server creates a new session and notifies the device. The device displays the username and opens the dashboard. If authentication fails, the server sends an error message to the device, which then displays this to the user.

[1239] Provision of automation education content

[1240] Once authentication is successful, the user selects educational content, such as the "Automation Fundamentals" course, from the dashboard. The device sends this selection information to the server, which retrieves the corresponding educational content from its database. The retrieved content is then displayed to the user through the device.

[1241] Question answering by generative artificial intelligence

[1242] Users can ask generative artificial intelligence questions about points that arise during the learning process of educational content. The user inputs a question, the device collects it, and sends it to the server. The server passes the question to the generative AI engine, which analyzes the question and generates an appropriate answer. This answer is then sent to the device via the server and displayed to the user.

[1243] Information sharing via bulletin board function

[1244] The system also provides a bulletin board function for users to share information. Users create new posts on the bulletin board, and the terminal sends the content of the post to the server. The server saves the post to a database, and if the save is successful, it retrieves a list of the latest posts and sends it to the terminal. The terminal displays this list, allowing other users to view and comment on it. If the save fails, an error message is sent to the terminal and displayed to the user.

[1245] Specific example

[1246] For example, if a user wants to ask a question about how to use an RPA tool, they might input the question, "How do I extract data from a specific webpage using an RPA tool?" The terminal sends this to the server, which then passes it to a generative artificial intelligence engine. The engine generates an answer such as, "To extract data from a webpage, you first need to set the appropriate selector, and then use a data scraping activity. You can find detailed guidelines below: [link]," and sends it to the terminal via the server. This allows the user to learn specific techniques.

[1247] In this way, by using the system of the present invention, users can efficiently improve their automation skills and receive support to solve practical problems. Furthermore, knowledge deepening can be expected as information sharing with other users is promoted.

[1248] The following describes the processing flow.

[1249] User login and authentication

[1250] Step 1:

[1251] The user enters their username and password into the login form.

[1252] Step 2:

[1253] The device collects the login form data, encrypts it, and sends it to the server.

[1254] Step 3:

[1255] The server executes a query against the database to search for records that match the entered username and password.

[1256] Step 4:

[1257] The database returns the corresponding user record.

[1258] Step 5:

[1259] The server checks the user record, and if a matching record exists, it creates a new session.

[1260] Step 6:

[1261] The server sends session information to the terminal.

[1262] Step 7:

[1263] The device receives session information, displays the username, and opens the dashboard.

[1264] Step 8:

[1265] If authentication fails, the server sends an error message to the terminal, which then displays it to the user.

[1266] Provision of automation education content

[1267] Step 1:

[1268] The user selects the "Automation Fundamentals" course from the dashboard.

[1269] Step 2:

[1270] The device collects user selection information and sends it to the server.

[1271] Step 3:

[1272] The server retrieves the educational content corresponding to the selected course from the database.

[1273] Step 4:

[1274] The database returns the corresponding course content.

[1275] Step 5:

[1276] The server sends the acquired course information to the terminal.

[1277] Step 6:

[1278] The device displays the course content to the user.

[1279] Question answering by generative artificial intelligence

[1280] Step 1:

[1281] The user inputs questions to the generative artificial intelligence to ask questions about points they are unsure of during the learning process.

[1282] Step 2:

[1283] The device collects user questions and sends them to the server.

[1284] Step 3:

[1285] The server sends the question to a generative artificial intelligence engine.

[1286] Step 4:

[1287] A generative artificial intelligence engine analyzes the question and generates an appropriate answer.

[1288] Step 5:

[1289] The generative artificial intelligence engine generates the answer and sends it to the server.

[1290] Step 6:

[1291] The server sends the response to the terminal.

[1292] Step 7:

[1293] The device displays the answer to the user.

[1294] Information sharing via bulletin board function

[1295] Step 1:

[1296] The user enters new content for the bulletin board.

[1297] Step 2:

[1298] The device collects the posted content and sends it to the server.

[1299] Step 3:

[1300] The server saves the posted content to the database.

[1301] Step 4:

[1302] The database returns the save status to the server.

[1303] Step 5:

[1304] If the server successfully saves the data, it will execute a query to retrieve the latest list of posts from the database.

[1305] Step 6:

[1306] The database returns a list of the most recent posts to the server.

[1307] Step 7:

[1308] The server sends a list of posts to the device.

[1309] Step 8:

[1310] The device displays a list of posts to the user, allowing other users to view and comment on them.

[1311] Step 9:

[1312] If saving fails, the server sends an error message to the terminal, which then displays it to the user.

[1313] Specific example

[1314] Step 1:

[1315] The user inputs a question to the generative artificial intelligence: "How can I extract data from a specific webpage using an RPA tool?"

[1316] Step 2:

[1317] The device collects questions and sends them to the server.

[1318] Step 3:

[1319] The server sends the question to a generative artificial intelligence engine.

[1320] Step 4:

[1321] The generative artificial intelligence engine generates the response: "To extract data from a webpage, first set the appropriate selector, then use a data scraping activity. You can find detailed guidelines below: [link]".

[1322] Step 5:

[1323] The generative artificial intelligence engine sends the answer to the server.

[1324] Step 6:

[1325] The server sends the response to the terminal.

[1326] Step 7:

[1327] The device displays the answer to the user.

[1328] The above is a description of the specific operation of each processing step in the present invention.

[1329] (Example 1)

[1330] 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."

[1331] In today's business environment, there is a growing need to quickly and efficiently acquire skills in automation technologies, particularly robotic process automation (RPA). However, users are often overwhelmed by the vast amount of information and technology available, making it difficult to learn smoothly. Furthermore, support for obtaining appropriate answers when questions arise is insufficient, and information sharing with other users is limited. To address these problems, an effective learning support system is necessary.

[1332] 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.

[1333] In this invention, the server includes means for receiving identification information entered by the user and accessing a database based on said identification information to authenticate the user; means for creating a new session and notifying the terminal if authentication is successful; and means for providing educational content related to automation to the authenticated user. This enables users to be authenticated smoothly and to be provided with a consistent learning experience.

[1334] Furthermore, the server is equipped with means to send user-inputted questions to a generative artificial intelligence model, generate appropriate answers, and display them to the user, as well as a bulletin board function that allows users to share information with other users. This enables users to get immediate answers to their questions and continue learning effectively. It also facilitates information sharing with other users, promoting the deepening of knowledge.

[1335] "User authentication" is the process of verifying a user's identity by referencing a database based on the identification information (username and password) entered by the user.

[1336] "Educational content" refers to learning materials provided to users to improve their skills and knowledge, specifically including courses and materials related to automation technology and RPA.

[1337] A "generative artificial intelligence model" is a type of artificial intelligence that has the ability to analyze questions entered by a user and generate appropriate answers.

[1338] A "question answering system" is a system that has the function of passing questions entered by the user to a generative artificial intelligence model, collecting the generated answers, and displaying them to the user.

[1339] The "bulletin board function" is a platform for users to share information with other users, and includes features that allow users to post questions and opinions and leave comments.

[1340] A "session" refers to a series of operations performed by a user from the time they log in to the system until they log out, and is used to manage the user's operation history and authentication status.

[1341] A "device" refers to a device that a user uses to access a system, and includes personal computers, smartphones, tablets, and other similar devices.

[1342] A "server" is a centralized computing system that receives requests from users, processes them, accesses databases, and returns appropriate responses.

[1343] The present invention is a system for users to efficiently improve their skills in automation technology, particularly robotic process automation (RPA), and is implemented in the following specific forms.

[1344] User login and authentication

[1345] The user enters their identification information, specifically their username and password. The terminal receives this information and sends it to the server. The server accesses the database (e.g., a MySQL database) and searches for a user record that matches the entered information. If a matching record exists, the server creates a new session and notifies the terminal. The terminal displays the username and opens the dashboard. If authentication fails, the server sends an error message to the terminal, which the terminal displays to the user.

[1346] Provision of automation education content

[1347] After successful authentication, users select educational content such as "Fundamentals of Automation" from the dashboard. The device sends this selection information to the server, which retrieves the corresponding educational content from its database. The retrieved content is then displayed to the user through the device. The educational content is provided in various formats, including videos, text, and interactive exercises.

[1348] Question answering by generative artificial intelligence

[1349] Users can ask generative artificial intelligence (e.g., GPT-4) questions that arise during the learning process of educational content. The user inputs the question, the device collects it, and sends it to the server. The server passes the question to the generative AI model, which analyzes the question and generates an appropriate answer. This answer is then sent to the device via the server and displayed to the user.

[1350] Specific example:

[1351] For example, a user might input the question, "How can I extract data from a specific webpage using an RPA tool?" The terminal sends this to a server, which then passes it to a generative artificial intelligence model. The model generates the answer, "To extract data from a webpage, you first need to set the appropriate selector, and then use a data scraping activity. You can find detailed guidelines below: [link]," and sends this answer back to the terminal via the server. This allows the user to learn specific techniques.

[1352] Information sharing via bulletin board function

[1353] The system also provides a bulletin board function for users to share information. Users create new posts on the bulletin board, and the terminal sends the content of the post to the server. The server saves the post to a database, and if the save is successful, it retrieves a list of the latest posts and sends it to the terminal. The terminal displays this list, allowing other users to view and comment on it. If the save fails, an error message is sent to the terminal and displayed to the user.

[1354] In this way, by using the system of the present invention, users can efficiently improve their automation skills and receive support to solve practical problems. Furthermore, knowledge deepening can be expected as information sharing with other users is promoted.

[1355] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1356] User login and authentication

[1357] Step 1:

[1358] The user enters their username and password.

[1359] Input: Username and password

[1360] Specific action: The user enters their username and password into the form on the login screen and clicks the login button.

[1361] Output: Authentication information

[1362] Step 2:

[1363] The device sends authentication information to the server.

[1364] Input: Authentication information

[1365] Specific operation: The terminal sends the username and password to the server as an HTTP request in JSON format.

[1366] Output: Request to the server

[1367] Step 3:

[1368] The server accesses the database and verifies the user information.

[1369] Input: Request to the server

[1370] Specific operation: The server issues a SELECT query to the MySQL database and searches for records where the username and password match.

[1371] Output: Authentication result (success / failure)

[1372] Step 4:

[1373] The server notifies the terminal of the authentication result.

[1374] Input: Authentication result

[1375] Specific operation: If authentication is successful, the server generates a new session ID and sends it to the terminal in the HTTP response. If authentication fails, it sends a response containing an error message.

[1376] Output: Session ID or error message

[1377] Step 5:

[1378] The device displays the username and opens the dashboard screen.

[1379] Input: Session ID or error message

[1380] Specific actions: If authentication is successful, the device will display the username on the dashboard screen; if authentication fails, an error message will be displayed on the login screen.

[1381] Output: Dashboard screen or error message

[1382] Provision of automation education content

[1383] Step 1:

[1384] The user selects educational content.

