System

Abstract

A system is provided.SOLUTION: A system comprising: means for storing profile information of a new employee, work contents of each department, features of members, and required skills in a database; means for inputting and transmitting a question by the new employee; means for receiving the question and transmitting the question to a AI; means for analyzing the question and retrieving related information from the database by the AI; means for generating advice based on the related information; and means for transmitting the generated advice to the new employee.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] When new employees are assigned to a job, they often have trouble with the content of their work and their relationships with the people in charge, and the speed at which they grow depends heavily on the quality of their senior colleagues and mentors, which is why the high turnover rate among new employees is a problem. For this reason, there is a need to provide high-quality support that allows new employees to learn their work efficiently and reduces the burden on mentors. [Means for solving the problem]

[0005] The present invention solves the above-mentioned problems with a system that includes: a means for storing new employee profile information, the work content of each department, member characteristics, and required skills in a database; a means for new employees to input and send questions using their terminals; a means for receiving the questions and sending them to AI; a means for the AI ​​to analyze the questions and search the database for related information; a means for generating advice based on the related information; and a means for sending the generated advice to the new employee's terminal. This allows new employees to efficiently resolve questions and problems related to their work, making it possible to provide high-quality support while reducing the burden on existing members.

[0006] "Profile Information" refers to data about new hires, such as personal information, history, skills, and areas of interest.

[0007] "Work content" refers to the details of the tasks and projects that each department must undertake, as well as the necessary procedures and progress.

[0008] "Member characteristics" refers to information about existing members in each department, such as their skill sets, years of experience, and responsibilities.

[0009] "Necessary skills" refers to the knowledge and techniques required to perform a specific task.

[0010] "Database" refers to an electronic data storage system for systematically managing and storing data such as profile information, job content, member characteristics, and required skills.

[0011] "Devices" refers to electronic devices such as smartphones and computers used by new employees.

[0012] "Questions" are written in text format and are questions that new employees have about their work or things they want to confirm.

[0013] "Receiving" refers to the system receiving the questions sent by new employees.

[0014] "AI" stands for artificial intelligence and refers to a program that analyzes data and generates advice according to defined conditions.

[0015] "Analysis" refers to the process by which AI understands the input question and analyzes its content.

[0016] "Search" refers to the process by which AI finds relevant information in a database.

[0017] "Advice" refers to specific instructions and guidelines for new employees generated by AI.

[0018] "Sending" refers to sending analysis results and advice to new employees' devices. [Brief explanation of the drawings]

[0019] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9]1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0020] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

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

[0022] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0023] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0024] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0025] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0026] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0027] [First embodiment]

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

[0029] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0030] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0031] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0032] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0033] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0034] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

[0036] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0037] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0038] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0039] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0040] This invention is a system that uses a skill-up advisor AI for new employees to support the efficient acquisition of work skills. Specifically, a server stores new employee profile information, the work content of each department, the characteristics of members, and required skills in a database, and new employees can input and send questions using their terminals. These questions are received by the server and sent to the AI. The AI ​​analyzes the questions, searches the database for relevant information, and generates advice based on the relevant information. The generated advice is sent by the server to the new employee's terminal.

[0041] Program processing overview (expressed in natural language)

[0042] 1. Initial setup by the server

[0043] The server stores new employee profile information, the job duties of each department, the characteristics of the members, and the required skills in a database. For example, the database might register "SNS campaign planning" and "data analysis" as the job duties of the "Marketing Department," and store "Excel" and "presentation" as required skills.

[0044] 2. New employees ask questions

[0045] New employees access the AI ​​advisor using their own devices (smartphones or PCs). They input specific questions in text format and submit them. For example, New Employee A might input "I would like to learn the basics of data analysis using Excel" and submit the text.

[0046] 3. The server receives the query

[0047] The server receives the new hire's question, prepares it for sending to the AI, and converts it into the appropriate format. The converted question is then passed to the AI ​​module.

[0048] 4. AI analyzes the question and generates advice

[0049] AI analyzes questions and extracts keywords and important phrases. For example, AI extracts keywords such as "Excel," "data analysis," and "basics," and retrieves information from a database about "basic Excel operations," "use of basic functions," and "data visualization." Based on the information retrieved, it generates appropriate advice. For example, the AI ​​generates advice such as, "First, learn basic Excel operations, then learn how to use functions, and finally master data visualization techniques."

[0050] 5. The server sends the advice

[0051] The server receives the advice from the AI, converts it into an appropriate format for sending to the new employee, and then sends it to the new employee's terminal. For example, the server converts the advice text into HTML format and sends it to the PC of new employee A.

[0052] 6. New employees receive advice

[0053] Advice from an AI advisor is received and displayed on the new employee's device. For example, new employee A receives advice on his / her PC such as "First, learn the basic operations of Excel, then learn how to use functions, and finally master data visualization techniques."

[0054] The purpose of this invention is to enable new employees to efficiently resolve questions and problems related to their work and improve their work skills through this series of processes. It also makes it possible to provide high-quality support while reducing the burden on existing members.

[0055] The processing flow will be explained below.

[0056] Step 1:

[0057] The server stores new employee profile information, the job description of each department, the characteristics of the members, and the required skills in a database. Specifically, the Marketing Department stores job descriptions such as "SNS campaign planning" and "data analysis" and the required skills such as "Excel" and "presentation."

[0058] Step 2:

[0059] The new employee, who is the user, accesses the AI ​​Advisor using his or her own device (smartphone or PC) and logs in. For example, new employee A logs in to the AI ​​Advisor from his or her PC.

[0060] Step 3:

[0061] Users input specific questions to the AI ​​advisor in text format and send them. For example, new employee A might input, "I want to learn the basics of data analysis using Excel."

[0062] Step 4:

[0063] The server receives questions sent by users. New employee A's question is, "I want to learn the basics of data analysis using Excel."

[0064] Step 5:

[0065] The server converts the received question into the appropriate format for sending to the AI. After conversion, the question is sent to the AI.

[0066] Step 6:

[0067] The AI ​​receives the question sent from the server and begins analysis. The AI ​​analyzes the question text and extracts keywords and important phrases. Specifically, it extracts the keywords "Excel," "data analysis," and "basics."

[0068] Step 7:

[0069] The AI ​​searches the database based on the extracted keywords to retrieve relevant information, for example, information on "basic Excel operations," "use of basic functions," and "data visualization."

[0070] Step 8:

[0071] Based on the information it acquires, the AI ​​generates optimal advice, such as "First, learn the basics of Excel, then learn how to use functions, and finally master data visualization techniques."

[0072] Step 9:

[0073] The server receives the advice provided by the AI ​​and converts it to send it to the user in an appropriate format, for example, converting the advice text into HTML.

[0074] Step 10:

[0075] The server sends the formatted advice to the new employee's terminal. The advice is sent to new employee A's PC.

[0076] Step 11:

[0077] Users can receive and display advice from the AI ​​advisor on their devices. For example, new employee A receives advice on his PC such as, "First, learn the basics of Excel, then learn how to use functions, and finally master data visualization techniques."

[0078] This series of steps allows new employees to efficiently resolve questions and problems related to their work, accelerating their growth.

[0079] Example 1

[0080] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0081] New employees need appropriate support and advice to efficiently acquire work skills. However, it is difficult for existing members to allocate time to each new employee, which can result in inconsistent quality of instruction. New employees also may not be able to quickly obtain appropriate answers to specific questions about their work, which can reduce their efficiency. To solve these problems, a system is needed that provides immediate and accurate advice to new employees regarding their questions and problems.

[0082] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0083] In this invention, the server includes: means for storing new employee profile information, the work content of each department, member characteristics, and required skills in a database; means for new employees to input and send questions using their terminals; means for receiving questions and converting them into an appropriate format for sending to AI; means for the AI ​​to analyze the questions and extract keywords and important phrases; means for searching the database based on the extracted keywords and important phrases to obtain related information; means for generating advice based on the related information; means for converting the generated advice into an appropriate format such as HTML format and sending it to the new employee's terminal; and means for receiving and displaying the advice on the new employee's terminal. This allows new employees to efficiently acquire work skills and receive high-quality support while reducing the burden on existing members.

[0084] "New employee profile information" is information that indicates the attributes, career history, skills, interests, etc. of each new employee.

[0085] "Business content of each department" is information indicating the specific business, roles, and responsibilities performed in each department within the company.

[0086] "Member characteristics" is information that indicates the personal characteristics of members of each department, such as their experience, skills, and personalities.

[0087] "Required skills" is information that indicates the techniques, knowledge, and abilities required to perform a specific job.

[0088] "Devices" are electronic devices such as computers, smartphones, and tablets used by new employees.

[0089] A "question" is text information that a new employee inputs to resolve a question or problem regarding the improvement of their work skills.

[0090] "AI" refers to programs and systems that use artificial intelligence technology to analyze and provide advice to new employees in response to their questions.

[0091] "Means for converting into a format" refers to the process of converting the received question or generated advice into an appropriate data format (e.g., JSON, HTML).

[0092] "Keywords and important phrases" are important words and phrases related to job skills extracted from the questions.

[0093] A "database" is a system for efficiently storing large amounts of information and making it easy to search and access.

[0094] "Advice" is specific guidance or recommendations generated by the AI ​​based on the new employee's questions.

[0095] This invention is a system that uses a skill-up advisor AI for new employees to support efficient acquisition of work skills. The basic operation of this system is to process information using a server, terminals, and AI modules and provide appropriate advice to new employees.

[0096] Initial Setup

[0097] The server stores new employee profile information, each department's job duties, member characteristics, and required skills in a database. High-performance server machines (such as the Dell PowerEdge series) are used for the hardware, and PostgreSQL is used as the database management system. Specifically, the server stores examples of the marketing department's job duties, such as "social media campaign planning" and "data analysis," and required skills, such as "Excel" and "presentations."

[0098] Enter and submit your question

[0099] New employees access the AI ​​advisor from their own devices (smartphones or PCs) using an internet browser (such as Google Chrome or Safari). For example, new employee A enters a question in text format, such as "I would like to learn the basics of data analysis using Excel," and submits it. This operation is performed using a web form on the user's device.

[0100] Receiving and converting questions

[0101] The server receives questions from new employees and converts them into JSON format to send to the AI. This process relies on a web server using Node.js or Python's Flask. The server receives HTTP requests, analyzes the contents of the request body, converts them into JSON format, and sends them to the AI ​​module.

[0102] Parsing the question and generating advice

[0103] The AI ​​analyzes the question it receives and extracts keywords and important phrases (e.g., "Excel," "data analysis," and "basics"). This process uses natural language processing techniques such as BERT and GPT. The AI ​​searches for related information from a database (e.g., "basic Excel operations," "use of basic functions," and "data visualization") and generates appropriate advice based on that information. For example, the AI ​​might generate advice such as, "First, master the basic operations of Excel, then learn how to use functions, and finally master data visualization techniques."

[0104] Sending Advice

[0105] The server receives the advice from the AI ​​and converts it into an appropriate format, such as HTML, for transmission to the new employee's device. Web server software such as Apache or Nginx is used for transmission.

[0106] Receiving and viewing advice

[0107] New employees receive and display advice from the AI ​​advisor on their own devices. For example, New Employee A displays the advice on his PC, "First, learn the basics of Excel, then learn how to use functions, and finally master data visualization techniques."

[0108] Examples of prompt statements

[0109] Some of the prompts that new employees can enter into their AI advisor include:

[0110] "Please teach me the basics of data analysis using Excel."

[0111] "I want to know the skills required for the marketing department."

[0112] "Please give me some advice on how to improve my presentation skills."

[0113] The system of the present invention allows new employees to efficiently acquire business skills, and allows existing members to receive high-quality support while reducing their burden.

[0114] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0115] Step 1: Server Initialization

[0116] The server stores new employee profile information, the job duties of each department, the characteristics of members, and the required skills in a database. This process uses a high-performance server machine and a database management system such as PostgreSQL. Information such as the new employee's personal attributes and the job duties of each department is received as input, and this information is saved in the database as output.

[0117] Specifically, the server executes SQL commands to initialize the database, create the necessary tables, and insert data.

[0118] Step 2: The new employee types in their question and submits it

[0119] New employees, who are users, access the AI ​​advisor from a web browser on their own devices (smartphones or PCs). They enter specific questions in text format and click the send button to send the question to the server. For example, they enter a question such as, "I would like to learn the basics of data analysis using Excel."

[0120] Specifically, the device displays a web form, and the new employee enters a question in the text box and clicks the "Submit" button.

[0121] Step 3: The server receives the query and performs format conversion.

[0122] The server receives questions from new employees and converts them into an appropriate format, such as JSON, to be sent to the AI. It receives text questions from users as input and generates JSON-formatted question data as output. This processing is done using web server technologies such as Node.js and Flask.

[0123] Specifically, the server receives an HTTP request, analyzes the contents of the request body, converts it into JSON format, and sends it to the AI ​​module.

[0124] Step 4: AI analyzes the question and extracts keywords

[0125] The AI ​​analyzes the questions it receives and extracts keywords and important phrases. It receives question data in JSON format as input and generates a list of extracted keywords and phrases as output. This process uses natural language processing techniques such as BERT and GPT.

[0126] Specifically, the AI ​​uses natural language processing technology to extract keywords and then generates a database search query based on them.

[0127] Step 5: AI searches the database for relevant information

[0128] The AI ​​then searches the database based on the extracted keywords and phrases to retrieve relevant information. As input, it receives a list of keywords and phrases, and as output, it retrieves a dataset containing relevant information. This process uses search techniques using SQL queries.

[0129] Specifically, it executes the search query generated by the AI ​​and retrieves relevant data from the database.

[0130] Step 6: AI generates advice

[0131] The AI ​​generates appropriate advice based on the relevant information it has acquired. It receives relevant information acquired from a database as input and generates written advice as output. This process uses natural language generation technology. For example, it generates advice such as, "First, learn the basic operations of Excel, then learn how to use functions, and finally master data visualization techniques."

[0132] Specifically, the AI ​​constructs sentences based on the information and outputs them as advice.

[0133] Step 7: The server formats and sends the advice

[0134] The server converts the advice received from the AI ​​into an appropriate format (e.g., HTML format) and sends it to the new employee's device. It receives the advice text from the AI ​​as input, generates the converted advice data as output, and sends it to the user's device. This process uses web server software such as Apache or Nginx.

[0135] Specifically, the server converts the advice text into HTML format and sends it as an HTTP response.

[0136] Step 8: New employees receive and view the advice

[0137] The terminal receives advice sent from the server and displays it to the user. It receives advice data in HTML format from the server as input and displays it on the browser as output. For example, it displays advice such as "First, learn the basic operations of Excel, then learn how to use functions, and finally master data visualization techniques."

[0138] Specifically, the terminal receives the HTTP response and displays the advice text in the web browser.

[0139] (Application example 1)

[0140] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0141] Currently, a significant amount of human resources must be expended in the process of quickly and efficiently training new worker robots to acquire the necessary skills and work methods. There are also concerns about errors and reduced efficiency due to insufficient knowledge of work processes and maintenance procedures. As a result, there is an increased risk of a decline in productivity and quality throughout the factory.

[0142] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0143] In this invention, the server includes means for storing profile information for a new worker, details of each work process, robot maintenance procedures, and required skills in a database, means for the new worker to input and send a question using a terminal, means for receiving the question and sending it to the AI, means for the AI ​​to analyze the question and search the database for related information, means for generating advice based on the related information, and means for sending the generated advice to the new worker's terminal. This allows the new worker robot to efficiently acquire the necessary skills and knowledge, saving human resources and reducing work errors.

[0144] "New workers" refer to work robots that have been newly assigned to work sites such as factories.

[0145] "Profile information" refers to data about each new worker, including basic information, characteristics, and history.

[0146] "Work process" is a concept that encompasses the specific work and procedures carried out within a factory.

[0147] "Maintenance procedures" refer to the maintenance and repair methods required for the proper operation of a worker robot.

[0148] "Required skills" refers to the skills and knowledge that new workers must acquire in order to carry out a specific work process.

[0149] A "database" refers to a structured collection of information that is systematically organized and stored, and can be searched and extracted as needed.

[0150] "Terminal" refers to the electronic device used by the new worker to enter and receive information.

[0151] "Questions" refer to specific inquiries about what a new worker wants to learn or a problem they want to solve.

[0152] "AI" refers to artificial intelligence, a technology that generates advice in response to questions through natural language processing and data analysis.

[0153] "Advice" refers to guidelines such as specific steps and learning methods generated by AI based on questions.

[0154] The present invention is a system that uses a new skill-up advisor AI for worker robots to support efficient work skill acquisition. To implement this invention, a cloud server, a database, a terminal (a tablet, a smartphone, or a robot-specific control terminal), and an artificial intelligence (AI) model are used. Specifically, the system is configured as follows:

[0155] The server stores the new worker robot's profile information, the details of each work process, robot maintenance procedures, and required skills in a database. For example, the database stores "screw tightening" and "part placement" as work contents for an "assembly process," and stores "torque adjustment" and "part identification" as required skills.

[0156] The new worker robot can use a terminal to input questions about specific operation methods and maintenance procedures in text format and send them to the server. For example, consider the case where the new worker robot inputs and sends the question, "I want to learn how to adjust the torque of a screw."

[0157] The server receives this question and prepares it for transmission to the AI, converting it into the appropriate format. The AI ​​analyzes the question and extracts keywords and important phrases. For example, it extracts the keywords "torque," "adjustment," and "method" and retrieves information from the database about "how to use a torque wrench," "checking the setting value," and "how to tighten a screw."

[0158] The AI ​​then generates appropriate advice based on the information it has acquired. For example, it generates advice such as "Use a torque wrench to set the appropriate torque value, then tighten the screws." The server receives this advice and sends it in an appropriate format to the new worker robot's terminal. Finally, the new worker robot receives and displays the advice from the AI ​​advisor on its terminal.

[0159] It is recommended to use TensorFlow or PyTorch for generative AI models, and spaCy or Transformers for natural language processing, which will enable new worker robots to efficiently acquire the necessary skills and knowledge, saving human resources and reducing work errors.

[0160] For example, if a robot types and sends the question, "What are the steps to replace a motor?", the AI ​​can retrieve relevant information from the database and generate specific advice such as, "First, disconnect the power, then remove the old motor, and install the new motor in the specified way."

[0161] Example prompt sentence:

[0162] Question: I want to learn how to torque screws.

[0163] Q: What is the procedure for replacing the motor?

[0164] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0165] Step 1:

[0166] The server stores the profile information for new workers, the details of each work process, robot maintenance procedures, and required skills in a database. The input is the profile information of the new worker and data related to the work process, and the output is the configuration information stored in the database. Specifically, the server executes SQL queries against the database to insert and update the required information.

[0167] Step 2:

[0168] The new worker uses a terminal to input a question and sends it to the server. The input is the question text of the new worker, and the output is the question data sent to the server. In concrete terms, a text input form is displayed on the terminal, and the new worker inputs a question and presses the "send" button.

[0169] Step 3:

[0170] The server receives questions from new workers and prepares them for sending to the AI ​​model. The input is the question data of the new worker, and the output is the formatted question data to be sent to the AI ​​model. Specifically, the server converts the received text into an appropriate format, such as JSON.

[0171] Step 4:

[0172] The AI ​​analyzes the question and searches for relevant information from a database. The input is a formatted question data, and the output is a dataset containing relevant information. Specifically, the AI ​​uses natural language processing techniques (e.g., spaCy or Transformers) to extract important keywords and execute a search query against the database.

[0173] Step 5:

[0174] The AI ​​generates appropriate advice based on the acquired information. The input is a dataset of search results, and the output is the generated advice text. Specifically, the AI ​​uses a generative AI model (e.g., TensorFlow or PyTorch) to generate advice based on the question.

[0175] Step 6:

[0176] The server receives advice from the AI ​​and converts it into an appropriate format for sending to the new worker's device. The input is advice text, and the output is formatted advice that is displayed on the new worker's device. Specifically, the server converts the advice text into HTML format or similar and sends it to the new worker's device.

