System

Abstract

To provide a system.SOLUTION: A system includes: means for accumulating employee information as knowledge; means for suggesting answers or an organization or a person as a consultation partner based on input consultation content; means for promoting communication between employees; communication means for transmitting and receiving messages in real time; means for providing a forum function for sharing knowledge or experience; and means for analyzing emotions of users, and suggesting an optimal consultation partner.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] In the past, improving the efficiency of communication and information sharing among employees has been an issue. In particular, it has been difficult to efficiently share information such as employees' skill sets and project achievements, and to find appropriate people to consult. [Means for solving the problem]

[0005] To solve this problem, this invention provides a system that accumulates employee information (department, skill set, project performance) as knowledge and suggests answers and organizations or people to consult with based on the content of the consultation entered.It also provides a means to stimulate communication between employees and aims to improve the efficiency of information sharing. [Brief explanation of the drawings]

[0006] [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. 2 is a sequence diagram showing a flow of processing in the data processing system according to the first embodiment of the first form example. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1 of Embodiment 1. [Figure 13] FIG. 10 is a sequence diagram showing a processing flow of a data processing system in a second embodiment of the second form example. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 of Embodiment Example 2. [Figure 15] FIG. 10 is a sequence diagram showing the flow of processing in a data processing system according to a third embodiment of the third embodiment. [Figure 16]FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 3 of Embodiment 3. [Figure 17] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the first embodiment of the first form example when an emotion engine is combined. [Figure 18] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1 of Form Example 1 when an emotion engine is combined. [Figure 19] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the second embodiment of the second form example when an emotion engine is combined. [Figure 20] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 of Form Example 2 when an emotion engine is combined. [Figure 21] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the third embodiment of the third form example when an emotion engine is combined. [Figure 22] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 3 of Form Example 3 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0007] 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.

[0008] First, the terms used in the following description will be explained.

[0009] 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, the 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), an APU (Accelerated Processing Unit), or a TPU (TENSOR PROCESSING UNIT (registered trademark)).

[0010] 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.

[0011] 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.

[0012] 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.

[0013] 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."

[0014] [First embodiment]

[0015] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0016] 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.

[0017] 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).

[0018] 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.

[0019] 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.

[0020] 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.

[0021] 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.

[0022] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0023] 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.

[0024] 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.

[0025] 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.

[0026] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0027] "Example 1"

[0028] The system of the present invention stores employee information (department, skill set, project performance) in a database. This database is updated whenever an employee acquires a new skill or participates in a new project. It is also updated appropriately when an employee resigns or changes departments.

[0029] "Example 2"

[0030] When the user enters the content of the consultation, the system searches the database and suggests the employees and organizations that are most suitable for the consultation. For example, if an employee needs to find employees with specific skills to start a new project, they can enter that skill as a keyword and the system will provide a list of employees with that skill.

[0031] "Example 3"

[0032] In addition, the system also provides functions to promote communication between employees. For example, the system has a chat function that allows employees to send messages to each other. The system also provides a forum function that allows employees to share their knowledge and experience with each other. This allows employees to share their knowledge and experience and receive feedback from other employees.

[0033] The processing flow of each embodiment will be described below.

[0034] "Example 1"

[0035] Step 1: Every time an employee learns a new skill or takes on a new project, enter that information into the system.

[0036] Step 2: The system stores the entered information in a database.

[0037] Step 3: If an employee leaves the company or changes departments, enter that information into the system and update the database.

[0038] "Example 2"

[0039] Step 1: Enter the consultation details into the system.

[0040] Step 2: The system searches the database and suggests employees and organizations that best fit the needs of the customer.

[0041] Step 3: Communicate with the proposed employees and organizations.

[0042] "Example 3"

[0043] Step 1: Employees use the system's chat function to exchange messages with other employees.

[0044] Step 2: Employees use the system's forum function to share their knowledge and experiences.

[0045] Step 3: Receive feedback from others and update your knowledge and experience as needed.

[0046] Example 1

[0047] Next, a description will be given of Example 1 of Form 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."

[0048] With conventional employee information management systems, updating employee skill sets and project achievements is done manually, making it difficult to keep information up to date. Furthermore, updating information when an employee leaves the company or changes departments is tedious, making it difficult to quickly search for employees with specific skill sets or project achievements. Furthermore, the lack of functionality to promote communication between employees hinders knowledge sharing within the organization.

[0049] The identification process by the identification processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means. In this invention, the server includes means for storing employee information (department, skill set, project performance) in a database, means for transmitting input information to the server, means for saving and updating information received by the server in the database, means for updating the database when an employee leaves the company or changes departments, means for searching for employees with specific skill sets or project performance, means for displaying search results to the user, and means for stimulating communication between employees. This enables rapid searches and information updates while keeping employee information up-to-date, thereby realizing knowledge sharing and stimulating communication within the organization.

[0050] "Employee information" refers to information such as an employee's department, skill set, and project track record.

[0051] "Database" refers to an information system for storing and managing employee information.

[0052] "Server" refers to a computer system for storing and updating information in a database.

[0053] "Terminal" refers to a device through which a user inputs information and transmits it to a server.

[0054] "User" means a person who utilizes the system to enter, retrieve, and display information.

[0055] A "skill set" refers to the collection of skills and knowledge that an employee possesses.

[0056] "Project performance" refers to the history and results of projects in which employees have participated.

[0057] "Search tools" refers to the ability to search the database for employees with specific skill sets or project experience.

[0058] "Means of communication" refers to functions that promote information exchange and contact between employees.

[0059] "Information update means" refers to the function for keeping the information in the database up to date when an employee leaves the company or changes departments.

[0060] This invention is a system that stores and manages employee information (department, skill set, project performance) in a database. The system consists of three main elements: a server, terminals, and users.

[0061] Hardware and software used

[0062] Server: Database server (e.g. MySQL (registered trademark), PostgreSQL)

[0063] Devices: PCs and mobile devices used by employees

[0064] Software: Web application (e.g., Django, Ruby on Rails)

[0065] Program processing flow

[0066] 1. Entering data

[0067] When a user acquires a new skill or participates in a new project, the user enters the required information into an input form in a web application.

[0068] Specifically, the user opens a web browser and enters "Python programming" into the skill addition form.

[0069] 2. Data transmission

[0070] The terminal transmits the information entered by the user to the server.

[0071] Specifically, the device sends "Python programming" skill information to the server using an HTTP POST request.

[0072] 3. Data storage

[0073] The server stores the received information in a database.

[0074] Specifically, the server adds a new record to the "skills" table in the database, saving "Python programming."

[0075] 4. Updating Data

[0076] The server updates the existing employee information.

[0077] Specifically, the server searches for the corresponding employee record and adds new skill information.

[0078] 5. Data Deletion

[0079] When a user leaves the company or changes departments, the administrator enters that information through a web application.

[0080] The terminal transmits the input information to the server.

[0081] The server updates the database based on the received information, deleting or changing the relevant employee information.

[0082] Specifically, the administrator clicks the "Resign" button, and the server deletes the corresponding employee record from the database.

[0083] 6. Searching for data

[0084] When a user wants to search for employees with a particular skill set or project experience, they enter a search query through the web application.

[0085] The terminal sends a search query to the server.

[0086] The server searches the database and returns the relevant employee information to the terminal.

[0087] Specifically, the user searches for employees with "Python programming" and the server returns a list of matching employees.

[0088] 7. Displaying Data

[0089] The terminal displays the returned information to the user.

[0090] Specifically, the terminal displays the search results on a web page, and the user sees a list of employees who have "Python programming."

[0091] Example prompts for generative AI models

[0092] "Generate a prompt statement to add newly acquired skills to the database."

[0093] "Generate a prompt to search for employees with specific project experience."

[0094] In this way, employee information can be kept up to date while enabling quick searches and updates, thereby stimulating knowledge sharing and communication within the organization.

[0095] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0096] Step 1: Enter your data

[0097] When a user acquires a new skill or participates in a new project, the user enters the required information into an input form in a web application.

[0098] Input: A user opens a web browser and types "Python programming" into the add skill form.

[0099] Output: The information entered is sent to the terminal.

[0100] Step 2: Sending data

[0101] The terminal transmits the information entered by the user to the server.

[0102] Input: User-entered "Python Programming" skill information.

[0103] Data processing: The device generates an HTTP POST request and creates a request containing the entered information.

[0104] Output: An HTTP POST request is sent to the server.

[0105] Step 3: Save your data

[0106] The server stores the received information in a database.

[0107] Input: "Python Programming" skill information sent from the device.

[0108] Data processing: The server adds a new record to the "skills" table in the database and saves the entered skill information.

[0109] Output: The new skill information is saved in the database.

[0110] Step 4: Update data

[0111] The server updates the existing employee information.

[0112] Input: A record in the database where the new skill information is saved.

[0113] Data processing: The server searches for the corresponding employee record and adds the new skill information.

[0114] Output: The updated employee information is saved in the database.

[0115] Step 5: Delete data

[0116] When a user leaves the company or changes departments, the administrator enters that information through a web application.

[0117] Input: The administrator clicks the "Resign" button and enters the relevant employee's information.

[0118] Data processing: The terminal sends the entered information to the server.

[0119] Output: The server deletes the corresponding employee record from the database.

[0120] Step 6: Search for data

[0121] When a user wants to search for employees with a particular skill set or project experience, they enter a search query through the web application.

[0122] Input: A user enters a query to search for employees with "Python programming."

[0123] Data processing: The device sends the search query to the server.

[0124] Output: The server searches the database and returns the relevant employee information to the terminal.

[0125] Step 7: View the data

[0126] The terminal displays the returned information to the user.

[0127] Input: Search results returned by the server.

[0128] Data processing: The device formats the search results for display on a web page.

[0129] Output: User sees a list of employees who have "Python Programming".

[0130] (Application example 1)

[0131] Next, a description will be given of Application Example 1 of Embodiment 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."

[0132] With the conventional employee information management system, it was difficult to effectively utilize employees' skill sets and project achievements, making it difficult to assign optimal tasks. Furthermore, updating information every time an employee acquired a new skill or participated in a project was time-consuming, making efficient operation impossible. Furthermore, there was a lack of ways to promote communication between employees, making it difficult to improve productivity across the organization.

[0133] 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.

[0134] In this invention, the server includes a means for accumulating employee information (department, skill set, project performance) as knowledge, a means for suggesting answers and organizations or people to consult with based on the input consultation content, a means for stimulating communication between employees, a means for suggesting optimal tasks based on the employee's skill set and project performance, and a means for updating employee information. This makes it possible to effectively utilize employees' skill sets and project performance to assign optimal tasks. Furthermore, updating employee information is automated, enabling efficient operations. Furthermore, this stimulates communication between employees, which is expected to improve productivity throughout the organization.

[0135] "Employee information" refers to information such as an employee's department, skill set, and project track record.

[0136] "Knowledge" refers to accumulated knowledge and information, especially employee information stored in a database.

[0137] "Consultation content" refers to the content of questions or consultations entered by employees.

[0138] "Answer" refers to the solution or information provided in response to the inquiry.

[0139] "Consultation destination" refers to organizations or individuals suggested based on the content of the consultation.

[0140] "Organization" refers to a group such as a company or department.

[0141] "Person" refers to a specific employee or professional.

[0142] "Communication" refers to the exchange of information and dialogue between employees.

[0143] A "skill set" refers to the collection of skills and abilities that an employee possesses.

[0144] "Project performance" refers to the history and results of projects in which employees have participated in the past.

[0145] "Best-fit work" refers to the work that is best suited to an employee based on their skill set and project performance.

[0146] "Update" refers to employee information being changed based on new skills or project achievements.

[0147] The system for implementing this invention accumulates employee information (department, skill set, project performance) as knowledge and suggests answers and organizations or people to consult with based on the input consultation content. It also has the function of stimulating communication between employees and suggesting optimal work based on employees' skill sets and project performance. It also has the function of updating employee information.

[0148] Hardware and software used

[0149] Hardware: Servers, factory robots, user devices (PCs, smartphones)

[0150] Software: SQLite database, Python program

[0151] System configuration

[0152] 1. Employee information collection:

[0153] The server stores information about employees' departments, skill sets, and project achievements in a database, allowing for centralized management of information about employees' skills and achievements.

[0154] 2. Proposal based on consultation:

[0155] The server then suggests the most appropriate answers and organizations or people to consult based on the consultation details entered by the user, allowing the user to quickly obtain appropriate information and support.

[0156] 3. Increased communication:

[0157] The server provides functionality to facilitate communication between employees, including functionality to facilitate contact with suggested organizations and individuals for consultation.

[0158] 4. Optimal working suggestions:

[0159] The server suggests the most suitable tasks based on the employee's skill set and project performance, allowing the factory robot to automatically assign the most suitable tasks to employees.

[0160] 5. Updating Employee Information:

[0161] The server automatically updates employee information whenever they acquire new skills or take on new projects, ensuring the database is always up-to-date.

[0162] Specific examples of processing

[0163] For example, if an employee with employee ID 1 has the skills of "welding" and "assembly," the server will suggest the work that best suits these skills from the database. When a user enters "Please suggest the best work based on the skill set of employee ID 1," the server will search the database and suggest the best work.