[1385] Input: Selection of educational content

[1386] Specific operation: The user selects educational content such as "Fundamentals of Automation" from the list of educational courses provided on the dashboard screen.

[1387] Output: Selections

[1388] Step 2:

[1389] The device sends the selection information to the server.

[1390] Input: Selection

[1391] Specific operation: The device sends the selected course ID to the server as an HTTP request in JSON format.

[1392] Output: Request to the server

[1393] Step 3:

[1394] The server retrieves educational content from the database.

[1395] Input: Request to the server

[1396] Specific operation: The server issues a SELECT query to the database and retrieves the relevant content information.

[1397] Output: Educational content data

[1398] Step 4:

[1399] The device displays educational content to the user.

[1400] Input: Educational content data

[1401] Specific operation: The terminal renders the educational content received from the server and displays it to the user.

[1402] Output: Display of educational content

[1403] Question answering by generative artificial intelligence

[1404] Step 1:

[1405] The user enters their question.

[1406] Input: Questions about points of doubt

[1407] Specific operation: If a user has a question while viewing educational content, they enter their question into a question form and submit it.

[1408] Output: Question content

[1409] Step 2:

[1410] The terminal sends the question to the server.

[1411] Input: Question content

[1412] Specific operation: The terminal sends the user's question to the server in JSON format.

[1413] Output: Request to the server

[1414] Step 3:

[1415] The server sends a question to the generative artificial intelligence model.

[1416] Input: Request to the server

[1417] Specific operation: The server sends a question as an API request to a generative artificial intelligence (e.g., GPT-4).

[1418] Output: Request to generative artificial intelligence

[1419] Step 4:

[1420] A generative artificial intelligence model generates the appropriate answer.

[1421] Input: Request to generative artificial intelligence

[1422] Specific operation: Generative artificial intelligence analyzes the question and generates an appropriate answer.

[1423] Output: Answer content

[1424] Step 5:

[1425] The server sends the response to the terminal.

[1426] Input: Answer content

[1427] Specific operation: The server sends the response received from the generative artificial intelligence to the terminal.

[1428] Output: Response to terminal

[1429] Step 6:

[1430] The device displays the answer to the user.

[1431] Input: Response to the terminal

[1432] Specific operation: The device renders the answer in a way that is easy for the user to read.

[1433] Output: Display of answers

[1434] Information sharing via bulletin board function

[1435] Step 1:

[1436] A user creates a new post on the bulletin board.

[1437] Input: Post content

[1438] Specific action: The user accesses the bulletin board screen, enters a new message, and presses the post button.

[1439] Output: Submission Request

[1440] Step 2:

[1441] The device sends the posted content to the server.

[1442] Input: Post request

[1443] Specific operation: The terminal sends the posted content to the server in JSON format.

[1444] Output: Request to the server

[1445] Step 3:

[1446] The server saves the post to the database.

[1447] Input: Request to the server

[1448] Specific operation: The server issues an INSERT query to the database and saves the posted content.

[1449] Output: Saved result

[1450] Step 4:

[1451] If saving is successful, the server retrieves the latest list of posts and sends it to the device.

[1452] Input: Saved result

[1453] Specific operation: If the save is successful, the server issues a SELECT query to retrieve the latest list of posts from the database.

[1454] Output: List of latest posts

[1455] Step 5:

[1456] The device displays a list of the latest posts to the user.

[1457] Input: Latest posts list

[1458] Specific operation: The device displays a list of the latest posts to the user, allowing other users to view and comment on them.

[1459] Output: Display of the latest posts

[1460] Based on the above process, this system efficiently supports the improvement of automation skills and information sharing.

[1461] (Application Example 1)

[1462] 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."

[1463] For users to efficiently acquire Robotic Process Automation (RPA) skills, it is crucial not only to provide appropriate educational content but also to receive prompt answers to questions and share information with other users. However, conventional systems have been unable to provide these in a centralized manner, making training particularly difficult in remote environments. Furthermore, the lack of learning environments utilizing advanced interfaces such as voice input and smart glasses has reduced user convenience.

[1464] 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.

[1465] In this invention, the server includes means for receiving identification information entered by a user and authenticating the user based on said identification information; means for providing the user with automation-related educational content if authentication is successful; means for collecting questions entered by the user and sending said questions to a generative artificial intelligence engine; means for displaying the answers received from the generative artificial intelligence engine to the user; means for providing a bulletin board function so that the user can share information with other users; means for the user to remotely access automation educational content via smart glasses; means for streaming the educational content in real time via a remote interface; and means for receiving voice input or text input and sending questions to the generative artificial intelligence engine in real time. This enables the user to learn advanced RPA skills regardless of location, get quick answers to their questions, and share information with other users.

[1466] User authentication is the process of verifying that a user is a legitimate user based on the identification information (username and password) that the user has entered.

[1467] "Automation education content" refers to educational materials such as learning materials and video tutorials provided to users to acquire robotic process automation (RPA) skills.

[1468] "Generative artificial intelligence" is an artificial intelligence technology that uses natural language processing and machine learning techniques to generate appropriate answers to user questions.

[1469] A "bulletin board function" is an online communication platform that allows users to share information and exchange opinions with other users.

[1470] "Smart glasses" are wearable devices that users wear and that have a display function to enhance visual information.

[1471] A "remote interface" is a system interface that allows users to access and operate a system from a remote location.

[1472] "Voice input" is the process by which a user inputs voice information into a system through a microphone.

[1473] "Real-time streaming display" is a technology that delivers educational content and other information to users in real time and displays it instantly.

[1474] This invention provides a system for users to efficiently improve their Robotic Process Automation (RPA) skills. The system includes user authentication, provision of automated training content, generative artificial intelligence-based question answering, and a bulletin board function enabling information sharing with other users. Furthermore, this invention enables remote training using smart glasses.

[1475] 1. User Authentication

[1476] The user wears smart glasses and enters their username and password via voice or text. The smart glasses send this information to the server. The server accesses the database and verifies the entered identification information. If authentication is successful, the server creates a new session and notifies the smart glasses. If authentication fails, the server sends an error message to the smart glasses and displays it to the user.

[1477] Example: The user says "Log in" by voice and enters their username and password. The smart glasses display shows "Welcome, [Username]".

[1478] 2. Provision of automation education content

[1479] Once authenticated, users select educational content using a remote interface via smart glasses. The smart glasses send this selection information to a server, which retrieves the corresponding educational content from its database. The retrieved educational content is then streamed in real time on the smart glasses' display.

[1480] Example: The "Fundamentals of Automation" course is played on the smart glasses' display. The user controls playback using voice commands.

[1481] 3. Question answering using generative artificial intelligence

[1482] If a user has questions while learning educational content, they can submit their questions via voice or text input. The smart glasses send the questions to a server, which then forwards them to a generative artificial intelligence engine. The generative AI engine analyzes the questions and generates appropriate answers. The generated answers are sent back to the smart glasses via the server and displayed to the user.

[1483] For example, if a user asks, "How can I extract data from a specific webpage using an RPA tool?", the generative artificial intelligence will respond, "To extract data from a webpage, first set the appropriate selector, and then use a data scraping activity."

[1484] 4. Information sharing via bulletin board function

[1485] The system provides a bulletin board function for users to share information. Users create new posts through their smart glasses, which then send the content of the post to the server. The server saves the post to a database, and if successful, retrieves a list of the latest posts and sends it to the smart glasses. Other users can view and comment on these posts.

[1486] Example: If a user posts on a message board asking "How do I fix the error in my new RPA script?", other users will provide answers and advice.

[1487] Hardware and software to be used

[1488] Smart glasses (wearable display, microphone, camera): Used by users to view and input educational content and answer questions.

[1489] Servers (authentication server, content delivery server): Provide user authentication, educational content delivery, question answering, and bulletin board functionality.

[1490] Generative artificial intelligence engine (natural language processing engine): Generates answers to user questions.

[1491] Database: Stores user information, educational content, and forum posts.

[1492] Example prompt: When the user types "How do I start the script?", the generative AI responds "To get started, first create a new project, then click the 'Run Script' button."

[1493] This allows users to efficiently acquire RPA skills even in a remote environment, obtain information in real time, and share information with other users.

[1494] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1495] Step 1:

[1496] The user puts on the smart glasses, says "login" by voice, and enters their username and password. The smart glasses send this information to the server. The server compares the entered identification information with a database and searches for a matching record. If a matching record exists, the server creates a new session and sends the session information to the smart glasses. If authentication is successful, the smart glasses display "Welcome, [Username]".

[1497] Input: Username, Password

[1498] Data processing: Database search

[1499] Output: Session information, authentication message

[1500] Step 2:

[1501] Users who successfully authenticate select automated educational content through the control panel on their smart glasses. The selection information is sent to the server, which accesses the database to retrieve the corresponding educational content. The retrieved educational content is then streamed in real time on the smart glasses' display.

[1502] Input: Educational content selection information

[1503] Data processing: Retrieve content from database and stream it.

[1504] Output: Streaming display of educational content

[1505] Step 3:

[1506] When a user encounters a question while learning educational content, they can ask it via voice or text input. The smart glasses send the question to a server. The server passes the question to a generative artificial intelligence engine, which analyzes the question and generates an appropriate answer. This answer is then sent back to the smart glasses via the server and displayed to the user.

[1507] Input: User's question

[1508] Data processing: Question analysis and answer generation using a generative artificial intelligence engine.

[1509] Output: Answer to the question

[1510] Step 4:

[1511] Users access the bulletin board via smart glasses and create new posts. The smart glasses send the post content to the server, which stores it in a database. If the save is successful, the server retrieves a list of the latest posts and sends it to the smart glasses. Other users can view and comment on these posts.

[1512] Input: Content to post on the bulletin board

[1513] Data processing: Saving posted content to the database and retrieving the latest posts.

[1514] Output: Updated bulletin board list

[1515] This system supports users in efficiently acquiring RPA skills even in remote environments, enabling quick answers to questions and information sharing with other users.

[1516] 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.

[1517] This invention is a system for users to efficiently improve their skills in automation technologies, particularly robotic process automation (RPA). The system includes user authentication, provision of automation training content, question answering using generative artificial intelligence, a bulletin board function that enables information sharing with other users, and an emotion engine that recognizes the user's emotions.

[1518] User login and authentication

[1519] First, the user enters their identification information, specifically their username and password. The device receives this information and sends it to the server. The server accesses the database and searches for a user record that matches the entered information. If a matching record exists, the server creates a new session and notifies the device. The device displays the username and opens the dashboard. If authentication fails, the server sends an error message to the device, which then displays this to the user.

[1520] Provision of automation education content

[1521] Once authentication is successful, the user selects educational content, such as the "Automation Fundamentals" course, from the dashboard. The device sends this selection information to the server, which retrieves the corresponding educational content from its database. The retrieved content is then displayed to the user through the device.