[0177] Step 7:

[0178] The new worker's terminal displays the received advice. The input is the formatted advice sent from the server, and the output is the advice text displayed on the screen. Specifically, a web browser or dedicated application installed on the terminal renders and displays the advice text.

[0179] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0180] This invention is a system that combines an emotion engine with a skill-up advisor AI for new employees to support the efficient and emotional acquisition of work skills. Specifically, a server stores new employee profile information, the work content of each department, the characteristics of members, and required skills in a database, and new employees input and send questions using their terminals. The questions are received by the server and sent to the AI, and the emotion engine analyzes the user's emotions. Based on the question and emotion information, the AI ​​searches the database for related information and generates advice. The generated advice is adjusted according to the user's emotions and sent to the new employee's terminal by the server.

[0181] Program processing overview (expressed in natural language)

[0182] 1. Initial setup by the server

[0183] The server stores new employee profile information, the job description of each department, the characteristics of the members, and the required skills in a database. For example, the job description of the "Marketing Department" might include "SNS campaign planning" and "data analysis," and the required skills might include "Excel" and "presentation."

[0184] 2. New employees ask questions

[0185] New employees use their own devices (smartphones or PCs) to access the AI ​​Advisor and log in. For example, new employee A logs in to the AI ​​Advisor from his or her PC.

[0186] 3. Enter and submit your question

[0187] New employees enter specific questions in text format and submit them. For example, new employee A enters and submits, "I would like to learn the basics of data analysis using Excel."

[0188] 4. The server receives the query

[0189] The server receives questions sent by new employees. New employee A's question is, "I want to learn the basics of data analysis using Excel."

[0190] 5. Emotion analysis using an emotion engine

[0191] The server prepares the received question for transmission to the AI, while having the emotion engine analyze the question text to recognize the user's emotions. For example, the emotion engine extracts emotions such as "confusion" or "anxiety" from the question text.

[0192] 6. AI-based analysis and advice generation

[0193] The AI ​​receives the question and sentiment analysis results sent from the server and begins its analysis. It extracts keywords from the question text, such as "Excel," "data analysis," and "basics." It also retrieves related information from the database while reflecting the sentiment information. For example, it searches for and retrieves information related to "basic Excel operations," "use of basic functions," and "data visualization."

[0194] 7. Generating Advice

[0195] Based on the information it acquires, the AI ​​generates optimal advice based on the user's emotions. For example, it generates advice such as "First, learn the basics of Excel, then learn how to use functions, and finally master data visualization techniques." However, if the user is feeling anxious, it will also include additional comments such as "Try not to rush and understand each step at a time."

[0196] 8. Server-Sent Advice

[0197] The server receives the advice provided by the AI ​​and converts it to be sent to the new employee in an appropriate format, for example, converting the advice text into HTML and formatting it as content containing advice based on emotions.

[0198] 9. New employees receive advice

[0199] Advice from an AI advisor is received and displayed on the new employee's device. For example, new employee A receives advice on his / her PC such as, "First, learn the basic operations of Excel, then learn how to use functions, and finally master data visualization techniques. Take your time and understand each step at a time."

[0200] In this way, the present invention supports the efficient acquisition of work skills while taking into consideration the user's feelings, allowing new employees to quickly resolve questions and problems related to their work and accelerating their growth. It also reduces the burden on existing members and makes it possible to provide high-quality support.

[0201] The processing flow will be explained below.

[0202] Step 1:

[0203] The server stores new employee profile information, the job content of each department, the characteristics of members, and the required skills in a database. Specifically, for the marketing department, "SNS campaign planning" and "data analysis" are registered as job content, and "Excel" and "presentation" are stored as required skills.

[0204] Step 2:

[0205] The new employee, who is the user, accesses the AI ​​Advisor using his or her own device (smartphone or PC) and logs in. For example, new employee A logs in to the AI ​​Advisor from his or her PC.

[0206] Step 3:

[0207] Users input questions to the AI ​​advisor in text format and send them. For example, new employee A might input, "I want to learn the basics of data analysis using Excel."

[0208] Step 4:

[0209] The server receives questions sent by users. New employee A's question is, "I want to learn the basics of data analysis using Excel."

[0210] Step 5:

[0211] The server converts the received questions into an appropriate format and sends them to the AI ​​and emotion engine, where the questions are formatted in a form suitable for analysis.

[0212] Step 6:

[0213] The AI ​​receives the question sent from the server and analyzes the question. The AI ​​analyzes the question text and extracts keywords and important phrases. For example, it extracts keywords such as "Excel," "data analysis," and "basics."

[0214] Step 7:

[0215] At the same time, the emotion engine analyzes the user's emotions from the question text. For example, the emotion engine extracts emotions such as "confusion" or "anxiety" from the text.

[0216] Step 8:

[0217] The AI ​​searches the database based on the extracted keywords to retrieve relevant information, for example, information on "basic Excel operations," "use of basic functions," and "data visualization."

[0218] Step 9:

[0219] Based on the information it acquires, the AI ​​generates appropriate advice while reflecting the user's emotions. For example, the AI ​​might generate advice such as "First, learn the basics of Excel, then learn how to use functions, and finally master data visualization techniques," and if the emotion expressed is "confused," it would include an additional comment such as "Try not to rush and understand it one step at a time."

[0220] Step 10:

[0221] The server receives the advice provided by the AI ​​and converts it into a format suitable for the user, for example, converting the advice text into HTML and formatting it according to emotions.

[0222] Step 11:

[0223] The server sends the formatted advice to the new employee's terminal. The advice is sent to new employee A's PC.

[0224] Step 12:

[0225] Users receive and display advice from an AI advisor on their devices. For example, new employee A receives the advice on his PC: "First, learn the basics of Excel, then learn how to use functions, and finally master data visualization techniques. Take your time and understand each step at a time."

[0226] This series of processes allows new employees to efficiently resolve work-related questions and problems and receive support tailored to their emotions. It also reduces the burden on existing members while providing high-quality support.

[0227] Example 2

[0228] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0229] In order for new employees to efficiently acquire work skills, it is necessary to provide prompt and appropriate advice that responds to each employee's feelings. However, current systems have difficulty providing advice that takes the user's feelings into account, and often take a long time to search for information and generate advice. As a result, new employees are unable to quickly resolve their work-related questions or problems, which can slow their growth.

[0230] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a means for storing new employee profile information, the work content of each department, member characteristics, and required skills in a database, a means for the new employee to input and send questions using a terminal, a means for receiving the questions and sending them to an AI, a means for analyzing the user's emotions from the question text, a means for the AI ​​to search the database for related information based on the question and the emotion analysis results, a means for generating advice based on the related information and the user's emotions, and a means for formatting the generated advice and sending it to the new employee's terminal. This enables new employees to quickly resolve questions and problems related to their work and speed up their growth. Furthermore, it reduces the burden on existing members and enables them to provide high-quality support.

[0231] A "new employee" refers to an employee who has just been hired by a company or organization.

[0232] "Profile Information" refers to information that includes details about a user, such as personal information, history, skills and experience, job title and department.

[0233] "Job Description" refers to the scope of work and responsibilities performed in a particular department or position.

[0234] "Member characteristics" refers to the skills, experience, personality, and working style of each employee belonging to a particular department or team.

[0235] "Required skills" refers to the abilities and knowledge required to perform a specific job or position.

[0236] A "database" refers to a collection of information that is structured, stored, and managed so that it can be efficiently searched and retrieved.

[0237] A "terminal" is a device that inputs and receives information, such as a smartphone or personal computer.

[0238] "AI" refers to artificial intelligence, specifically algorithms and models that recognize patterns in questions and data to generate appropriate answers and recommendations.

[0239] "Means for analyzing emotions" refers to technologies and algorithms for extracting and recognizing emotions from text entered by a user.

[0240] "Related information" refers to information searched from a database as content that corresponds to the user's question or feelings.

[0241] "Advice generation means" refers to a process or system for providing optimal advice or guidance based on a user's question.

[0242] The "means for formatting and transmitting" refers to a process for converting the generated advice into a specific format and transmitting it appropriately to the user's terminal.

[0243] The present invention combines an emotion engine with a skill improvement advisory system for new employees to support the acquisition of work skills efficiently and in accordance with emotions. Specific embodiments for carrying out the present invention will be described below.

[0244] The server stores new employee profile information, the job description of each department, the characteristics of each member, and the required skills in a database. Specifically, it connects to the company's human resources system via API and is set up to retrieve profile information in real time. A relational database system such as MongoDB or MySQL is suitable for the database used.

[0245] Users access the AI ​​advisor system using their own devices (smartphones or personal computers). Access is via a browser-based web application, and in many cases single sign-on (SSO) technology is implemented. Once the user logs in, an interface for entering questions is provided.

[0246] When a user enters a specific question in text format and submits it, the device sends the input text to the server as an HTTP request. For example, a user might enter "I want to learn the basics of data analysis using Excel" and press the submit button.

[0247] The server parses the received HTTP request and extracts the text portion. At the same time, metadata such as the user ID and the time of submission is also recorded. This text is then passed to the emotion engine, which uses natural language processing techniques (for example, Python's NLTK library or the Google Cloud Natural Language API) to analyze the user's emotions. Specifically, it detects emotions such as "confusion" or "anxiety" from the text and generates a related score.

[0248] The sentiment analysis results and question content are then sent to an artificial intelligence (AI) system. The AI ​​system uses a generative AI model, such as GPT-4, to extract keywords from the question text and search a database for related information. Specifically, it analyzes keywords such as "Excel," "data analysis," and "basics," and searches for and retrieves information on "basic Excel operations," "using basic functions," and "data visualization."

[0249] Based on the information acquired by the AI, the system generates optimal advice based on the user's emotions. For example, it generates advice that includes specific steps, such as "First, learn basic Excel operations, then learn how to use functions, and finally master data visualization techniques." If the user's emotion is "anxious," the system will add an additional comment such as "Try not to rush and understand each step one by one."

[0250] The server then receives the generated advice, converts it into a format suitable for the user, and sends it to the user. Specifically, the server converts the generated advice text into HTML and formats the advice according to the results of sentiment analysis. This process uses a template engine such as Jinja2.

[0251] Finally, the advice generated on the user's device is received and displayed on the browser. For example, new employee A reads advice on his / her PC such as, "First, learn the basic operations of Excel, then learn how to use functions, and finally master data visualization techniques. Take your time and understand each step at a time."

[0252] (Examples of specific examples and prompts)

[0253] As a concrete example, consider the case where a new employee asks, "I want to know how to give more effective presentations." The emotion engine analyzes emotions such as "nervous." The AI ​​then analyzes keywords such as "presentation," "effective," and "method" and searches for related information. As a result, it generates advice such as "how to create effective slides" and "tips for speaking," and adds comments according to the emotion, such as "It's okay to be nervous, just tackle each step one by one."

[0254] Example prompt sentence:

[0255] "As an AI skill-up advisor for new employees, generate advice that takes emotions into account in response to the following question: 'I want to know how to give presentations more effectively.' Let's say the user is nervous."

[0256] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0257] Step 1:

[0258] The server stores new employee profile information, the work content of each department, the characteristics of members, and required skills in a database. For example, it can be set up to connect to a company's human resources system via API and retrieve profile information in real time. The input is data received from the human resources system, and the output is the information stored in the database. Specifically, each piece of information is structured and stored using a database system such as MongoDB or MySQL.

[0259] Step 2:

[0260] New employees (users) access and log in to the AI ​​advisor system using their own devices (smartphones or personal computers). The input is the new employee's login information (ID and password), and the output is a message indicating whether the login was successful or unsuccessful. Browser-based web applications may use single sign-on (SSO) technology for security reasons.

[0261] Step 3:

[0262] The user enters a specific question in text format through the AI ​​advisor's interface and submits it. The input is the question text entered by the user, and the output is data sent to the server in the form of an HTTP request. For example, the user might enter "I would like to learn the basics of data analysis using Excel" and click the submit button.

[0263] Step 4:

[0264] The server receives the HTTP request sent by the user and analyzes the question. The input is the HTTP request, and the output is the parsed text portion and metadata (user ID, submission time, etc.). If the received data is in JSON format, it performs specific processing to parse and extract the text portion.

[0265] Step 5:

[0266] The server passes the received text to the emotion engine, which then analyzes the user's emotion from the question text. The input is the question text, and the output is the extracted emotion score. Specifically, the engine uses the Python NLTK library and Google Cloud Natural Language API to detect emotions such as "confusion" and "anxiety."

[0267] Step 6:

[0268] The server sends the question text and the sentiment analysis results to the AI ​​system. The input is the question text and sentiment score, and the output is the information search results by the AI ​​system. The AI ​​first extracts keywords and identifies keywords such as "Excel," "data analysis," and "basics." It then uses these keywords to search for related information from a database. The AI ​​model used is a generative AI model such as GPT-4.

[0269] Step 7:

[0270] Based on the searched information, the AI ​​generates advice that corresponds to the user's emotions. The input is the search result information and emotion score, and the output is the generated specific advice. For example, it generates advice such as "First, learn the basic operations of Excel, then learn how to use functions, and finally master data visualization techniques." At this time, it adds comments that correspond to the user's emotions, such as "Try not to rush and understand each step at a time."

[0271] Step 8:

[0272] The server formats the generated advice and sends it to the new employee's device in the appropriate format. The input is the generated advice, and the output is the formatted advice. Specifically, the generated advice text is converted into HTML format and advice based on the sentiment analysis results is included. The formatting process is performed using a template engine such as Jinja2.

[0273] Step 9:

[0274] Advice from the AI ​​advisor is received and displayed on the user's device. The input is formatted advice sent from the server, and the output is the content displayed in the browser. For example, the user reads advice such as, "First, learn the basic operations of Excel, then learn how to use functions, and finally master data visualization techniques. Take your time and understand each step at a time."

[0275] The above is a specific processing flow in the system of the present invention, and the input, data processing, and output at each step are clearly shown.

[0276] (Application example 2)

[0277] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0278] In modern industry, improving the work skills of new employees and troubleshooting industrial automation equipment are important issues that directly affect productivity and efficiency. However, new employees tend to have many questions and anxieties, and automation equipment often causes errors. A system that provides efficient and emotionally sensitive advice and solutions to these issues is needed.

[0279] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for storing profile information, job content, employee characteristics, and required skills in a database, means for new employees or automated equipment to input and send questions or error reports using a terminal, and means for receiving questions or error reports and sending them to the AI. This makes it possible to provide efficient and appropriate advice and countermeasures for the questions, anxieties, and errors that new employees and automated equipment face.

[0280] "New employees" refers to employees who have been newly hired by a company or other organization.

[0281] "Industrial automation equipment" refers to automated machinery and equipment used in factories and production lines.

[0282] "Profile Information" refers to basic attribute information stored about each new employee or automated device.

[0283] "Work station" refers to the location or facility where a particular job or task is performed.

[0284] "Members" refers to employees or workers working at a company or work station.

[0285] "Terminal" refers to a device used to input or output information, such as a smartphone or computer.

[0286] "Questions" refer to sentences or text that express doubts or problems that new employees or automated equipment have.

[0287] "Error reporting" refers to notifications or information sent by automated equipment when it detects a malfunction or problem.

[0288] An "emotion engine" refers to an algorithm or software that analyzes a user's emotional state from input text.

[0289] "Advice" refers to advice or solutions provided in response to questions or error reports.

[0290] "Countermeasures" refer to specific actions or steps to be taken in response to an error or problem.

[0291] To implement this invention, the following interactions between a server, a terminal, and a user are required.

[0292] 1. System Configuration

[0293] 1.1 Server Configuration

[0294] The server stores profile information for new employees and industrial automation equipment in a database, including the work content of each work station, the characteristics of the employees, and the required skills. It also has a means of receiving questions and error reports and sending them to the AI. It also sends advice and countermeasures generated by the AI ​​to new employees and automation equipment.

[0295] 1.2 Terminal configuration

[0296] Terminals are devices used by new employees and automated equipment to input questions and error reports and send them to the server. These terminals include smartphones, PCs, and tablets.

[0297] 1.3 User operations

[0298] New employees, who are users, use terminals to input questions or problems about their daily work in text format and send them to the server. Similarly, automated equipment also reports errors or malfunctions that occur during work to the server.

[0299] 2. Program Processing

[0300] 2.1 Initial Setup

[0301] The server stores profile information for new employees and automated equipment, as well as the job content, characteristics of the employees, and required skills for each work station in a database. For example, "welding metal parts" is registered as the job content for a "welding line," and "welding techniques" and "safe operations" are stored as required skills.

[0302] 2.2 Receiving Questions or Error Reports

[0303] Users, such as new employees and automated equipment, input and send specific questions or error reports in text format from their own devices. For example, a new employee might type and send, "I don't know how to set up the welding machine," or an automated device might report, "There's an insufficient power error."

[0304] 2.3 Analysis by Emotion Engine

[0305] When the server receives a question or error report, it uses an emotion engine to analyze the input text and extract its emotional information before sending it to the AI.

[0306] 2.4 Analysis and advice generation using AI

[0307] Based on the emotional information received from the emotion engine, questions, and error reports, the AI ​​searches the database for relevant data and generates optimal advice and countermeasures. For example, it generates advice that takes into consideration emotions, such as "Try not to rush and understand each step at a time."

[0308] 2.5 Sending Advice

[0309] The server receives the advice and measures generated by the AI ​​and sends them to the user's device in an appropriate format.

[0310] 3. Specific Examples

[0311] Let's consider the case where a new employee asks on their smartphone, "I want to learn the basics of data analysis using Excel." In this case, the emotion engine recognizes emotions such as "confusion" or "anxiety," and based on that information, the AI ​​suggests advice such as, "Start with the basic operations of Excel, then learn how to use functions, and finally master data visualization techniques." If the emotion is "anxiety," the AI ​​also includes an additional comment such as, "Try not to rush and understand it one step at a time."

[0312] Prompt Sentence Examples

[0313] Robot ID: R002

[0314] Question: "My parts are not properly aligned during assembly. What should I do?"

[0315] Emotion: "Anxiety"

[0316] In this way, the system of the present invention is able to provide efficient and empathetic advice and solutions to problems faced by new employees and industrial automation equipment.

[0317] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0318] Step 1: Initial Setup

[0319] The server stores profile information for new employees and automated equipment, the work content of each work station, the characteristics of the employees, and the required skills in a database. The server receives input from the new employee's attribute information, work content, and skill requirements, which it then stores in the database. The output is the appropriately stored profile information and work data. Specific operations include adding and updating records in the database.

[0320] Step 2: Submit a question or error report

[0321] A user, such as a new employee or an automated device, uses a terminal to input and send a specific question or error report in text format. The input is the user's text question or error report. The terminal sends this to the server. The output is the question or error report received by the server. The specific operation is to send data from the terminal to the server.

[0322] Step 3: Receiving a question or error report

[0323] The server receives questions or error reports sent by users. The input is text data sent from the terminal. The server receives this and temporarily stores it in a database. The output is text data prepared for sentiment analysis. Specifically, the server adds the text data to a queue for analysis.

[0324] Step 4: Analysis by the Emotion Engine

[0325] The server sends the received question or error report to the emotion engine, which extracts the user's emotional information. The input is text data stored in a queue. The emotion engine analyzes this and extracts emotions such as "confusion" or "anxiety." The output is data containing the emotional information. Specifically, it uses natural language processing tools to generate emotional information from text.

[0326] Step 5: AI analysis and advice generation

[0327] Based on text data with emotional information added, the AI ​​searches for relevant information from a database and generates optimal advice or countermeasures. The input is text data with emotional information. The AI ​​analyzes this, extracts relevant information from the database, and generates advice or countermeasures that take emotions into consideration. The output is the generated advice or countermeasures. Specifically, the system uses a generative AI model to create advice statements.

[0328] Step 6: Formatting the advice

[0329] The server converts the advice provided by the AI ​​into an appropriate format. The input is the text data of the advice or action generated by the AI. The server formats this into HTML or another appropriate format. The output is the formatted advice or action. Specifically, it runs a script that converts the text data into a different file format.