[0164] Prompt Sentence Examples

[0165] "Please suggest the best tasks for employee ID 1 based on their skill set."

[0166] In this way, the system can effectively utilize employees' skill sets and project experience to optimally assign tasks. It also automates updating employee information, leading to efficient operations. It also promotes communication between employees, which is expected to improve productivity across the organization.

[0167] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0168] Step 1:

[0169] The server stores employee information (department, skill set, project performance) in a database.

[0170] Input: Employee's department, skill set, project performance

[0171] Output: Employee information stored in the database

[0172] What it does: The server adds information about employees to the database whenever they acquire new skills or join new projects. It also updates the database when employees leave the company or change departments.

[0173] Step 2:

[0174] The user inputs the consultation content from the terminal.

[0175] Input: Consultation details

[0176] Output: Consultation details sent to the server

[0177] Specific operation: The user uses a terminal (PC or smartphone) to input the consultation content and send it to the server.

[0178] Step 3:

[0179] The server suggests answers and organizations or people to consult based on the input consultation content.

[0180] Input: Consultation details, employee information stored in the database

[0181] Output: Suggested answers and organizations or people to consult

[0182] Specific operation: The server analyzes the content of the consultation and refers to employee information stored in a database to select the most appropriate answer and the organization or person to consult.

[0183] Step 4:

[0184] The server provides functions to promote communication between employees.

[0185] Input: Suggested organization or person to consult

[0186] Output: A means of communication to facilitate communication

[0187] Specific operation: The server provides functions (e.g., chat functions and email notifications) to facilitate contact with the suggested organizations and people to consult with.

[0188] Step 5:

[0189] The server suggests the best work to do based on employees' skill sets and project experience.

[0190] Input: Employee skill sets, project performance

[0191] Output: Optimal work suggestions

[0192] Specific operation: The server refers to the employee's skill set and project track record stored in a database, and selects and proposes the most suitable work.

[0193] Step 6:

[0194] The server updates the employee information.

[0195] Input: New skills and project achievements

[0196] Output: Updated employee information

[0197] What it does: The server automatically updates employee information in the database whenever an employee acquires a new skill or takes on a new project.

[0198] Example 2

[0199] Next, a description will be given of Example 2 of Form 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."

[0200] With the previous system, it was difficult to find the right person to consult based on an employee's skills and experience, which led to problems with inactive communication between employees. Furthermore, there was a lack of a way to quickly and accurately suggest the right employee or organization based on the content of the consultation, which could lead to a decline in project efficiency.

[0201] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0202] In this invention, the server includes means for accumulating employee information (department, skill set, project performance) as knowledge, means for extracting keywords based on the input consultation content, means for searching the database based on the extracted keywords and generating a list of relevant employees and organizations, means for providing the generated list to the user, and means for stimulating communication between employees. This enables the user to quickly and accurately find the appropriate employee or organization, stimulating communication between employees and improving project efficiency.

[0203] "Employee information" refers to data about employees, such as department, skill set, and project performance.

[0204] "Knowledge" refers to accumulated information and knowledge, including employee information in particular.

[0205] "Consultation content" refers to the content of questions or requests that users input into the system.

[0206] "Keywords" refer to important words and phrases extracted from the content of the consultation.

[0207] A "database" refers to a system that stores data such as employee information in an organized manner and makes it searchable.

[0208] "List" refers to a list of relevant employees and organizations generated as search results.

[0209] "User" refers to a person who uses the system to input the details of a consultation and receive the results.

[0210] "Means to promote communication" refers to functions and methods for promoting information exchange and collaboration among employees.

[0211] This invention is a system that accumulates employee information as knowledge and suggests appropriate employees and organizations based on the content of an inquiry that has been input. A specific embodiment of this system will be described below.

[0212] System configuration

[0213] The system uses the following hardware and software:

[0214] Hardware: Servers (e.g., general-purpose servers), terminals (e.g., personal computers, smartphones)

[0215] Software: database management systems (e.g., MySQL), search algorithms (e.g., ElasticSearch (registered trademark))

[0216] Program processing

[0217] The server receives the consultation content from the user. The consultation content includes keywords for searching for employees with specific skills and experience. The server searches the database based on the received keywords and generates a list of relevant employees and organizations.

[0218] The system works as follows:

[0219] 1. The user enters the consultation content. For example, "We are looking for an employee with Python programming skills for a new project."

[0220] 2. The device sends the entered consultation details to the server. At this time, the device sends the data using an HTTP request.

[0221] 3. The server receives the consultation content and extracts keywords. For example, it extracts the keyword "Python programming."

[0222] 4. The server searches the database and generates a list of matching employees and organizations, using Elasticsearch for fast and efficient searching.

[0223] 5. The server sends the generated list to the device, again using an HTTP response to send the data.

[0224] 6. The terminal displays the list to the user, who can then select the appropriate employee or organization from the displayed list.

[0225] Specific examples

[0226] For example, a user may enter "I'm looking for an employee with Python programming skills for a new project" into a terminal. The terminal then sends this request to the server. The server receives the request and extracts the keyword "Python programming." The server then uses Elasticsearch to search the MySQL database and generate a list of employees with Python programming skills. The server then sends the generated list to the terminal, which then displays it to the user. The user can then select a suitable employee from the displayed list.

[0227] Example prompts to input to a generative AI model:

[0228] "We're looking for employees with Python programming skills for a new project. Can you suggest suitable candidates?"

[0229] After entering this prompt, the system will search the database and provide a list of employees who have Python programming skills.

[0230] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0231] Step 1:

[0232] The user inputs the consultation content.

[0233] The user inputs their inquiry into the device to find employees with specific skills and experience. For example, they might input "I'm looking for an employee with Python programming skills for a new project." The input inquiry is saved on the device.

[0234] Step 2:

[0235] The terminal transmits the input consultation content to the server.

[0236] The terminal sends the consultation details entered by the user to the server as an HTTP request. The input data is sent to the server in text format.

[0237] Step 3:

[0238] The server receives the consultation content and extracts keywords.

[0239] The server analyzes the consultation content received from the device and extracts important keywords. For example, the keyword "Python programming" is extracted. The extracted keywords are used in the next search process.

[0240] Step 4:

[0241] The server searches the database and generates a list of relevant employees and organizations.

[0242] The server uses Elasticsearch to search the MySQL database based on the extracted keywords, and generates a list of employees with Python programming skills. The list contains employee information retrieved from the database.

[0243] Step 5:

[0244] The server sends the generated list to the terminal.

[0245] The server sends the generated list of employees and organizations to the terminal as an HTTP response in text or JSON format.

[0246] Step 6:

[0247] The terminal displays the list to the user.

[0248] The terminal displays the list received from the server to the user, who can then select the appropriate employee or organization from the displayed list. The display format can be a list or a table.

[0249] (Application example 2)

[0250] Next, a description will be given of Application Example 2 of Form 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."

[0251] Conventional systems accumulate employee information as knowledge and can suggest appropriate organizations and individuals based on the content of the consultation, but they lack the functionality to quickly search for and suggest workers with specific skills. Furthermore, the means to stimulate communication between employees are limited, and the functionality to promote effective communication with the suggested consultation partners is insufficient. This makes it difficult to quickly find workers with the skills necessary to perform specific tasks within the factory, resulting in a decline in work efficiency.

[0252] The identification process by the identification 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 accumulating employee information (department, skill set, project performance) as knowledge, means for suggesting answers and organizations or people to consult with based on the input consultation content, means for stimulating communication between employees, and means for searching for and suggesting workers with specific skills. This makes it possible to quickly search for and suggest workers with specific skills, thereby improving work efficiency in the factory.

[0253] "Employee information" refers to information such as an employee's department, skill set, and project track record.

[0254] "Knowledge" refers to accumulated information and knowledge, including employee information in particular.

[0255] "Consultation content" refers to the questions or consultation content that users enter into the system.

[0256] An "organization" refers to a group or group formed with a specific purpose.

[0257] A "person" refers to an individual with particular skills or knowledge.

[0258] "Communication" refers to the act of exchanging information and opinions.

[0259] "Skills" refer to the abilities and techniques required to perform specific tasks or jobs.

[0260] "Worker" refers to a worker who performs specific tasks in a factory or on a work site.

[0261] "Search" refers to the act of finding specific information from a database or the like.

[0262] "Proposal" refers to the act of presenting a particular option or solution.

[0263] The system for implementing this invention includes means for accumulating employee information (department, skill set, project performance) as knowledge, means for suggesting answers and organizations or people to consult with based on the input consultation content, means for stimulating communication between employees, and means for searching for and suggesting workers with specific skills.

[0264] The server uses an SQLite database to store employee information, including department, skill set, project performance, etc. When a user searches for workers with specific skills, the server searches the database based on the entered skill keywords and generates a list of workers with the corresponding skills.

[0265] The system is implemented using a Python program. When a user inputs a skill keyword, the server executes a search query against the SQLite database to retrieve the corresponding worker information. The retrieved information is then displayed to the user in a list format.

[0266] As a concrete example, consider the case where a new welding machine is introduced in a factory and workers with the skills to operate that welding machine are needed. When a user enters "welding machine operation," the server searches the database and generates a list of workers with that skill. The user can then select an appropriate worker based on this list.

[0267] An example of a prompt is as follows:

[0268] "We are looking for employees with the skills to operate new welding machines. Please provide us with a list of employees with the skills to operate welding machines."

[0269] This system makes it possible to quickly search for and suggest workers with specific skills, thereby improving work efficiency within the factory.

[0270] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0271] Step 1:

[0272] A user uses a terminal to input keywords to search for workers with specific skills. The input keywords are sent to the server. The input data are keywords related to the skills the user is looking for.

[0273] Step 2:

[0274] The server searches the SQLite database based on the received keywords. It generates a search query and extracts workers with the corresponding skills from the employee information in the database (department, skill set, project history). The input data is the keyword entered by the user, and the output data is a list of workers with the corresponding skills.

[0275] Step 3:

[0276] The server formats the list of workers obtained as search results and converts it into a format for display to the user. Specifically, it compiles information such as the worker's name, department, skill set, and project performance into a list. The input data is the worker information obtained as search results, and the output data is the formatted list of workers.

[0277] Step 4:

[0278] The server sends the formatted list of workers to the user's terminal. The user can check the list of workers with the relevant skills on the terminal. The input data is the formatted list of workers, and the output data is the list of workers displayed on the user's terminal.

[0279] Step 5:

[0280] The user selects an appropriate worker based on the displayed list of workers. Specific work requests and communication can then be made to the selected worker. The input data is the list of workers confirmed by the user, and the output data is the content of the work requests and communication sent to the selected worker.

[0281] Example 3

[0282] Next, a description will be given of a third embodiment of the third embodiment. 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."

[0283] Conventional employee information management systems have the problem of not encouraging active communication between employees and preventing sufficient sharing of knowledge and experience. Furthermore, the lack of real-time messaging and forum functionality means that information exchange between employees is not smooth. This can lead to a decline in employee productivity and cooperation.

[0284] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[0285] In this invention, the server includes means for accumulating employee information (department, skill set, project performance) as knowledge, means for suggesting answers and organizations or people to consult with based on the consultation content entered, means for stimulating communication between employees, means for sending and receiving messages in real time, and means for providing a forum for sharing knowledge and experience. This facilitates communication between employees and enables the smooth sharing of knowledge and experience.

[0286] "Employee information" refers to information such as an employee's department, skill set, and project track record.

[0287] "Knowledge" refers to the accumulation of employee information and data on knowledge and experience that is stored in a shareable format.

[0288] "Consultation content" refers to the questions and consultation content that employees enter into the system.

[0289] "Answer" refers to the solution or information provided in response to the inquiry.

[0290] "Consultation destination" refers to organizations or individuals suggested based on the content of the consultation.

[0291] "Means to promote communication" refers to functions that enable employees to smoothly exchange information and opinions with each other.

[0292] "Means of sending and receiving messages in real time" refers to the ability for employees to send and receive messages instantly.

[0293] "Forum" refers to an online message board where employees can share knowledge and experiences and exchange opinions.

[0294] "Server" refers to a computer system that manages the entire system and provides various functions.

[0295] "Terminal" refers to a device (e.g., PC, smartphone) used by an employee to access and operate the system.

[0296] This invention is a system for promoting communication among employees and sharing knowledge and experience. This system operates in cooperation with three parties: a server, a terminal, and a user.

[0297] Hardware and software used

[0298] Hardware:

[0299] High-performance servers (e.g., high-performance computer systems)

[0300] Device (e.g. PC, smartphone)

[0301] software:

[0302] Chat functionality: APIs for real-time messaging (e.g., messaging APIs)

[0303] Forum functionality: Online bulletin board software for sharing knowledge and experiences (e.g., forum software)

[0304] Specific operation of the system

[0305] server:

[0306] The server stores employee information (department, skill set, project track record) as knowledge. This allows it to suggest appropriate answers and organizations or people to consult with based on the consultation content entered. The server also provides a function for sending and receiving messages in real time, promoting active communication between employees. Furthermore, the server provides a forum function, providing a place for employees to share their knowledge and experience.