[1522] Question answering by generative artificial intelligence

[1523] When a user encounters a question while learning educational content, they input the question into a generative artificial intelligence (AI). The device collects the question and sends it to an emotion engine. The emotion engine analyzes the user's emotions and sends that emotional state as additional information to the server. The server passes the question and emotion information back to the generative AI engine, which analyzes it and generates an appropriate answer. The tone and content of the answer are adjusted according to the user's emotions. The generated answer is sent to the device via the server and displayed to the user.

[1524] Information sharing via bulletin board function

[1525] The system also provides a bulletin board function for users to share information. Users create new posts on the bulletin board, and the terminal sends the content of the post to the server. The server saves the content of the post to a database, and if the save is successful, it retrieves a list of the latest posts and sends it to the terminal. The terminal displays this list, allowing other users to view and comment on it. If the save fails, an error message is sent to the terminal and displayed to the user.

[1526] Specific examples of combinations of emotional engines

[1527] For example, if a user wants to ask a question about how to use an RPA tool, they might input the question, "How do I extract data from a specific webpage using an RPA tool?" The terminal sends this to the server, which then sends it to the emotion engine. The emotion engine analyzes the user's emotional state, and if it determines that the user is feeling anxious, it sends the result to the server. The server passes this emotional information along with the question to a generative artificial intelligence engine, which, based on the emotional state, generates a message such as, "To extract data from a webpage, you first need to set the appropriate selector, and then use a data scraping activity. If this is your first time, please refer to the link below. There is also a video with detailed guidelines, so don't worry." This answer is sent to the terminal via the server and displayed to the user.

[1528] Utilizing user sentiment data

[1529] Furthermore, user sentiment data is stored in a database, allowing a generative artificial intelligence engine to provide personalized answers based on past sentiment data the next time a question is asked. For example, when asking similar questions, it can provide more relaxing language and reference materials.

[1530] In this way, the system of the present invention not only allows users to efficiently improve their RPA skills but also provides a more personalized learning experience by offering support tailored to their emotional state. This allows users to engage in learning with peace of mind, and as a result, skill acquisition is accelerated.

[1531] The following describes the processing flow.

[1532] User login and authentication

[1533] Step 1:

[1534] The user enters their username and password into the login form.

[1535] Step 2:

[1536] The device collects the login form data, encrypts it, and sends it to the server.

[1537] Step 3:

[1538] The server executes a query against the database to search for records that match the entered username and password.

[1539] Step 4:

[1540] The database returns the corresponding user record.

[1541] Step 5:

[1542] The server checks the user record, and if a matching record exists, it creates a new session.

[1543] Step 6:

[1544] The server sends session information to the terminal.

[1545] Step 7:

[1546] The device receives session information, displays the username, and opens the dashboard.

[1547] Step 8:

[1548] If authentication fails, the server sends an error message to the terminal, which then displays it to the user.

[1549] Provision of automation education content

[1550] Step 1:

[1551] The user selects the "Automation Fundamentals" course from the dashboard.

[1552] Step 2:

[1553] The device collects user selection information and sends it to the server.

[1554] Step 3:

[1555] The server retrieves the educational content corresponding to the selected course from the database.

[1556] Step 4:

[1557] The database returns the corresponding course content.

[1558] Step 5:

[1559] The server sends the acquired course information to the terminal.

[1560] Step 6:

[1561] The device displays the course content to the user.

[1562] Question answering by generative artificial intelligence

[1563] Step 1:

[1564] The user inputs questions to the generative artificial intelligence to ask questions about points they are unsure of during the learning process.

[1565] Step 2:

[1566] The device collects user questions and sends them to the sentiment engine.

[1567] Step 3:

[1568] The emotion engine analyzes the user's emotions and generates emotion data.

[1569] Step 4:

[1570] The emotion engine sends emotion data to the server.

[1571] Step 5:

[1572] The server sends the question and sentiment data to a generative artificial intelligence engine.

[1573] Step 6:

[1574] A generative artificial intelligence engine analyzes questions and emotion data to generate responses that are appropriate to the emotions.

[1575] Step 7:

[1576] The generative artificial intelligence engine generates the answer and sends it to the server.

[1577] Step 8:

[1578] The server sends the response to the terminal.

[1579] Step 9:

[1580] The device displays the answer to the user.

[1581] Information sharing via bulletin board function

[1582] Step 1:

[1583] The user enters new content for the bulletin board.

[1584] Step 2:

[1585] The device collects the posted content and sends it to the server.

[1586] Step 3:

[1587] The server saves the posted content to the database.

[1588] Step 4:

[1589] The database returns the save status to the server.

[1590] Step 5:

[1591] If the server successfully saves the data, it will execute a query to retrieve the latest list of posts from the database.

[1592] Step 6:

[1593] The database returns a list of the most recent posts to the server.

[1594] Step 7:

[1595] The server sends a list of posts to the device.

[1596] Step 8:

[1597] The device displays a list of posts to the user, allowing other users to view and comment on them.

[1598] Step 9:

[1599] If saving fails, the server sends an error message to the terminal, which then displays it to the user.

[1600] Specific example: Questions about how to use RPA tools

[1601] Step 1:

[1602] The user inputs a question to the generative artificial intelligence: "How can I extract data from a specific webpage using an RPA tool?"

[1603] Step 2:

[1604] The device collects questions and sends them to the server, which then also sends them to the emotion engine.

[1605] Step 3:

[1606] The emotion engine analyzes the user's emotional state from their questions, determines it to be "anxious," and sends the result to the server.

[1607] Step 4:

[1608] The server sends the question and "anxiety" emotion data to a generative artificial intelligence engine.

[1609] Step 5:

[1610] A generative artificial intelligence engine analyzes questions and sentiment data to generate sentiment-sensitive responses. For example, it might create a response like, "To extract data from a webpage, you first need to set the appropriate selectors, and then use a data scraping activity. If this is your first time, please refer to the link below. There is also a video with detailed guidelines, so don't worry."

[1611] Step 6:

[1612] The generative artificial intelligence engine generates the answer and sends it to the server.

[1613] Step 7:

[1614] The server sends the response to the terminal.

[1615] Step 8:

[1616] The device displays the response to the user. This allows the user to receive a response that has been adjusted based on sentiment data.

[1617] Utilizing user sentiment data

[1618] Step 1:

[1619] The questions submitted by users, along with their sentiment data, and their corresponding answers are stored in a database.

[1620] Step 2:

[1621] The next time the same user asks a question, the generative artificial intelligence engine can provide a personalized answer based on past sentiment data. For example, if a user was previously identified as "anxious," the engine will provide an answer carefully designed to make them feel "reassured" again.

[1622] In this way, the system of the present invention not only allows users to efficiently improve their automation skills, but also provides a more personalized learning experience by offering detailed support tailored to their emotional state. As a result, users can engage in learning with peace of mind, and consequently, skill acquisition is accelerated.

[1623] (Example 2)

[1624] 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."

[1625] Traditional robotic process automation (RPA) training systems lack personalized responses to user questions and fail to provide support that takes into account the user's emotional state. Furthermore, information sharing among users is often limited, posing challenges to improving learning efficiency and maintaining sustained motivation.

[1626] 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.

[1627] In this invention, the server includes means for receiving identification information entered by the user and authenticating the user based on said identification information; means for providing the user with educational content related to automation if authentication is successful; means for collecting questions entered by the user and sending said questions to a generative artificial intelligence engine; means for displaying the answers received from the generative artificial intelligence engine to the user; means for providing a bulletin board function so that the user can share information with other users; means for analyzing the user's emotional state, adding that information, and sending it to the generative artificial intelligence engine; and means for storing the user's emotional data in a database and generating personalized answers for the next time a question is asked. This enables personalized support based on the user's emotional state, allowing for efficient learning and the maintenance of continuous motivation.

[1628] "Identification information" refers to information used by a user when accessing the system, including, for example, usernames and passwords.

[1629] "Authentication" is the process of verifying whether the identification information entered by the user is correct.

[1630] "Educational content related to automation" refers to educational materials and training resources related to robotic process automation (RPA).

[1631] A "question" refers to any doubts or inquiries that a user may have while learning educational content.

[1632] A "generative artificial intelligence engine" refers to an artificial intelligence model that analyzes user questions and generates corresponding answers.

[1633] A "bulletin board function" refers to an online platform for users to share information and communicate with each other.

[1634] "Emotional state" refers to the user's current psychological state and emotions, and is the subject of analysis by the system.

[1635] A "personalized response" refers to a response that is tailored based on the user's individual circumstances and past data.

[1636] This invention is a system for users to efficiently improve their skills in automation technology, particularly robotic process automation (RPA). The system includes user authentication, provision of automation training content, question answering using generative artificial intelligence, a bulletin board function that enables information sharing with other users, and an emotion engine that recognizes the user's emotions.

[1637] User login and authentication

[1638] First, the user enters their identification information, specifically their username and password. The device receives this information and sends it to the server. The server accesses the database and searches for a user record that matches the entered information. If a matching record exists, the server creates a new session and notifies the device. The device displays the username and opens the dashboard. If authentication fails, the server sends an error message to the device, which then displays this to the user.

[1639] Provision of automation education content

[1640] Once authentication is successful, the user selects educational content, such as the "Automation Fundamentals" course, from the dashboard. The device sends this selection information to the server, which retrieves the corresponding educational content from its database. The retrieved content is then displayed to the user through the device.

[1641] Question answering by generative artificial intelligence

[1642] When a user encounters a question while learning educational content, they input the question into a generative artificial intelligence (AI). The device collects the question and sends it to an emotion engine. The emotion engine analyzes the user's emotions and sends that emotional state as additional information to the server. The server passes the question and emotion information back to the generative AI engine, which analyzes it and generates an appropriate answer. The tone and content of the answer are adjusted according to the user's emotions. The generated answer is sent to the device via the server and displayed to the user.

[1643] Specific example:

[1644] A user can input a question such as, "How can I extract data from a specific webpage using an RPA tool?" The terminal sends this to the server, which then sends it to the emotion engine. The emotion engine analyzes the user's emotional state, and if it determines that the user is feeling anxious, it sends the result to the server. The server then passes the question, based on the emotional information, to a generative artificial intelligence engine, which generates an answer such as, "To extract data from a webpage, you must first set the appropriate selector, and then use a data scraping activity. If this is your first time, please refer to the link below. There is also a video with detailed guidelines, so please don't worry." This answer is then sent to the terminal via the server and displayed to the user.

[1645] Information sharing via bulletin board function

[1646] The system also provides a bulletin board function for users to share information. Users create new posts on the bulletin board, and the terminal sends the content of the post to the server. The server saves the content of the post to a database, and if the save is successful, it retrieves a list of the latest posts and sends it to the terminal. The terminal displays this list, allowing other users to view and comment on it. If the save fails, an error message is sent to the terminal and displayed to the user.