[0330] Step 7: Submitting Advice

[0331] The server sends formatted advice and measures to the terminals of new employees and automated equipment. The input is the formatted advice and measures. The server sends this to the terminal. The output is the advice and measures displayed on the terminal. The specific operation is data transmission from the server to the terminal.

[0332] Step 8: Receive and view advice

[0333] The terminal receives advice and measures sent from the server and displays them to the user. The input is the advice text sent from the server. The terminal displays this on the screen. The output is the specific advice and measures displayed to the user. The specific operation is to display the received data on the user interface.

[0334] This allows for efficient and empathetic advice and solutions to problems faced by new employees and industrial automation equipment.

[0335] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0336] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0337] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0338] [Second embodiment]

[0339] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0340] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0341] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0342] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0343] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0344] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0345] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0346] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0347] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0348] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0349] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0350] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0351] This invention is a system that uses a skill-up advisor AI for new employees to support the efficient acquisition of work skills. Specifically, a server stores new employee profile information, the work content of each department, the characteristics of members, and required skills in a database, and new employees can input and send questions using their terminals. These questions are received by the server and sent to the AI. The AI ​​analyzes the questions, searches the database for relevant information, and generates advice based on the relevant information. The generated advice is sent by the server to the new employee's terminal.

[0352] Program processing overview (expressed in natural language)

[0353] 1. Initial setup by the server

[0354] The server stores new employee profile information, the job duties of each department, the characteristics of the members, and the required skills in a database. For example, the database might register "SNS campaign planning" and "data analysis" as the job duties of the "Marketing Department," and store "Excel" and "presentation" as required skills.

[0355] 2. New employees ask questions

[0356] New employees access the AI ​​advisor using their own devices (smartphones or PCs). They input specific questions in text format and submit them. For example, New Employee A might input "I would like to learn the basics of data analysis using Excel" and submit the text.

[0357] 3. The server receives the query

[0358] The server receives the new hire's question, prepares it for sending to the AI, and converts it into the appropriate format. The converted question is then passed to the AI ​​module.

[0359] 4. AI analyzes the question and generates advice

[0360] AI analyzes questions and extracts keywords and important phrases. For example, AI extracts keywords such as "Excel," "data analysis," and "basics," and retrieves information from a database about "basic Excel operations," "use of basic functions," and "data visualization." Based on the information retrieved, it generates appropriate advice. For example, the AI ​​generates advice such as, "First, learn basic Excel operations, then learn how to use functions, and finally master data visualization techniques."

[0361] 5. The server sends the advice

[0362] The server receives the advice from the AI, converts it into an appropriate format for sending to the new employee, and then sends it to the new employee's terminal. For example, the server converts the advice text into HTML format and sends it to the PC of new employee A.

[0363] 6. New employees receive advice

[0364] Advice from an AI advisor is received and displayed on the new employee's device. For example, new employee A receives advice on his / her PC such as "First, learn the basic operations of Excel, then learn how to use functions, and finally master data visualization techniques."

[0365] The purpose of this invention is to enable new employees to efficiently resolve questions and problems related to their work and improve their work skills through this series of processes. It also makes it possible to provide high-quality support while reducing the burden on existing members.

[0366] The processing flow will be explained below.

[0367] Step 1:

[0368] The server stores new employee profile information, the job description of each department, the characteristics of the members, and the required skills in a database. Specifically, the Marketing Department stores job descriptions such as "SNS campaign planning" and "data analysis" and the required skills such as "Excel" and "presentation."

[0369] Step 2:

[0370] The new employee, who is the user, accesses the AI ​​Advisor using his or her own device (smartphone or PC) and logs in. For example, new employee A logs in to the AI ​​Advisor from his or her PC.

[0371] Step 3:

[0372] Users input specific questions to the AI ​​advisor in text format and send them. For example, new employee A might input, "I want to learn the basics of data analysis using Excel."

[0373] Step 4:

[0374] The server receives questions sent by users. New employee A's question is, "I want to learn the basics of data analysis using Excel."

[0375] Step 5:

[0376] The server converts the received question into the appropriate format for sending to the AI. After conversion, the question is sent to the AI.

[0377] Step 6:

[0378] The AI ​​receives the question sent from the server and begins analysis. The AI ​​analyzes the question text and extracts keywords and important phrases. Specifically, it extracts the keywords "Excel," "data analysis," and "basics."

[0379] Step 7:

[0380] The AI ​​searches the database based on the extracted keywords to retrieve relevant information, for example, information on "basic Excel operations," "use of basic functions," and "data visualization."

[0381] Step 8:

[0382] Based on the information it acquires, the AI ​​generates optimal advice, such as "First, learn the basics of Excel, then learn how to use functions, and finally master data visualization techniques."

[0383] Step 9:

[0384] The server receives the advice provided by the AI ​​and converts it to send it to the user in an appropriate format, for example, converting the advice text into HTML.

[0385] Step 10:

[0386] The server sends the formatted advice to the new employee's terminal. The advice is sent to new employee A's PC.

[0387] Step 11:

[0388] Users can receive and display advice from the AI ​​advisor on their devices. For example, new employee A receives advice on his PC such as, "First, learn the basics of Excel, then learn how to use functions, and finally master data visualization techniques."

[0389] This series of steps allows new employees to efficiently resolve questions and problems related to their work, accelerating their growth.

[0390] Example 1

[0391] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0392] New employees need appropriate support and advice to efficiently acquire work skills. However, it is difficult for existing members to allocate time to each new employee, which can result in inconsistent quality of instruction. New employees also may not be able to quickly obtain appropriate answers to specific questions about their work, which can reduce their efficiency. To solve these problems, a system is needed that provides immediate and accurate advice to new employees regarding their questions and problems.

[0393] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0394] In this invention, the server includes: means for storing new employee profile information, the work content of each department, member characteristics, and required skills in a database; means for new employees to input and send questions using their terminals; means for receiving questions and converting them into an appropriate format for sending to AI; means for the AI ​​to analyze the questions and extract keywords and important phrases; means for searching the database based on the extracted keywords and important phrases to obtain related information; means for generating advice based on the related information; means for converting the generated advice into an appropriate format such as HTML format and sending it to the new employee's terminal; and means for receiving and displaying the advice on the new employee's terminal. This allows new employees to efficiently acquire work skills and receive high-quality support while reducing the burden on existing members.

[0395] "New employee profile information" is information that indicates the attributes, career history, skills, interests, etc. of each new employee.

[0396] "Business content of each department" is information indicating the specific business, roles, and responsibilities performed in each department within the company.

[0397] "Member characteristics" is information that indicates the personal characteristics of members of each department, such as their experience, skills, and personalities.

[0398] "Required skills" is information that indicates the techniques, knowledge, and abilities required to perform a specific job.

[0399] "Devices" are electronic devices such as computers, smartphones, and tablets used by new employees.

[0400] A "question" is text information that a new employee inputs to resolve a question or problem regarding the improvement of their work skills.

[0401] "AI" refers to programs and systems that use artificial intelligence technology to analyze and provide advice to new employees in response to their questions.

[0402] "Means for converting into a format" refers to the process of converting the received question or generated advice into an appropriate data format (e.g., JSON, HTML).

[0403] "Keywords and important phrases" are important words and phrases related to job skills extracted from the questions.

[0404] A "database" is a system for efficiently storing large amounts of information and making it easy to search and access.

[0405] "Advice" is specific guidance or recommendations generated by the AI ​​based on the new employee's questions.

[0406] This invention is a system that uses a skill-up advisor AI for new employees to support efficient acquisition of work skills. The basic operation of this system is to process information using a server, terminals, and AI modules and provide appropriate advice to new employees.

[0407] Initial Setup

[0408] The server stores new employee profile information, each department's job duties, member characteristics, and required skills in a database. High-performance server machines (such as the Dell PowerEdge series) are used for the hardware, and PostgreSQL is used as the database management system. Specifically, the server stores examples of the marketing department's job duties, such as "social media campaign planning" and "data analysis," and required skills, such as "Excel" and "presentations."

[0409] Enter and submit your question

[0410] New employees access the AI ​​advisor from their own devices (smartphones or PCs) using an internet browser (such as Google Chrome or Safari). For example, new employee A enters a question in text format, such as "I would like to learn the basics of data analysis using Excel," and submits it. This operation is performed using a web form on the user's device.

[0411] Receiving and converting questions

[0412] The server receives questions from new employees and converts them into JSON format to send to the AI. This process relies on a web server using Node.js or Python's Flask. The server receives HTTP requests, analyzes the contents of the request body, converts them into JSON format, and sends them to the AI ​​module.

[0413] Parsing the question and generating advice

[0414] The AI ​​analyzes the question it receives and extracts keywords and important phrases (e.g., "Excel," "data analysis," and "basics"). This process uses natural language processing techniques such as BERT and GPT. The AI ​​searches for related information from a database (e.g., "basic Excel operations," "use of basic functions," and "data visualization") and generates appropriate advice based on that information. For example, the AI ​​might generate advice such as, "First, master the basic operations of Excel, then learn how to use functions, and finally master data visualization techniques."

[0415] Sending Advice

[0416] The server receives the advice from the AI ​​and converts it into an appropriate format, such as HTML, for transmission to the new employee's device. Web server software such as Apache or Nginx is used for transmission.

[0417] Receiving and viewing advice

[0418] New employees receive and display advice from the AI ​​advisor on their own devices. For example, New Employee A displays the advice on his PC, "First, learn the basics of Excel, then learn how to use functions, and finally master data visualization techniques."

[0419] Examples of prompt statements

[0420] Some of the prompts that new employees can enter into their AI advisor include:

[0421] "Please teach me the basics of data analysis using Excel."

[0422] "I want to know the skills required for the marketing department."

[0423] "Please give me some advice on how to improve my presentation skills."

[0424] The system of the present invention allows new employees to efficiently acquire business skills, and allows existing members to receive high-quality support while reducing their burden.

[0425] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0426] Step 1: Server Initialization

[0427] The server stores new employee profile information, the job duties of each department, the characteristics of members, and the required skills in a database. This process uses a high-performance server machine and a database management system such as PostgreSQL. Information such as the new employee's personal attributes and the job duties of each department is received as input, and this information is saved in the database as output.

[0428] Specifically, the server executes SQL commands to initialize the database, create the necessary tables, and insert data.

[0429] Step 2: The new employee types in their question and submits it

[0430] New employees, who are users, access the AI ​​advisor from a web browser on their own devices (smartphones or PCs). They enter specific questions in text format and click the send button to send the question to the server. For example, they enter a question such as, "I would like to learn the basics of data analysis using Excel."

[0431] Specifically, the device displays a web form, and the new employee enters a question in the text box and clicks the "Submit" button.

[0432] Step 3: The server receives the query and performs format conversion.

[0433] The server receives questions from new employees and converts them into an appropriate format, such as JSON, to be sent to the AI. It receives text questions from users as input and generates JSON-formatted question data as output. This processing is done using web server technologies such as Node.js and Flask.

[0434] Specifically, the server receives an HTTP request, analyzes the contents of the request body, converts it into JSON format, and sends it to the AI ​​module.

[0435] Step 4: AI analyzes the question and extracts keywords

[0436] The AI ​​analyzes the questions it receives and extracts keywords and important phrases. It receives question data in JSON format as input and generates a list of extracted keywords and phrases as output. This process uses natural language processing techniques such as BERT and GPT.

[0437] Specifically, the AI ​​uses natural language processing technology to extract keywords and then generates a database search query based on them.

[0438] Step 5: AI searches the database for relevant information

[0439] The AI ​​then searches the database based on the extracted keywords and phrases to retrieve relevant information. As input, it receives a list of keywords and phrases, and as output, it retrieves a dataset containing relevant information. This process uses search techniques using SQL queries.

[0440] Specifically, it executes the search query generated by the AI ​​and retrieves relevant data from the database.

[0441] Step 6: AI generates advice

[0442] The AI ​​generates appropriate advice based on the relevant information it has acquired. It receives relevant information acquired from a database as input and generates written advice as output. This process uses natural language generation technology. For example, it generates advice such as, "First, learn the basic operations of Excel, then learn how to use functions, and finally master data visualization techniques."

[0443] Specifically, the AI ​​constructs sentences based on the information and outputs them as advice.

[0444] Step 7: The server formats and sends the advice

[0445] The server converts the advice received from the AI ​​into an appropriate format (e.g., HTML format) and sends it to the new employee's device. It receives the advice text from the AI ​​as input, generates the converted advice data as output, and sends it to the user's device. This process uses web server software such as Apache or Nginx.

[0446] Specifically, the server converts the advice text into HTML format and sends it as an HTTP response.

[0447] Step 8: New employees receive and view the advice

[0448] The terminal receives advice sent from the server and displays it to the user. It receives advice data in HTML format from the server as input and displays it on the browser as output. For example, it displays advice such as "First, learn the basic operations of Excel, then learn how to use functions, and finally master data visualization techniques."

[0449] Specifically, the terminal receives the HTTP response and displays the advice text in the web browser.

[0450] (Application example 1)

[0451] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0452] Currently, a significant amount of human resources must be expended in the process of quickly and efficiently training new worker robots to acquire the necessary skills and work methods. There are also concerns about errors and reduced efficiency due to insufficient knowledge of work processes and maintenance procedures. As a result, there is an increased risk of a decline in productivity and quality throughout the factory.

[0453] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0454] In this invention, the server includes means for storing profile information for a new worker, details of each work process, robot maintenance procedures, and required skills in a database, means for the new worker to input and send a question using a terminal, means for receiving the question and sending it to the AI, means for the AI ​​to analyze the question and search the database for related information, means for generating advice based on the related information, and means for sending the generated advice to the new worker's terminal. This allows the new worker robot to efficiently acquire the necessary skills and knowledge, saving human resources and reducing work errors.

[0455] "New workers" refer to work robots that have been newly assigned to work sites such as factories.

[0456] "Profile information" refers to data about each new worker, including basic information, characteristics, and history.

[0457] "Work process" is a concept that encompasses the specific work and procedures carried out within a factory.

[0458] "Maintenance procedures" refer to the maintenance and repair methods required for the proper operation of a worker robot.

[0459] "Required skills" refers to the skills and knowledge that new workers must acquire in order to carry out a specific work process.

[0460] A "database" refers to a structured collection of information that is systematically organized and stored, and can be searched and extracted as needed.

[0461] "Terminal" refers to the electronic device used by the new worker to enter and receive information.

[0462] "Questions" refer to specific inquiries about what a new worker wants to learn or a problem they want to solve.

[0463] "AI" refers to artificial intelligence, a technology that generates advice in response to questions through natural language processing and data analysis.

[0464] "Advice" refers to guidelines such as specific steps and learning methods generated by AI based on questions.

[0465] The present invention is a system that uses a new skill-up advisor AI for worker robots to support efficient work skill acquisition. To implement this invention, a cloud server, a database, a terminal (a tablet, a smartphone, or a robot-specific control terminal), and an artificial intelligence (AI) model are used. Specifically, the system is configured as follows:

[0466] The server stores the new worker robot's profile information, the details of each work process, robot maintenance procedures, and required skills in a database. For example, the database stores "screw tightening" and "part placement" as work contents for an "assembly process," and stores "torque adjustment" and "part identification" as required skills.

[0467] The new worker robot can use a terminal to input questions about specific operation methods and maintenance procedures in text format and send them to the server. For example, consider the case where the new worker robot inputs and sends the question, "I want to learn how to adjust the torque of a screw."

[0468] The server receives this question and prepares it for transmission to the AI, converting it into the appropriate format. The AI ​​analyzes the question and extracts keywords and important phrases. For example, it extracts the keywords "torque," "adjustment," and "method" and retrieves information from the database about "how to use a torque wrench," "checking the setting value," and "how to tighten a screw."

[0469] The AI ​​then generates appropriate advice based on the information it has acquired. For example, it generates advice such as "Use a torque wrench to set the appropriate torque value, then tighten the screws." The server receives this advice and sends it in an appropriate format to the new worker robot's terminal. Finally, the new worker robot receives and displays the advice from the AI ​​advisor on its terminal.

[0470] It is recommended to use TensorFlow or PyTorch for generative AI models, and spaCy or Transformers for natural language processing, which will enable new worker robots to efficiently acquire the necessary skills and knowledge, saving human resources and reducing work errors.

[0471] For example, if a robot types and sends the question, "What are the steps to replace a motor?", the AI ​​can retrieve relevant information from the database and generate specific advice such as, "First, disconnect the power, then remove the old motor, and install the new motor in the specified way."

[0472] Example prompt sentence:

[0473] Question: I want to learn how to torque screws.

[0474] Q: What is the procedure for replacing the motor?

[0475] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0476] Step 1:

[0477] The server stores the profile information for new workers, the details of each work process, robot maintenance procedures, and required skills in a database. The input is the profile information of the new worker and data related to the work process, and the output is the configuration information stored in the database. Specifically, the server executes SQL queries against the database to insert and update the required information.

[0478] Step 2:

[0479] The new worker uses a terminal to input a question and sends it to the server. The input is the question text of the new worker, and the output is the question data sent to the server. In concrete terms, a text input form is displayed on the terminal, and the new worker inputs a question and presses the "send" button.

[0480] Step 3:

[0481] The server receives questions from new workers and prepares them for sending to the AI ​​model. The input is the question data of the new worker, and the output is the formatted question data to be sent to the AI ​​model. Specifically, the server converts the received text into an appropriate format, such as JSON.

[0482] Step 4:

[0483] The AI ​​analyzes the question and searches for relevant information from a database. The input is a formatted question data, and the output is a dataset containing relevant information. Specifically, the AI ​​uses natural language processing techniques (e.g., spaCy or Transformers) to extract important keywords and execute a search query against the database.

[0484] Step 5:

[0485] The AI ​​generates appropriate advice based on the acquired information. The input is a dataset of search results, and the output is the generated advice text. Specifically, the AI ​​uses a generative AI model (e.g., TensorFlow or PyTorch) to generate advice based on the question.

[0486] Step 6:

[0487] The server receives advice from the AI ​​and converts it into an appropriate format for sending to the new worker's device. The input is advice text, and the output is formatted advice that is displayed on the new worker's device. Specifically, the server converts the advice text into HTML format or similar and sends it to the new worker's device.

[0488] Step 7:

[0489] The new worker's terminal displays the received advice. The input is the formatted advice sent from the server, and the output is the advice text displayed on the screen. Specifically, a web browser or dedicated application installed on the terminal renders and displays the advice text.

[0490] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0491] This invention is a system that combines an emotion engine with a skill-up advisor AI for new employees to support the efficient and emotional acquisition of work skills. Specifically, a server stores new employee profile information, the work content of each department, the characteristics of members, and required skills in a database, and new employees input and send questions using their terminals. The questions are received by the server and sent to the AI, and the emotion engine analyzes the user's emotions. Based on the question and emotion information, the AI ​​searches the database for related information and generates advice. The generated advice is adjusted according to the user's emotions and sent to the new employee's terminal by the server.

[0492] Program processing overview (expressed in natural language)

[0493] 1. Initial setup by the server

[0494] The server stores new employee profile information, the job description of each department, the characteristics of the members, and the required skills in a database. For example, the job description of the "Marketing Department" might include "SNS campaign planning" and "data analysis," and the required skills might include "Excel" and "presentation."

[0495] 2. New employees ask questions

[0496] New employees use their own devices (smartphones or PCs) to access the AI ​​Advisor and log in. For example, new employee A logs in to the AI ​​Advisor from his or her PC.

[0497] 3. Enter and submit your question

[0498] New employees enter specific questions in text format and submit them. For example, new employee A enters and submits, "I would like to learn the basics of data analysis using Excel."

[0499] 4. The server receives the query

[0500] The server receives questions sent by new employees. New employee A's question is, "I want to learn the basics of data analysis using Excel."

[0501] 5. Emotion analysis using an emotion engine

[0502] The server prepares the received question for transmission to the AI, while having the emotion engine analyze the question text to recognize the user's emotions. For example, the emotion engine extracts emotions such as "confusion" or "anxiety" from the question text.