[0307] Device:

[0308] Terminals are devices that users use to access and operate the system. Users can use the terminals to send and receive messages in real time using the chat function, and can also use the forum function to share knowledge and experience and get feedback from other employees.

[0309] User:

[0310] Users are employees who use the system. They can use the chat and forum functions on their terminals to communicate with other employees. For example, if User A sends a message to User B saying, "Thank you for your hard work. Could you please send me the materials for today's meeting?", the message sent from User A's terminal is delivered to User B's terminal via the server. User B can receive the message and reply in real time.

[0311] Also, if user C posts a topic called "New Project Proposal" to the forum, the post sent from user C's device will be stored in the database via the server. Other users can view and comment on the topic.

[0312] Prompt Sentence Examples

[0313] "Design a system to facilitate communication between employees. The system should include real-time chat functionality and forum functionality for knowledge sharing. Use high-performance computer systems as the hardware and messaging APIs and forum software."

[0314] In this way, it is clearly explained how the server, terminal, and user cooperate to operate the system. The flow of the specific processing in the third embodiment will be explained with reference to FIG.

[0315] Step 1:

[0316] The user types a chat message.

[0317] A user opens a chat application on a terminal and enters text into a message input field, which is temporarily stored in the terminal's memory.

[0318] Step 2:

[0319] The device sends a message to the server.

[0320] The terminal sends the message entered by the user to the server using a messaging API. The message is sent as an HTTP request. The input is the user's message, and the output is an HTTP request to the server.

[0321] Step 3:

[0322] The server receives and processes the message.

[0323] The server parses the received HTTP request, extracts the message content and sender information, and processes the message to route it to the appropriate recipient. The input is the HTTP request, and the output is the recipient information and the message content.

[0324] Step 4:

[0325] The server sends the message to the recipient's terminal.

[0326] The server sends a message to the recipient's device. The recipient's device receives the message in real time via a messaging API. The input is recipient information and message content, and the output is an HTTP response to the recipient's device.

[0327] Step 5:

[0328] The recipient's device displays the message.

[0329] The receiver's device displays the received message in the chat application interface. The receiver can check the message and reply. The input is the HTTP response, and the output is the message displayed in the chat application interface.

[0330] Step 6:

[0331] A user creates a post in a forum.

[0332] A user opens a forum application on their device and enters a new topic or comment, which is temporarily stored in the device's memory.

[0333] Step 7:

[0334] The device sends the post to the server.

[0335] The terminal sends user-created posts to the server using the forum API. Posts are sent as HTTP requests. The input is the user post, and the output is an HTTP request to the server.

[0336] Step 8:

[0337] The server stores the posts in a database.

[0338] The server stores the received posts in a database. The database holds information such as the post content, author, and creation date. The input is an HTTP request, and the output is the post data stored in the database.

[0339] Step 9:

[0340] The server notifies other users of updates to the forum.

[0341] The server notifies other users when a new post has been made to the forum. The notification is done in real time. The input is the post data stored in the database, and the output is the notification to other users.

[0342] Step 10:

[0343] Other users' devices will display forum updates.

[0344] Other users' devices receive forum updates and display new posts in the application interface. Users can view and comment on new posts. The input is notifications, and the output is new posts displayed in the forum application interface.

[0345] (Application example 3)

[0346] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[0347] While conventional robots used in factories can perform individual tasks efficiently, they face the challenge of having difficulty sharing work progress and problems due to a lack of communication between robots. Furthermore, there is no way for robots to share the knowledge and experience they have gained with other robots, which can lead to a decline in overall work efficiency. To solve these issues, a system is needed that allows robots to communicate efficiently with each other and share knowledge and experience.

[0348] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[0349] In this invention, the server includes a means for accumulating employee information (department, skill set, project record) as knowledge, a means for suggesting answers and organizations or people to consult with based on the consultation content entered, a means for promoting communication between employees, a means for providing a chat function that allows robots to send messages to each other, and a means for providing a forum function for robots to share knowledge and experience. This enables robots to communicate with each other efficiently and quickly share work progress and problems. Furthermore, by sharing the knowledge and experience gained by robots with other robots, overall work efficiency can be improved.

[0350] "Employee information" refers to information about employees, such as department, skill set, and project performance.

[0351] "Knowledge" refers to accumulated information and knowledge, such as employee information and robot knowledge and experience.

[0352] "Consultation content" refers to questions or issues entered by employees or robots.

[0353] An "answer" is a solution or information provided in response to a question.

[0354] "Consultation destination" refers to an organization or person suggested based on the content of the consultation.

[0355] An "organization" is a group or group formed with a specific purpose.

[0356] A "person" is an individual with a specific role or skill.

[0357] "Communication" is the act of exchanging information and opinions.

[0358] The "chat function" allows robots and employees to send messages to each other.

[0359] The "forum function" is a function that allows robots and employees to share knowledge and experiences.

[0360] "Work efficiency" refers to the ability or degree to which work is performed efficiently.

[0361] "Progress" refers to the progress of a task or project.

[0362] A "problem" is a challenge or obstacle that arises in a task or project.

[0363] The system for implementing this invention aims to enable robots used in a factory to communicate with each other efficiently and share knowledge and experience. A specific embodiment of this system will be described below.

[0364] System Configuration

[0365] The system consists of the following main components:

[0366] 1. Server: Employee information (department, skill set, project track record) is accumulated as knowledge, and based on the inputted consultation content, answers and organizations or people to consult are suggested.

[0367] 2. Robot: A robot that works in a factory and has chat and forum functions.

[0368] 3. Network: A network for communication between the server and the robot.

[0369] Program processing

[0370] The server processes the data using the following means:

[0371] Employee information storage: The server stores employee information such as department, skill set, and project performance in a database. This data also includes the knowledge and experience gained by the robot during its work.

[0372] Analysis of consultation content: The server analyzes the consultation content entered by the robot or employee and suggests appropriate answers and organizations or people to consult.

[0373] Chat function: Robots can send messages to each other via the server, allowing them to share their work progress and problems in real time.

[0374] Forum function: Robots can post the knowledge and experience they gain during their work on the forum and share it with other robots.

[0375] Hardware and software used

[0376] Hardware: Robots, servers, and network equipment used in factories

[0377] Software: Python programs, database management systems (e.g., MySQL), thread libraries

[0378] Specific examples

[0379] For example, if a robot discovers a new, efficient work procedure in a factory, it can share that knowledge with other robots through the forum function, allowing other robots to adopt the same efficient procedure, improving overall work efficiency.

[0380] Example prompt sentence:

[0381] A robot in your factory has discovered a new, more efficient way to work. Think about how you can share this knowledge with other robots to improve their work efficiency.

[0382] In this way, robots can communicate with each other efficiently and share knowledge and experience, improving work efficiency throughout the factory and enabling quicker response when problems arise.

[0383] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[0384] Step 1:

[0385] The server accumulates employee information (department, skill set, project performance) in a database. As input, it receives information provided by each employee and robot and stores it in the database. As data processing, it converts the information into an appropriate format and stores it in the database. As output, it obtains the accumulated employee information.

[0386] Step 2:

[0387] The server receives the consultation content input from the robot or an employee. It receives the text data of the consultation content as input and analyzes it. As data processing, it uses natural language processing technology to analyze the consultation content and identify the appropriate answer or organization or person to consult. As output, it obtains a suggested answer or person to consult.

[0388] Step 3:

[0389] The server sends the suggested answers and information on where to consult to the robot. As input, it receives the answers and information on where to consult obtained in step 2 and sends this to the robot. As data processing, it converts the information into an appropriate format and sends it to the robot. As output, the robot receives the suggested answers and information on where to consult.

[0390] Step 4:

[0391] Based on the information received from the server, the robot exchanges messages with other robots using the chat function. As input, it generates a message based on the information received from the server and sends it to other robots. As data calculation, it generates and sends a message. As output, other robots receive the message.

[0392] Step 5:

[0393] Robots use the forum function to share the knowledge and experience they gain while working. As input, they post the knowledge and experience they gain while working to the forum. As data processing, the posted content is converted into an appropriate format and saved in the forum. As output, other robots can obtain the knowledge and experience from the forum.

[0394] Step 6:

[0395] The server accumulates the knowledge and experience posted on the forum in a database. As input, it receives the knowledge and experience posted by the robots and stores it in the database. As data processing, it converts the information into an appropriate format and stores it in the database. As output, it obtains the accumulated knowledge and experience.

[0396] Step 7:

[0397] The robot improves work efficiency based on the knowledge and experience it gains from the forum. As input, it receives knowledge and experience acquired from the forum and applies it to the work. As data calculation, it optimizes the work procedure based on the knowledge and experience. As output, work efficiency is improved.

[0398] 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.

[0399] "Example 1"

[0400] One embodiment of the present invention is a system incorporating an emotion engine. This system accumulates employee information (department, skill set, project performance) as knowledge and suggests answers and organizations or people to consult with based on the content of the consultation entered. Furthermore, the emotion engine recognizes the user's emotions and suggests organizations or people to consult with based on those emotions. Specifically, if it recognizes that the user is feeling stressed, it suggests employees who are thought to be able to alleviate that stress.

[0401] "Example 2"

[0402] Another embodiment of the present invention is a system in which an emotion engine has the function of promoting communication between employees. This system recognizes the user's emotions and suggests communication methods based on those emotions. Specifically, if the system recognizes that the user is feeling joy, it encourages communication with employees who share that joy.

[0403] "Example 3"

[0404] Furthermore, as another embodiment of the present invention, there is a system in which an emotion engine suggests organizations or people to consult with based on employee information accumulated as knowledge and the user's emotions. This system combines the user's emotions and employee information to suggest the most appropriate person to consult with. Specifically, if it recognizes that the user is feeling anxious, it suggests experienced employees who are thought to be able to alleviate the anxiety.

[0405] The processing flow of each embodiment will be described below.

[0406] "Example 1"

[0407] Step 1: The system accumulates employee information (department, skill set, project performance) as knowledge.

[0408] Step 2: When the user inputs the content of their inquiry, the system will suggest answers and organizations or people to consult based on the content.

[0409] Step 3: The emotion engine recognizes the user's emotions and suggests organizations or people to consult with based on those emotions. Specifically, if the engine recognizes that the user is feeling stressed, it will suggest employees who are thought to be able to alleviate that stress.

[0410] "Example 2"

[0411] Step 1: The emotion engine recognizes the user's emotion.

[0412] Step 2: The emotion engine suggests ways to communicate based on the emotion. Specifically, if the engine recognizes that the user is feeling happy, it will encourage communication with employees who share that happiness.

[0413] "Example 3"

[0414] Step 1: The emotion engine combines the user's emotions with employee information to suggest the best person to consult.

[0415] Step 2: Specifically, if it is recognized that the user is feeling anxious, it will suggest experienced employees who may be able to alleviate that anxiety.

[0416] Example 1

[0417] Next, a description will be given of Example 1 of Form 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."

[0418] While conventional employee information management systems can manage employee skill sets and project performance, they lack the functionality to suggest appropriate consultations based on the user's emotions. Furthermore, they lack specific methods for promoting communication between employees, which means they are unable to fully reduce employee stress or improve work efficiency.

[0419] 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.

[0420] In this invention, the server includes means for accumulating employee information (department, skill set, project performance) as knowledge, means for suggesting answers and organizations or people to consult with based on the consultation content entered, means for recognizing the user's emotions using an emotion engine and suggesting organizations or people to consult with based on those emotions, and means for stimulating communication between employees. This makes it possible to suggest appropriate organizations or people to consult with based on the user's emotions, thereby reducing employee stress and improving work efficiency.

[0421] "Employee information" refers to information such as an employee's department, skill set, and project track record.

[0422] "Knowledge" refers to the accumulation of employee information and the knowledge and information shared within the organization.

[0423] An "emotion engine" refers to software or algorithms that analyze emotions from user input and suggest appropriate responses based on those emotions.

[0424] "Consultation content" refers to the content of the consultation or question that the user inputs into the system.

[0425] "Consultation destination" refers to an organization or person suggested based on the content of the user's consultation.

[0426] "Means to promote communication" refers to functions and methods for promoting interaction and information sharing among employees.

[0427] A "server" is a computer that is the central part of a system and performs processes such as data storage, analysis, and proposals.

[0428] "Terminal" refers to a device through which a user accesses the system to enter information and view results.

[0429] This invention is a system that stores employee information (department, skill set, project performance) in a database and suggests appropriate answers and consultations based on the content of the user's consultation. It also includes a function that uses an emotion engine to recognize the user's emotions and suggests consultations based on those emotions.

[0430] System configuration

[0431] The server stores employee information in a database. Specifically, the database is updated every time an employee acquires a new skill or participates in a new project. The database is also updated appropriately when an employee leaves the company or changes departments. The server can use, for example, MySQL or PostgreSQL as its database management system (DBMS).

[0432] The terminal accepts input from the user. When the user inputs the consultation content, the content is sent to the server. The terminal is often implemented as a web browser or a mobile application.

[0433] The server analyzes the received consultation content and recognizes the user's emotions using an emotion engine, which can use, for example, the emotion analysis function of Google® Cloud Natural Language API or IBM Watson®.