[1647] Utilizing user sentiment data

[1648] Furthermore, user sentiment data is stored in a database, allowing a generative artificial intelligence engine to provide personalized answers based on past sentiment data the next time a question is asked. For example, when asking similar questions, it can provide expressions and reference materials that help the user relax.

[1649] Hardware and software to use

[1650] The operation of this system requires servers, terminals (PCs, tablets, smartphones, etc.), a database management system (DBMS), a generative artificial intelligence engine (e.g., ChatGPT, BERT), and an emotion recognition engine. These elements work together to create a system that supports the improvement of users' RPA skills.

[1651] As a result, the system of the present invention can not only enable users to efficiently improve their RPA skills, but also provide a more personalized learning experience by offering support tailored to their emotional state.

[1652] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1653] Step 1:

[1654] The user enters their username and password on the login screen.

[1655] Input: User's username and password.

[1656] Operation: The user enters their identification information into the system.

[1657] Output: The entered authentication information is sent to the terminal.

[1658] Step 2:

[1659] The terminal sends the user's input information to the server.

[1660] Input: User's username and password.

[1661] Operation: The terminal receives user input and sends it to the server.

[1662] Output: Authentication information sent to the server.

[1663] Step 3:

[1664] The server accesses the database and searches for records that match the entered information.

[1665] Input: Username and password sent to the server.

[1666] Operation: The server queries the database and evaluates the authentication information.

[1667] Output: Authentication result (success or failure).

[1668] Step 4:

[1669] The server sends the authentication result to the terminal and notifies the user.

[1670] Input: Authentication result.

[1671] Operation: If authentication is successful, the server creates a new session and sends the information to the terminal. If authentication fails, it generates an error message.

[1672] Output: Session information or error messages are sent to the terminal.

[1673] Step 5:

[1674] The device displays the authentication result to the user.

[1675] Input: Session information or error message.

[1676] Operation: The terminal displays information received from the server to the user.

[1677] Output: The user will be able to access the dashboard (on success) or an error message will be displayed (on failure).

[1678] Step 6:

[1679] Users who successfully authenticate can select educational content from the dashboard.

[1680] Input: User's content selection.

[1681] Operation: Users select educational content of interest on the dashboard.

[1682] Output: Selected content information is sent to the device.

[1683] Step 7:

[1684] The device sends the selection information to the server.

[1685] Input: Selected educational content information.

[1686] Operation: The terminal receives the user's selection information and sends it to the server.

[1687] Output: Content selection information sent to the server.

[1688] Step 8:

[1689] The server retrieves the relevant educational content from the database.

[1690] Input: Content selection information sent to the server.

[1691] Operation: The server accesses the database and retrieves the relevant educational content.

[1692] Output: Acquired educational content.

[1693] Step 9:

[1694] The device displays educational content to the user.

[1695] Input: Acquired educational content.

[1696] Operation: The terminal displays educational content received from the server to the user.

[1697] Output: The user becomes able to view the educational content.

[1698] Step 10:

[1699] Users input questions as points of confusion during their learning process.

[1700] Input: User's question.

[1701] Operation: The user enters questions that arise while learning educational content into the device.

[1702] Output: The entered question is sent to the terminal.

[1703] Step 11:

[1704] The device sends the question to the emotion engine.

[1705] Input: The question that was entered.

[1706] Operation: The terminal sends the user's question to the sentiment engine.

[1707] Output: The question sent to the emotion engine.

[1708] Step 12:

[1709] The emotion engine analyzes the user's emotions and sends the results to the server.

[1710] Input: User's question.

[1711] Operation: The emotion engine analyzes the user's emotional state based on the content of the question.

[1712] Output: The analyzed emotion information is sent to the server.

[1713] Step 13:

[1714] The server sends the question and sentiment information to a generative artificial intelligence engine.

[1715] Input: User's question and sentiment information.

[1716] Operation: The server sends the question and sentiment information to a generative artificial intelligence engine.

[1717] Output: Questions and sentiment information sent to the generative artificial intelligence engine.

[1718] Step 14:

[1719] A generative artificial intelligence engine generates answers to questions.

[1720] Input: Question and sentiment information.

[1721] Operation: The generative artificial intelligence engine generates appropriate answers based on the question and sentiment information.

[1722] Output: Generated answer.

[1723] Step 15:

[1724] The server sends the generated response to the terminal.

[1725] Input: Generated response.

[1726] Operation: The server receives the generated response and sends it to the terminal.

[1727] Output: The response sent to the terminal.

[1728] Step 16:

[1729] The terminal displays the generated response to the user.

[1730] Input: Response sent from the server.

[1731] Operation: The terminal displays the generated response to the user.

[1732] Output: The user will be able to view the answer.

[1733] Step 17:

[1734] A user creates a new post on the bulletin board.

[1735] Input: Post content.

[1736] Action: The user enters a new post on the bulletin board.

[1737] Output: The entered post content is sent to the device.

[1738] Step 18:

[1739] The device sends the posted content to the server.

[1740] Input: Post content.

[1741] Operation: The terminal receives user input and sends it to the server.

[1742] Output: The content of the post sent to the server.

[1743] Step 19:

[1744] The server saves the posted content to a database and sends the saved result to the terminal.

[1745] Input: Post content.

[1746] Operation: The server saves the posted content to the database and determines whether the save was successful or unsuccessful.

[1747] Output: The saved result is sent to the terminal.

[1748] Step 20:

[1749] The device displays the saved results to the user and updates the list of posts.

[1750] Input: Saved results and a list of the latest posts.

[1751] Operation: The terminal displays a message to the user depending on the save result, and if the save is successful, it displays a list of the latest posts.

[1752] Output: The user will be able to view the latest posts.

[1753] Step 21:

[1754] The emotion engine stores the user's emotional data in a database.

[1755] Input: User sentiment data.

[1756] Operation: The emotion engine saves the analyzed emotion data to a database.

[1757] Output: Emotional data stored in the database.

[1758] Step 22:

[1759] The next time a question is asked, the server sends past sentiment data to a generative artificial intelligence engine to generate a personalized response.

[1760] Input: Past sentiment data and a new question.

[1761] Operation: The server sends questions to a generative artificial intelligence engine based on past sentiment data, which then generates personalized answers.

[1762] Output: Personalized response.

[1763] (Application Example 2)

[1764] 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."

[1765] In modern factories and businesses, improving skills in efficient automation technologies, particularly robotic process automation (RPA), requires employees to acquire a broad range of knowledge and practical skills individually. However, providing appropriate education and support tailored to each employee's individual skill level and emotional state is extremely difficult. Furthermore, a lack of information sharing raises concerns about decreased productivity and the occurrence of problems.

[1766] 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.

[1767] In this invention, the server includes means for receiving identification information entered by a user and authenticating the user based on said identification information; means for providing the user with educational content related to automation if authentication is successful; means for providing content related to automated work in the factory as educational content; means for collecting questions entered by the user and sending said questions to a generative artificial intelligence engine; means for displaying the answers received from the generative artificial intelligence engine to the user; means for providing a bulletin board function so that the user can share information with other users; and means for analyzing the user's emotional state using an emotion engine, and for the generative artificial intelligence engine to provide the user with personalized answers based on the results. This enables personalized education and support tailored to the skills and emotional state of employees, and also promotes information sharing.

[1768] "User-entered identification information" refers to information that a user enters to identify themselves, specifically including usernames and passwords.

[1769] "Means of authentication" refers to a function that performs a process to verify that a user is a legitimate user based on the identification information entered by the user.

[1770] "Educational content related to automation" refers to educational materials and content that provide users with knowledge and skills related to automation technologies and robotic process automation (RPA).

[1771] A "generative artificial intelligence engine" refers to a machine learning model or algorithm that generates appropriate answers to input questions.

[1772] The term "bulletin board function" refers to online forums or bulletin boards where users can share information and engage in discussions with other users.

[1773] An "emotion engine" refers to software or algorithms that analyze a user's emotional state and adjust the output of other functions based on that information.

[1774] "Content related to automation work within the factory" refers to information and educational content regarding specific procedures and methods related to automation processes and machine operation in a factory.

[1775] "Means of collecting questions" refers to a function that receives questions entered by users and stores or processes them for analysis and answer generation.

[1776] "Means of displaying to the user" refers to functions that visually present generated information or answers to the user.

[1777] "Means of sharing information" refers to platforms and functions that allow multiple users to exchange and share information with one another.

[1778] A "personalized response" refers to a response that is customized according to the user's individual circumstances and needs.

[1779] Modes for carrying out the invention

[1780] The embodiments for carrying out the present invention are shown below.

[1781] System Overview

[1782] This invention is a system for efficiently improving the skills of factory employees in Robotic Process Automation (RPA). The system includes user authentication, provision of automated training content, question answering using generative artificial intelligence, a bulletin board function, and an emotion engine.

[1783] Hardware and software to be used

[1784] Hardware: Smartphones, factory robot panels

[1785] Software: Flask (Python framework), Emotion Engine library, RPAContentAPI, generative artificial intelligence model

[1786] User Authentication

[1787] The server receives identification information (username and password) entered by the user using a smartphone or a panel on a factory robot. Based on this, the server searches the database for the corresponding user record and performs authentication. If authentication is successful, the server creates a new session and notifies the terminal. If authentication fails, an error message is sent to the terminal and displayed to the user.

[1788] Provision of automation education content

[1789] Users who successfully authenticate select educational content related to automated tasks within the factory from the dashboard. The terminal sends this selection information to the server, which uses the RPAContentAPI to retrieve the corresponding educational content from the database and display it to the user. This allows users to learn the basics of automated tasks and RPA.

[1790] Question answering by generative artificial intelligence

[1791] If a user has questions about how to learn educational content, they enter their question. The device sends this question to an emotion engine, which analyzes the user's emotional state. The analysis results are sent to a server, where a generative artificial intelligence engine generates an appropriate answer based on the analyzed question and emotional information. The generated answer is adjusted in content and tone according to the user's emotional state, and is sent to the device via the server and displayed to the user.

[1792] Information sharing via bulletin board function

[1793] The system also provides a bulletin board function for users to share information. Users create new posts on the bulletin board, and their devices send the content of those posts to the server. The server stores this content in a database, making it available for other users to view and comment on. If saving fails, an error message is sent to the device and displayed to the user.

[1794] The use of the emotion engine and specific examples.

[1795] The emotion engine is used when a user has a question about how to use the RPA tool. For example, if the user enters the question, "How do I extract data from a specific webpage using the RPA tool?", the terminal sends this to the server, and the emotion engine analyzes the user's emotional state. Depending on the analysis results, if it is determined that the user is feeling anxious, that information is passed to the generative artificial intelligence engine, and the response will include a tone such as "Don't worry." The generated response is sent to the terminal via the server and displayed to the user.

[1796] Example of a prompt

[1797] "How can I extract data from a specific webpage using an RPA tool?"