[0503] 6. AI-based analysis and advice generation

[0504] The AI ​​receives the question and sentiment analysis results sent from the server and begins its analysis. It extracts keywords from the question text, such as "Excel," "data analysis," and "basics." It also retrieves related information from the database while reflecting the sentiment information. For example, it searches for and retrieves information related to "basic Excel operations," "use of basic functions," and "data visualization."

[0505] 7. Generating Advice

[0506] Based on the information it acquires, the AI ​​generates optimal advice based on the user's emotions. For example, it generates advice such as "First, learn the basics of Excel, then learn how to use functions, and finally master data visualization techniques." However, if the user is feeling anxious, it will also include additional comments such as "Try not to rush and understand each step at a time."

[0507] 8. Server-Sent Advice

[0508] The server receives the advice provided by the AI ​​and converts it to be sent to the new employee in an appropriate format, for example, converting the advice text into HTML and formatting it as content containing advice based on emotions.

[0509] 9. New employees receive advice

[0510] Advice from an AI advisor is received and displayed on the new employee's device. For example, new employee A receives advice on his / her PC such as, "First, learn the basic operations of Excel, then learn how to use functions, and finally master data visualization techniques. Take your time and understand each step at a time."

[0511] In this way, the present invention supports the efficient acquisition of work skills while taking into consideration the user's feelings, allowing new employees to quickly resolve questions and problems related to their work and accelerating their growth. It also reduces the burden on existing members and makes it possible to provide high-quality support.

[0512] The processing flow will be explained below.

[0513] Step 1:

[0514] The server stores new employee profile information, the job content of each department, the characteristics of members, and the required skills in a database. Specifically, for the marketing department, "SNS campaign planning" and "data analysis" are registered as job content, and "Excel" and "presentation" are stored as required skills.

[0515] Step 2:

[0516] The new employee, who is the user, accesses the AI ​​Advisor using his or her own device (smartphone or PC) and logs in. For example, new employee A logs in to the AI ​​Advisor from his or her PC.

[0517] Step 3:

[0518] Users input questions to the AI ​​advisor in text format and send them. For example, new employee A might input, "I want to learn the basics of data analysis using Excel."

[0519] Step 4:

[0520] The server receives questions sent by users. New employee A's question is, "I want to learn the basics of data analysis using Excel."

[0521] Step 5:

[0522] The server converts the received questions into an appropriate format and sends them to the AI ​​and emotion engine, where the questions are formatted in a form suitable for analysis.

[0523] Step 6:

[0524] The AI ​​receives the question sent from the server and analyzes the question. The AI ​​analyzes the question text and extracts keywords and important phrases. For example, it extracts keywords such as "Excel," "data analysis," and "basics."

[0525] Step 7:

[0526] At the same time, the emotion engine analyzes the user's emotions from the question text. For example, the emotion engine extracts emotions such as "confusion" or "anxiety" from the text.

[0527] Step 8:

[0528] The AI ​​searches the database based on the extracted keywords to retrieve relevant information, for example, information on "basic Excel operations," "use of basic functions," and "data visualization."

[0529] Step 9:

[0530] Based on the information it acquires, the AI ​​generates appropriate advice while reflecting the user's emotions. For example, the AI ​​might generate advice such as "First, learn the basics of Excel, then learn how to use functions, and finally master data visualization techniques," and if the emotion expressed is "confused," it would include an additional comment such as "Try not to rush and understand it one step at a time."

[0531] Step 10:

[0532] The server receives the advice provided by the AI ​​and converts it into a format suitable for the user, for example, converting the advice text into HTML and formatting it according to emotions.

[0533] Step 11:

[0534] The server sends the formatted advice to the new employee's terminal. The advice is sent to new employee A's PC.

[0535] Step 12:

[0536] Users receive and display advice from an AI advisor on their devices. For example, new employee A receives the advice on his PC: "First, learn the basics of Excel, then learn how to use functions, and finally master data visualization techniques. Take your time and understand each step at a time."

[0537] This series of processes allows new employees to efficiently resolve work-related questions and problems and receive support tailored to their emotions. It also reduces the burden on existing members while providing high-quality support.

[0538] Example 2

[0539] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0540] In order for new employees to efficiently acquire work skills, it is necessary to provide prompt and appropriate advice that responds to each employee's feelings. However, current systems have difficulty providing advice that takes the user's feelings into account, and often take a long time to search for information and generate advice. As a result, new employees are unable to quickly resolve their work-related questions or problems, which can slow their growth.

[0541] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a means for storing new employee profile information, the work content of each department, member characteristics, and required skills in a database, a means for the new employee to input and send questions using a terminal, a means for receiving the questions and sending them to an AI, a means for analyzing the user's emotions from the question text, a means for the AI ​​to search the database for related information based on the question and the emotion analysis results, a means for generating advice based on the related information and the user's emotions, and a means for formatting the generated advice and sending it to the new employee's terminal. This enables new employees to quickly resolve questions and problems related to their work and speed up their growth. Furthermore, it reduces the burden on existing members and enables them to provide high-quality support.

[0542] A "new employee" refers to an employee who has just been hired by a company or organization.

[0543] "Profile Information" refers to information that includes details about a user, such as personal information, history, skills and experience, job title and department.

[0544] "Job Description" refers to the scope of work and responsibilities performed in a particular department or position.

[0545] "Member characteristics" refers to the skills, experience, personality, and working style of each employee belonging to a particular department or team.

[0546] "Required skills" refers to the abilities and knowledge required to perform a specific job or position.

[0547] A "database" refers to a collection of information that is structured, stored, and managed so that it can be efficiently searched and retrieved.

[0548] A "terminal" is a device that inputs and receives information, such as a smartphone or personal computer.

[0549] "AI" refers to artificial intelligence, specifically algorithms and models that recognize patterns in questions and data to generate appropriate answers and recommendations.

[0550] "Means for analyzing emotions" refers to technologies and algorithms for extracting and recognizing emotions from text entered by a user.

[0551] "Related information" refers to information searched from a database as content that corresponds to the user's question or feelings.

[0552] "Advice generation means" refers to a process or system for providing optimal advice or guidance based on a user's question.

[0553] The "means for formatting and transmitting" refers to a process for converting the generated advice into a specific format and transmitting it appropriately to the user's terminal.

[0554] The present invention combines an emotion engine with a skill improvement advisory system for new employees to support the acquisition of work skills efficiently and in accordance with emotions. Specific embodiments for carrying out the present invention will be described below.

[0555] The server stores new employee profile information, the job description of each department, the characteristics of each member, and the required skills in a database. Specifically, it connects to the company's human resources system via API and is set up to retrieve profile information in real time. A relational database system such as MongoDB or MySQL is suitable for the database used.

[0556] Users access the AI ​​advisor system using their own devices (smartphones or personal computers). Access is via a browser-based web application, and in many cases single sign-on (SSO) technology is implemented. Once the user logs in, an interface for entering questions is provided.

[0557] When a user enters a specific question in text format and submits it, the device sends the input text to the server as an HTTP request. For example, a user might enter "I want to learn the basics of data analysis using Excel" and press the submit button.

[0558] The server parses the received HTTP request and extracts the text portion. At the same time, metadata such as the user ID and the time of submission is also recorded. This text is then passed to the emotion engine, which uses natural language processing techniques (for example, Python's NLTK library or the Google Cloud Natural Language API) to analyze the user's emotions. Specifically, it detects emotions such as "confusion" or "anxiety" from the text and generates a related score.

[0559] The sentiment analysis results and question content are then sent to an artificial intelligence (AI) system. The AI ​​system uses a generative AI model, such as GPT-4, to extract keywords from the question text and search a database for related information. Specifically, it analyzes keywords such as "Excel," "data analysis," and "basics," and searches for and retrieves information on "basic Excel operations," "using basic functions," and "data visualization."

[0560] Based on the information acquired by the AI, the system generates optimal advice based on the user's emotions. For example, it generates advice that includes specific steps, such as "First, learn basic Excel operations, then learn how to use functions, and finally master data visualization techniques." If the user's emotion is "anxious," the system will add an additional comment such as "Try not to rush and understand each step one by one."

[0561] The server then receives the generated advice, converts it into a format suitable for the user, and sends it to the user. Specifically, the server converts the generated advice text into HTML and formats the advice according to the results of sentiment analysis. This process uses a template engine such as Jinja2.

[0562] Finally, the advice generated on the user's device is received and displayed on the browser. For example, new employee A reads advice on his / her PC such as, "First, learn the basic operations of Excel, then learn how to use functions, and finally master data visualization techniques. Take your time and understand each step at a time."

[0563] (Examples of specific examples and prompts)

[0564] As a concrete example, consider the case where a new employee asks, "I want to know how to give more effective presentations." The emotion engine analyzes emotions such as "nervous." The AI ​​then analyzes keywords such as "presentation," "effective," and "method" and searches for related information. As a result, it generates advice such as "how to create effective slides" and "tips for speaking," and adds comments according to the emotion, such as "It's okay to be nervous, just tackle each step one by one."

[0565] Example prompt sentence:

[0566] "As an AI skill-up advisor for new employees, generate advice that takes emotions into account in response to the following question: 'I want to know how to give presentations more effectively.' Let's say the user is nervous."

[0567] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0568] Step 1:

[0569] The server stores new employee profile information, the work content of each department, the characteristics of members, and required skills in a database. For example, it can be set up to connect to a company's human resources system via API and retrieve profile information in real time. The input is data received from the human resources system, and the output is the information stored in the database. Specifically, each piece of information is structured and stored using a database system such as MongoDB or MySQL.

[0570] Step 2:

[0571] New employees (users) access and log in to the AI ​​advisor system using their own devices (smartphones or personal computers). The input is the new employee's login information (ID and password), and the output is a message indicating whether the login was successful or unsuccessful. Browser-based web applications may use single sign-on (SSO) technology for security reasons.

[0572] Step 3:

[0573] The user enters a specific question in text format through the AI ​​advisor's interface and submits it. The input is the question text entered by the user, and the output is data sent to the server in the form of an HTTP request. For example, the user might enter "I would like to learn the basics of data analysis using Excel" and click the submit button.

[0574] Step 4:

[0575] The server receives the HTTP request sent by the user and analyzes the question. The input is the HTTP request, and the output is the parsed text portion and metadata (user ID, submission time, etc.). If the received data is in JSON format, it performs specific processing to parse and extract the text portion.

[0576] Step 5:

[0577] The server passes the received text to the emotion engine, which then analyzes the user's emotion from the question text. The input is the question text, and the output is the extracted emotion score. Specifically, the engine uses the Python NLTK library and Google Cloud Natural Language API to detect emotions such as "confusion" and "anxiety."

[0578] Step 6:

[0579] The server sends the question text and the sentiment analysis results to the AI ​​system. The input is the question text and sentiment score, and the output is the information search results by the AI ​​system. The AI ​​first extracts keywords and identifies keywords such as "Excel," "data analysis," and "basics." It then uses these keywords to search for related information from a database. The AI ​​model used is a generative AI model such as GPT-4.

[0580] Step 7:

[0581] Based on the searched information, the AI ​​generates advice that corresponds to the user's emotions. The input is the search result information and emotion score, and the output is the generated specific advice. For example, it generates advice such as "First, learn the basic operations of Excel, then learn how to use functions, and finally master data visualization techniques." At this time, it adds comments that correspond to the user's emotions, such as "Try not to rush and understand each step at a time."

[0582] Step 8:

[0583] The server formats the generated advice and sends it to the new employee's device in the appropriate format. The input is the generated advice, and the output is the formatted advice. Specifically, the generated advice text is converted into HTML format and advice based on the sentiment analysis results is included. The formatting process is performed using a template engine such as Jinja2.

[0584] Step 9:

[0585] Advice from the AI ​​advisor is received and displayed on the user's device. The input is formatted advice sent from the server, and the output is the content displayed in the browser. For example, the user reads advice such as, "First, learn the basic operations of Excel, then learn how to use functions, and finally master data visualization techniques. Take your time and understand each step at a time."

[0586] The above is a specific processing flow in the system of the present invention, and the input, data processing, and output at each step are clearly shown.

[0587] (Application example 2)

[0588] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0589] In modern industry, improving the work skills of new employees and troubleshooting industrial automation equipment are important issues that directly affect productivity and efficiency. However, new employees tend to have many questions and anxieties, and automation equipment often causes errors. A system that provides efficient and emotionally sensitive advice and solutions to these issues is needed.

[0590] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for storing profile information, job content, employee characteristics, and required skills in a database, means for new employees or automated equipment to input and send questions or error reports using a terminal, and means for receiving questions or error reports and sending them to the AI. This makes it possible to provide efficient and appropriate advice and countermeasures for the questions, anxieties, and errors that new employees and automated equipment face.

[0591] "New employees" refers to employees who have been newly hired by a company or other organization.

[0592] "Industrial automation equipment" refers to automated machinery and equipment used in factories and production lines.

[0593] "Profile Information" refers to basic attribute information stored about each new employee or automated device.

[0594] "Work station" refers to the location or facility where a particular job or task is performed.

[0595] "Members" refers to employees or workers working at a company or work station.

[0596] "Terminal" refers to a device used to input or output information, such as a smartphone or computer.

[0597] "Questions" refer to sentences or text that express doubts or problems that new employees or automated equipment have.

[0598] "Error reporting" refers to notifications or information sent by automated equipment when it detects a malfunction or problem.

[0599] An "emotion engine" refers to an algorithm or software that analyzes a user's emotional state from input text.

[0600] "Advice" refers to advice or solutions provided in response to questions or error reports.

[0601] "Countermeasures" refer to specific actions or steps to be taken in response to an error or problem.

[0602] To implement this invention, the following interactions between a server, a terminal, and a user are required.

[0603] 1. System Configuration

[0604] 1.1 Server Configuration

[0605] The server stores profile information for new employees and industrial automation equipment in a database, including the work content of each work station, the characteristics of the employees, and the required skills. It also has a means of receiving questions and error reports and sending them to the AI. It also sends advice and countermeasures generated by the AI ​​to new employees and automation equipment.

[0606] 1.2 Terminal configuration

[0607] Terminals are devices used by new employees and automated equipment to input questions and error reports and send them to the server. These terminals include smartphones, PCs, and tablets.

[0608] 1.3 User operations

[0609] New employees, who are users, use terminals to input questions or problems about their daily work in text format and send them to the server. Similarly, automated equipment also reports errors or malfunctions that occur during work to the server.

[0610] 2. Program Processing

[0611] 2.1 Initial Setup

[0612] The server stores profile information for new employees and automated equipment, as well as the job content, characteristics of the employees, and required skills for each work station in a database. For example, "welding metal parts" is registered as the job content for a "welding line," and "welding techniques" and "safe operations" are stored as required skills.

[0613] 2.2 Receiving Questions or Error Reports

[0614] Users, such as new employees and automated equipment, input and send specific questions or error reports in text format from their own devices. For example, a new employee might type and send, "I don't know how to set up the welding machine," or an automated device might report, "There's an insufficient power error."

[0615] 2.3 Analysis by Emotion Engine

[0616] When the server receives a question or error report, it uses an emotion engine to analyze the input text and extract its emotional information before sending it to the AI.

[0617] 2.4 Analysis and advice generation using AI

[0618] Based on the emotional information received from the emotion engine, questions, and error reports, the AI ​​searches the database for relevant data and generates optimal advice and countermeasures. For example, it generates advice that takes into consideration emotions, such as "Try not to rush and understand each step at a time."

[0619] 2.5 Sending Advice

[0620] The server receives the advice and measures generated by the AI ​​and sends them to the user's device in an appropriate format.

[0621] 3. Specific Examples

[0622] Let's consider the case where a new employee asks on their smartphone, "I want to learn the basics of data analysis using Excel." In this case, the emotion engine recognizes emotions such as "confusion" or "anxiety," and based on that information, the AI ​​suggests advice such as, "Start with the basic operations of Excel, then learn how to use functions, and finally master data visualization techniques." If the emotion is "anxiety," the AI ​​also includes an additional comment such as, "Try not to rush and understand it one step at a time."

[0623] Prompt Sentence Examples

[0624] Robot ID: R002

[0625] Question: "My parts are not properly aligned during assembly. What should I do?"

[0626] Emotion: "Anxiety"

[0627] In this way, the system of the present invention is able to provide efficient and empathetic advice and solutions to problems faced by new employees and industrial automation equipment.

[0628] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0629] Step 1: Initial Setup

[0630] The server stores profile information for new employees and automated equipment, the work content of each work station, the characteristics of the employees, and the required skills in a database. The server receives input from the new employee's attribute information, work content, and skill requirements, which it then stores in the database. The output is the appropriately stored profile information and work data. Specific operations include adding and updating records in the database.

[0631] Step 2: Submit a question or error report

[0632] A user, such as a new employee or an automated device, uses a terminal to input and send a specific question or error report in text format. The input is the user's text question or error report. The terminal sends this to the server. The output is the question or error report received by the server. The specific operation is to send data from the terminal to the server.

[0633] Step 3: Receiving a question or error report

[0634] The server receives questions or error reports sent by users. The input is text data sent from the terminal. The server receives this and temporarily stores it in a database. The output is text data prepared for sentiment analysis. Specifically, the server adds the text data to a queue for analysis.

[0635] Step 4: Analysis by the Emotion Engine

[0636] The server sends the received question or error report to the emotion engine, which extracts the user's emotional information. The input is text data stored in a queue. The emotion engine analyzes this and extracts emotions such as "confusion" or "anxiety." The output is data containing the emotional information. Specifically, it uses natural language processing tools to generate emotional information from text.

[0637] Step 5: AI analysis and advice generation

[0638] Based on text data with emotional information added, the AI ​​searches for relevant information from a database and generates optimal advice or countermeasures. The input is text data with emotional information. The AI ​​analyzes this, extracts relevant information from the database, and generates advice or countermeasures that take emotions into consideration. The output is the generated advice or countermeasures. Specifically, the system uses a generative AI model to create advice statements.

[0639] Step 6: Formatting the advice

[0640] The server converts the advice provided by the AI ​​into an appropriate format. The input is the text data of the advice or action generated by the AI. The server formats this into HTML or another appropriate format. The output is the formatted advice or action. Specifically, it runs a script that converts the text data into a different file format.

[0641] Step 7: Submitting Advice

[0642] The server sends formatted advice and measures to the terminals of new employees and automated equipment. The input is the formatted advice and measures. The server sends this to the terminal. The output is the advice and measures displayed on the terminal. The specific operation is data transmission from the server to the terminal.

[0643] Step 8: Receive and view advice

[0644] The terminal receives advice and measures sent from the server and displays them to the user. The input is the advice text sent from the server. The terminal displays this on the screen. The output is the specific advice and measures displayed to the user. The specific operation is to display the received data on the user interface.

[0645] This allows for efficient and empathetic advice and solutions to problems faced by new employees and industrial automation equipment.

[0646] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0647] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0648] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0649] [Third embodiment]

[0650] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0651] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0652] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0653] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0654] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0655] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0656] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0657] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0658] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0659] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0660] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0661] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0662] This invention is a system that uses a skill-up advisor AI for new employees to support the efficient acquisition of work skills. Specifically, a server stores new employee profile information, the work content of each department, the characteristics of members, and required skills in a database, and new employees can input and send questions using their terminals. These questions are received by the server and sent to the AI. The AI ​​analyzes the questions, searches the database for relevant information, and generates advice based on the relevant information. The generated advice is sent by the server to the new employee's terminal.

[0663] Program processing overview (expressed in natural language)

[0664] 1. Initial setup by the server

[0665] The server stores new employee profile information, the job duties of each department, the characteristics of the members, and the required skills in a database. For example, the database might register "SNS campaign planning" and "data analysis" as the job duties of the "Marketing Department," and store "Excel" and "presentation" as required skills.

[0666] 2. New employees ask questions

[0667] New employees access the AI ​​advisor using their own devices (smartphones or PCs). They input specific questions in text format and submit them. For example, New Employee A might input "I would like to learn the basics of data analysis using Excel" and submit the text.

[0668] 3. The server receives the query

[0669] The server receives the new hire's question, prepares it for sending to the AI, and converts it into the appropriate format. The converted question is then passed to the AI ​​module.