[0434] The server then searches the database for appropriate organizations or people to consult with based on the emotions it recognizes. For example, if it recognizes that the user is feeling stressed, it will suggest employees who can help alleviate that stress.

[0435] The terminal displays the suggestions received from the server to the user, who can then select an appropriate consultation provider based on the displayed information.

[0436] Specific examples

[0437] If a user types, "I've been feeling a lot of stress at work lately," the emotion engine will recognize the word "stress." The server will search its database for employees with skills that can help reduce stress and suggest them to the user.

[0438] Example prompt sentence:

[0439] "I've been feeling a lot of pressure at work lately and it's stressful. Who can I talk to?"

[0440] This system efficiently manages employee information and suggests appropriate consultation sources based on the user's emotions, thereby contributing to reducing employee stress and improving work efficiency.

[0441] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0442] Step 1:

[0443] The user inputs the consultation content from the terminal.

[0444] Specific actions: The user enters "I've been feeling a lot of pressure at work lately and it's stressful" into the input form displayed on the device screen.

[0445] Input: User's inquiry (text format)

[0446] Output: Consultation details entered into the terminal

[0447] Step 2:

[0448] The terminal transmits the input consultation content to the server.

[0449] Specific operation: The device converts the consultation content entered by the user into JSON format and sends it to the server using an HTTP POST request.

[0450] Input: Consultation details entered into the device (text format)

[0451] Output: Consultation details sent to the server (JSON format)

[0452] Step 3:

[0453] The server analyzes the consultation content and recognizes the user's emotions using an emotion engine.

[0454] Specific operation: The server parses the received JSON data and passes it to the emotion engine. The emotion engine extracts the emotion "stress" from the text and returns it to the server.

[0455] Input: Consultation content sent to the server (JSON format)

[0456] Output: Emotion recognized by the emotion engine (e.g., stress)

[0457] Step 4:

[0458] Based on the emotion recognized by the server, a search is made for appropriate organizations or people to consult from a database.

[0459] Specific operation: The server executes a database query to search for employees who have skills that can help reduce stress or who have received similar consultations in the past. For example, it searches for employees with the skill "stress management."

[0460] Input: Emotion recognized by the emotion engine (e.g., stress)

[0461] Output: Information on appropriate organizations and people to consult found in the database

[0462] Step 5:

[0463] The server sends the search results to the terminal.

[0464] Specific operation: The server converts the search results into JSON format and sends them to the terminal as an HTTP response.

[0465] Input: Information on appropriate organizations and people to consult found in the database

[0466] Output: Search results sent to the device (JSON format)

[0467] Step 6:

[0468] The terminal displays the search results to the user.

[0469] Specific operation: The device analyzes the received JSON data and displays to the user, "Please consult with employee A, who has stress management skills."

[0470] Input: Search results sent to the terminal (JSON format)

[0471] Output: Search results displayed to the user (in text format)

[0472] (Application example 1)

[0473] Next, a description will be given of Application Example 1 of Embodiment 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."

[0474] Conventional employee information management systems have difficulty providing appropriate support and advice that takes into account employees' emotions. Furthermore, the robots working in factories lacked the functionality to recognize employees' emotions and suggest appropriate actions, preventing them from fully reducing stress and promoting efficient communication. This created challenges for improving employee satisfaction and productivity.

[0475] 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.

[0476] In this invention, the server includes means for accumulating employee information (department, skill set, project performance) as knowledge, means for suggesting answers and organizations or people to consult with based on the consultation content entered, means for stimulating communication between employees, means for recognizing the user's emotions using an emotion engine and suggesting appropriate actions based on those emotions, and means installed in robots working in factories to recognize the emotions of workers and suggest appropriate actions when stress is detected. This makes it possible to provide appropriate support and advice that takes employees' emotions into consideration, thereby reducing stress among workers and promoting efficient communication.

[0477] "Employee information" refers to information such as an employee's department, skill set, and project track record.

[0478] "Knowledge" refers to accumulated information and knowledge, including employee information in particular.

[0479] An "emotion engine" refers to a system that recognizes a user's emotions and suggests appropriate actions based on those emotions.

[0480] "Consultation content" refers to the question or matter of consultation entered by the user.

[0481] "Organizations and individuals" refers to appropriate departments and employees that are suggested as suitable contact points based on the content of the consultation.

[0482] "Means to promote communication" refers to functions that promote interaction and information sharing between employees.

[0483] "Robots working in factories" refers to automated machinery that performs work in factories.

[0484] "Workers" refers to human employees working in a factory.

[0485] "Stress" refers to the mental or physical strain felt by workers.

[0486] "Appropriate action" refers to specific actions or countermeasures suggested based on the user's feelings and the content of their inquiry.

[0487] To implement the present invention, the following system configuration is required.

[0488] System Configuration

[0489] 1. Hardware:

[0490] Robots working in a factory

[0491] Camera for emotion recognition

[0492] server

[0493] 2. Software:

[0494] Python

[0495] emotion_recognition library

[0496] database_connector library

[0497] Program processing explanation

[0498] The server stores employee information (department, skill set, project performance) in a database. The database is updated whenever an employee acquires a new skill or participates in a new project. It is also updated appropriately when an employee resigns or changes departments.

[0499] The emotion engine recognizes the user's emotions and suggests appropriate actions based on those emotions. Specifically, if a robot working in a factory recognizes the emotions of a worker and detects stress, it will suggest actions to reduce that stress.

[0500] Specific examples

[0501] For example, consider a system in which a robot working in a factory detects stress in a worker and suggests the worker take a break. In this system, an emotion recognition camera captures the worker's facial expressions and analyzes their emotions using the emotion_recognition library. Based on the analysis results, the server suggests appropriate actions.

[0502] Prompt Sentence Examples

[0503] Examples of prompts to be input to a generative AI model include:

[0504] "Design a system where a robot working in a factory can recognize the emotions of workers and suggest appropriate actions if it senses stress. Specifically, include a function that suggests a worker take a break if they are feeling stressed."

[0505] By using this prompt, the generative AI model is expected to propose a specific system design.

[0506] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0507] Step 1:

[0508] The server stores employee information (department, skill set, project performance) in a database. As input, basic employee information and project participation history are provided. This information is saved in the database and updated every time an employee acquires a new skill or participates in a new project. As output, the latest employee information is saved in the database.

[0509] Step 2:

[0510] The server receives facial expression data of the worker acquired from the emotion recognition camera. As input, the image data captured by the camera is provided. Using the emotion_recognition library, this image data is analyzed to recognize the worker's emotions. As output, the recognized emotion data is generated.

[0511] Step 3:

[0512] The server evaluates the worker's stress level based on the recognized emotion data. The emotion data is provided as input. The emotion engine is used to calculate the stress level and evaluate the result. The stress level evaluation result is generated as output.

[0513] Step 4:

[0514] The server proposes appropriate actions based on the stress level assessment results. As input, the stress level assessment results are provided. If the stress level is high, the server determines specific actions, such as suggesting a break to the worker. As output, the proposed actions are generated.

[0515] Step 5:

[0516] The terminal notifies the worker of the action proposed by the server. As input, the proposed action is provided. Using the notification system, a message suggesting a break is displayed to the worker. As output, the notification to the worker is complete.

[0517] Step 6:

[0518] The user (worker) receives the notification and follows the suggested action. As input, the notified message is provided. The worker performs the action, such as taking a break. As output, the worker's stress is reduced.

[0519] Example 2

[0520] Next, a description will be given of Example 2 of Form 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."

[0521] Conventional employee information management systems made it difficult for users to quickly find employees with specific skills or experience. They also lacked appropriate methods for encouraging communication between employees, and in particular did not promote communication based on users' emotions. This led to problems such as reduced project efficiency and employee satisfaction.

[0522] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0523] In this invention, the server includes means for accepting consultation details entered by the user, means for searching a database based on the accepted consultation details and suggesting relevant employees or organizations, means for recognizing the user's emotions and suggesting communication methods based on those emotions, and means for promoting communication with the suggested employees or organizations. This enables the user to quickly find appropriate employees or organizations and further promotes communication based on emotions.

[0524] A "user" is a person who uses the system to input the details of a consultation and provides information to find appropriate employees or organizations.

[0525] "Consultation content" is information that a user enters into the system about a particular skill or experience, or a problem they want to solve.

[0526] A "database" is a collection of information that stores information such as employee skills, experience, and department.

[0527] An "employee" is a member of an organization whose information is registered in the database and who possesses particular skills and experience.

[0528] An "organization" is a group such as a department or team to which employees belong.

[0529] "Emotion" refers to a psychological state that can be recognized from the user's facial expression, tone of voice, etc.

[0530] "Communication methods" are means of exchanging information and interacting with other employees or organizations that are suggested based on the user's feelings.

[0531] "Suggestions" are information about suitable employees, organizations, or communication methods that the system provides to the user.

[0532] "Knowledge" refers to information such as employee skills, experience, and department that is stored in a database.

[0533] "Searching" is the process of extracting information from a database based on specific criteria.

[0534] "Analysis" is the process of processing a user's emotional data and determining their psychological state.

[0535] "Facilitation" means providing support and encouragement to promote communication with the proposed employee or organization.

[0536] MODE FOR CARRYING OUT THE INVENTION

[0537] This invention is a system that searches a database based on the consultation content entered by the user and suggests relevant employees and organizations. It also includes a function to recognize the user's emotions, suggest communication methods based on those emotions, and promote communication between employees.

[0538] Hardware and software used

[0539] 1. Device:

[0540] A device that allows users to input their consultation details. Specifically, this includes PCs, smartphones, tablets, etc.

[0541] The device is equipped with a camera and microphone, which are used to collect the user's facial expressions and tone of voice.

[0542] 2. Server:

[0543] A central processing unit for database search, sentiment analysis, and suggestion generation.

[0544] The software used includes relational database management systems (RDBMS) such as MySQL and PostgreSQL, OpenCV (image processing library), Google Cloud Speech-to-Text (voice recognition service), and Emotion API (emotion analysis engine).

[0545] Program processing

[0546] 1. User enters the consultation details:

[0547] The user enters the details of their inquiry into an input form on the device. For example, they might enter, "I'm looking for an employee with expertise in data science."

[0548] 2. The device sends the input to the server:

[0549] The device sends the entered consultation details to the server as an HTTP request using the HTTPS protocol.

[0550] 3. The server searches the database:

[0551] The server analyzes the received consultation content and extracts keywords, such as "data science."

[0552] The server searches the MySQL database based on the extracted keywords and retrieves the corresponding employee information using an SQL query.

[0553] 4. The server generates the search results:

[0554] The server generates a list of employees that match the search results. For example, it generates a list of "Ichiro Sato (7 years of data science experience), Jiro Yamada (5 years of data science experience)."

[0555] 5. The server sends the results to the device:

[0556] The server sends the generated list to the terminal in JSON format.

[0557] 6. The terminal displays the results to the user:

[0558] The device displays the received search results to the user, who can check the results on the screen.

[0559] Communication promotion function using emotion engine

[0560] 1. Recognize user emotions:

[0561] The device's built-in camera and microphone are used to collect the user's facial expressions and tone of voice in real time.

[0562] 2. The device sends the emotion data to the server:

[0563] The device sends the collected emotion data to the server as an HTTP request using the HTTPS protocol.

[0564] 3. The server analyzes the emotion:

[0565] The server analyzes the received emotion data using software called Emotion API. For example, it analyzes whether the user is feeling happy.

[0566] 4. The server suggests a communication method:

[0567] The server then suggests appropriate communication methods based on the analysis results, such as "Would you like to set up a meeting with a colleague who shares your joy?"

[0568] 5. The server sends the proposal to the device:

[0569] The server sends the proposal to the terminal in JSON format.

[0570] 6. The device displays the suggestions to the user:

[0571] The device displays the received suggestions to the user, who can then check them on the screen.

[0572] 7. User accepts the suggestion:

[0573] If the user accepts the offer, the terminal sends the information to the server.

[0574] 8. The server sends notifications to the appropriate employees:

[0575] The server sends notifications to the appropriate employees and facilitates communication. Notifications are sent via email and chat tools.

[0576] Examples of specific examples and prompts

[0577] Examples:

[0578] Enter your inquiry: "We are looking for an employee with expertise in data science."

[0579] Search results: "Ichiro Sato (7 years of data science experience), Jiro Yamada (5 years of data science experience)"

[0580] Example prompt sentence:

[0581] Looking for a Project Management employee?

[0582] We are looking for employees with project management experience. Please provide us with a list.

[0583] When using the Emotion Engine:

[0584] If the user is feeling happy, suggest communicating with an employee who shares that emotion.

[0585] The above is an embodiment of the present invention.

[0586] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0587] Program processing flow

[0588] Database search function

[0589] Step 1:

[0590] The user inputs the consultation content.

[0591] Input: The user enters the consultation details into the input form on the device.

[0592] What happens: The user types "We're looking for someone with expertise in data science" and clicks the submit button.

[0593] Output: The input is displayed on the terminal.

[0594] Step 2:

[0595] The device sends the input to the server.