[1798] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1799] Step 1:

[1800] The user enters identification information (username and password) using a smartphone or a panel on a factory robot. The terminal receives the entered identification information and sends it to the server. At this stage, the input is the username and password, and the output is the data sent to the server.

[1801] Step 2:

[1802] The server searches the database based on the received user identification information to find the corresponding user record. The input for the database search is the identification information, and the output is either the user record (if it exists) or an error message (if it does not exist).

[1803] Step 3:

[1804] When the server finds a user record, it creates a new session and notifies the terminal. The input is the user record, and the output is the new session information. Based on this session information, the terminal displays a login success message to the user.

[1805] Step 4:

[1806] If authentication is successful, the user selects educational content related to automated factory operations from the dashboard. The terminal sends the selected content information to the server. The input is the selected content information, and the output is the data sent to the server.

[1807] Step 5:

[1808] The server uses the RPAContentAPI to retrieve the relevant educational content from the database. The input is content selection information, and the output is the retrieved educational content. The server sends the retrieved educational content to the terminal, which then displays it to the user.

[1809] Step 6:

[1810] When a user encounters a question while learning educational content, they input the question, and the device sends this question to the emotion engine. The input is the user's question, and the output is the data sent to the emotion engine.

[1811] Step 7:

[1812] The emotion engine analyzes the user's emotional state along with their question. The input is the user's question and emotional data, and the output is the analyzed emotional information. This analyzed information is then sent to the server.

[1813] Step 8:

[1814] The server passes the analyzed question and sentiment information to a generative artificial intelligence engine, which then generates an appropriate answer. The input is the analyzed question and sentiment information, and the output is the generated answer. This answer is sent to the terminal via the server, and the terminal displays the answer to the user.

[1815] Step 9:

[1816] The user creates a new post using the bulletin board function. The terminal sends the content entered by the user to the server. The input is the post content, and the output is the data sent to the server.

[1817] Step 10:

[1818] The server saves the posted content to the database. If the save is successful, it retrieves the latest list of posts and sends it to the terminal for display to the user. The input is the posted content, and the output is the updated list of posts. If the save fails, an error message is sent to the terminal and displayed to the user.

[1819] In this way, a system is realized that allows users to efficiently improve their RPA skills through each processing step.

[1820] 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.

[1821] 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.

[1822] 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.

[1823] [Fourth Embodiment]

[1824] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1825] 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.

[1826] 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).

[1827] 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.

[1828] 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.

[1829] 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).

[1830] 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.

[1831] 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.

[1832] 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.

[1833] 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.

[1834] 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.

[1835] 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.

[1836] 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".

[1837] This invention is a system for users to efficiently improve their skills in automation technologies, particularly robotic process automation (RPA). The system includes user authentication, provision of automation training content, question answering using generative artificial intelligence, and a bulletin board function that enables information sharing with other users.

[1838] User login and authentication

[1839] First, the user enters their identification information, specifically their username and password. The device receives this information and sends it to the server. The server accesses the database and searches for a user record that matches the entered information. If a matching record exists, the server creates a new session and notifies the device. The device displays the username and opens the dashboard. If authentication fails, the server sends an error message to the device, which then displays this to the user.

[1840] Provision of automation education content

[1841] Once authentication is successful, the user selects educational content, such as the "Automation Fundamentals" course, from the dashboard. The device sends this selection information to the server, which retrieves the corresponding educational content from its database. The retrieved content is then displayed to the user through the device.

[1842] Question answering by generative artificial intelligence

[1843] Users can ask generative artificial intelligence questions about points that arise during the learning process of educational content. The user inputs a question, the device collects it, and sends it to the server. The server passes the question to the generative AI engine, which analyzes the question and generates an appropriate answer. This answer is then sent to the device via the server and displayed to the user.

[1844] Information sharing via bulletin board function

[1845] The system also provides a bulletin board function for users to share information. Users create new posts on the bulletin board, and the terminal sends the content of the post to the server. The server saves the post to a database, and if the save is successful, it retrieves a list of the latest posts and sends it to the terminal. The terminal displays this list, allowing other users to view and comment on it. If the save fails, an error message is sent to the terminal and displayed to the user.

[1846] Specific example

[1847] For example, if a user wants to ask a question about how to use an RPA tool, they might input the question, "How do I extract data from a specific webpage using an RPA tool?" The terminal sends this to the server, which then passes it to a generative artificial intelligence engine. The engine generates an answer such as, "To extract data from a webpage, you first need to set the appropriate selector, and then use a data scraping activity. You can find detailed guidelines below: [link]," and sends it to the terminal via the server. This allows the user to learn specific techniques.

[1848] In this way, by using the system of the present invention, users can efficiently improve their automation skills and receive support to solve practical problems. Furthermore, knowledge deepening can be expected as information sharing with other users is promoted.

[1849] The following describes the processing flow.

[1850] User login and authentication

[1851] Step 1:

[1852] The user enters their username and password into the login form.

[1853] Step 2:

[1854] The device collects the login form data, encrypts it, and sends it to the server.

[1855] Step 3:

[1856] The server executes a query against the database to search for records that match the entered username and password.

[1857] Step 4:

[1858] The database returns the corresponding user record.

[1859] Step 5:

[1860] The server checks the user record, and if a matching record exists, it creates a new session.

[1861] Step 6:

[1862] The server sends session information to the terminal.

[1863] Step 7:

[1864] The device receives session information, displays the username, and opens the dashboard.

[1865] Step 8:

[1866] If authentication fails, the server sends an error message to the terminal, which then displays it to the user.

[1867] Provision of automation education content

[1868] Step 1:

[1869] The user selects the "Automation Fundamentals" course from the dashboard.

[1870] Step 2:

[1871] The device collects user selection information and sends it to the server.

[1872] Step 3:

[1873] The server retrieves the educational content corresponding to the selected course from the database.

[1874] Step 4:

[1875] The database returns the corresponding course content.

[1876] Step 5:

[1877] The server sends the acquired course information to the terminal.

[1878] Step 6:

[1879] The device displays the course content to the user.

[1880] Question answering by generative artificial intelligence

[1881] Step 1:

[1882] The user inputs questions to the generative artificial intelligence to ask questions about points they are unsure of during the learning process.

[1883] Step 2:

[1884] The device collects user questions and sends them to the server.

[1885] Step 3:

[1886] The server sends the question to a generative artificial intelligence engine.

[1887] Step 4:

[1888] A generative artificial intelligence engine analyzes the question and generates an appropriate answer.

[1889] Step 5:

[1890] The generative artificial intelligence engine generates the answer and sends it to the server.

[1891] Step 6:

[1892] The server sends the response to the terminal.

[1893] Step 7:

[1894] The device displays the answer to the user.

[1895] Information sharing via bulletin board function

[1896] Step 1:

[1897] The user enters new content for the bulletin board.

[1898] Step 2:

[1899] The device collects the posted content and sends it to the server.

[1900] Step 3:

[1901] The server saves the posted content to the database.

[1902] Step 4:

[1903] The database returns the save status to the server.

[1904] Step 5:

[1905] If the server successfully saves the data, it will execute a query to retrieve the latest list of posts from the database.

[1906] Step 6:

[1907] The database returns a list of the most recent posts to the server.

[1908] Step 7:

[1909] The server sends a list of posts to the device.

[1910] Step 8:

[1911] The device displays a list of posts to the user, allowing other users to view and comment on them.

[1912] Step 9:

[1913] If saving fails, the server sends an error message to the terminal, which then displays it to the user.

[1914] Specific example

[1915] Step 1:

[1916] The user inputs a question to the generative artificial intelligence: "How can I extract data from a specific webpage using an RPA tool?"

[1917] Step 2:

[1918] The device collects questions and sends them to the server.

[1919] Step 3:

[1920] The server sends the question to a generative artificial intelligence engine.

[1921] Step 4:

[1922] The generative artificial intelligence engine generates the response: "To extract data from a webpage, first set the appropriate selector, then use a data scraping activity. You can find detailed guidelines below: [link]".

[1923] Step 5:

[1924] The generative artificial intelligence engine sends the answer to the server.

[1925] Step 6:

[1926] The server sends the response to the terminal.

[1927] Step 7:

[1928] The device displays the answer to the user.

[1929] The above is a description of the specific operation of each processing step in the present invention.

[1930] (Example 1)

[1931] 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".

[1932] In today's business environment, there is a growing need to quickly and efficiently acquire skills in automation technologies, particularly robotic process automation (RPA). However, users are often overwhelmed by the vast amount of information and technology available, making it difficult to learn smoothly. Furthermore, support for obtaining appropriate answers when questions arise is insufficient, and information sharing with other users is limited. To address these problems, an effective learning support system is necessary.

[1933] 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.

[1934] In this invention, the server includes means for receiving identification information entered by the user and accessing a database based on said identification information to authenticate the user; means for creating a new session and notifying the terminal if authentication is successful; and means for providing educational content related to automation to the authenticated user. This enables users to be authenticated smoothly and to be provided with a consistent learning experience.

[1935] Furthermore, the server is equipped with means to send user-inputted questions to a generative artificial intelligence model, generate appropriate answers, and display them to the user, as well as a bulletin board function that allows users to share information with other users. This enables users to get immediate answers to their questions and continue learning effectively. It also facilitates information sharing with other users, promoting the deepening of knowledge.

[1936] "User authentication" is the process of verifying a user's identity by referencing a database based on the identification information (username and password) entered by the user.

[1937] "Educational content" refers to learning materials provided to users to improve their skills and knowledge, specifically including courses and materials related to automation technology and RPA.

[1938] A "generative artificial intelligence model" is a type of artificial intelligence that has the ability to analyze questions entered by a user and generate appropriate answers.

[1939] A "question answering system" is a system that has the function of passing questions entered by the user to a generative artificial intelligence model, collecting the generated answers, and displaying them to the user.

[1940] The "bulletin board function" is a platform for users to share information with other users, and includes features that allow users to post questions and opinions and leave comments.

[1941] A "session" refers to a series of operations performed by a user from the time they log in to the system until they log out, and is used to manage the user's operation history and authentication status.

[1942] A "device" refers to a device that a user uses to access a system, and includes personal computers, smartphones, tablets, and other similar devices.

[1943] A "server" is a centralized computing system that receives requests from users, processes them, accesses databases, and returns appropriate responses.

[1944] The present invention is a system for users to efficiently improve their skills in automation technology, particularly robotic process automation (RPA), and is implemented in the following specific forms.

[1945] User login and authentication

[1946] The user enters their identification information, specifically their username and password. The terminal receives this information and sends it to the server. The server accesses the database (e.g., a MySQL database) and searches for a user record that matches the entered information. If a matching record exists, the server creates a new session and notifies the terminal. The terminal displays the username and opens the dashboard. If authentication fails, the server sends an error message to the terminal, which the terminal displays to the user.