[0670] 4. AI analyzes the question and generates advice

[0671] AI analyzes questions and extracts keywords and important phrases. For example, AI extracts keywords such as "Excel," "data analysis," and "basics," and retrieves information from a database about "basic Excel operations," "use of basic functions," and "data visualization." Based on the information retrieved, it generates appropriate advice. For example, the AI ​​generates advice such as, "First, learn basic Excel operations, then learn how to use functions, and finally master data visualization techniques."

[0672] 5. The server sends the advice

[0673] The server receives the advice from the AI, converts it into an appropriate format for sending to the new employee, and then sends it to the new employee's terminal. For example, the server converts the advice text into HTML format and sends it to the PC of new employee A.

[0674] 6. New employees receive advice

[0675] Advice from an AI advisor is received and displayed on the new employee's device. For example, new employee A receives advice on his / her PC such as "First, learn the basic operations of Excel, then learn how to use functions, and finally master data visualization techniques."

[0676] The purpose of this invention is to enable new employees to efficiently resolve questions and problems related to their work and improve their work skills through this series of processes. It also makes it possible to provide high-quality support while reducing the burden on existing members.

[0677] The processing flow will be explained below.

[0678] Step 1:

[0679] The server stores new employee profile information, the job description of each department, the characteristics of the members, and the required skills in a database. Specifically, the Marketing Department stores job descriptions such as "SNS campaign planning" and "data analysis" and the required skills such as "Excel" and "presentation."

[0680] Step 2:

[0681] The new employee, who is the user, accesses the AI ​​Advisor using his or her own device (smartphone or PC) and logs in. For example, new employee A logs in to the AI ​​Advisor from his or her PC.

[0682] Step 3:

[0683] Users input specific questions to the AI ​​advisor in text format and send them. For example, new employee A might input, "I want to learn the basics of data analysis using Excel."

[0684] Step 4:

[0685] The server receives questions sent by users. New employee A's question is, "I want to learn the basics of data analysis using Excel."

[0686] Step 5:

[0687] The server converts the received question into the appropriate format for sending to the AI. After conversion, the question is sent to the AI.

[0688] Step 6:

[0689] The AI ​​receives the question sent from the server and begins analysis. The AI ​​analyzes the question text and extracts keywords and important phrases. Specifically, it extracts the keywords "Excel," "data analysis," and "basics."

[0690] Step 7:

[0691] The AI ​​searches the database based on the extracted keywords to retrieve relevant information, for example, information on "basic Excel operations," "use of basic functions," and "data visualization."

[0692] Step 8:

[0693] Based on the information it acquires, the AI ​​generates optimal advice, such as "First, learn the basics of Excel, then learn how to use functions, and finally master data visualization techniques."

[0694] Step 9:

[0695] The server receives the advice provided by the AI ​​and converts it to send it to the user in an appropriate format, for example, converting the advice text into HTML.

[0696] Step 10:

[0697] The server sends the formatted advice to the new employee's terminal. The advice is sent to new employee A's PC.

[0698] Step 11:

[0699] Users can receive and display advice from the AI ​​advisor on their devices. For example, new employee A receives advice on his PC such as, "First, learn the basics of Excel, then learn how to use functions, and finally master data visualization techniques."

[0700] This series of steps allows new employees to efficiently resolve questions and problems related to their work, accelerating their growth.

[0701] Example 1

[0702] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0703] New employees need appropriate support and advice to efficiently acquire work skills. However, it is difficult for existing members to allocate time to each new employee, which can result in inconsistent quality of instruction. New employees also may not be able to quickly obtain appropriate answers to specific questions about their work, which can reduce their efficiency. To solve these problems, a system is needed that provides immediate and accurate advice to new employees regarding their questions and problems.

[0704] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0705] In this invention, the server includes: means for storing new employee profile information, the work content of each department, member characteristics, and required skills in a database; means for new employees to input and send questions using their terminals; means for receiving questions and converting them into an appropriate format for sending to AI; means for the AI ​​to analyze the questions and extract keywords and important phrases; means for searching the database based on the extracted keywords and important phrases to obtain related information; means for generating advice based on the related information; means for converting the generated advice into an appropriate format such as HTML format and sending it to the new employee's terminal; and means for receiving and displaying the advice on the new employee's terminal. This allows new employees to efficiently acquire work skills and receive high-quality support while reducing the burden on existing members.

[0706] "New employee profile information" is information that indicates the attributes, career history, skills, interests, etc. of each new employee.

[0707] "Business content of each department" is information indicating the specific business, roles, and responsibilities performed in each department within the company.

[0708] "Member characteristics" is information that indicates the personal characteristics of members of each department, such as their experience, skills, and personalities.

[0709] "Required skills" is information that indicates the techniques, knowledge, and abilities required to perform a specific job.

[0710] "Devices" are electronic devices such as computers, smartphones, and tablets used by new employees.

[0711] A "question" is text information that a new employee inputs to resolve a question or problem regarding the improvement of their work skills.

[0712] "AI" refers to programs and systems that use artificial intelligence technology to analyze and provide advice to new employees in response to their questions.

[0713] "Means for converting into a format" refers to the process of converting the received question or generated advice into an appropriate data format (e.g., JSON, HTML).

[0714] "Keywords and important phrases" are important words and phrases related to job skills extracted from the questions.

[0715] A "database" is a system for efficiently storing large amounts of information and making it easy to search and access.

[0716] "Advice" is specific guidance or recommendations generated by the AI ​​based on the new employee's questions.

[0717] This invention is a system that uses a skill-up advisor AI for new employees to support efficient acquisition of work skills. The basic operation of this system is to process information using a server, terminals, and AI modules and provide appropriate advice to new employees.

[0718] Initial Setup

[0719] The server stores new employee profile information, each department's job duties, member characteristics, and required skills in a database. High-performance server machines (such as the Dell PowerEdge series) are used for the hardware, and PostgreSQL is used as the database management system. Specifically, the server stores examples of the marketing department's job duties, such as "social media campaign planning" and "data analysis," and required skills, such as "Excel" and "presentations."

[0720] Enter and submit your question

[0721] New employees access the AI ​​advisor from their own devices (smartphones or PCs) using an internet browser (such as Google Chrome or Safari). For example, new employee A enters a question in text format, such as "I would like to learn the basics of data analysis using Excel," and submits it. This operation is performed using a web form on the user's device.

[0722] Receiving and converting questions

[0723] The server receives questions from new employees and converts them into JSON format to send to the AI. This process relies on a web server using Node.js or Python's Flask. The server receives HTTP requests, analyzes the contents of the request body, converts them into JSON format, and sends them to the AI ​​module.

[0724] Parsing the question and generating advice

[0725] The AI ​​analyzes the question it receives and extracts keywords and important phrases (e.g., "Excel," "data analysis," and "basics"). This process uses natural language processing techniques such as BERT and GPT. The AI ​​searches for related information from a database (e.g., "basic Excel operations," "use of basic functions," and "data visualization") and generates appropriate advice based on that information. For example, the AI ​​might generate advice such as, "First, master the basic operations of Excel, then learn how to use functions, and finally master data visualization techniques."

[0726] Sending Advice

[0727] The server receives the advice from the AI ​​and converts it into an appropriate format, such as HTML, for transmission to the new employee's device. Web server software such as Apache or Nginx is used for transmission.

[0728] Receiving and viewing advice

[0729] New employees receive and display advice from the AI ​​advisor on their own devices. For example, New Employee A displays the advice on his PC, "First, learn the basics of Excel, then learn how to use functions, and finally master data visualization techniques."

[0730] Examples of prompt statements

[0731] Some of the prompts that new employees can enter into their AI advisor include:

[0732] "Please teach me the basics of data analysis using Excel."

[0733] "I want to know the skills required for the marketing department."

[0734] "Please give me some advice on how to improve my presentation skills."

[0735] The system of the present invention allows new employees to efficiently acquire business skills, and allows existing members to receive high-quality support while reducing their burden.

[0736] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0737] Step 1: Server Initialization

[0738] The server stores new employee profile information, the job duties of each department, the characteristics of members, and the required skills in a database. This process uses a high-performance server machine and a database management system such as PostgreSQL. Information such as the new employee's personal attributes and the job duties of each department is received as input, and this information is saved in the database as output.

[0739] Specifically, the server executes SQL commands to initialize the database, create the necessary tables, and insert data.

[0740] Step 2: The new employee types in their question and submits it

[0741] New employees, who are users, access the AI ​​advisor from a web browser on their own devices (smartphones or PCs). They enter specific questions in text format and click the send button to send the question to the server. For example, they enter a question such as, "I would like to learn the basics of data analysis using Excel."

[0742] Specifically, the device displays a web form, and the new employee enters a question in the text box and clicks the "Submit" button.

[0743] Step 3: The server receives the query and performs format conversion.

[0744] The server receives questions from new employees and converts them into an appropriate format, such as JSON, to be sent to the AI. It receives text questions from users as input and generates JSON-formatted question data as output. This processing is done using web server technologies such as Node.js and Flask.

[0745] Specifically, the server receives an HTTP request, analyzes the contents of the request body, converts it into JSON format, and sends it to the AI ​​module.

[0746] Step 4: AI analyzes the question and extracts keywords

[0747] The AI ​​analyzes the questions it receives and extracts keywords and important phrases. It receives question data in JSON format as input and generates a list of extracted keywords and phrases as output. This process uses natural language processing techniques such as BERT and GPT.

[0748] Specifically, the AI ​​uses natural language processing technology to extract keywords and then generates a database search query based on them.

[0749] Step 5: AI searches the database for relevant information

[0750] The AI ​​then searches the database based on the extracted keywords and phrases to retrieve relevant information. As input, it receives a list of keywords and phrases, and as output, it retrieves a dataset containing relevant information. This process uses search techniques using SQL queries.

[0751] Specifically, it executes the search query generated by the AI ​​and retrieves relevant data from the database.

[0752] Step 6: AI generates advice

[0753] The AI ​​generates appropriate advice based on the relevant information it has acquired. It receives relevant information acquired from a database as input and generates written advice as output. This process uses natural language generation technology. For example, it generates advice such as, "First, learn the basic operations of Excel, then learn how to use functions, and finally master data visualization techniques."

[0754] Specifically, the AI ​​constructs sentences based on the information and outputs them as advice.

[0755] Step 7: The server formats and sends the advice

[0756] The server converts the advice received from the AI ​​into an appropriate format (e.g., HTML format) and sends it to the new employee's device. It receives the advice text from the AI ​​as input, generates the converted advice data as output, and sends it to the user's device. This process uses web server software such as Apache or Nginx.

[0757] Specifically, the server converts the advice text into HTML format and sends it as an HTTP response.

[0758] Step 8: New employees receive and view the advice

[0759] The terminal receives advice sent from the server and displays it to the user. It receives advice data in HTML format from the server as input and displays it on the browser as output. For example, it displays advice such as "First, learn the basic operations of Excel, then learn how to use functions, and finally master data visualization techniques."

[0760] Specifically, the terminal receives the HTTP response and displays the advice text in the web browser.

[0761] (Application example 1)

[0762] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0763] Currently, a significant amount of human resources must be expended in the process of quickly and efficiently training new worker robots to acquire the necessary skills and work methods. There are also concerns about errors and reduced efficiency due to insufficient knowledge of work processes and maintenance procedures. As a result, there is an increased risk of a decline in productivity and quality throughout the factory.

[0764] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0765] In this invention, the server includes means for storing profile information for a new worker, details of each work process, robot maintenance procedures, and required skills in a database, means for the new worker to input and send a question using a terminal, means for receiving the question and sending it to the AI, means for the AI ​​to analyze the question and search the database for related information, means for generating advice based on the related information, and means for sending the generated advice to the new worker's terminal. This allows the new worker robot to efficiently acquire the necessary skills and knowledge, saving human resources and reducing work errors.

[0766] "New workers" refer to work robots that have been newly assigned to work sites such as factories.

[0767] "Profile information" refers to data about each new worker, including basic information, characteristics, and history.

[0768] "Work process" is a concept that encompasses the specific work and procedures carried out within a factory.

[0769] "Maintenance procedures" refer to the maintenance and repair methods required for the proper operation of a worker robot.

[0770] "Required skills" refers to the skills and knowledge that new workers must acquire in order to carry out a specific work process.

[0771] A "database" refers to a structured collection of information that is systematically organized and stored, and can be searched and extracted as needed.

[0772] "Terminal" refers to the electronic device used by the new worker to enter and receive information.

[0773] "Questions" refer to specific inquiries about what a new worker wants to learn or a problem they want to solve.

[0774] "AI" refers to artificial intelligence, a technology that generates advice in response to questions through natural language processing and data analysis.

[0775] "Advice" refers to guidelines such as specific steps and learning methods generated by AI based on questions.

[0776] The present invention is a system that uses a new skill-up advisor AI for worker robots to support efficient work skill acquisition. To implement this invention, a cloud server, a database, a terminal (a tablet, a smartphone, or a robot-specific control terminal), and an artificial intelligence (AI) model are used. Specifically, the system is configured as follows:

[0777] The server stores the new worker robot's profile information, the details of each work process, robot maintenance procedures, and required skills in a database. For example, the database stores "screw tightening" and "part placement" as work contents for an "assembly process," and stores "torque adjustment" and "part identification" as required skills.

[0778] The new worker robot can use a terminal to input questions about specific operation methods and maintenance procedures in text format and send them to the server. For example, consider the case where the new worker robot inputs and sends the question, "I want to learn how to adjust the torque of a screw."

[0779] The server receives this question and prepares it for transmission to the AI, converting it into the appropriate format. The AI ​​analyzes the question and extracts keywords and important phrases. For example, it extracts the keywords "torque," "adjustment," and "method" and retrieves information from the database about "how to use a torque wrench," "checking the setting value," and "how to tighten a screw."

[0780] The AI ​​then generates appropriate advice based on the information it has acquired. For example, it generates advice such as "Use a torque wrench to set the appropriate torque value, then tighten the screws." The server receives this advice and sends it in an appropriate format to the new worker robot's terminal. Finally, the new worker robot receives and displays the advice from the AI ​​advisor on its terminal.

[0781] It is recommended to use TensorFlow or PyTorch for generative AI models, and spaCy or Transformers for natural language processing, which will enable new worker robots to efficiently acquire the necessary skills and knowledge, saving human resources and reducing work errors.

[0782] For example, if a robot types and sends the question, "What are the steps to replace a motor?", the AI ​​can retrieve relevant information from the database and generate specific advice such as, "First, disconnect the power, then remove the old motor, and install the new motor in the specified way."

[0783] Example prompt sentence:

[0784] Question: I want to learn how to torque screws.

[0785] Q: What is the procedure for replacing the motor?

[0786] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0787] Step 1:

[0788] The server stores the profile information for new workers, the details of each work process, robot maintenance procedures, and required skills in a database. The input is the profile information of the new worker and data related to the work process, and the output is the configuration information stored in the database. Specifically, the server executes SQL queries against the database to insert and update the required information.

[0789] Step 2:

[0790] The new worker uses a terminal to input a question and sends it to the server. The input is the question text of the new worker, and the output is the question data sent to the server. In concrete terms, a text input form is displayed on the terminal, and the new worker inputs a question and presses the "send" button.

[0791] Step 3:

[0792] The server receives questions from new workers and prepares them for sending to the AI ​​model. The input is the question data of the new worker, and the output is the formatted question data to be sent to the AI ​​model. Specifically, the server converts the received text into an appropriate format, such as JSON.

[0793] Step 4:

[0794] The AI ​​analyzes the question and searches for relevant information from a database. The input is a formatted question data, and the output is a dataset containing relevant information. Specifically, the AI ​​uses natural language processing techniques (e.g., spaCy or Transformers) to extract important keywords and execute a search query against the database.

[0795] Step 5:

[0796] The AI ​​generates appropriate advice based on the acquired information. The input is a dataset of search results, and the output is the generated advice text. Specifically, the AI ​​uses a generative AI model (e.g., TensorFlow or PyTorch) to generate advice based on the question.

[0797] Step 6:

[0798] The server receives advice from the AI ​​and converts it into an appropriate format for sending to the new worker's device. The input is advice text, and the output is formatted advice that is displayed on the new worker's device. Specifically, the server converts the advice text into HTML format or similar and sends it to the new worker's device.

[0799] Step 7:

[0800] The new worker's terminal displays the received advice. The input is the formatted advice sent from the server, and the output is the advice text displayed on the screen. Specifically, a web browser or dedicated application installed on the terminal renders and displays the advice text.

[0801] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0802] This invention is a system that combines an emotion engine with a skill-up advisor AI for new employees to support the efficient and emotional acquisition of work skills. Specifically, a server stores new employee profile information, the work content of each department, the characteristics of members, and required skills in a database, and new employees input and send questions using their terminals. The questions are received by the server and sent to the AI, and the emotion engine analyzes the user's emotions. Based on the question and emotion information, the AI ​​searches the database for related information and generates advice. The generated advice is adjusted according to the user's emotions and sent to the new employee's terminal by the server.

[0803] Program processing overview (expressed in natural language)

[0804] 1. Initial setup by the server

[0805] The server stores new employee profile information, the job description of each department, the characteristics of the members, and the required skills in a database. For example, the job description of the "Marketing Department" might include "SNS campaign planning" and "data analysis," and the required skills might include "Excel" and "presentation."

[0806] 2. New employees ask questions

[0807] New employees use their own devices (smartphones or PCs) to access the AI ​​Advisor and log in. For example, new employee A logs in to the AI ​​Advisor from his or her PC.

[0808] 3. Enter and submit your question

[0809] New employees enter specific questions in text format and submit them. For example, new employee A enters and submits, "I would like to learn the basics of data analysis using Excel."

[0810] 4. The server receives the query

[0811] The server receives questions sent by new employees. New employee A's question is, "I want to learn the basics of data analysis using Excel."

[0812] 5. Emotion analysis using an emotion engine

[0813] The server prepares the received question for transmission to the AI, while having the emotion engine analyze the question text to recognize the user's emotions. For example, the emotion engine extracts emotions such as "confusion" or "anxiety" from the question text.

[0814] 6. AI-based analysis and advice generation

[0815] The AI ​​receives the question and sentiment analysis results sent from the server and begins its analysis. It extracts keywords from the question text, such as "Excel," "data analysis," and "basics." It also retrieves related information from the database while reflecting the sentiment information. For example, it searches for and retrieves information related to "basic Excel operations," "use of basic functions," and "data visualization."

[0816] 7. Generating Advice

[0817] Based on the information it acquires, the AI ​​generates optimal advice based on the user's emotions. For example, it generates advice such as "First, learn the basics of Excel, then learn how to use functions, and finally master data visualization techniques." However, if the user is feeling anxious, it will also include additional comments such as "Try not to rush and understand each step at a time."

[0818] 8. Server-Sent Advice

[0819] The server receives the advice provided by the AI ​​and converts it to be sent to the new employee in an appropriate format, for example, converting the advice text into HTML and formatting it as content containing advice based on emotions.

[0820] 9. New employees receive advice

[0821] Advice from an AI advisor is received and displayed on the new employee's device. For example, new employee A receives advice on his / her PC such as, "First, learn the basic operations of Excel, then learn how to use functions, and finally master data visualization techniques. Take your time and understand each step at a time."

[0822] In this way, the present invention supports the efficient acquisition of work skills while taking into consideration the user's feelings, allowing new employees to quickly resolve questions and problems related to their work and accelerating their growth. It also reduces the burden on existing members and makes it possible to provide high-quality support.

[0823] The processing flow will be explained below.

[0824] Step 1:

[0825] The server stores new employee profile information, the job content of each department, the characteristics of members, and the required skills in a database. Specifically, for the marketing department, "SNS campaign planning" and "data analysis" are registered as job content, and "Excel" and "presentation" are stored as required skills.

[0826] Step 2:

[0827] The new employee, who is the user, accesses the AI ​​Advisor using his or her own device (smartphone or PC) and logs in. For example, new employee A logs in to the AI ​​Advisor from his or her PC.

[0828] Step 3:

[0829] Users input questions to the AI ​​advisor in text format and send them. For example, new employee A might input, "I want to learn the basics of data analysis using Excel."