[0596] Input: The consultation content entered by the user.

[0597] Specific operation: The device sends the input consultation details to the server as an HTTP request using the HTTPS protocol.

[0598] Output: The server receives the consultation content.

[0599] Step 3:

[0600] The server searches the database.

[0601] Input: Received consultation content.

[0602] Specific operation: The server analyzes the received consultation content and extracts keywords. For example, the keyword "data science" is extracted. The server searches the MySQL database based on the extracted keywords. It uses an SQL query to retrieve the relevant employee information.

[0603] Output: A list of matching employees.

[0604] Step 4:

[0605] The server generates the search results.

[0606] Input: Employee information retrieved from the database.

[0607] Specific operation: The server generates a list of employees that match the search results. For example, it generates a list of "Ichiro Sato (7 years of data science experience), Jiro Yamada (5 years of data science experience)."

[0608] Output: The generated employee list.

[0609] Step 5:

[0610] The server sends the results to the terminal.

[0611] Input: The generated employee list.

[0612] Specific operation: The server sends the generated list to the terminal in JSON format.

[0613] Output: The terminal receives the employee list.

[0614] Step 6:

[0615] The terminal displays the results to the user.

[0616] Input: Employee list received from the server.

[0617] Specific operation: The device displays the received search results to the user, who can check the results on the screen.

[0618] Output: User checks employee list.

[0619] Communication promotion function using emotion engine

[0620] Step 1:

[0621] Recognize user emotions.

[0622] Input: The user's facial expression and tone of voice.

[0623] What it does: It uses the device's built-in camera and microphone to collect the user's facial expressions and tone of voice in real time.

[0624] Output: Collected emotion data.

[0625] Step 2:

[0626] The device transmits the emotion data to the server.

[0627] Input: Collected emotion data.

[0628] Specific operation: The device sends the collected emotion data to the server as an HTTP request using the HTTPS protocol.

[0629] Output: The server receives the emotion data.

[0630] Step 3:

[0631] The server analyzes the emotions.

[0632] Input: Received emotion data.

[0633] Specific operation: The server analyzes the received emotion data using software called Emotion API. For example, it analyzes that the user is feeling joy.

[0634] Output: Emotional state as a result of the analysis.

[0635] Step 4:

[0636] The server suggests a communication method.

[0637] Input: Emotional state as the result of the analysis.

[0638] Specific operation: The server suggests appropriate communication methods based on the analysis results, for example, "Would you like to set up a meeting with a colleague who shares your joy?"

[0639] Output: Proposal.

[0640] Step 5:

[0641] The server sends the proposal to the device.

[0642] Input: Proposal.

[0643] Specific operation: The server sends the proposal content to the device in JSON format.

[0644] Output: The device receives the proposal.

[0645] Step 6:

[0646] The terminal displays the suggestions to the user.

[0647] Input: The proposal received from the server.

[0648] Specific operation: The device displays the received suggestions to the user, who can then check the suggestions on the screen.

[0649] Output: User confirms the suggestion.

[0650] Step 7:

[0651] The user accepts the suggestion.

[0652] Input: Proposal.

[0653] Specific behavior: When the user accepts the suggestion, the device sends the information to the server.

[0654] Output: The server receives the offer acceptance information.

[0655] Step 8:

[0656] The server sends notifications to the appropriate employees.

[0657] Input: Proposal acceptance information.

[0658] What it does: The server sends notifications to the appropriate employees and facilitates communication. Notifications are sent via email and chat tools.

[0659] Output: The appropriate employee receives a notification.

[0660] (Application example 2)

[0661] Next, a description will be given of Application Example 2 of Form 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."

[0662] Conventional factory systems have had limitations in improving work efficiency and stimulating communication between workers, making it difficult to quickly find workers or machines with specific skills. Furthermore, there was no system that recognized workers' emotions and suggested appropriate communication methods, preventing sufficient improvements to the work environment. This resulted in problems such as reduced work efficiency and increased worker stress.

[0663] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0664] In this invention, the server includes means for accumulating employee information (department, skill set, project performance) as knowledge, means for suggesting answers and organizations or people to consult with based on the consultation content entered, means for stimulating communication between employees, means for searching for and suggesting workers or machines with specific skills, and means for recognizing the emotions of workers using an emotion recognition engine and suggesting appropriate communication methods.This enables improved work efficiency in the factory and smoother communication between workers.

[0665] "Employee information" refers to data about employees, such as department, skill set, and project performance.

[0666] "Knowledge" refers to accumulated information and knowledge that can be used for specific purposes.

[0667] "Consultation content" refers to the content of the question or problem that the user inputs into the system.

[0668] An "organization" refers to a group or group formed with a specific purpose.

[0669] A "person" refers to an individual with particular skills or knowledge.

[0670] "Communication" refers to the act of exchanging information and emotions.

[0671] "Worker" refers to a worker who performs specific tasks in a factory or on a work site.

[0672] "Machine" refers to a device or robot that performs a specific task automatically.

[0673] An "emotion recognition engine" refers to technology that identifies human emotions from data such as images and audio.

[0674] "Appropriate communication method" refers to the most effective means of exchanging information depending on the other person's feelings and the situation.

[0675] A system for carrying out this invention is configured as follows: The server includes means for accumulating employee information (department, skill set, project performance) as knowledge, means for suggesting answers and organizations or people to consult with based on the consultation content entered, means for stimulating communication between employees, means for searching for and suggesting workers or machines with specific skills, and means for recognizing the emotions of workers using an emotion recognition engine and suggesting appropriate communication methods.

[0676] First, the server uses an SQLite database to store employee information, including each employee's department, skill set, project history, etc. When a user searches for workers or machines with a particular skill, the server searches this database and provides a list of matching workers or machines.

[0677] Next, an emotion recognition engine (e.g., EmotionRecognizer) is used to recognize emotions from the worker's image and voice data. Based on the recognized emotions, the server suggests appropriate communication methods. These suggestions include, for example, communication methods that help the worker relax if they are feeling stressed, or methods that allow them to share their joy if they are feeling happy.

[0678] For example, if welding work needs to be done in a factory, the user searches for workers and machines with the skill "welding." The server searches the database and provides a list of relevant workers and machines. It also recognizes emotions using images of workers, and if a worker is feeling stressed, it suggests communication methods to help them relax.

[0679] Examples of prompts to input to a generative AI model include:

[0680] "Search for workers and machines with welding skills to perform welding work in the factory. Also, recognize the emotions of workers and suggest appropriate ways to communicate."

[0681] This system will improve work efficiency within the factory and enable smooth communication between workers.

[0682] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0683] Step 1:

[0684] Users enter keywords to search for workers or machines with specific skills.

[0685] Input: The keyword entered by the user (e.g. "welding")

[0686] Output: The keyword is sent to the server

[0687] Step 2:

[0688] The server searches an SQLite database to retrieve a list of workers and machines that match the entered keywords.

[0689] Input: The keyword entered by the user

[0690] Data processing: Matching skillsets in the database with keywords

[0691] Output: List of applicable workers and machines

[0692] Step 3:

[0693] The server provides the user with a list of workers and machines acquired.

[0694] Input: List of applicable workers and machines

[0695] Output: The list is displayed to the user

[0696] Step 4:

[0697] The user sends image and audio data to the server to recognize the worker's emotions.

[0698] Input: User-supplied image and audio data

[0699] Output: Image and audio data is sent to the server

[0700] Step 5:

[0701] The server uses an emotion recognition engine (EmotionRecognizer) to recognize the worker's emotions from the transmitted image and audio data.

[0702] Input: image and audio data

[0703] Data calculation: Emotion recognition engine analyzes data and identifies emotions

[0704] Output: Recognized emotion (e.g., "stressed")

[0705] Step 6:

[0706] The server suggests an appropriate communication method based on the recognized emotion.

[0707] Input: Recognized emotion

[0708] Data processing: Selecting communication methods based on emotions

[0709] Output: Suggestion of appropriate communication methods (e.g., "How to relax")

[0710] Step 7:

[0711] The server provides the suggested communication methods to the user.

[0712] Input: Appropriate communication methods

[0713] Output: The user is shown the suggestion

[0714] Example 3

[0715] Next, a description will be given of a third embodiment of the third embodiment. 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."

[0716] In modern companies, there are problems such as a lack of communication between employees and insufficient sharing of knowledge and experiences. There is also the challenge of employees finding it difficult to find appropriate counseling for emotional issues. These problems can have a negative impact on employee productivity and mental health, so effective solutions are needed.

[0717] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[0718] In this invention, the server includes means for accumulating employee information (department, skill set, project record) as knowledge, means for suggesting answers and organizations or people to consult with based on the consultation content entered, means for stimulating communication between employees, communication means for sending and receiving messages in real time, means for providing a forum function for sharing knowledge and experience, and means for analyzing user emotions and suggesting the most appropriate person to consult with. This promotes communication between employees, encourages the sharing of knowledge and experience, and makes it possible to suggest the most appropriate person to consult with based on the user's emotions.

[0719] "Employee information" refers to information such as an employee's department, skill set, and project track record.

[0720] "Knowledge" refers to accumulated employee information, knowledge, and experience.

[0721] "Consultation content" refers to questions, concerns, and matters for consultation entered by the user.

[0722] "Means of making suggestions" refers to the function of selecting and presenting appropriate answers and organizations or people to consult with based on the consultation content entered.

[0723] "Means to promote communication" refers to functions that enable employees to smoothly exchange information and opinions with each other.

[0724] "Communication methods" refers to the technologies and protocols used to send and receive messages in real time.

[0725] The "forum function" refers to an online platform where employees can share knowledge and experiences and exchange opinions.

[0726] "Means for analyzing emotions" refers to the technology or algorithms used to analyze and identify emotions from user input.

[0727] "Means to suggest people to consult" refers to the function of selecting and presenting appropriate organizations or people to consult with based on the analyzed emotions.

[0728] The present invention is a system that stimulates communication between employees, promotes the sharing of knowledge and experience, and suggests appropriate consultations based on the user's feelings. Specific embodiments of this system are described below.

[0729] Chat feature

[0730] The server provides a chat function that allows employees to send and receive messages in real time. This function is built using Node.js and Socket.IO. The terminal provides a chat client that runs on a browser, allowing users to exchange messages with other employees through the browser.

[0731] Examples:

[0732] The user types a message saying, "How's the project going?" and sends it.

[0733] The terminal sends this message to the server, which forwards it to the recipient.

[0734] The recipient's device displays the message and the recipient replies, "Everything is going well."

[0735] Forum feature

[0736] The server provides a forum function for employees to share knowledge and experience. The backend for this function is built using the Django framework and the database is PostgreSQL. The terminal provides a frontend built using React.js, and users can access the forum through a browser.

[0737] Examples:

[0738] A user creates a topic called "Opinions on a new technology wanted."

[0739] Another user posts a comment saying, "I used technology X on project Y and it was very useful."

[0740] Consultation suggestion function based on emotion engine

[0741] The server uses an emotion engine to suggest the best place to seek advice based on the user's emotions and employee information. This function uses NLTK, a Python natural language processing library, and an emotion analysis model. The server uses the Django framework to build the backend for the emotion engine and MySQL as the database. Users can access the emotion engine through their browser and receive suggestions for where to seek advice.

[0742] Examples:

[0743] The user types, "Recently, I've been feeling anxious about the pressure at work."

[0744] The server analyzes this input and identifies the emotion "anxiety."

[0745] The server searches the knowledge base for "experienced employee D who can alleviate the anxiety" and suggests it to the user.

[0746] This promotes communication between employees and encourages the sharing of knowledge and experiences. In addition, since appropriate consultations are suggested based on the user's feelings, it also contributes to the mental health care of employees. The flow of the identification process in the third embodiment will be described with reference to FIG. 21.

[0747] Chat feature

[0748] Step 1:

[0749] The user enters a message.

[0750] Specific behavior: The user accesses the chat interface on a browser and types "How's the project going?" in the message input field.

[0751] Input: The message entered by the user.

[0752] Output: The message is displayed in the input field.

[0753] Step 2:

[0754] The device sends a message to the server.

[0755] Specific operation: The terminal sends the input message to the server via WebSocket.

[0756] Input: The message entered by the user.

[0757] Output: The message is sent to the server.

[0758] Step 3:

[0759] The server receives the message and forwards it to the specified recipient.

[0760] Specific behavior: The server parses the received message and forwards it over the WebSocket connection to the specified recipient.

[0761] Input: Message sent from terminal.

[0762] Output: The message is forwarded to the recipient.

[0763] Step 4:

[0764] The recipient's device displays the message.

[0765] Specific operation: The recipient's device displays the message received from the server in the chat interface.

[0766] Input: The message forwarded from the server.

[0767] Output: The message appears in the recipient's chat interface.

[0768] Forum feature

[0769] Step 1:

[0770] A user creates a new topic.

[0771] Specific Action: A user accesses a forum interface and fills out a form to create a new topic with "I'm looking for opinions on a new technology."

[0772] Input: Topic information entered by the user.

[0773] Output: The topic information is displayed in a form.

[0774] Step 2:

[0775] The terminal transmits topic information to the server.