[1947] Provision of automation education content

[1948] After successful authentication, users select educational content such as "Fundamentals of Automation" from the dashboard. The device sends this selection information to the server, which retrieves the corresponding educational content from its database. The retrieved content is then displayed to the user through the device. The educational content is provided in various formats, including videos, text, and interactive exercises.

[1949] Question answering by generative artificial intelligence

[1950] Users can ask generative artificial intelligence (e.g., GPT-4) questions that arise during the learning process of educational content. The user inputs the question, the device collects it, and sends it to the server. The server passes the question to the generative AI model, which analyzes the question and generates an appropriate answer. This answer is then sent to the device via the server and displayed to the user.

[1951] Specific example:

[1952] For example, a user might input the question, "How can I extract data from a specific webpage using an RPA tool?" The terminal sends this to a server, which then passes it to a generative artificial intelligence model. The model generates the answer, "To extract data from a webpage, you first need to set the appropriate selector, and then use a data scraping activity. You can find detailed guidelines below: [link]," and sends this answer back to the terminal via the server. This allows the user to learn specific techniques.

[1953] Information sharing via bulletin board function

[1954] The system also provides a bulletin board function for users to share information. Users create new posts on the bulletin board, and the terminal sends the content of the post to the server. The server saves the post to a database, and if the save is successful, it retrieves a list of the latest posts and sends it to the terminal. The terminal displays this list, allowing other users to view and comment on it. If the save fails, an error message is sent to the terminal and displayed to the user.

[1955] In this way, by using the system of the present invention, users can efficiently improve their automation skills and receive support to solve practical problems. Furthermore, knowledge deepening can be expected as information sharing with other users is promoted.

[1956] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1957] User login and authentication

[1958] Step 1:

[1959] The user enters their username and password.

[1960] Input: Username and password

[1961] Specific action: The user enters their username and password into the form on the login screen and clicks the login button.

[1962] Output: Authentication information

[1963] Step 2:

[1964] The device sends authentication information to the server.

[1965] Input: Authentication information

[1966] Specific operation: The terminal sends the username and password to the server as an HTTP request in JSON format.

[1967] Output: Request to the server

[1968] Step 3:

[1969] The server accesses the database and verifies the user information.

[1970] Input: Request to the server

[1971] Specific operation: The server issues a SELECT query to the MySQL database and searches for records where the username and password match.

[1972] Output: Authentication result (success / failure)

[1973] Step 4:

[1974] The server notifies the terminal of the authentication result.

[1975] Input: Authentication result

[1976] Specific operation: If authentication is successful, the server generates a new session ID and sends it to the terminal in the HTTP response. If authentication fails, it sends a response containing an error message.

[1977] Output: Session ID or error message

[1978] Step 5:

[1979] The device displays the username and opens the dashboard screen.

[1980] Input: Session ID or error message

[1981] Specific actions: If authentication is successful, the device will display the username on the dashboard screen; if authentication fails, an error message will be displayed on the login screen.

[1982] Output: Dashboard screen or error message

[1983] Provision of automation education content

[1984] Step 1:

[1985] The user selects educational content.

[1986] Input: Selection of educational content

[1987] Specific operation: The user selects educational content such as "Fundamentals of Automation" from the list of educational courses provided on the dashboard screen.

[1988] Output: Selections

[1989] Step 2:

[1990] The device sends the selection information to the server.

[1991] Input: Selection

[1992] Specific operation: The device sends the selected course ID to the server as an HTTP request in JSON format.

[1993] Output: Request to the server

[1994] Step 3:

[1995] The server retrieves educational content from the database.

[1996] Input: Request to the server

[1997] Specific operation: The server issues a SELECT query to the database and retrieves the relevant content information.

[1998] Output: Educational content data

[1999] Step 4:

[2000] The device displays educational content to the user.

[2001] Input: Educational content data

[2002] Specific operation: The terminal renders the educational content received from the server and displays it to the user.

[2003] Output: Display of educational content

[2004] Question answering by generative artificial intelligence

[2005] Step 1:

[2006] The user enters their question.

[2007] Input: Questions about points of doubt

[2008] Specific operation: If a user has a question while viewing educational content, they enter their question into a question form and submit it.

[2009] Output: Question content

[2010] Step 2:

[2011] The terminal sends the question to the server.

[2012] Input: Question content

[2013] Specific operation: The terminal sends the user's question to the server in JSON format.

[2014] Output: Request to the server

[2015] Step 3:

[2016] The server sends a question to the generative artificial intelligence model.

[2017] Input: Request to the server

[2018] Specific operation: The server sends a question as an API request to a generative artificial intelligence (e.g., GPT-4).

[2019] Output: Request to generative artificial intelligence

[2020] Step 4:

[2021] A generative artificial intelligence model generates the appropriate answer.

[2022] Input: Request to generative artificial intelligence

[2023] Specific operation: Generative artificial intelligence analyzes the question and generates an appropriate answer.

[2024] Output: Answer content

[2025] Step 5:

[2026] The server sends the response to the terminal.

[2027] Input: Answer content

[2028] Specific operation: The server sends the response received from the generative artificial intelligence to the terminal.

[2029] Output: Response to terminal

[2030] Step 6:

[2031] The device displays the answer to the user.

[2032] Input: Response to the terminal

[2033] Specific operation: The device renders the answer in a way that is easy for the user to read.

[2034] Output: Display of answers

[2035] Information sharing via bulletin board function

[2036] Step 1:

[2037] A user creates a new post on the bulletin board.

[2038] Input: Post content

[2039] Specific action: The user accesses the bulletin board screen, enters a new message, and presses the post button.

[2040] Output: Submission Request

[2041] Step 2:

[2042] The device sends the posted content to the server.

[2043] Input: Post request

[2044] Specific operation: The terminal sends the posted content to the server in JSON format.

[2045] Output: Request to the server

[2046] Step 3:

[2047] The server saves the post to the database.

[2048] Input: Request to the server

[2049] Specific operation: The server issues an INSERT query to the database and saves the posted content.

[2050] Output: Saved result

[2051] Step 4:

[2052] If saving is successful, the server retrieves the latest list of posts and sends it to the device.

[2053] Input: Saved result

[2054] Specific operation: If the save is successful, the server issues a SELECT query to retrieve the latest list of posts from the database.

[2055] Output: List of latest posts

[2056] Step 5:

[2057] The device displays a list of the latest posts to the user.

[2058] Input: Latest posts list

[2059] Specific operation: The device displays a list of the latest posts to the user, allowing other users to view and comment on them.

[2060] Output: Display of the latest posts

[2061] Based on the above process, this system efficiently supports the improvement of automation skills and information sharing.

[2062] (Application Example 1)

[2063] 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".

[2064] For users to efficiently acquire Robotic Process Automation (RPA) skills, it is crucial not only to provide appropriate educational content but also to receive prompt answers to questions and share information with other users. However, conventional systems have been unable to provide these in a centralized manner, making training particularly difficult in remote environments. Furthermore, the lack of learning environments utilizing advanced interfaces such as voice input and smart glasses has reduced user convenience.

[2065] 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.

[2066] In this invention, the server includes means for receiving identification information entered by a user and authenticating the user based on said identification information; means for providing the user with automation-related educational content if authentication is successful; means for collecting questions entered by the user and sending said questions to a generative artificial intelligence engine; means for displaying the answers received from the generative artificial intelligence engine to the user; means for providing a bulletin board function so that the user can share information with other users; means for the user to remotely access automation educational content via smart glasses; means for streaming the educational content in real time via a remote interface; and means for receiving voice input or text input and sending questions to the generative artificial intelligence engine in real time. This enables the user to learn advanced RPA skills regardless of location, get quick answers to their questions, and share information with other users.

[2067] User authentication is the process of verifying that a user is a legitimate user based on the identification information (username and password) that the user has entered.

[2068] "Automation education content" refers to educational materials such as learning materials and video tutorials provided to users to acquire robotic process automation (RPA) skills.

[2069] "Generative artificial intelligence" is an artificial intelligence technology that uses natural language processing and machine learning techniques to generate appropriate answers to user questions.

[2070] A "bulletin board function" is an online communication platform that allows users to share information and exchange opinions with other users.

[2071] "Smart glasses" are wearable devices that users wear and that have a display function to enhance visual information.

[2072] A "remote interface" is a system interface that allows users to access and operate a system from a remote location.

[2073] "Voice input" is the process by which a user inputs voice information into a system through a microphone.

[2074] "Real-time streaming display" is a technology that delivers educational content and other information to users in real time and displays it instantly.

[2075] This invention provides a system for users to efficiently improve their Robotic Process Automation (RPA) skills. The system includes user authentication, provision of automated training content, generative artificial intelligence-based question answering, and a bulletin board function enabling information sharing with other users. Furthermore, this invention enables remote training using smart glasses.

[2076] 1. User Authentication

[2077] The user wears smart glasses and enters their username and password via voice or text. The smart glasses send this information to the server. The server accesses the database and verifies the entered identification information. If authentication is successful, the server creates a new session and notifies the smart glasses. If authentication fails, the server sends an error message to the smart glasses and displays it to the user.

[2078] Example: The user says "Log in" by voice and enters their username and password. The smart glasses display shows "Welcome, [Username]".

[2079] 2. Provision of automation education content

[2080] Once authenticated, users select educational content using a remote interface via smart glasses. The smart glasses send this selection information to a server, which retrieves the corresponding educational content from its database. The retrieved educational content is then streamed in real time on the smart glasses' display.

[2081] Example: The "Fundamentals of Automation" course is played on the smart glasses' display. The user controls playback using voice commands.

[2082] 3. Question answering using generative artificial intelligence

[2083] If a user has questions while learning educational content, they can submit their questions via voice or text input. The smart glasses send the questions to a server, which then forwards them to a generative artificial intelligence engine. The generative AI engine analyzes the questions and generates appropriate answers. The generated answers are sent back to the smart glasses via the server and displayed to the user.

[2084] For example, if a user asks, "How can I extract data from a specific webpage using an RPA tool?", the generative artificial intelligence will respond, "To extract data from a webpage, first set the appropriate selector, and then use a data scraping activity."

[2085] 4. Information sharing via bulletin board function

[2086] The system provides a bulletin board function for users to share information. Users create new posts through their smart glasses, which then send the content of the post to the server. The server saves the post to a database, and if successful, retrieves a list of the latest posts and sends it to the smart glasses. Other users can view and comment on these posts.

[2087] Example: If a user posts on a message board asking "How do I fix the error in my new RPA script?", other users will provide answers and advice.

[2088] Hardware and software to be used

[2089] Smart glasses (wearable display, microphone, camera): Used by users to view and input educational content and answer questions.

[2090] Servers (authentication server, content delivery server): Provide user authentication, educational content delivery, question answering, and bulletin board functionality.

[2091] Generative artificial intelligence engine (natural language processing engine): Generates answers to user questions.

[2092] Database: Stores user information, educational content, and forum posts.