[0830] Step 4:

[0831] The server receives questions sent by users. New employee A's question is, "I want to learn the basics of data analysis using Excel."

[0832] Step 5:

[0833] The server converts the received questions into an appropriate format and sends them to the AI ​​and emotion engine, where the questions are formatted in a form suitable for analysis.

[0834] Step 6:

[0835] The AI ​​receives the question sent from the server and analyzes the question. The AI ​​analyzes the question text and extracts keywords and important phrases. For example, it extracts keywords such as "Excel," "data analysis," and "basics."

[0836] Step 7:

[0837] At the same time, the emotion engine analyzes the user's emotions from the question text. For example, the emotion engine extracts emotions such as "confusion" or "anxiety" from the text.

[0838] Step 8:

[0839] The AI ​​searches the database based on the extracted keywords to retrieve relevant information, for example, information on "basic Excel operations," "use of basic functions," and "data visualization."

[0840] Step 9:

[0841] Based on the information it acquires, the AI ​​generates appropriate advice while reflecting the user's emotions. For example, the AI ​​might generate advice such as "First, learn the basics of Excel, then learn how to use functions, and finally master data visualization techniques," and if the emotion expressed is "confused," it would include an additional comment such as "Try not to rush and understand it one step at a time."

[0842] Step 10:

[0843] The server receives the advice provided by the AI ​​and converts it into a format suitable for the user, for example, converting the advice text into HTML and formatting it according to emotions.

[0844] Step 11:

[0845] The server sends the formatted advice to the new employee's terminal. The advice is sent to new employee A's PC.

[0846] Step 12:

[0847] Users receive and display advice from an AI advisor on their devices. For example, new employee A receives the advice on his PC: "First, learn the basics of Excel, then learn how to use functions, and finally master data visualization techniques. Take your time and understand each step at a time."

[0848] This series of processes allows new employees to efficiently resolve work-related questions and problems and receive support tailored to their emotions. It also reduces the burden on existing members while providing high-quality support.

[0849] Example 2

[0850] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0851] In order for new employees to efficiently acquire work skills, it is necessary to provide prompt and appropriate advice that responds to each employee's feelings. However, current systems have difficulty providing advice that takes the user's feelings into account, and often take a long time to search for information and generate advice. As a result, new employees are unable to quickly resolve their work-related questions or problems, which can slow their growth.

[0852] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a means for storing new employee profile information, the work content of each department, member characteristics, and required skills in a database, a means for the new employee to input and send questions using a terminal, a means for receiving the questions and sending them to an AI, a means for analyzing the user's emotions from the question text, a means for the AI ​​to search the database for related information based on the question and the emotion analysis results, a means for generating advice based on the related information and the user's emotions, and a means for formatting the generated advice and sending it to the new employee's terminal. This enables new employees to quickly resolve questions and problems related to their work and speed up their growth. Furthermore, it reduces the burden on existing members and enables them to provide high-quality support.

[0853] A "new employee" refers to an employee who has just been hired by a company or organization.

[0854] "Profile Information" refers to information that includes details about a user, such as personal information, history, skills and experience, job title and department.

[0855] "Job Description" refers to the scope of work and responsibilities performed in a particular department or position.

[0856] "Member characteristics" refers to the skills, experience, personality, and working style of each employee belonging to a particular department or team.

[0857] "Required skills" refers to the abilities and knowledge required to perform a specific job or position.

[0858] A "database" refers to a collection of information that is structured, stored, and managed so that it can be efficiently searched and retrieved.

[0859] A "terminal" is a device that inputs and receives information, such as a smartphone or personal computer.

[0860] "AI" refers to artificial intelligence, specifically algorithms and models that recognize patterns in questions and data to generate appropriate answers and recommendations.

[0861] "Means for analyzing emotions" refers to technologies and algorithms for extracting and recognizing emotions from text entered by a user.

[0862] "Related information" refers to information searched from a database as content that corresponds to the user's question or feelings.

[0863] "Advice generation means" refers to a process or system for providing optimal advice or guidance based on a user's question.

[0864] The "means for formatting and transmitting" refers to a process for converting the generated advice into a specific format and transmitting it appropriately to the user's terminal.

[0865] The present invention combines an emotion engine with a skill improvement advisory system for new employees to support the acquisition of work skills efficiently and in accordance with emotions. Specific embodiments for carrying out the present invention will be described below.

[0866] The server stores new employee profile information, the job description of each department, the characteristics of each member, and the required skills in a database. Specifically, it connects to the company's human resources system via API and is set up to retrieve profile information in real time. A relational database system such as MongoDB or MySQL is suitable for the database used.

[0867] Users access the AI ​​advisor system using their own devices (smartphones or personal computers). Access is via a browser-based web application, and in many cases single sign-on (SSO) technology is implemented. Once the user logs in, an interface for entering questions is provided.

[0868] When a user enters a specific question in text format and submits it, the device sends the input text to the server as an HTTP request. For example, a user might enter "I want to learn the basics of data analysis using Excel" and press the submit button.

[0869] The server parses the received HTTP request and extracts the text portion. At the same time, metadata such as the user ID and the time of submission is also recorded. This text is then passed to the emotion engine, which uses natural language processing techniques (for example, Python's NLTK library or the Google Cloud Natural Language API) to analyze the user's emotions. Specifically, it detects emotions such as "confusion" or "anxiety" from the text and generates a related score.

[0870] The sentiment analysis results and question content are then sent to an artificial intelligence (AI) system. The AI ​​system uses a generative AI model, such as GPT-4, to extract keywords from the question text and search a database for related information. Specifically, it analyzes keywords such as "Excel," "data analysis," and "basics," and searches for and retrieves information on "basic Excel operations," "using basic functions," and "data visualization."

[0871] Based on the information acquired by the AI, the system generates optimal advice based on the user's emotions. For example, it generates advice that includes specific steps, such as "First, learn basic Excel operations, then learn how to use functions, and finally master data visualization techniques." If the user's emotion is "anxious," the system will add an additional comment such as "Try not to rush and understand each step one by one."

[0872] The server then receives the generated advice, converts it into a format suitable for the user, and sends it to the user. Specifically, the server converts the generated advice text into HTML and formats the advice according to the results of sentiment analysis. This process uses a template engine such as Jinja2.

[0873] Finally, the advice generated on the user's device is received and displayed on the browser. For example, new employee A reads advice on his / her PC such as, "First, learn the basic operations of Excel, then learn how to use functions, and finally master data visualization techniques. Take your time and understand each step at a time."

[0874] (Examples of specific examples and prompts)

[0875] As a concrete example, consider the case where a new employee asks, "I want to know how to give more effective presentations." The emotion engine analyzes emotions such as "nervous." The AI ​​then analyzes keywords such as "presentation," "effective," and "method" and searches for related information. As a result, it generates advice such as "how to create effective slides" and "tips for speaking," and adds comments according to the emotion, such as "It's okay to be nervous, just tackle each step one by one."

[0876] Example prompt sentence:

[0877] "As an AI skill-up advisor for new employees, generate advice that takes emotions into account in response to the following question: 'I want to know how to give presentations more effectively.' Let's say the user is nervous."

[0878] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0879] Step 1:

[0880] The server stores new employee profile information, the work content of each department, the characteristics of members, and required skills in a database. For example, it can be set up to connect to a company's human resources system via API and retrieve profile information in real time. The input is data received from the human resources system, and the output is the information stored in the database. Specifically, each piece of information is structured and stored using a database system such as MongoDB or MySQL.

[0881] Step 2:

[0882] New employees (users) access and log in to the AI ​​advisor system using their own devices (smartphones or personal computers). The input is the new employee's login information (ID and password), and the output is a message indicating whether the login was successful or unsuccessful. Browser-based web applications may use single sign-on (SSO) technology for security reasons.

[0883] Step 3:

[0884] The user enters a specific question in text format through the AI ​​advisor's interface and submits it. The input is the question text entered by the user, and the output is data sent to the server in the form of an HTTP request. For example, the user might enter "I would like to learn the basics of data analysis using Excel" and click the submit button.

[0885] Step 4:

[0886] The server receives the HTTP request sent by the user and analyzes the question. The input is the HTTP request, and the output is the parsed text portion and metadata (user ID, submission time, etc.). If the received data is in JSON format, it performs specific processing to parse and extract the text portion.

[0887] Step 5:

[0888] The server passes the received text to the emotion engine, which then analyzes the user's emotion from the question text. The input is the question text, and the output is the extracted emotion score. Specifically, the engine uses the Python NLTK library and Google Cloud Natural Language API to detect emotions such as "confusion" and "anxiety."

[0889] Step 6:

[0890] The server sends the question text and the sentiment analysis results to the AI ​​system. The input is the question text and sentiment score, and the output is the information search results by the AI ​​system. The AI ​​first extracts keywords and identifies keywords such as "Excel," "data analysis," and "basics." It then uses these keywords to search for related information from a database. The AI ​​model used is a generative AI model such as GPT-4.

[0891] Step 7:

[0892] Based on the searched information, the AI ​​generates advice that corresponds to the user's emotions. The input is the search result information and emotion score, and the output is the generated specific advice. For example, it generates advice such as "First, learn the basic operations of Excel, then learn how to use functions, and finally master data visualization techniques." At this time, it adds comments that correspond to the user's emotions, such as "Try not to rush and understand each step at a time."

[0893] Step 8:

[0894] The server formats the generated advice and sends it to the new employee's device in the appropriate format. The input is the generated advice, and the output is the formatted advice. Specifically, the generated advice text is converted into HTML format and advice based on the sentiment analysis results is included. The formatting process is performed using a template engine such as Jinja2.

[0895] Step 9:

[0896] Advice from the AI ​​advisor is received and displayed on the user's device. The input is formatted advice sent from the server, and the output is the content displayed in the browser. For example, the user reads advice such as, "First, learn the basic operations of Excel, then learn how to use functions, and finally master data visualization techniques. Take your time and understand each step at a time."

[0897] The above is a specific processing flow in the system of the present invention, and the input, data processing, and output at each step are clearly shown.

[0898] (Application example 2)

[0899] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0900] In modern industry, improving the work skills of new employees and troubleshooting industrial automation equipment are important issues that directly affect productivity and efficiency. However, new employees tend to have many questions and anxieties, and automation equipment often causes errors. A system that provides efficient and emotionally sensitive advice and solutions to these issues is needed.

[0901] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for storing profile information, job content, employee characteristics, and required skills in a database, means for new employees or automated equipment to input and send questions or error reports using a terminal, and means for receiving questions or error reports and sending them to the AI. This makes it possible to provide efficient and appropriate advice and countermeasures for the questions, anxieties, and errors that new employees and automated equipment face.

[0902] "New employees" refers to employees who have been newly hired by a company or other organization.

[0903] "Industrial automation equipment" refers to automated machinery and equipment used in factories and production lines.

[0904] "Profile Information" refers to basic attribute information stored about each new employee or automated device.

[0905] "Work station" refers to the location or facility where a particular job or task is performed.

[0906] "Members" refers to employees or workers working at a company or work station.

[0907] "Terminal" refers to a device used to input or output information, such as a smartphone or computer.

[0908] "Questions" refer to sentences or text that express doubts or problems that new employees or automated equipment have.

[0909] "Error reporting" refers to notifications or information sent by automated equipment when it detects a malfunction or problem.

[0910] An "emotion engine" refers to an algorithm or software that analyzes a user's emotional state from input text.

[0911] "Advice" refers to advice or solutions provided in response to questions or error reports.

[0912] "Countermeasures" refer to specific actions or steps to be taken in response to an error or problem.

[0913] To implement this invention, the following interactions between a server, a terminal, and a user are required.

[0914] 1. System Configuration

[0915] 1.1 Server Configuration

[0916] The server stores profile information for new employees and industrial automation equipment in a database, including the work content of each work station, the characteristics of the employees, and the required skills. It also has a means of receiving questions and error reports and sending them to the AI. It also sends advice and countermeasures generated by the AI ​​to new employees and automation equipment.

[0917] 1.2 Terminal configuration

[0918] Terminals are devices used by new employees and automated equipment to input questions and error reports and send them to the server. These terminals include smartphones, PCs, and tablets.

[0919] 1.3 User operations

[0920] New employees, who are users, use terminals to input questions or problems about their daily work in text format and send them to the server. Similarly, automated equipment also reports errors or malfunctions that occur during work to the server.

[0921] 2. Program Processing

[0922] 2.1 Initial Setup

[0923] The server stores profile information for new employees and automated equipment, as well as the job content, characteristics of the employees, and required skills for each work station in a database. For example, "welding metal parts" is registered as the job content for a "welding line," and "welding techniques" and "safe operations" are stored as required skills.

[0924] 2.2 Receiving Questions or Error Reports

[0925] Users, such as new employees and automated equipment, input and send specific questions or error reports in text format from their own devices. For example, a new employee might type and send, "I don't know how to set up the welding machine," or an automated device might report, "There's an insufficient power error."

[0926] 2.3 Analysis by Emotion Engine

[0927] When the server receives a question or error report, it uses an emotion engine to analyze the input text and extract its emotional information before sending it to the AI.

[0928] 2.4 Analysis and advice generation using AI

[0929] Based on the emotional information received from the emotion engine, questions, and error reports, the AI ​​searches the database for relevant data and generates optimal advice and countermeasures. For example, it generates advice that takes into consideration emotions, such as "Try not to rush and understand each step at a time."

[0930] 2.5 Sending Advice

[0931] The server receives the advice and measures generated by the AI ​​and sends them to the user's device in an appropriate format.

[0932] 3. Specific Examples

[0933] Let's consider the case where a new employee asks on their smartphone, "I want to learn the basics of data analysis using Excel." In this case, the emotion engine recognizes emotions such as "confusion" or "anxiety," and based on that information, the AI ​​suggests advice such as, "Start with the basic operations of Excel, then learn how to use functions, and finally master data visualization techniques." If the emotion is "anxiety," the AI ​​also includes an additional comment such as, "Try not to rush and understand it one step at a time."

[0934] Prompt Sentence Examples

[0935] Robot ID: R002

[0936] Question: "My parts are not properly aligned during assembly. What should I do?"

[0937] Emotion: "Anxiety"

[0938] In this way, the system of the present invention is able to provide efficient and empathetic advice and solutions to problems faced by new employees and industrial automation equipment.

[0939] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0940] Step 1: Initial Setup

[0941] The server stores profile information for new employees and automated equipment, the work content of each work station, the characteristics of the employees, and the required skills in a database. The server receives input from the new employee's attribute information, work content, and skill requirements, which it then stores in the database. The output is the appropriately stored profile information and work data. Specific operations include adding and updating records in the database.

[0942] Step 2: Submit a question or error report

[0943] A user, such as a new employee or an automated device, uses a terminal to input and send a specific question or error report in text format. The input is the user's text question or error report. The terminal sends this to the server. The output is the question or error report received by the server. The specific operation is to send data from the terminal to the server.

[0944] Step 3: Receiving a question or error report

[0945] The server receives questions or error reports sent by users. The input is text data sent from the terminal. The server receives this and temporarily stores it in a database. The output is text data prepared for sentiment analysis. Specifically, the server adds the text data to a queue for analysis.

[0946] Step 4: Analysis by the Emotion Engine

[0947] The server sends the received question or error report to the emotion engine, which extracts the user's emotional information. The input is text data stored in a queue. The emotion engine analyzes this and extracts emotions such as "confusion" or "anxiety." The output is data containing the emotional information. Specifically, it uses natural language processing tools to generate emotional information from text.

[0948] Step 5: AI analysis and advice generation

[0949] Based on text data with emotional information added, the AI ​​searches for relevant information from a database and generates optimal advice or countermeasures. The input is text data with emotional information. The AI ​​analyzes this, extracts relevant information from the database, and generates advice or countermeasures that take emotions into consideration. The output is the generated advice or countermeasures. Specifically, the system uses a generative AI model to create advice statements.

[0950] Step 6: Formatting the advice

[0951] The server converts the advice provided by the AI ​​into an appropriate format. The input is the text data of the advice or action generated by the AI. The server formats this into HTML or another appropriate format. The output is the formatted advice or action. Specifically, it runs a script that converts the text data into a different file format.

[0952] Step 7: Submitting Advice

[0953] The server sends formatted advice and measures to the terminals of new employees and automated equipment. The input is the formatted advice and measures. The server sends this to the terminal. The output is the advice and measures displayed on the terminal. The specific operation is data transmission from the server to the terminal.

[0954] Step 8: Receive and view advice

[0955] The terminal receives advice and measures sent from the server and displays them to the user. The input is the advice text sent from the server. The terminal displays this on the screen. The output is the specific advice and measures displayed to the user. The specific operation is to display the received data on the user interface.

[0956] This allows for efficient and empathetic advice and solutions to problems faced by new employees and industrial automation equipment.

[0957] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0958] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0959] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[0960] [Fourth embodiment]

[0961] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0962] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0963] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0964] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[0965] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0966] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0967] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0968] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[0969] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0970] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0971] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0972] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0973] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[0974] This invention is a system that uses a skill-up advisor AI for new employees to support the efficient acquisition of work skills. Specifically, a server stores new employee profile information, the work content of each department, the characteristics of members, and required skills in a database, and new employees can input and send questions using their terminals. These questions are received by the server and sent to the AI. The AI ​​analyzes the questions, searches the database for relevant information, and generates advice based on the relevant information. The generated advice is sent by the server to the new employee's terminal.

[0975] Program processing overview (expressed in natural language)

[0976] 1. Initial setup by the server

[0977] The server stores new employee profile information, the job duties of each department, the characteristics of the members, and the required skills in a database. For example, the database might register "SNS campaign planning" and "data analysis" as the job duties of the "Marketing Department," and store "Excel" and "presentation" as required skills.

[0978] 2. New employees ask questions

[0979] New employees access the AI ​​advisor using their own devices (smartphones or PCs). They input specific questions in text format and submit them. For example, New Employee A might input "I would like to learn the basics of data analysis using Excel" and submit the text.

[0980] 3. The server receives the query

[0981] The server receives the new hire's question, prepares it for sending to the AI, and converts it into the appropriate format. The converted question is then passed to the AI ​​module.

[0982] 4. AI analyzes the question and generates advice

[0983] AI analyzes questions and extracts keywords and important phrases. For example, AI extracts keywords such as "Excel," "data analysis," and "basics," and retrieves information from a database about "basic Excel operations," "use of basic functions," and "data visualization." Based on the information retrieved, it generates appropriate advice. For example, the AI ​​generates advice such as, "First, learn basic Excel operations, then learn how to use functions, and finally master data visualization techniques."

[0984] 5. The server sends the advice

[0985] The server receives the advice from the AI, converts it into an appropriate format for sending to the new employee, and then sends it to the new employee's terminal. For example, the server converts the advice text into HTML format and sends it to the PC of new employee A.

[0986] 6. New employees receive advice

[0987] Advice from an AI advisor is received and displayed on the new employee's device. For example, new employee A receives advice on his / her PC such as "First, learn the basic operations of Excel, then learn how to use functions, and finally master data visualization techniques."

[0988] The purpose of this invention is to enable new employees to efficiently resolve questions and problems related to their work and improve their work skills through this series of processes. It also makes it possible to provide high-quality support while reducing the burden on existing members.

[0989] The processing flow will be explained below.

[0990] Step 1:

[0991] The server stores new employee profile information, the job description of each department, the characteristics of the members, and the required skills in a database. Specifically, the Marketing Department stores job descriptions such as "SNS campaign planning" and "data analysis" and the required skills such as "Excel" and "presentation."

[0992] Step 2:

[0993] The new employee, who is the user, accesses the AI ​​Advisor using his or her own device (smartphone or PC) and logs in. For example, new employee A logs in to the AI ​​Advisor from his or her PC.

[0994] Step 3:

[0995] Users input specific questions to the AI ​​advisor in text format and send them. For example, new employee A might input, "I want to learn the basics of data analysis using Excel."

[0996] Step 4:

[0997] The server receives questions sent by users. New employee A's question is, "I want to learn the basics of data analysis using Excel."