[0776] Specific operation: The terminal sends the entered topic information to the server via an HTTP POST request.

[0777] Input: Topic information entered by the user.

[0778] Output: The topic information is sent to the server.

[0779] Step 3:

[0780] The server stores the topic information in a database.

[0781] Specific operation: The server stores the received topic information in a database.

[0782] Input: Topic information sent from the device.

[0783] Output: Topic information is stored in the database.

[0784] Step 4:

[0785] Other users post comments to the topic.

[0786] Specific behavior: Other users enter comments on the topic through the forum interface, posting "I used technology X in project Y and found it very useful."

[0787] Input: Comments entered by other users.

[0788] Output: The comment is added to the topic.

[0789] Step 5:

[0790] The server saves the comment in a database and notifies the topic creator.

[0791] Specific operation: The server stores the received comment in a database and sends a notification to the topic creator.

[0792] Input: Comments submitted by other users.

[0793] Output: The comment is saved to the database and a notification is sent to the topic creator.

[0794] Consultation suggestion function based on emotion engine

[0795] Step 1:

[0796] The user inputs the emotion.

[0797] Specific actions: The user accesses the emotion engine interface and inputs, "Recently, I've been feeling anxious because of the pressure at work."

[0798] Input: Emotion information entered by the user.

[0799] Output: Emotion information is displayed in the input field.

[0800] Step 2:

[0801] The device transmits the emotion information to the server.

[0802] Specific operation: The device sends the input emotion information to the server via an HTTP POST request.

[0803] Input: Emotion information entered by the user.

[0804] Output: The emotion information is sent to the server.

[0805] Step 3:

[0806] The server analyzes the emotional information.

[0807] Specific operation: The server uses Python's NLTK library to analyze emotion information and identify the emotion "anxiety."

[0808] Input: Emotion information sent from the device.

[0809] Output: Parsed emotion information.

[0810] Step 4:

[0811] The server searches the knowledge base for an appropriate person to consult.

[0812] Specific operation: The server searches for "experienced employee D who can alleviate the anxiety" based on employee information stored in the knowledge base.

[0813] Input: Parsed sentiment information and knowledge-based employee information.

[0814] Output: Information on appropriate contacts.

[0815] Step 5:

[0816] The server returns the suggestions to the user.

[0817] Specific operation: The server returns the search results to the user and suggests that "Employee D is a good person to consult with to alleviate your concerns."

[0818] Input: appropriate consultation information.

[0819] Output: The proposed results are displayed to the user.

[0820] (Application example 3)

[0821] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[0822] Conventional factory communication systems often resulted in a lack of communication between workers, resulting in insufficient sharing of knowledge and experience. Furthermore, the system did not suggest appropriate places to seek advice based on the worker's feelings, which could delay problem resolution. This led to issues such as reduced work efficiency and employee satisfaction.

[0823] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[0824] In this invention, the server includes a means for accumulating employee information (department, skill set, project performance) as knowledge, a means for suggesting answers and organizations or people to consult with based on the input consultation content, a means for promoting communication between employees, a means for performing emotion analysis, and a means for suggesting the most appropriate person to consult with based on the results of the emotion analysis. This promotes communication between workers, makes it easier to share knowledge and experience, and makes it possible to suggest appropriate people to consult with based on emotions.

[0825] "Employee information" refers to data about employees, such as department, skill set, and project performance.

[0826] "Knowledge" refers to the collection of knowledge and experience accumulated within an organization.

[0827] "Consultation details" refers to the details of a question or problem that a user enters into the system.

[0828] "Answer" refers to the solution or information that the system provides in response to the user's inquiry.

[0829] "Consultation destination" refers to an organization or person suggested based on the content of the user's consultation.

[0830] "Means for promoting communication" refers to functions that allow employees to send messages to each other and share knowledge and experiences.

[0831] "Sentiment analysis" refers to the process of analyzing emotions from user input.

[0832] "Means for suggesting the most suitable person to consult" refers to a function that suggests the most suitable person to consult for the user based on the results of emotion analysis.

[0833] To implement this invention, a specific program must be installed on the robots used in the factory. This program stores employee information as knowledge and has the function of suggesting answers and organizations or people to consult based on the input consultation content. It also includes a function to perform emotion analysis and suggest the most appropriate consultation based on the results.

[0834] Hardware and software used

[0835] Hardware: Robots used in factories (e.g. KUKA, ABB)

[0836] Software: Python, TextBlob (sentiment analysis library)

[0837] Data processing and calculation

[0838] Accumulation of employee information

[0839] The server stores employee information (department, skill set, project performance) in a database, which is used to store employee knowledge and experience.

[0840] Input and analysis of consultation details

[0841] When a user inputs their question through the robot, the server analyzes the content and suggests appropriate answers and where to seek advice.To perform sentiment analysis, the TextBlob library is used to analyze emotions from the user's input.

[0842] Emotion analysis and consultation suggestions

[0843] Based on the results of the emotion analysis, the server will suggest the most appropriate counselor. For example, if a user enters "I'm worried because things haven't been going well at work recently," emotion analysis will determine this as "negative" and suggest an appropriate counselor.

[0844] Specific examples

[0845] Example prompt sentence:

[0846] "Recently, things haven't been going well at work and I'm worried."

[0847] "I'm having trouble figuring out how to operate this new machine."

[0848] "I'm glad the project is progressing well."

[0849] This will promote communication between workers, make it easier to share knowledge and experience, and enable suggestions for appropriate consultation based on emotions.

[0850] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[0851] Step 1:

[0852] The user inputs the consultation content through the robot.

[0853] Input: User's concerns (e.g., "Recently, things haven't been going well at work and I'm worried.")

[0854] Output: Text data of the consultation content

[0855] Specific operation: The user uses the robot's interface to input the content of their inquiry in text format.

[0856] Step 2:

[0857] The server receives the entered consultation content and performs emotion analysis.

[0858] Input: Text data of consultation content

[0859] Output: The result of the sentiment analysis (e.g. "negative")

[0860] Specific operation: The server uses the TextBlob library to analyze the text data of the consultation content and determine the emotion.

[0861] Step 3:

[0862] The server will suggest the most appropriate person to consult based on the results of emotion analysis.

[0863] Input: Sentiment analysis results (e.g., "negative"), employee information accumulated as knowledge

[0864] Output: Suggested contact (e.g., "Counselor")

[0865] Specific operation: The server compares the results of the emotion analysis with the knowledge database and selects the appropriate person to consult.

[0866] Step 4:

[0867] The server notifies the user of the suggested consultation destinations.

[0868] Input: Suggested contact (e.g., "Counselor")

[0869] Output: A message to inform the user

[0870] Specific operation: The server displays a message through the robot's interface to inform the user of the suggested consultation information.

[0871] Step 5:

[0872] The user initiates communication with the suggested contact.

[0873] Input: Proposed consultation information

[0874] Output: Start of communication

[0875] Specific behavior: The user uses the robot's interface to exchange messages with the suggested contacts.

[0876] 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.

[0877] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ) 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.

[0878] Another example of generative AI is Gemini (registered trademark) (Internet search engine). <url: https: gemini.google.com ?hl="ja">) are mentioned.

[0879] 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.

[0880] [Second embodiment]

[0881] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0882] 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.

[0883] 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).

[0884] 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.

[0885] 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.

[0886] 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).

[0887] 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.

[0888] 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.

[0889] 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.

[0890] 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.

[0891] 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.

[0892] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0893] "Example 1"

[0894] The system of the present invention stores employee information (department, skill set, project performance) in a database. This database is updated whenever an employee acquires a new skill or participates in a new project. It is also updated appropriately when an employee resigns or changes departments.

[0895] "Example 2"

[0896] When the user enters the content of the consultation, the system searches the database and suggests the employees and organizations that are most suitable for the consultation. For example, if an employee needs to find employees with specific skills to start a new project, they can enter that skill as a keyword and the system will provide a list of employees with that skill.

[0897] "Example 3"

[0898] In addition, the system also provides functions to promote communication between employees. For example, the system has a chat function that allows employees to send messages to each other. The system also provides a forum function that allows employees to share their knowledge and experience with each other. This allows employees to share their knowledge and experience and receive feedback from other employees.

[0899] The processing flow of each embodiment will be described below.

[0900] "Example 1"

[0901] Step 1: Every time an employee learns a new skill or takes on a new project, enter that information into the system.

[0902] Step 2: The system stores the entered information in a database.

[0903] Step 3: If an employee leaves the company or changes departments, enter that information into the system and update the database.

[0904] "Example 2"

[0905] Step 1: Enter the consultation details into the system.

[0906] Step 2: The system searches the database and suggests employees and organizations that best fit the needs of the customer.

[0907] Step 3: Communicate with the proposed employees and organizations.

[0908] "Example 3"

[0909] Step 1: Employees use the system's chat function to exchange messages with other employees.

[0910] Step 2: Employees use the system's forum function to share their knowledge and experiences.

[0911] Step 3: Receive feedback from others and update your knowledge and experience as needed.

[0912] Example 1

[0913] Next, a description will be given of Example 1 of Form 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."

[0914] With conventional employee information management systems, updating employee skill sets and project achievements is done manually, making it difficult to keep information up to date. Furthermore, updating information when an employee leaves the company or changes departments is tedious, making it difficult to quickly search for employees with specific skill sets or project achievements. Furthermore, the lack of functionality to promote communication between employees hinders knowledge sharing within the organization.

[0915] The identification process by the identification processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means. In this invention, the server includes means for storing employee information (department, skill set, project performance) in a database, means for transmitting input information to the server, means for saving and updating information received by the server in the database, means for updating the database when an employee leaves the company or changes departments, means for searching for employees with specific skill sets or project performance, means for displaying search results to the user, and means for stimulating communication between employees. This enables rapid searches and information updates while keeping employee information up-to-date, thereby realizing knowledge sharing and stimulating communication within the organization.

[0916] "Employee information" refers to information such as an employee's department, skill set, and project track record.

[0917] "Database" refers to an information system for storing and managing employee information.

[0918] "Server" refers to a computer system for storing and updating information in a database.

[0919] "Terminal" refers to a device through which a user inputs information and transmits it to a server.

[0920] "User" means a person who utilizes the system to enter, retrieve, and display information.

[0921] A "skill set" refers to the collection of skills and knowledge that an employee possesses.

[0922] "Project performance" refers to the history and results of projects in which employees have participated.

[0923] "Search tools" refers to the ability to search the database for employees with specific skill sets or project experience.

[0924] "Means of communication" refers to functions that promote information exchange and contact between employees.

[0925] "Information update means" refers to the function for keeping the information in the database up to date when an employee leaves the company or changes departments.

[0926] This invention is a system that stores and manages employee information (department, skill set, project performance) in a database. The system consists of three main elements: a server, terminals, and users.

[0927] Hardware and software used

[0928] Server: Database server (e.g. MySQL, PostgreSQL)

[0929] Devices: PCs and mobile devices used by employees

[0930] Software: Web application (e.g., Django, Ruby on Rails)

[0931] Program processing flow

[0932] 1. Entering data

[0933] When a user acquires a new skill or participates in a new project, the user enters the required information into an input form in a web application.

[0934] Specifically, the user opens a web browser and enters "Python programming" into the skill addition form.

[0935] 2. Data transmission

[0936] The terminal transmits the information entered by the user to the server.

[0937] Specifically, the device sends "Python programming" skill information to the server using an HTTP POST request.

[0938] 3. Data storage

[0939] The server stores the received information in a database.

[0940] Specifically, the server adds a new record to the "skills" table in the database, saving "Python programming."

[0941] 4. Updating Data

[0942] The server updates the existing employee information.

[0943] Specifically, the server searches for the corresponding employee record and adds new skill information.

[0944] 5. Data Deletion

[0945] When a user leaves the company or changes departments, the administrator enters that information through a web application.

[0946] The terminal transmits the input information to the server.

[0947] The server updates the database based on the received information, deleting or changing the relevant employee information.

[0948] Specifically, the administrator clicks the "Resign" button, and the server deletes the corresponding employee record from the database.

[0949] 6. Searching for data

[0950] When a user wants to search for employees with a particular skill set or project experience, they enter a search query through the web application.

[0951] The terminal sends a search query to the server.

[0952] The server searches the database and returns the relevant employee information to the terminal.

[0953] Specifically, the user searches for employees with "Python programming" and the server returns a list of matching employees.

[0954] 7. Displaying Data

[0955] The terminal displays the returned information to the user.

[0956] Specifically, the terminal displays the search results on a web page, and the user sees a list of employees who have "Python programming."

[0957] Example prompts for generative AI models

[0958] "Generate a prompt statement to add newly acquired skills to the database."

[0959] "Generate a prompt to search for employees with specific project experience."

[0960] In this way, employee information can be kept up to date while enabling quick searches and updates, thereby stimulating knowledge sharing and communication within the organization.

[0961] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0962] Step 1: Enter your data

[0963] When a user acquires a new skill or participates in a new project, the user enters the required information into an input form in a web application.

[0964] Input: A user opens a web browser and types "Python programming" into the add skill form.

[0965] Output: The information entered is sent to the terminal.

[0966] Step 2: Sending data

[0967] The terminal transmits the information entered by the user to the server.