[2093] Example prompt: When the user types "How do I start the script?", the generative AI responds "To get started, first create a new project, then click the 'Run Script' button."

[2094] This allows users to efficiently acquire RPA skills even in a remote environment, obtain information in real time, and share information with other users.

[2095] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[2096] Step 1:

[2097] The user puts on the smart glasses, says "login" by voice, and enters their username and password. The smart glasses send this information to the server. The server compares the entered identification information with a database and searches for a matching record. If a matching record exists, the server creates a new session and sends the session information to the smart glasses. If authentication is successful, the smart glasses display "Welcome, [Username]".

[2098] Input: Username, Password

[2099] Data processing: Database search

[2100] Output: Session information, authentication message

[2101] Step 2:

[2102] Users who successfully authenticate select automated educational content through the control panel on their smart glasses. The selection information is sent to the server, which accesses the database to retrieve the corresponding educational content. The retrieved educational content is then streamed in real time on the smart glasses' display.

[2103] Input: Educational content selection information

[2104] Data processing: Retrieve content from database and stream it.

[2105] Output: Streaming display of educational content

[2106] Step 3:

[2107] When a user encounters a question while learning educational content, they can ask it via voice or text input. The smart glasses send the question to a server. The server passes the question to a generative artificial intelligence engine, which analyzes the question and generates an appropriate answer. This answer is then sent back to the smart glasses via the server and displayed to the user.

[2108] Input: User's question

[2109] Data processing: Question analysis and answer generation using a generative artificial intelligence engine.

[2110] Output: Answer to the question

[2111] Step 4:

[2112] Users access the bulletin board via smart glasses and create new posts. The smart glasses send the post content to the server, which stores it in a database. If the save is successful, the server retrieves a list of the latest posts and sends it to the smart glasses. Other users can view and comment on these posts.

[2113] Input: Content to post on the bulletin board

[2114] Data processing: Saving posted content to the database and retrieving the latest posts.

[2115] Output: Updated bulletin board list

[2116] This system supports users in efficiently acquiring RPA skills even in remote environments, enabling quick answers to questions and information sharing with other users.

[2117] 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.

[2118] This invention is a system for users to efficiently improve their skills in automation technologies, particularly robotic process automation (RPA). The system includes user authentication, provision of automation training content, question answering using generative artificial intelligence, a bulletin board function that enables information sharing with other users, and an emotion engine that recognizes the user's emotions.

[2119] User login and authentication

[2120] First, the user enters their identification information, specifically their username and password. The device receives this information and sends it to the server. The server accesses the database and searches for a user record that matches the entered information. If a matching record exists, the server creates a new session and notifies the device. The device displays the username and opens the dashboard. If authentication fails, the server sends an error message to the device, which then displays this to the user.

[2121] Provision of automation education content

[2122] Once authentication is successful, the user selects educational content, such as the "Automation Fundamentals" course, from the dashboard. The device sends this selection information to the server, which retrieves the corresponding educational content from its database. The retrieved content is then displayed to the user through the device.

[2123] Question answering by generative artificial intelligence

[2124] When a user encounters a question while learning educational content, they input the question into a generative artificial intelligence (AI). The device collects the question and sends it to an emotion engine. The emotion engine analyzes the user's emotions and sends that emotional state as additional information to the server. The server passes the question and emotion information back to the generative AI engine, which analyzes it and generates an appropriate answer. The tone and content of the answer are adjusted according to the user's emotions. The generated answer is sent to the device via the server and displayed to the user.

[2125] Information sharing via bulletin board function

[2126] The system also provides a bulletin board function for users to share information. Users create new posts on the bulletin board, and the terminal sends the content of the post to the server. The server saves the content of the post to a database, and if the save is successful, it retrieves a list of the latest posts and sends it to the terminal. The terminal displays this list, allowing other users to view and comment on it. If the save fails, an error message is sent to the terminal and displayed to the user.

[2127] Specific examples of combinations of emotional engines

[2128] For example, if a user wants to ask a question about how to use an RPA tool, they might input the question, "How do I extract data from a specific webpage using an RPA tool?" The terminal sends this to the server, which then sends it to the emotion engine. The emotion engine analyzes the user's emotional state, and if it determines that the user is feeling anxious, it sends the result to the server. The server passes this emotional information along with the question to a generative artificial intelligence engine, which, based on the emotional state, generates a message such as, "To extract data from a webpage, you first need to set the appropriate selector, and then use a data scraping activity. If this is your first time, please refer to the link below. There is also a video with detailed guidelines, so don't worry." This answer is sent to the terminal via the server and displayed to the user.

[2129] Utilizing user sentiment data

[2130] Furthermore, user sentiment data is stored in a database, allowing a generative artificial intelligence engine to provide personalized answers based on past sentiment data the next time a question is asked. For example, when asking similar questions, it can provide more relaxing language and reference materials.

[2131] In this way, the system of the present invention not only allows users to efficiently improve their RPA skills but also provides a more personalized learning experience by offering support tailored to their emotional state. This allows users to engage in learning with peace of mind, and as a result, skill acquisition is accelerated.

[2132] The following describes the processing flow.

[2133] User login and authentication

[2134] Step 1:

[2135] The user enters their username and password into the login form.

[2136] Step 2:

[2137] The device collects the login form data, encrypts it, and sends it to the server.

[2138] Step 3:

[2139] The server executes a query against the database to search for records that match the entered username and password.

[2140] Step 4:

[2141] The database returns the corresponding user record.

[2142] Step 5:

[2143] The server checks the user record, and if a matching record exists, it creates a new session.

[2144] Step 6:

[2145] The server sends session information to the terminal.

[2146] Step 7:

[2147] The device receives session information, displays the username, and opens the dashboard.

[2148] Step 8:

[2149] If authentication fails, the server sends an error message to the terminal, which then displays it to the user.

[2150] Provision of automation education content

[2151] Step 1:

[2152] The user selects the "Automation Fundamentals" course from the dashboard.

[2153] Step 2:

[2154] The device collects user selection information and sends it to the server.

[2155] Step 3:

[2156] The server retrieves the educational content corresponding to the selected course from the database.

[2157] Step 4:

[2158] The database returns the corresponding course content.

[2159] Step 5:

[2160] The server sends the acquired course information to the terminal.

[2161] Step 6:

[2162] The device displays the course content to the user.

[2163] Question answering by generative artificial intelligence

[2164] Step 1:

[2165] The user inputs questions to the generative artificial intelligence to ask questions about points they are unsure of during the learning process.

[2166] Step 2:

[2167] The device collects user questions and sends them to the sentiment engine.

[2168] Step 3:

[2169] The emotion engine analyzes the user's emotions and generates emotion data.

[2170] Step 4:

[2171] The emotion engine sends emotion data to the server.

[2172] Step 5:

[2173] The server sends the question and sentiment data to a generative artificial intelligence engine.

[2174] Step 6:

[2175] A generative artificial intelligence engine analyzes questions and emotion data to generate responses that are appropriate to the emotions.

[2176] Step 7:

[2177] The generative artificial intelligence engine generates the answer and sends it to the server.

[2178] Step 8:

[2179] The server sends the response to the terminal.

[2180] Step 9:

[2181] The device displays the answer to the user.

[2182] Information sharing via bulletin board function

[2183] Step 1:

[2184] The user enters new content for the bulletin board.

[2185] Step 2:

[2186] The device collects the posted content and sends it to the server.

[2187] Step 3:

[2188] The server saves the posted content to the database.

[2189] Step 4:

[2190] The database returns the save status to the server.

[2191] Step 5:

[2192] If the server successfully saves the data, it will execute a query to retrieve the latest list of posts from the database.

[2193] Step 6:

[2194] The database returns a list of the most recent posts to the server.

[2195] Step 7:

[2196] The server sends a list of posts to the device.

[2197] Step 8:

[2198] The device displays a list of posts to the user, allowing other users to view and comment on them.

[2199] Step 9:

[2200] If saving fails, the server sends an error message to the terminal, which then displays it to the user.

[2201] Specific example: Questions about how to use RPA tools

[2202] Step 1:

[2203] The user inputs a question to the generative artificial intelligence: "How can I extract data from a specific webpage using an RPA tool?"

[2204] Step 2:

[2205] The device collects questions and sends them to the server, which then also sends them to the emotion engine.

[2206] Step 3:

[2207] The emotion engine analyzes the user's emotional state from their questions, determines it to be "anxious," and sends the result to the server.

[2208] Step 4:

[2209] The server sends the question and "anxiety" emotion data to a generative artificial intelligence engine.

[2210] Step 5:

[2211] A generative artificial intelligence engine analyzes questions and sentiment data to generate sentiment-sensitive responses. For example, it might create a response like, "To extract data from a webpage, you first need to set the appropriate selectors, and then use a data scraping activity. If this is your first time, please refer to the link below. There is also a video with detailed guidelines, so don't worry."

[2212] Step 6:

[2213] The generative artificial intelligence engine generates the answer and sends it to the server.

[2214] Step 7:

[2215] The server sends the response to the terminal.

[2216] Step 8:

[2217] The device displays the response to the user. This allows the user to receive a response that has been adjusted based on sentiment data.

[2218] Utilizing user sentiment data

[2219] Step 1:

[2220] The questions submitted by users, along with their sentiment data, and their corresponding answers are stored in a database.

[2221] Step 2:

[2222] The next time the same user asks a question, the generative artificial intelligence engine can provide a personalized answer based on past sentiment data. For example, if a user was previously identified as "anxious," the engine will provide an answer carefully designed to make them feel "reassured" again.

[2223] In this way, the system of the present invention not only allows users to efficiently improve their automation skills, but also provides a more personalized learning experience by offering detailed support tailored to their emotional state. As a result, users can engage in learning with peace of mind, and consequently, skill acquisition is accelerated.

[2224] (Example 2)

[2225] 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".

[2226] Traditional robotic process automation (RPA) training systems lack personalized responses to user questions and fail to provide support that takes into account the user's emotional state. Furthermore, information sharing among users is often limited, posing challenges to improving learning efficiency and maintaining sustained motivation.

[2227] 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.

[2228] In this invention, the server includes means for receiving identification information entered by the user and authenticating the user based on said identification information; means for providing the user with educational content related to automation if authentication is successful; means for collecting questions entered by the user and sending said questions to a generative artificial intelligence engine; means for displaying the answers received from the generative artificial intelligence engine to the user; means for providing a bulletin board function so that the user can share information with other users; means for analyzing the user's emotional state, adding that information, and sending it to the generative artificial intelligence engine; and means for storing the user's emotional data in a database and generating personalized answers for the next time a question is asked. This enables personalized support based on the user's emotional state, allowing for efficient learning and the maintenance of continuous motivation.

[2229] "Identification information" refers to information used by a user when accessing the system, including, for example, usernames and passwords.

[2230] "Authentication" is the process of verifying whether the identification information entered by the user is correct.