[0998] Step 5:

[0999] The server converts the received question into the appropriate format for sending to the AI. After conversion, the question is sent to the AI.

[1000] Step 6:

[1001] The AI ​​receives the question sent from the server and begins analysis. The AI ​​analyzes the question text and extracts keywords and important phrases. Specifically, it extracts the keywords "Excel," "data analysis," and "basics."

[1002] Step 7:

[1003] The AI ​​searches the database based on the extracted keywords to retrieve relevant information, for example, information on "basic Excel operations," "use of basic functions," and "data visualization."

[1004] Step 8:

[1005] Based on the information it acquires, the AI ​​generates optimal advice, such as "First, learn the basics of Excel, then learn how to use functions, and finally master data visualization techniques."

[1006] Step 9:

[1007] The server receives the advice provided by the AI ​​and converts it to send it to the user in an appropriate format, for example, converting the advice text into HTML.

[1008] Step 10:

[1009] The server sends the formatted advice to the new employee's terminal. The advice is sent to new employee A's PC.

[1010] Step 11:

[1011] Users can receive and display advice from the AI ​​advisor on their devices. For example, new employee A receives advice on his PC such as, "First, learn the basics of Excel, then learn how to use functions, and finally master data visualization techniques."

[1012] This series of steps allows new employees to efficiently resolve questions and problems related to their work, accelerating their growth.

[1013] Example 1

[1014] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1015] New employees need appropriate support and advice to efficiently acquire work skills. However, it is difficult for existing members to allocate time to each new employee, which can result in inconsistent quality of instruction. New employees also may not be able to quickly obtain appropriate answers to specific questions about their work, which can reduce their efficiency. To solve these problems, a system is needed that provides immediate and accurate advice to new employees regarding their questions and problems.

[1016] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1017] In this invention, the server includes: means for storing new employee profile information, the work content of each department, member characteristics, and required skills in a database; means for new employees to input and send questions using their terminals; means for receiving questions and converting them into an appropriate format for sending to AI; means for the AI ​​to analyze the questions and extract keywords and important phrases; means for searching the database based on the extracted keywords and important phrases to obtain related information; means for generating advice based on the related information; means for converting the generated advice into an appropriate format such as HTML format and sending it to the new employee's terminal; and means for receiving and displaying the advice on the new employee's terminal. This allows new employees to efficiently acquire work skills and receive high-quality support while reducing the burden on existing members.

[1018] "New employee profile information" is information that indicates the attributes, career history, skills, interests, etc. of each new employee.

[1019] "Business content of each department" is information indicating the specific business, roles, and responsibilities performed in each department within the company.

[1020] "Member characteristics" is information that indicates the personal characteristics of members of each department, such as their experience, skills, and personalities.

[1021] "Required skills" is information that indicates the techniques, knowledge, and abilities required to perform a specific job.

[1022] "Devices" are electronic devices such as computers, smartphones, and tablets used by new employees.

[1023] A "question" is text information that a new employee inputs to resolve a question or problem regarding the improvement of their work skills.

[1024] "AI" refers to programs and systems that use artificial intelligence technology to analyze and provide advice to new employees in response to their questions.

[1025] "Means for converting into a format" refers to the process of converting the received question or generated advice into an appropriate data format (e.g., JSON, HTML).

[1026] "Keywords and important phrases" are important words and phrases related to job skills extracted from the questions.

[1027] A "database" is a system for efficiently storing large amounts of information and making it easy to search and access.

[1028] "Advice" is specific guidance or recommendations generated by the AI ​​based on the new employee's questions.

[1029] This invention is a system that uses a skill-up advisor AI for new employees to support efficient acquisition of work skills. The basic operation of this system is to process information using a server, terminals, and AI modules and provide appropriate advice to new employees.

[1030] Initial Setup

[1031] The server stores new employee profile information, each department's job duties, member characteristics, and required skills in a database. High-performance server machines (such as the Dell PowerEdge series) are used for the hardware, and PostgreSQL is used as the database management system. Specifically, the server stores examples of the marketing department's job duties, such as "social media campaign planning" and "data analysis," and required skills, such as "Excel" and "presentations."

[1032] Enter and submit your question

[1033] New employees access the AI ​​advisor from their own devices (smartphones or PCs) using an internet browser (such as Google Chrome or Safari). For example, new employee A enters a question in text format, such as "I would like to learn the basics of data analysis using Excel," and submits it. This operation is performed using a web form on the user's device.

[1034] Receiving and converting questions

[1035] The server receives questions from new employees and converts them into JSON format to send to the AI. This process relies on a web server using Node.js or Python's Flask. The server receives HTTP requests, analyzes the contents of the request body, converts them into JSON format, and sends them to the AI ​​module.

[1036] Parsing the question and generating advice

[1037] The AI ​​analyzes the question it receives and extracts keywords and important phrases (e.g., "Excel," "data analysis," and "basics"). This process uses natural language processing techniques such as BERT and GPT. The AI ​​searches for related information from a database (e.g., "basic Excel operations," "use of basic functions," and "data visualization") and generates appropriate advice based on that information. For example, the AI ​​might generate advice such as, "First, master the basic operations of Excel, then learn how to use functions, and finally master data visualization techniques."

[1038] Sending Advice

[1039] The server receives the advice from the AI ​​and converts it into an appropriate format, such as HTML, for transmission to the new employee's device. Web server software such as Apache or Nginx is used for transmission.

[1040] Receiving and viewing advice

[1041] New employees receive and display advice from the AI ​​advisor on their own devices. For example, New Employee A displays the advice on his PC, "First, learn the basics of Excel, then learn how to use functions, and finally master data visualization techniques."

[1042] Examples of prompt statements

[1043] Some of the prompts that new employees can enter into their AI advisor include:

[1044] "Please teach me the basics of data analysis using Excel."

[1045] "I want to know the skills required for the marketing department."

[1046] "Please give me some advice on how to improve my presentation skills."

[1047] The system of the present invention allows new employees to efficiently acquire business skills, and allows existing members to receive high-quality support while reducing their burden.

[1048] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1049] Step 1: Server Initialization

[1050] The server stores new employee profile information, the job duties of each department, the characteristics of members, and the required skills in a database. This process uses a high-performance server machine and a database management system such as PostgreSQL. Information such as the new employee's personal attributes and the job duties of each department is received as input, and this information is saved in the database as output.

[1051] Specifically, the server executes SQL commands to initialize the database, create the necessary tables, and insert data.

[1052] Step 2: The new employee types in their question and submits it

[1053] New employees, who are users, access the AI ​​advisor from a web browser on their own devices (smartphones or PCs). They enter specific questions in text format and click the send button to send the question to the server. For example, they enter a question such as, "I would like to learn the basics of data analysis using Excel."

[1054] Specifically, the device displays a web form, and the new employee enters a question in the text box and clicks the "Submit" button.

[1055] Step 3: The server receives the query and performs format conversion.

[1056] The server receives questions from new employees and converts them into an appropriate format, such as JSON, to be sent to the AI. It receives text questions from users as input and generates JSON-formatted question data as output. This processing is done using web server technologies such as Node.js and Flask.

[1057] Specifically, the server receives an HTTP request, analyzes the contents of the request body, converts it into JSON format, and sends it to the AI ​​module.

[1058] Step 4: AI analyzes the question and extracts keywords

[1059] The AI ​​analyzes the questions it receives and extracts keywords and important phrases. It receives question data in JSON format as input and generates a list of extracted keywords and phrases as output. This process uses natural language processing techniques such as BERT and GPT.

[1060] Specifically, the AI ​​uses natural language processing technology to extract keywords and then generates a database search query based on them.

[1061] Step 5: AI searches the database for relevant information

[1062] The AI ​​then searches the database based on the extracted keywords and phrases to retrieve relevant information. As input, it receives a list of keywords and phrases, and as output, it retrieves a dataset containing relevant information. This process uses search techniques using SQL queries.

[1063] Specifically, it executes the search query generated by the AI ​​and retrieves relevant data from the database.

[1064] Step 6: AI generates advice

[1065] The AI ​​generates appropriate advice based on the relevant information it has acquired. It receives relevant information acquired from a database as input and generates written advice as output. This process uses natural language generation technology. For example, it generates advice such as, "First, learn the basic operations of Excel, then learn how to use functions, and finally master data visualization techniques."

[1066] Specifically, the AI ​​constructs sentences based on the information and outputs them as advice.

[1067] Step 7: The server formats and sends the advice

[1068] The server converts the advice received from the AI ​​into an appropriate format (e.g., HTML format) and sends it to the new employee's device. It receives the advice text from the AI ​​as input, generates the converted advice data as output, and sends it to the user's device. This process uses web server software such as Apache or Nginx.

[1069] Specifically, the server converts the advice text into HTML format and sends it as an HTTP response.

[1070] Step 8: New employees receive and view the advice

[1071] The terminal receives advice sent from the server and displays it to the user. It receives advice data in HTML format from the server as input and displays it on the browser as output. For example, it displays advice such as "First, learn the basic operations of Excel, then learn how to use functions, and finally master data visualization techniques."

[1072] Specifically, the terminal receives the HTTP response and displays the advice text in the web browser.

[1073] (Application example 1)

[1074] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1075] Currently, a significant amount of human resources must be expended in the process of quickly and efficiently training new worker robots to acquire the necessary skills and work methods. There are also concerns about errors and reduced efficiency due to insufficient knowledge of work processes and maintenance procedures. As a result, there is an increased risk of a decline in productivity and quality throughout the factory.

[1076] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1077] In this invention, the server includes means for storing profile information for a new worker, details of each work process, robot maintenance procedures, and required skills in a database, means for the new worker to input and send a question using a terminal, means for receiving the question and sending it to the AI, means for the AI ​​to analyze the question and search the database for related information, means for generating advice based on the related information, and means for sending the generated advice to the new worker's terminal. This allows the new worker robot to efficiently acquire the necessary skills and knowledge, saving human resources and reducing work errors.

[1078] "New workers" refer to work robots that have been newly assigned to work sites such as factories.

[1079] "Profile information" refers to data about each new worker, including basic information, characteristics, and history.

[1080] "Work process" is a concept that encompasses the specific work and procedures carried out within a factory.

[1081] "Maintenance procedures" refer to the maintenance and repair methods required for the proper operation of a worker robot.

[1082] "Required skills" refers to the skills and knowledge that new workers must acquire in order to carry out a specific work process.

[1083] A "database" refers to a structured collection of information that is systematically organized and stored, and can be searched and extracted as needed.

[1084] "Terminal" refers to the electronic device used by the new worker to enter and receive information.

[1085] "Questions" refer to specific inquiries about what a new worker wants to learn or a problem they want to solve.

[1086] "AI" refers to artificial intelligence, a technology that generates advice in response to questions through natural language processing and data analysis.

[1087] "Advice" refers to guidelines such as specific steps and learning methods generated by AI based on questions.

[1088] The present invention is a system that uses a new skill-up advisor AI for worker robots to support efficient work skill acquisition. To implement this invention, a cloud server, a database, a terminal (a tablet, a smartphone, or a robot-specific control terminal), and an artificial intelligence (AI) model are used. Specifically, the system is configured as follows:

[1089] The server stores the new worker robot's profile information, the details of each work process, robot maintenance procedures, and required skills in a database. For example, the database stores "screw tightening" and "part placement" as work contents for an "assembly process," and stores "torque adjustment" and "part identification" as required skills.

[1090] The new worker robot can use a terminal to input questions about specific operation methods and maintenance procedures in text format and send them to the server. For example, consider the case where the new worker robot inputs and sends the question, "I want to learn how to adjust the torque of a screw."

[1091] The server receives this question and prepares it for transmission to the AI, converting it into the appropriate format. The AI ​​analyzes the question and extracts keywords and important phrases. For example, it extracts the keywords "torque," "adjustment," and "method" and retrieves information from the database about "how to use a torque wrench," "checking the setting value," and "how to tighten a screw."

[1092] The AI ​​then generates appropriate advice based on the information it has acquired. For example, it generates advice such as "Use a torque wrench to set the appropriate torque value, then tighten the screws." The server receives this advice and sends it in an appropriate format to the new worker robot's terminal. Finally, the new worker robot receives and displays the advice from the AI ​​advisor on its terminal.

[1093] It is recommended to use TensorFlow or PyTorch for generative AI models, and spaCy or Transformers for natural language processing, which will enable new worker robots to efficiently acquire the necessary skills and knowledge, saving human resources and reducing work errors.

[1094] For example, if a robot types and sends the question, "What are the steps to replace a motor?", the AI ​​can retrieve relevant information from the database and generate specific advice such as, "First, disconnect the power, then remove the old motor, and install the new motor in the specified way."

[1095] Example prompt sentence:

[1096] Question: I want to learn how to torque screws.

[1097] Q: What is the procedure for replacing the motor?

[1098] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1099] Step 1:

[1100] The server stores the profile information for new workers, the details of each work process, robot maintenance procedures, and required skills in a database. The input is the profile information of the new worker and data related to the work process, and the output is the configuration information stored in the database. Specifically, the server executes SQL queries against the database to insert and update the required information.

[1101] Step 2:

[1102] The new worker uses a terminal to input a question and sends it to the server. The input is the question text of the new worker, and the output is the question data sent to the server. In concrete terms, a text input form is displayed on the terminal, and the new worker inputs a question and presses the "send" button.

[1103] Step 3:

[1104] The server receives questions from new workers and prepares them for sending to the AI ​​model. The input is the question data of the new worker, and the output is the formatted question data to be sent to the AI ​​model. Specifically, the server converts the received text into an appropriate format, such as JSON.

[1105] Step 4:

[1106] The AI ​​analyzes the question and searches for relevant information from a database. The input is a formatted question data, and the output is a dataset containing relevant information. Specifically, the AI ​​uses natural language processing techniques (e.g., spaCy or Transformers) to extract important keywords and execute a search query against the database.

[1107] Step 5:

[1108] The AI ​​generates appropriate advice based on the acquired information. The input is a dataset of search results, and the output is the generated advice text. Specifically, the AI ​​uses a generative AI model (e.g., TensorFlow or PyTorch) to generate advice based on the question.

[1109] Step 6:

[1110] The server receives advice from the AI ​​and converts it into an appropriate format for sending to the new worker's device. The input is advice text, and the output is formatted advice that is displayed on the new worker's device. Specifically, the server converts the advice text into HTML format or similar and sends it to the new worker's device.

[1111] Step 7:

[1112] The new worker's terminal displays the received advice. The input is the formatted advice sent from the server, and the output is the advice text displayed on the screen. Specifically, a web browser or dedicated application installed on the terminal renders and displays the advice text.

[1113] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1114] This invention is a system that combines an emotion engine with a skill-up advisor AI for new employees to support the efficient and emotional acquisition of work skills. Specifically, a server stores new employee profile information, the work content of each department, the characteristics of members, and required skills in a database, and new employees input and send questions using their terminals. The questions are received by the server and sent to the AI, and the emotion engine analyzes the user's emotions. Based on the question and emotion information, the AI ​​searches the database for related information and generates advice. The generated advice is adjusted according to the user's emotions and sent to the new employee's terminal by the server.

[1115] Program processing overview (expressed in natural language)

[1116] 1. Initial setup by the server

[1117] The server stores new employee profile information, the job description of each department, the characteristics of the members, and the required skills in a database. For example, the job description of the "Marketing Department" might include "SNS campaign planning" and "data analysis," and the required skills might include "Excel" and "presentation."

[1118] 2. New employees ask questions

[1119] New employees use their own devices (smartphones or PCs) to access the AI ​​Advisor and log in. For example, new employee A logs in to the AI ​​Advisor from his or her PC.

[1120] 3. Enter and submit your question

[1121] New employees enter specific questions in text format and submit them. For example, new employee A enters and submits, "I would like to learn the basics of data analysis using Excel."

[1122] 4. The server receives the query

[1123] The server receives questions sent by new employees. New employee A's question is, "I want to learn the basics of data analysis using Excel."

[1124] 5. Emotion analysis using an emotion engine

[1125] The server prepares the received question for transmission to the AI, while having the emotion engine analyze the question text to recognize the user's emotions. For example, the emotion engine extracts emotions such as "confusion" or "anxiety" from the question text.

[1126] 6. AI-based analysis and advice generation

[1127] The AI ​​receives the question and sentiment analysis results sent from the server and begins its analysis. It extracts keywords from the question text, such as "Excel," "data analysis," and "basics." It also retrieves related information from the database while reflecting the sentiment information. For example, it searches for and retrieves information related to "basic Excel operations," "use of basic functions," and "data visualization."

[1128] 7. Generating Advice

[1129] Based on the information it acquires, the AI ​​generates optimal advice based on the user's emotions. For example, it generates advice such as "First, learn the basics of Excel, then learn how to use functions, and finally master data visualization techniques." However, if the user is feeling anxious, it will also include additional comments such as "Try not to rush and understand each step at a time."

[1130] 8. Server-Sent Advice

[1131] The server receives the advice provided by the AI ​​and converts it to be sent to the new employee in an appropriate format, for example, converting the advice text into HTML and formatting it as content containing advice based on emotions.

[1132] 9. New employees receive advice

[1133] Advice from an AI advisor is received and displayed on the new employee's device. For example, new employee A receives advice on his / her PC such as, "First, learn the basic operations of Excel, then learn how to use functions, and finally master data visualization techniques. Take your time and understand each step at a time."

[1134] In this way, the present invention supports the efficient acquisition of work skills while taking into consideration the user's feelings, allowing new employees to quickly resolve questions and problems related to their work and accelerating their growth. It also reduces the burden on existing members and makes it possible to provide high-quality support.

[1135] The processing flow will be explained below.

[1136] Step 1:

[1137] The server stores new employee profile information, the job content of each department, the characteristics of members, and the required skills in a database. Specifically, for the marketing department, "SNS campaign planning" and "data analysis" are registered as job content, and "Excel" and "presentation" are stored as required skills.

[1138] Step 2:

[1139] The new employee, who is the user, accesses the AI ​​Advisor using his or her own device (smartphone or PC) and logs in. For example, new employee A logs in to the AI ​​Advisor from his or her PC.

[1140] Step 3:

[1141] Users input questions to the AI ​​advisor in text format and send them. For example, new employee A might input, "I want to learn the basics of data analysis using Excel."

[1142] Step 4:

[1143] The server receives questions sent by users. New employee A's question is, "I want to learn the basics of data analysis using Excel."

[1144] Step 5:

[1145] The server converts the received questions into an appropriate format and sends them to the AI ​​and emotion engine, where the questions are formatted in a form suitable for analysis.

[1146] Step 6:

[1147] The AI ​​receives the question sent from the server and analyzes the question. The AI ​​analyzes the question text and extracts keywords and important phrases. For example, it extracts keywords such as "Excel," "data analysis," and "basics."

[1148] Step 7:

[1149] At the same time, the emotion engine analyzes the user's emotions from the question text. For example, the emotion engine extracts emotions such as "confusion" or "anxiety" from the text.

[1150] Step 8:

[1151] The AI ​​searches the database based on the extracted keywords to retrieve relevant information, for example, information on "basic Excel operations," "use of basic functions," and "data visualization."

[1152] Step 9:

[1153] Based on the information it acquires, the AI ​​generates appropriate advice while reflecting the user's emotions. For example, the AI ​​might generate advice such as "First, learn the basics of Excel, then learn how to use functions, and finally master data visualization techniques," and if the emotion expressed is "confused," it would include an additional comment such as "Try not to rush and understand it one step at a time."

[1154] Step 10:

[1155] The server receives the advice provided by the AI ​​and converts it into a format suitable for the user, for example, converting the advice text into HTML and formatting it according to emotions.

[1156] Step 11:

[1157] The server sends the formatted advice to the new employee's terminal. The advice is sent to new employee A's PC.

[1158] Step 12:

[1159] Users receive and display advice from an AI advisor on their devices. For example, new employee A receives the advice on his PC: "First, learn the basics of Excel, then learn how to use functions, and finally master data visualization techniques. Take your time and understand each step at a time."

[1160] This series of processes allows new employees to efficiently resolve work-related questions and problems and receive support tailored to their emotions. It also reduces the burden on existing members while providing high-quality support.