[0968] Input: User-entered "Python Programming" skill information.

[0969] Data processing: The device generates an HTTP POST request and creates a request containing the entered information.

[0970] Output: An HTTP POST request is sent to the server.

[0971] Step 3: Save your data

[0972] The server stores the received information in a database.

[0973] Input: "Python Programming" skill information sent from the device.

[0974] Data processing: The server adds a new record to the "skills" table in the database and saves the entered skill information.

[0975] Output: The new skill information is saved in the database.

[0976] Step 4: Update data

[0977] The server updates the existing employee information.

[0978] Input: A record in the database where the new skill information is saved.

[0979] Data processing: The server searches for the corresponding employee record and adds the new skill information.

[0980] Output: The updated employee information is saved in the database.

[0981] Step 5: Delete data

[0982] When a user leaves the company or changes departments, the administrator enters that information through a web application.

[0983] Input: The administrator clicks the "Resign" button and enters the relevant employee's information.

[0984] Data processing: The terminal sends the entered information to the server.

[0985] Output: The server deletes the corresponding employee record from the database.

[0986] Step 6: Search for data

[0987] When a user wants to search for employees with a particular skill set or project experience, they enter a search query through the web application.

[0988] Input: A user enters a query to search for employees with "Python programming."

[0989] Data processing: The device sends the search query to the server.

[0990] Output: The server searches the database and returns the relevant employee information to the terminal.

[0991] Step 7: View the data

[0992] The terminal displays the returned information to the user.

[0993] Input: Search results returned by the server.

[0994] Data processing: The device formats the search results for display on a web page.

[0995] Output: User sees a list of employees who have "Python Programming".

[0996] (Application example 1)

[0997] Next, a description will be given of Application Example 1 of Form 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."

[0998] With the conventional employee information management system, it was difficult to effectively utilize employees' skill sets and project achievements, making it difficult to assign optimal tasks. Furthermore, updating information every time an employee acquired a new skill or participated in a project was time-consuming, making efficient operation impossible. Furthermore, there was a lack of ways to promote communication between employees, making it difficult to improve productivity across the organization.

[0999] 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.

[1000] In this invention, the server includes a means for accumulating employee information (department, skill set, project performance) as knowledge, a means for suggesting answers and organizations or people to consult with based on the input consultation content, a means for stimulating communication between employees, a means for suggesting optimal tasks based on the employee's skill set and project performance, and a means for updating employee information. This makes it possible to effectively utilize employees' skill sets and project performance to assign optimal tasks. Furthermore, updating employee information is automated, enabling efficient operations. Furthermore, this stimulates communication between employees, which is expected to improve productivity throughout the organization.

[1001] "Employee information" refers to information such as an employee's department, skill set, and project track record.

[1002] "Knowledge" refers to accumulated knowledge and information, especially employee information stored in a database.

[1003] "Consultation content" refers to the content of questions or consultations entered by employees.

[1004] "Answer" refers to the solution or information provided in response to the inquiry.

[1005] "Consultation destination" refers to organizations or individuals suggested based on the content of the consultation.

[1006] "Organization" refers to a group such as a company or department.

[1007] "Person" refers to a specific employee or professional.

[1008] "Communication" refers to the exchange of information and dialogue between employees.

[1009] A "skill set" refers to the collection of skills and abilities that an employee possesses.

[1010] "Project performance" refers to the history and results of projects in which employees have participated in the past.

[1011] "Best-fit work" refers to the work that is best suited to an employee based on their skill set and project performance.

[1012] "Update" refers to employee information being changed based on new skills or project achievements.

[1013] The system for implementing this invention accumulates employee information (department, skill set, project performance) as knowledge and suggests answers and organizations or people to consult with based on the input consultation content. It also has the function of stimulating communication between employees and suggesting optimal work based on employees' skill sets and project performance. It also has the function of updating employee information.

[1014] Hardware and software used

[1015] Hardware: Servers, factory robots, user devices (PCs, smartphones)

[1016] Software: SQLite database, Python program

[1017] System configuration

[1018] 1. Employee information collection:

[1019] The server stores information about employees' departments, skill sets, and project achievements in a database, allowing for centralized management of information about employees' skills and achievements.

[1020] 2. Proposal based on consultation:

[1021] The server then suggests the most appropriate answers and organizations or people to consult based on the consultation details entered by the user, allowing the user to quickly obtain appropriate information and support.

[1022] 3. Increased communication:

[1023] The server provides functionality to facilitate communication between employees, including functionality to facilitate contact with suggested organizations and individuals for consultation.

[1024] 4. Optimal working suggestions:

[1025] The server suggests the most suitable tasks based on the employee's skill set and project performance, allowing the factory robot to automatically assign the most suitable tasks to employees.

[1026] 5. Updating Employee Information:

[1027] The server automatically updates employee information whenever they acquire new skills or take on new projects, ensuring the database is always up-to-date.

[1028] Specific examples of processing

[1029] For example, if an employee with employee ID 1 has the skills of "welding" and "assembly," the server will suggest the most suitable work for these skills from the database. When a user inputs "Please suggest the best work based on the skill set of employee ID 1," the server will search the database and suggest the best work.

[1030] Prompt Sentence Examples

[1031] "Please suggest the best tasks for employee ID 1 based on their skill set."

[1032] In this way, the system can effectively utilize employees' skill sets and project experience to optimally assign tasks. It also automates updating employee information, leading to efficient operations. It also promotes communication between employees, which is expected to improve productivity across the organization.

[1033] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1034] Step 1:

[1035] The server stores employee information (department, skill set, project performance) in a database.

[1036] Input: Employee's department, skill set, project performance

[1037] Output: Employee information stored in the database

[1038] What it does: The server adds information about employees to the database whenever they acquire new skills or join new projects. It also updates the database when employees leave the company or change departments.

[1039] Step 2:

[1040] The user inputs the consultation content from the terminal.

[1041] Input: Consultation details

[1042] Output: Consultation details sent to the server

[1043] Specific operation: The user uses a terminal (PC or smartphone) to input the consultation content and send it to the server.

[1044] Step 3:

[1045] The server suggests answers and organizations or people to consult based on the input consultation content.

[1046] Input: Consultation details, employee information stored in the database

[1047] Output: Suggested answers and organizations or people to consult

[1048] Specific operation: The server analyzes the content of the consultation and refers to employee information stored in a database to select the most appropriate answer and the organization or person to consult.

[1049] Step 4:

[1050] The server provides functions to promote communication between employees.

[1051] Input: Suggested organization or person to consult

[1052] Output: A means of communication to facilitate communication

[1053] Specific operation: The server provides functions (e.g., chat functions and email notifications) to facilitate contact with the suggested organizations and people to consult with.

[1054] Step 5:

[1055] The server suggests the best work to do based on employees' skill sets and project experience.

[1056] Input: Employee skill sets, project performance

[1057] Output: Optimal work suggestions

[1058] Specific operation: The server refers to the employee's skill set and project track record stored in a database, and selects and proposes the most suitable work.

[1059] Step 6:

[1060] The server updates the employee information.

[1061] Input: New skills and project achievements

[1062] Output: Updated employee information

[1063] What it does: The server automatically updates employee information in the database whenever an employee acquires a new skill or takes on a new project.

[1064] Example 2

[1065] Next, a description will be given of Example 2 of Form 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."

[1066] With the previous system, it was difficult to find the right person to consult based on an employee's skills and experience, which led to problems with inactive communication between employees. Furthermore, there was a lack of a way to quickly and accurately suggest the right employee or organization based on the content of the consultation, which could lead to a decline in project efficiency.

[1067] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1068] In this invention, the server includes means for accumulating employee information (department, skill set, project performance) as knowledge, means for extracting keywords based on the input consultation content, means for searching the database based on the extracted keywords and generating a list of relevant employees and organizations, means for providing the generated list to the user, and means for stimulating communication between employees. This enables the user to quickly and accurately find the appropriate employee or organization, stimulating communication between employees and improving project efficiency.

[1069] "Employee information" refers to data about employees, such as department, skill set, and project performance.

[1070] "Knowledge" refers to accumulated information and knowledge, including employee information in particular.

[1071] "Consultation content" refers to the content of questions or requests that users input into the system.

[1072] "Keywords" refer to important words and phrases extracted from the content of the consultation.

[1073] A "database" refers to a system that stores data such as employee information in an organized manner and makes it searchable.

[1074] "List" refers to a list of relevant employees and organizations generated as search results.

[1075] "User" refers to a person who uses the system to input the details of a consultation and receive the results.

[1076] "Means to promote communication" refers to functions and methods for promoting information exchange and collaboration among employees.

[1077] This invention is a system that accumulates employee information as knowledge and suggests appropriate employees and organizations based on the content of an inquiry that has been input. A specific embodiment of this system will be described below.

[1078] System configuration

[1079] The system uses the following hardware and software:

[1080] Hardware: Servers (e.g., general-purpose servers), terminals (e.g., personal computers, smartphones)

[1081] Software: database management systems (e.g., MySQL), search algorithms (e.g., Elasticsearch)

[1082] Program processing

[1083] The server receives the consultation content from the user. The consultation content includes keywords for searching for employees with specific skills and experience. The server searches the database based on the received keywords and generates a list of relevant employees and organizations.

[1084] The system works as follows:

[1085] 1. The user enters the consultation content. For example, "We are looking for an employee with Python programming skills for a new project."

[1086] 2. The device sends the entered consultation details to the server. At this time, the device sends the data using an HTTP request.

[1087] 3. The server receives the consultation content and extracts keywords. For example, it extracts the keyword "Python programming."

[1088] 4. The server searches the database and generates a list of matching employees and organizations, using Elasticsearch for fast and efficient searching.

[1089] 5. The server sends the generated list to the device, again using an HTTP response to send the data.

[1090] 6. The terminal displays the list to the user, who can then select the appropriate employee or organization from the displayed list.

[1091] Specific examples

[1092] For example, a user may enter "I'm looking for an employee with Python programming skills for a new project" into a terminal. The terminal then sends this request to the server. The server receives the request and extracts the keyword "Python programming." The server then uses Elasticsearch to search the MySQL database and generate a list of employees with Python programming skills. The server then sends the generated list to the terminal, which then displays it to the user. The user can then select a suitable employee from the displayed list.

[1093] Example prompts to input to a generative AI model:

[1094] "We're looking for employees with Python programming skills for a new project. Can you suggest suitable candidates?"

[1095] After entering this prompt, the system will search the database and provide a list of employees who have Python programming skills.

[1096] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1097] Step 1:

[1098] The user inputs the consultation content.

[1099] The user inputs their inquiry into the device to find employees with specific skills and experience. For example, they might input "I'm looking for an employee with Python programming skills for a new project." The input inquiry is saved on the device.

[1100] Step 2:

[1101] The terminal transmits the input consultation content to the server.

[1102] The terminal sends the consultation details entered by the user to the server as an HTTP request. The input data is sent to the server in text format.

[1103] Step 3:

[1104] The server receives the consultation content and extracts keywords.

[1105] The server analyzes the consultation content received from the device and extracts important keywords. For example, the keyword "Python programming" is extracted. The extracted keywords are used in the next search process.

[1106] Step 4:

[1107] The server searches the database and generates a list of relevant employees and organizations.

[1108] The server uses Elasticsearch to search the MySQL database based on the extracted keywords, and generates a list of employees with Python programming skills. The list contains employee information retrieved from the database.

[1109] Step 5:

[1110] The server sends the generated list to the terminal.

[1111] The server sends the generated list of employees and organizations to the terminal as an HTTP response in text or JSON format.

[1112] Step 6:

[1113] The terminal displays the list to the user.

[1114] The terminal displays the list received from the server to the user, who can then select the appropriate employee or organization from the displayed list. The display format can be a list or a table.

[1115] (Application example 2)

[1116] Next, a description will be given of Application Example 2 of Form 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."

[1117] Conventional systems accumulate employee information as knowledge and can suggest appropriate organizations and individuals based on the content of the consultation, but they lack the functionality to quickly search for and suggest workers with specific skills. Furthermore, the means to stimulate communication between employees are limited, and the functionality to promote effective communication with the suggested consultation partners is insufficient. This makes it difficult to quickly find workers with the skills necessary to perform specific tasks within the factory, resulting in a decline in work efficiency.

[1118] The identification process by the identification 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 accumulating employee information (department, skill set, project performance) as knowledge, means for suggesting answers and organizations or people to consult with based on the input consultation content, means for stimulating communication between employees, and means for searching for and suggesting workers with specific skills. This makes it possible to quickly search for and suggest workers with specific skills, thereby improving work efficiency in the factory.

[1119] "Employee information" refers to information such as an employee's department, skill set, and project track record.

[1120] "Knowledge" refers to accumulated information and knowledge, including employee information in particular.

[1121] "Consultation content" refers to the questions or consultation content that users enter into the system.

[1122] An "organization" refers to a group or group formed with a specific purpose.

[1123] A "person" refers to an individual with particular skills or knowledge.

[1124] "Communication" refers to the act of exchanging information and opinions.

[1125] "Skills" refer to the abilities and techniques required to perform specific tasks or jobs.