[2231] "Educational content related to automation" refers to educational materials and training resources related to robotic process automation (RPA).

[2232] A "question" refers to any doubts or inquiries that a user may have while learning educational content.

[2233] A "generative artificial intelligence engine" refers to an artificial intelligence model that analyzes user questions and generates corresponding answers.

[2234] A "bulletin board function" refers to an online platform for users to share information and communicate with each other.

[2235] "Emotional state" refers to the user's current psychological state and emotions, and is the subject of analysis by the system.

[2236] A "personalized response" refers to a response that is tailored based on the user's individual circumstances and past data.

[2237] This invention is a system for users to efficiently improve their skills in automation technology, particularly robotic process automation (RPA). The system includes user authentication, provision of automation training content, question answering using generative artificial intelligence, a bulletin board function that enables information sharing with other users, and an emotion engine that recognizes the user's emotions.

[2238] User login and authentication

[2239] First, the user enters their identification information, specifically their username and password. The device receives this information and sends it to the server. The server accesses the database and searches for a user record that matches the entered information. If a matching record exists, the server creates a new session and notifies the device. The device displays the username and opens the dashboard. If authentication fails, the server sends an error message to the device, which then displays this to the user.

[2240] Provision of automation education content

[2241] Once authentication is successful, the user selects educational content, such as the "Automation Fundamentals" course, from the dashboard. The device sends this selection information to the server, which retrieves the corresponding educational content from its database. The retrieved content is then displayed to the user through the device.

[2242] Question answering by generative artificial intelligence

[2243] When a user encounters a question while learning educational content, they input the question into a generative artificial intelligence (AI). The device collects the question and sends it to an emotion engine. The emotion engine analyzes the user's emotions and sends that emotional state as additional information to the server. The server passes the question and emotion information back to the generative AI engine, which analyzes it and generates an appropriate answer. The tone and content of the answer are adjusted according to the user's emotions. The generated answer is sent to the device via the server and displayed to the user.

[2244] Specific example:

[2245] A user can input a question such as, "How can I extract data from a specific webpage using an RPA tool?" The terminal sends this to the server, which then sends it to the emotion engine. The emotion engine analyzes the user's emotional state, and if it determines that the user is feeling anxious, it sends the result to the server. The server then passes the question, based on the emotional information, to a generative artificial intelligence engine, which generates an answer such as, "To extract data from a webpage, you must first set the appropriate selector, and then use a data scraping activity. If this is your first time, please refer to the link below. There is also a video with detailed guidelines, so please don't worry." This answer is then sent to the terminal via the server and displayed to the user.

[2246] Information sharing via bulletin board function

[2247] The system also provides a bulletin board function for users to share information. Users create new posts on the bulletin board, and the terminal sends the content of the post to the server. The server saves the content of the post to a database, and if the save is successful, it retrieves a list of the latest posts and sends it to the terminal. The terminal displays this list, allowing other users to view and comment on it. If the save fails, an error message is sent to the terminal and displayed to the user.

[2248] Utilizing user sentiment data

[2249] Furthermore, user sentiment data is stored in a database, allowing a generative artificial intelligence engine to provide personalized answers based on past sentiment data the next time a question is asked. For example, when asking similar questions, it can provide expressions and reference materials that help the user relax.

[2250] Hardware and software to use

[2251] The operation of this system requires servers, terminals (PCs, tablets, smartphones, etc.), a database management system (DBMS), a generative artificial intelligence engine (e.g., ChatGPT, BERT), and an emotion recognition engine. These elements work together to create a system that supports the improvement of users' RPA skills.

[2252] As a result, the system of the present invention can not only enable users to efficiently improve their RPA skills, but also provide a more personalized learning experience by offering support tailored to their emotional state.

[2253] The flow of the specific processing in Example 2 will be explained using Figure 13.

[2254] Step 1:

[2255] The user enters their username and password on the login screen.

[2256] Input: User's username and password.

[2257] Operation: The user enters their identification information into the system.

[2258] Output: The entered authentication information is sent to the terminal.

[2259] Step 2:

[2260] The terminal sends the user's input information to the server.

[2261] Input: User's username and password.

[2262] Operation: The terminal receives user input and sends it to the server.

[2263] Output: Authentication information sent to the server.

[2264] Step 3:

[2265] The server accesses the database and searches for records that match the entered information.

[2266] Input: Username and password sent to the server.

[2267] Operation: The server queries the database and evaluates the authentication information.

[2268] Output: Authentication result (success or failure).

[2269] Step 4:

[2270] The server sends the authentication result to the terminal and notifies the user.

[2271] Input: Authentication result.

[2272] Operation: If authentication is successful, the server creates a new session and sends the information to the terminal. If authentication fails, it generates an error message.

[2273] Output: Session information or error messages are sent to the terminal.

[2274] Step 5:

[2275] The device displays the authentication result to the user.

[2276] Input: Session information or error message.

[2277] Operation: The terminal displays information received from the server to the user.

[2278] Output: The user will be able to access the dashboard (on success) or an error message will be displayed (on failure).

[2279] Step 6:

[2280] Users who successfully authenticate can select educational content from the dashboard.

[2281] Input: User's content selection.

[2282] Operation: Users select educational content of interest on the dashboard.

[2283] Output: Selected content information is sent to the device.

[2284] Step 7:

[2285] The device sends the selection information to the server.

[2286] Input: Selected educational content information.

[2287] Operation: The terminal receives the user's selection information and sends it to the server.

[2288] Output: Content selection information sent to the server.

[2289] Step 8:

[2290] The server retrieves the relevant educational content from the database.

[2291] Input: Content selection information sent to the server.

[2292] Operation: The server accesses the database and retrieves the relevant educational content.

[2293] Output: Acquired educational content.

[2294] Step 9:

[2295] The device displays educational content to the user.

[2296] Input: Acquired educational content.

[2297] Operation: The terminal displays educational content received from the server to the user.

[2298] Output: The user becomes able to view the educational content.

[2299] Step 10:

[2300] Users input questions as points of confusion during their learning process.

[2301] Input: User's question.

[2302] Operation: The user enters questions that arise while learning educational content into the device.

[2303] Output: The entered question is sent to the terminal.

[2304] Step 11:

[2305] The device sends the question to the emotion engine.

[2306] Input: The question that was entered.

[2307] Operation: The terminal sends the user's question to the sentiment engine.

[2308] Output: The question sent to the emotion engine.

[2309] Step 12:

[2310] The emotion engine analyzes the user's emotions and sends the results to the server.

[2311] Input: User's question.

[2312] Operation: The emotion engine analyzes the user's emotional state based on the content of the question.

[2313] Output: The analyzed emotion information is sent to the server.

[2314] Step 13:

[2315] The server sends the question and sentiment information to a generative artificial intelligence engine.

[2316] Input: User's question and sentiment information.

[2317] Operation: The server sends the question and sentiment information to a generative artificial intelligence engine.

[2318] Output: Questions and sentiment information sent to the generative artificial intelligence engine.

[2319] Step 14:

[2320] A generative artificial intelligence engine generates answers to questions.

[2321] Input: Question and sentiment information.

[2322] Operation: The generative artificial intelligence engine generates appropriate answers based on the question and sentiment information.

[2323] Output: Generated answer.

[2324] Step 15:

[2325] The server sends the generated response to the terminal.

[2326] Input: Generated response.

[2327] Operation: The server receives the generated response and sends it to the terminal.

[2328] Output: The response sent to the terminal.

[2329] Step 16:

[2330] The terminal displays the generated response to the user.

[2331] Input: Response sent from the server.

[2332] Operation: The terminal displays the generated response to the user.

[2333] Output: The user will be able to view the answer.

[2334] Step 17:

[2335] A user creates a new post on the bulletin board.

[2336] Input: Post content.

[2337] Action: The user enters a new post on the bulletin board.

[2338] Output: The entered post content is sent to the device.

[2339] Step 18:

[2340] The device sends the posted content to the server.

[2341] Input: Post content.

[2342] Operation: The terminal receives user input and sends it to the server.

[2343] Output: The content of the post sent to the server.

[2344] Step 19:

[2345] The server saves the posted content to a database and sends the saved result to the terminal.

[2346] Input: Post content.

[2347] Operation: The server saves the posted content to the database and determines whether the save was successful or unsuccessful.

[2348] Output: The saved result is sent to the terminal.

[2349] Step 20:

[2350] The device displays the saved results to the user and updates the list of posts.

[2351] Input: Saved results and a list of the latest posts.

[2352] Operation: The terminal displays a message to the user depending on the save result, and if the save is successful, it displays a list of the latest posts.

[2353] Output: The user will be able to view the latest posts.

[2354] Step 21:

[2355] The emotion engine stores the user's emotional data in a database.

[2356] Input: User sentiment data.

[2357] Operation: The emotion engine saves the analyzed emotion data to a database.

[2358] Output: Emotional data stored in the database.

[2359] Step 22:

[2360] The next time a question is asked, the server sends past sentiment data to a generative artificial intelligence engine to generate a personalized response.

[2361] Input: Past sentiment data and a new question.

[2362] Operation: The server sends questions to a generative artificial intelligence engine based on past sentiment data, which then generates personalized answers.

[2363] Output: Personalized response.

[2364] (Application Example 2)

[2365] 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".

[2366] In modern factories and businesses, improving skills in efficient automation technologies, particularly robotic process automation (RPA), requires employees to acquire a broad range of knowledge and practical skills individually. However, providing appropriate education and support tailored to each employee's individual skill level and emotional state is extremely difficult. Furthermore, a lack of information sharing raises concerns about decreased productivity and the occurrence of problems.

[2367] 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.

[2368] In this invention, the server includes means for receiving identification information entered by a user and authenticating the user based on said identification information; means for providing the user with educational content related to automation if authentication is successful; means for providing content related to automated work in the factory as educational content; means for collecting questions entered by the user and sending said questions to a generative artificial intelligence engine; means for displaying the answers received from the generative artificial intelligence engine to the user; means for providing a bulletin board function so that the user can share information with other users; and means for analyzing the user's emotional state using an emotion engine, and for the generative artificial intelligence engine to provide the user with personalized answers based on the results. This enables personalized education and support tailored to the skills and emotional state of employees, and also promotes information sharing.

[2369] "User-entered identification information" refers to...

Claims

1. A means for receiving identification information entered by a user and authenticating the user based on said identification information, A means of providing users with educational content on automation upon successful authentication, A means for collecting questions entered by a user and sending those questions to a generative artificial intelligence engine, A means of displaying the response received from the generative artificial intelligence engine to the user, It provides a bulletin board function, a means for users to share information with other users, A system that includes this.

2. The system according to claim 1, further comprising means for retrieving user-selected automation-related educational content from a database and displaying it to the user according to the selection.

3. The system according to claim 1, further comprising means for displaying an error message to the user in the event of authentication failure.

Images