[1161] Example 2

[1162] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1163] In order for new employees to efficiently acquire work skills, it is necessary to provide prompt and appropriate advice that responds to each employee's feelings. However, current systems have difficulty providing advice that takes the user's feelings into account, and often take a long time to search for information and generate advice. As a result, new employees are unable to quickly resolve their work-related questions or problems, which can slow their growth.

[1164] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a means for storing new employee profile information, the work content of each department, member characteristics, and required skills in a database, a means for the new employee to input and send questions using a terminal, a means for receiving the questions and sending them to an AI, a means for analyzing the user's emotions from the question text, a means for the AI ​​to search the database for related information based on the question and the emotion analysis results, a means for generating advice based on the related information and the user's emotions, and a means for formatting the generated advice and sending it to the new employee's terminal. This enables new employees to quickly resolve questions and problems related to their work and speed up their growth. Furthermore, it reduces the burden on existing members and enables them to provide high-quality support.

[1165] A "new employee" refers to an employee who has just been hired by a company or organization.

[1166] "Profile Information" refers to information that includes details about a user, such as personal information, history, skills and experience, job title and department.

[1167] "Job Description" refers to the scope of work and responsibilities performed in a particular department or position.

[1168] "Member characteristics" refers to the skills, experience, personality, and working style of each employee belonging to a particular department or team.

[1169] "Required skills" refers to the abilities and knowledge required to perform a specific job or position.

[1170] A "database" refers to a collection of information that is structured, stored, and managed so that it can be efficiently searched and retrieved.

[1171] A "terminal" is a device that inputs and receives information, such as a smartphone or personal computer.

[1172] "AI" refers to artificial intelligence, specifically algorithms and models that recognize patterns in questions and data to generate appropriate answers and recommendations.

[1173] "Means for analyzing emotions" refers to technologies and algorithms for extracting and recognizing emotions from text entered by a user.

[1174] "Related information" refers to information searched from a database as content that corresponds to the user's question or feelings.

[1175] "Advice generation means" refers to a process or system for providing optimal advice or guidance based on a user's question.

[1176] The "means for formatting and transmitting" refers to a process for converting the generated advice into a specific format and transmitting it appropriately to the user's terminal.

[1177] The present invention combines an emotion engine with a skill improvement advisory system for new employees to support the acquisition of work skills efficiently and in accordance with emotions. Specific embodiments for carrying out the present invention will be described below.

[1178] The server stores new employee profile information, the job description of each department, the characteristics of each member, and the required skills in a database. Specifically, it connects to the company's human resources system via API and is set up to retrieve profile information in real time. A relational database system such as MongoDB or MySQL is suitable for the database used.

[1179] Users access the AI ​​advisor system using their own devices (smartphones or personal computers). Access is via a browser-based web application, and in many cases single sign-on (SSO) technology is implemented. Once the user logs in, an interface for entering questions is provided.

[1180] When a user enters a specific question in text format and submits it, the device sends the input text to the server as an HTTP request. For example, a user might enter "I want to learn the basics of data analysis using Excel" and press the submit button.

[1181] The server parses the received HTTP request and extracts the text portion. At the same time, metadata such as the user ID and the time of submission is also recorded. This text is then passed to the emotion engine, which uses natural language processing techniques (for example, Python's NLTK library or the Google Cloud Natural Language API) to analyze the user's emotions. Specifically, it detects emotions such as "confusion" or "anxiety" from the text and generates a related score.

[1182] The sentiment analysis results and question content are then sent to an artificial intelligence (AI) system. The AI ​​system uses a generative AI model, such as GPT-4, to extract keywords from the question text and search a database for related information. Specifically, it analyzes keywords such as "Excel," "data analysis," and "basics," and searches for and retrieves information on "basic Excel operations," "using basic functions," and "data visualization."

[1183] Based on the information acquired by the AI, the system generates optimal advice based on the user's emotions. For example, it generates advice that includes specific steps, such as "First, learn basic Excel operations, then learn how to use functions, and finally master data visualization techniques." If the user's emotion is "anxious," the system will add an additional comment such as "Try not to rush and understand each step one by one."

[1184] The server then receives the generated advice, converts it into a format suitable for the user, and sends it to the user. Specifically, the server converts the generated advice text into HTML and formats the advice according to the results of sentiment analysis. This process uses a template engine such as Jinja2.

[1185] Finally, the advice generated on the user's device is received and displayed on the browser. For example, new employee A reads advice on his / her PC such as, "First, learn the basic operations of Excel, then learn how to use functions, and finally master data visualization techniques. Take your time and understand each step at a time."

[1186] (Examples of specific examples and prompts)

[1187] As a concrete example, consider the case where a new employee asks, "I want to know how to give more effective presentations." The emotion engine analyzes emotions such as "nervous." The AI ​​then analyzes keywords such as "presentation," "effective," and "method" and searches for related information. As a result, it generates advice such as "how to create effective slides" and "tips for speaking," and adds comments according to the emotion, such as "It's okay to be nervous, just tackle each step one by one."

[1188] Example prompt sentence:

[1189] "As an AI skill-up advisor for new employees, generate advice that takes emotions into account in response to the following question: 'I want to know how to give presentations more effectively.' Let's say the user is nervous."

[1190] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1191] Step 1:

[1192] The server stores new employee profile information, the work content of each department, the characteristics of members, and required skills in a database. For example, it can be set up to connect to a company's human resources system via API and retrieve profile information in real time. The input is data received from the human resources system, and the output is the information stored in the database. Specifically, each piece of information is structured and stored using a database system such as MongoDB or MySQL.

[1193] Step 2:

[1194] New employees (users) access and log in to the AI ​​advisor system using their own devices (smartphones or personal computers). The input is the new employee's login information (ID and password), and the output is a message indicating whether the login was successful or unsuccessful. Browser-based web applications may use single sign-on (SSO) technology for security reasons.

[1195] Step 3:

[1196] The user enters a specific question in text format through the AI ​​advisor's interface and submits it. The input is the question text entered by the user, and the output is data sent to the server in the form of an HTTP request. For example, the user might enter "I would like to learn the basics of data analysis using Excel" and click the submit button.

[1197] Step 4:

[1198] The server receives the HTTP request sent by the user and analyzes the question. The input is the HTTP request, and the output is the parsed text portion and metadata (user ID, submission time, etc.). If the received data is in JSON format, it performs specific processing to parse and extract the text portion.

[1199] Step 5:

[1200] The server passes the received text to the emotion engine, which then analyzes the user's emotion from the question text. The input is the question text, and the output is the extracted emotion score. Specifically, the engine uses the Python NLTK library and Google Cloud Natural Language API to detect emotions such as "confusion" and "anxiety."

[1201] Step 6:

[1202] The server sends the question text and the sentiment analysis results to the AI ​​system. The input is the question text and sentiment score, and the output is the information search results by the AI ​​system. The AI ​​first extracts keywords and identifies keywords such as "Excel," "data analysis," and "basics." It then uses these keywords to search for related information from a database. The AI ​​model used is a generative AI model such as GPT-4.

[1203] Step 7:

[1204] Based on the searched information, the AI ​​generates advice that corresponds to the user's emotions. The input is the search result information and emotion score, and the output is the generated specific advice. For example, it generates advice such as "First, learn the basic operations of Excel, then learn how to use functions, and finally master data visualization techniques." At this time, it adds comments that correspond to the user's emotions, such as "Try not to rush and understand each step at a time."

[1205] Step 8:

[1206] The server formats the generated advice and sends it to the new employee's device in the appropriate format. The input is the generated advice, and the output is the formatted advice. Specifically, the generated advice text is converted into HTML format and advice based on the sentiment analysis results is included. The formatting process is performed using a template engine such as Jinja2.

[1207] Step 9:

[1208] Advice from the AI ​​advisor is received and displayed on the user's device. The input is formatted advice sent from the server, and the output is the content displayed in the browser. For example, the user reads advice such as, "First, learn the basic operations of Excel, then learn how to use functions, and finally master data visualization techniques. Take your time and understand each step at a time."

[1209] The above is a specific processing flow in the system of the present invention, and the input, data processing, and output at each step are clearly shown.

[1210] (Application example 2)

[1211] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1212] In modern industry, improving the work skills of new employees and troubleshooting industrial automation equipment are important issues that directly affect productivity and efficiency. However, new employees tend to have many questions and anxieties, and automation equipment often causes errors. A system that provides efficient and emotionally sensitive advice and solutions to these issues is needed.

[1213] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for storing profile information, job content, employee characteristics, and required skills in a database, means for new employees or automated equipment to input and send questions or error reports using a terminal, and means for receiving questions or error reports and sending them to the AI. This makes it possible to provide efficient and appropriate advice and countermeasures for the questions, anxieties, and errors that new employees and automated equipment face.

[1214] "New employees" refers to employees who have been newly hired by a company or other organization.

[1215] "Industrial automation equipment" refers to automated machinery and equipment used in factories and production lines.

[1216] "Profile Information" refers to basic attribute information stored about each new employee or automated device.

[1217] "Work station" refers to the location or facility where a particular job or task is performed.

[1218] "Members" refers to employees or workers working at a company or work station.

[1219] "Terminal" refers to a device used to input or output information, such as a smartphone or computer.

[1220] "Questions" refer to sentences or text that express doubts or problems that new employees or automated equipment have.

[1221] "Error reporting" refers to notifications or information sent by automated equipment when it detects a malfunction or problem.

[1222] An "emotion engine" refers to an algorithm or software that analyzes a user's emotional state from input text.

[1223] "Advice" refers to advice or solutions provided in response to questions or error reports.

[1224] "Countermeasures" refer to specific actions or steps to be taken in response to an error or problem.

[1225] To implement this invention, the following interactions between a server, a terminal, and a user are required.

[1226] 1. System Configuration

[1227] 1.1 Server Configuration

[1228] The server stores profile information for new employees and industrial automation equipment in a database, including the work content of each work station, the characteristics of the employees, and the required skills. It also has a means of receiving questions and error reports and sending them to the AI. It also sends advice and countermeasures generated by the AI ​​to new employees and automation equipment.

[1229] 1.2 Terminal configuration

[1230] Terminals are devices used by new employees and automated equipment to input questions and error reports and send them to the server. These terminals include smartphones, PCs, and tablets.

[1231] 1.3 User operations

[1232] New employees, who are users, use terminals to input questions or problems about their daily work in text format and send them to the server. Similarly, automated equipment also reports errors or malfunctions that occur during work to the server.

[1233] 2. Program Processing

[1234] 2.1 Initial Setup

[1235] The server stores profile information for new employees and automated equipment, as well as the job content, characteristics of the employees, and required skills for each work station in a database. For example, "welding metal parts" is registered as the job content for a "welding line," and "welding techniques" and "safe operations" are stored as required skills.

[1236] 2.2 Receiving Questions or Error Reports

[1237] Users, such as new employees and automated equipment, input and send specific questions or error reports in text format from their own devices. For example, a new employee might type and send, "I don't know how to set up the welding machine," or an automated device might report, "There's an insufficient power error."

[1238] 2.3 Analysis by Emotion Engine

[1239] When the server receives a question or error report, it uses an emotion engine to analyze the input text and extract its emotional information before sending it to the AI.

[1240] 2.4 Analysis and advice generation using AI

[1241] Based on the emotional information received from the emotion engine, questions, and error reports, the AI ​​searches the database for relevant data and generates optimal advice and countermeasures. For example, it generates advice that takes into consideration emotions, such as "Try not to rush and understand each step at a time."

[1242] 2.5 Sending Advice

[1243] The server receives the advice and measures generated by the AI ​​and sends them to the user's device in an appropriate format.

[1244] 3. Specific Examples

[1245] Let's consider the case where a new employee asks on their smartphone, "I want to learn the basics of data analysis using Excel." In this case, the emotion engine recognizes emotions such as "confusion" or "anxiety," and based on that information, the AI ​​suggests advice such as, "Start with the basic operations of Excel, then learn how to use functions, and finally master data visualization techniques." If the emotion is "anxiety," the AI ​​also includes an additional comment such as, "Try not to rush and understand it one step at a time."

[1246] Prompt Sentence Examples

[1247] Robot ID: R002

[1248] Question: "My parts are not properly aligned during assembly. What should I do?"

[1249] Emotion: "Anxiety"

[1250] In this way, the system of the present invention is able to provide efficient and empathetic advice and solutions to problems faced by new employees and industrial automation equipment.

[1251] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1252] Step 1: Initial Setup

[1253] The server stores profile information for new employees and automated equipment, the work content of each work station, the characteristics of the employees, and the required skills in a database. The server receives input from the new employee's attribute information, work content, and skill requirements, which it then stores in the database. The output is the appropriately stored profile information and work data. Specific operations include adding and updating records in the database.

[1254] Step 2: Submit a question or error report

[1255] A user, such as a new employee or an automated device, uses a terminal to input and send a specific question or error report in text format. The input is the user's text question or error report. The terminal sends this to the server. The output is the question or error report received by the server. The specific operation is to send data from the terminal to the server.

[1256] Step 3: Receiving a question or error report

[1257] The server receives questions or error reports sent by users. The input is text data sent from the terminal. The server receives this and temporarily stores it in a database. The output is text data prepared for sentiment analysis. Specifically, the server adds the text data to a queue for analysis.

[1258] Step 4: Analysis by the Emotion Engine

[1259] The server sends the received question or error report to the emotion engine, which extracts the user's emotional information. The input is text data stored in a queue. The emotion engine analyzes this and extracts emotions such as "confusion" or "anxiety." The output is data containing the emotional information. Specifically, it uses natural language processing tools to generate emotional information from text.

[1260] Step 5: AI analysis and advice generation

[1261] Based on text data with emotional information added, the AI ​​searches for relevant information from a database and generates optimal advice or countermeasures. The input is text data with emotional information. The AI ​​analyzes this, extracts relevant information from the database, and generates advice or countermeasures that take emotions into consideration. The output is the generated advice or countermeasures. Specifically, the system uses a generative AI model to create advice statements.

[1262] Step 6: Formatting the advice

[1263] The server converts the advice provided by the AI ​​into an appropriate format. The input is the text data of the advice or action generated by the AI. The server formats this into HTML or another appropriate format. The output is the formatted advice or action. Specifically, it runs a script that converts the text data into a different file format.

[1264] Step 7: Submitting Advice

[1265] The server sends formatted advice and measures to the terminals of new employees and automated equipment. The input is the formatted advice and measures. The server sends this to the terminal. The output is the advice and measures displayed on the terminal. The specific operation is data transmission from the server to the terminal.

[1266] Step 8: Receive and view advice

[1267] The terminal receives advice and measures sent from the server and displays them to the user. The input is the advice text sent from the server. The terminal displays this on the screen. The output is the specific advice and measures displayed to the user. The specific operation is to display the received data on the user interface.

[1268] This allows for efficient and empathetic advice and solutions to problems faced by new employees and industrial automation equipment.

[1269] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1270] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1271] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1272] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1273] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1274] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1275] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1276] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1277] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1278] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1279] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1280] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1281] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1282] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1283] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1284] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1285] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1286] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1287] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1288] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1289] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1290] The following is further disclosed regarding the above embodiment.

[1291] (Claim 1)

[1292] A means of storing new employee profile information, the work content of each department, the characteristics of members, and the required skills in a database;

[1293] A means for new employees to input and send questions using a terminal;

[1294] A means for receiving and sending questions to the AI;

[1295] A means for AI to analyze questions and search for relevant information from a database;

[1296] a means for generating advice based on relevant information;

[1297] A means for transmitting the generated advice to the new employee's terminal;

[1298] A system including:

[1299] (Claim 2)

[1300] 2. The system of claim 1, further comprising means for the AI ​​to search a database based on keywords extracted from the question.

[1301] (Claim 3)

[1302] 2. The system according to claim 1, further comprising means for formatting the generated advice and transmitting it to the new employee's terminal in an appropriate format.

[1303] "Example 1"

[1304] (Claim 1)

[1305] A means of storing new employee profile information, the work content of each department, the characteristics of members, and the required skills in a database;

[1306] A means for new employees to input and send questions using a terminal;

[1307] A means for receiving and converting questions into an appropriate format for transmission to the AI;

[1308] AI analyzes questions and extracts keywords and important phrases.

[1309] A means of searching the database based on the extracted keywords and key phrases to obtain relevant information;

[1310] a means for generating advice based on relevant information;

[1311] A means for converting the generated advice into an appropriate format such as HTML and sending it to the new employee's device;

[1312] A means for receiving and displaying advice on the new employee's device;

[1313] A system including:

[1314] (Claim 2)

[1315] 2. The system of claim 1, further comprising means for the AI ​​to search a database based on keywords extracted from the question.

[1316] (Claim 3)

[1317] 2. The system according to claim 1, further comprising means for formatting the generated advice and transmitting it to the new employee's terminal in an appropriate format.

[1318] "Application Example 1"

[1319] (Claim 1)

[1320] A means for storing profile information for new workers, the contents of each work process, robot maintenance procedures, and required skills in a database;

[1321] A means for the new worker to input and send a question using a terminal;

[1322] A means for receiving and sending questions to the AI;

[1323] A means for AI to analyze questions and search for relevant information from a database;

[1324] a means for generating advice based on relevant information;

[1325] A means for transmitting the generated advice to the terminal of the new worker;

[1326] A system including:

[1327] (Claim 2)

[1328] 2. The system of claim 1, further comprising means for the AI ​​to search a database based on keywords extracted from the question.

[1329] (Claim 3)

[1330] 2. The system of claim 1, further comprising means for formatting the generated advice and transmitting it in an appropriate format to the new worker's terminal.

[1331] "Example 2: Combining Emotion Engines"

[1332] (Claim 1)

[1333] A means of storing new employee profile information, the work content of each department, the characteristics of members, and the required skills in a database;

[1334] A means for new employees to input and send questions using a terminal;

[1335] A means for receiving and sending questions to the AI;

[1336] A means for analyzing user sentiment from question text;

[1337] A means for AI to search for relevant information from a database based on the question and sentiment analysis results;

[1338] means for generating advice according to relevant information and user sentiment;

[1339] A means for formatting the generated advice and sending it to the new employee's terminal;

[1340] A system including:

[1341] (Claim 2)

[1342] 2. The system of claim 1, wherein the AI ​​comprises means for searching a database based on the question and the sentiment analysis results.

[1343] (Claim 3)

[1344] 2. The system according to claim 1, further comprising means for formatting the generated advice to include additional comments according to the user's feelings and transmitting the advice to the new employee's terminal in an appropriate format.

[1345] "Application example 2 when combining emotion engines"

[1346] (Claim 1)

[1347] A means for storing profile information of new employees or industrial automation equipment, and the work content, characteristics of members, and required skills of each work station in a database;

[1348] a means for a new employee or an automated device to use the terminal to input and transmit a question or error report;

[1349] a means for receiving and sending questions or error reports to the AI;

[1350] A means for the AI ​​to analyze the question or error report and search a database for relevant information;

[1351] a means for generating advice or measures based on the relevant information;

[1352] means for transmitting the generated advice or measures to the terminal of the new employee or automated equipment;

[1353] A system including:

[1354] (Claim 2)

[1355] 10. The system of claim 1, further comprising means for the AI ​​to search the database based on keywords extracted from the question or error report.

[1356] (Claim 3)

[1357] 2. The system of claim 1, further comprising means for formatting the generated advice or measures and transmitting them in an appropriate format to a terminal of a new employee or automated equipment. [Explanation of symbols]

[1358] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of storing new employee profile information, the work content of each department, the characteristics of members, and the required skills in a database; A means for new employees to input and send questions using a terminal; A means for receiving and sending questions to the AI; A means for AI to analyze questions and search for relevant information from a database; a means for generating advice based on relevant information; A means for transmitting the generated advice to the new employee's terminal; A system including:

2. 2. The system of claim 1, further comprising means for the AI ​​to search the database based on keywords extracted from the query.

3. 2. The system according to claim 1, further comprising means for formatting the generated advice and transmitting it to the new employee's terminal in an appropriate format.

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