[1126] "Worker" refers to a worker who performs specific tasks in a factory or on a work site.

[1127] "Search" refers to the act of finding specific information from a database or the like.

[1128] "Proposal" refers to the act of presenting a particular option or solution.

[1129] The system for implementing this invention includes means for accumulating employee information (department, skill set, project performance) as knowledge, means for suggesting answers and organizations or people to consult with based on the input consultation content, means for stimulating communication between employees, and means for searching for and suggesting workers with specific skills.

[1130] The server uses an SQLite database to store employee information, including department, skill set, project performance, etc. When a user searches for workers with specific skills, the server searches the database based on the entered skill keywords and generates a list of workers with the corresponding skills.

[1131] The system is implemented using a Python program. When a user inputs a skill keyword, the server executes a search query against the SQLite database to retrieve the corresponding worker information. The retrieved information is then displayed to the user in a list format.

[1132] As a concrete example, consider the case where a new welding machine is introduced in a factory and workers with the skills to operate that welding machine are needed. When a user enters "welding machine operation," the server searches the database and generates a list of workers with that skill. The user can then select an appropriate worker based on this list.

[1133] An example of a prompt is as follows:

[1134] "We are looking for employees with the skills to operate new welding machines. Please provide us with a list of employees with the skills to operate welding machines."

[1135] This system makes it possible to quickly search for and suggest workers with specific skills, thereby improving work efficiency within the factory.

[1136] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1137] Step 1:

[1138] A user uses a terminal to input keywords to search for workers with specific skills. The input keywords are sent to the server. The input data are keywords related to the skills the user is looking for.

[1139] Step 2:

[1140] The server searches the SQLite database based on the received keywords. It generates a search query and extracts workers with the corresponding skills from the employee information in the database (department, skill set, project history). The input data is the keyword entered by the user, and the output data is a list of workers with the corresponding skills.

[1141] Step 3:

[1142] The server formats the list of workers obtained as search results and converts it into a format for display to the user. Specifically, it compiles information such as the worker's name, department, skill set, and project performance into a list. The input data is the worker information obtained as search results, and the output data is the formatted list of workers.

[1143] Step 4:

[1144] The server sends the formatted list of workers to the user's terminal. The user can check the list of workers with the relevant skills on the terminal. The input data is the formatted list of workers, and the output data is the list of workers displayed on the user's terminal.

[1145] Step 5:

[1146] The user selects an appropriate worker based on the displayed list of workers. Specific work requests and communication can then be made to the selected worker. The input data is the list of workers confirmed by the user, and the output data is the content of the work requests and communication sent to the selected worker.

[1147] Example 3

[1148] Next, a description will be given of Example 3 of Form Example 3. 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."

[1149] Conventional employee information management systems have the problem of not encouraging active communication between employees and preventing sufficient sharing of knowledge and experience. Furthermore, the lack of real-time messaging and forum functionality means that information exchange between employees is not smooth. This can lead to a decline in employee productivity and cooperation.

[1150] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[1151] In this invention, the server includes means for accumulating employee information (department, skill set, project performance) as knowledge, means for suggesting answers and organizations or people to consult with based on the consultation content entered, means for stimulating communication between employees, means for sending and receiving messages in real time, and means for providing a forum for sharing knowledge and experience. This facilitates communication between employees and enables the smooth sharing of knowledge and experience.

[1152] "Employee information" refers to information such as an employee's department, skill set, and project track record.

[1153] "Knowledge" refers to the accumulation of employee information and data on knowledge and experience that is stored in a shareable format.

[1154] "Consultation content" refers to the questions and consultation content that employees enter into the system.

[1155] "Answer" refers to the solution or information provided in response to the inquiry.

[1156] "Consultation destination" refers to organizations or individuals suggested based on the content of the consultation.

[1157] "Means to promote communication" refers to functions that enable employees to smoothly exchange information and opinions with each other.

[1158] "Means of sending and receiving messages in real time" refers to the ability for employees to send and receive messages instantly.

[1159] "Forum" refers to an online message board where employees can share knowledge and experiences and exchange opinions.

[1160] "Server" refers to a computer system that manages the entire system and provides various functions.

[1161] "Terminal" refers to a device (e.g., PC, smartphone) used by an employee to access and operate the system.

[1162] This invention is a system for promoting communication among employees and sharing knowledge and experience. This system operates in cooperation with three parties: a server, a terminal, and a user.

[1163] Hardware and software used

[1164] Hardware:

[1165] High-performance servers (e.g., high-performance computer systems)

[1166] Device (e.g. PC, smartphone)

[1167] software:

[1168] Chat functionality: APIs for real-time messaging (e.g., messaging APIs)

[1169] Forum functionality: Online bulletin board software for sharing knowledge and experiences (e.g., forum software)

[1170] Specific operation of the system

[1171] server:

[1172] The server stores employee information (department, skill set, project track record) as knowledge. This allows it to suggest appropriate answers and organizations or people to consult with based on the consultation content entered. The server also provides a function for sending and receiving messages in real time, promoting active communication between employees. Furthermore, the server provides a forum function, providing a place for employees to share their knowledge and experience.

[1173] Device:

[1174] Terminals are devices that users use to access and operate the system. Users can use the terminals to send and receive messages in real time using the chat function, and can also use the forum function to share knowledge and experience and get feedback from other employees.

[1175] User:

[1176] Users are employees who use the system. They can use the chat and forum functions on their terminals to communicate with other employees. For example, if User A sends a message to User B saying, "Thank you for your hard work. Could you please send me the materials for today's meeting?", the message sent from User A's terminal is delivered to User B's terminal via the server. User B can receive the message and reply in real time.

[1177] Also, if user C posts a topic called "New Project Proposal" to the forum, the post sent from user C's device will be stored in the database via the server. Other users can view and comment on the topic.

[1178] Prompt Sentence Examples

[1179] "Design a system to facilitate communication between employees. The system should include real-time chat functionality and forum functionality for knowledge sharing. Use high-performance computer systems as the hardware and messaging APIs and forum software."

[1180] In this way, it is clearly explained how the server, terminal, and user cooperate to operate the system. The flow of the specific processing in the third embodiment will be explained with reference to FIG.

[1181] Step 1:

[1182] The user types a chat message.

[1183] A user opens a chat application on a terminal and enters text into a message input field, which is temporarily stored in the terminal's memory.

[1184] Step 2:

[1185] The device sends a message to the server.

[1186] The terminal sends the message entered by the user to the server using a messaging API. The message is sent as an HTTP request. The input is the user's message, and the output is an HTTP request to the server.

[1187] Step 3:

[1188] The server receives and processes the message.

[1189] The server parses the received HTTP request, extracts the message content and sender information, and processes the message to route it to the appropriate recipient. The input is the HTTP request, and the output is the recipient information and the message content.

[1190] Step 4:

[1191] The server sends the message to the recipient's terminal.

[1192] The server sends a message to the recipient's device. The recipient's device receives the message in real time via a messaging API. The input is recipient information and message content, and the output is an HTTP response to the recipient's device.

[1193] Step 5:

[1194] The recipient's device displays the message.

[1195] The receiver's device displays the received message in the chat application interface. The receiver can check the message and reply. The input is the HTTP response, and the output is the message displayed in the chat application interface.

[1196] Step 6:

[1197] A user creates a post in a forum.

[1198] A user opens a forum application on their device and enters a new topic or comment, which is temporarily stored in the device's memory.

[1199] Step 7:

[1200] The device sends the post to the server.

[1201] The terminal sends user-created posts to the server using the forum API. Posts are sent as HTTP requests. The input is the user post, and the output is an HTTP request to the server.

[1202] Step 8:

[1203] The server stores the posts in a database.

[1204] The server stores the received posts in a database. The database holds information such as the post content, author, and creation date. The input is an HTTP request, and the output is the post data stored in the database.

[1205] Step 9:

[1206] The server notifies other users of updates to the forum.

[1207] The server notifies other users when a new post has been made to the forum. The notification is done in real time. The input is the post data stored in the database, and the output is the notification to other users.

[1208] Step 10:

[1209] Other users' devices will display forum updates.

[1210] Other users' devices receive forum updates and display new posts in the application interface. Users can view and comment on new posts. The input is notifications, and the output is new posts displayed in the forum application interface.

[1211] (Application example 3)

[1212] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[1213] While conventional robots used in factories can perform individual tasks efficiently, they face the challenge of having difficulty sharing work progress and problems due to a lack of communication between robots. Furthermore, there is no way for robots to share the knowledge and experience they have gained with other robots, which can lead to a decline in overall work efficiency. To solve these issues, a system is needed that allows robots to communicate efficiently with each other and share knowledge and experience.

[1214] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[1215] In this invention, the server includes a means for accumulating employee information (department, skill set, project record) as knowledge, a means for suggesting answers and organizations or people to consult with based on the consultation content entered, a means for promoting communication between employees, a means for providing a chat function that allows robots to send messages to each other, and a means for providing a forum function for robots to share knowledge and experience. This enables robots to communicate with each other efficiently and quickly share work progress and problems. Furthermore, by sharing the knowledge and experience gained by robots with other robots, overall work efficiency can be improved.

[1216] "Employee information" refers to information about employees, such as department, skill set, and project performance.

[1217] "Knowledge" refers to accumulated information and knowledge, such as employee information and robot knowledge and experience.

[1218] "Consultation content" refers to questions or issues entered by employees or robots.

[1219] An "answer" is a solution or information provided in response to a question.

[1220] "Consultation destination" refers to an organization or person suggested based on the content of the consultation.

[1221] An "organization" is a group or group formed with a specific purpose.

[1222] A "person" is an individual with a specific role or skill.

[1223] "Communication" is the act of exchanging information and opinions.

[1224] The "chat function" allows robots and employees to send messages to each other.

[1225] The "forum function" is a function that allows robots and employees to share knowledge and experiences.

[1226] "Work efficiency" refers to the ability or degree to which work is performed efficiently.

[1227] "Progress" refers to the progress of a task or project.

[1228] A "problem" is a challenge or obstacle that arises in a task or project.

[1229] The system for implementing this invention aims to enable robots used in a factory to communicate with each other efficiently and share knowledge and experience. A specific embodiment of this system will be described below.

[1230] System Configuration

[1231] The system consists of the following main components:

[1232] 1. Server: Employee information (department, skill set, project track record) is accumulated as knowledge, and based on the inputted consultation content, answers and organizations or people to consult are suggested.

[1233] 2. Robot: A robot that works in a factory and has chat and forum functions.

[1234] 3. Network: A network for communication between the server and the robot.

[1235] Program processing

[1236] The server processes the data using the following means:

[1237] Employee information storage: The server stores employee information such as department, skill set, and project performance in a database. This data also includes the knowledge and experience gained by the robot during its work.

[1238] Analysis of consultation content: The server analyzes the consultation content entered by the robot or employee and suggests appropriate answers and organizations or people to consult.

[1239] Chat function: Robots can send messages to each other via the server, allowing them to share their work progress and problems in real time.

[1240] Forum function: Robots can post the knowledge and experience they gain during their work on the forum and share it with other robots.

[1241] Hardware and software used

[1242] Hardware: Robots, servers, and network equipment used in factories

[1243] Software: Python programs, database management systems (e.g., MySQL), thread libraries

[1244] Specific examples

[1245] For example, if a robot discovers a new, efficient work procedure in a factory, it can share that knowledge with other robots through the forum function, allowing other robots to adopt the same efficient procedure, improving overall work efficiency.

[1246] Example prompt sentence:

[1247] A robot in your factory has discovered a new, more efficient way to work. Think about how you can share this knowledge with other robots to improve their work efficiency.

[1248] In this way, robots can communicate with each other efficiently and share knowledge and experience, improving work efficiency throughout the factory and enabling quicker response when problems arise.

[1249] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1250] Step 1:

[1251] The server accumulates employee information (department, skill set, project performance) in a database. As input, it receives information provided by each employee and robot and stores it in the database. As data processing, it converts the information into an appropriate format and stores it in the database. As output, it obtains the accumulated employee information.

[1252] Step 2:

[1253] The server receives the consultation content input from the robot or an employee. It receives the text data of the consultation content as input and analyzes it. As data processing, it uses natural language processing technology to analyze the consultation content and identify the appropriate answer or organization or person to consult. As output, it obtains a suggested answer or person to consult.

[1254] Step 3:

[1255] The server sends the suggested answers and information on where to consult to the robot. As input, it receives the answers and information on where to consult obtained in step 2 and sends this to the robot. As data processing, it converts the information into an appropriate format and sends it to the robot. As output, the robot receives the suggested answers and information on where to consult.

[1256] Step 4:

[1257] Based on the information received from the server, the robot exchanges messages with other robots using the chat function. As input, it generates a message based on the information received from the server and sends it to other robots. As data calculation, it generates and sends a message. As output, other robots receive the message.

[1258] Step 5:

[1259] Robots use the forum function to share the knowledge and experience they gain while working. As input, they post the knowledge and experience they gain while working to the forum. As data processing, the posted content is converted into an appropriate format and saved in the forum. As output, other robots can obtain the knowledge and experience from the forum.

[1260] Step 6:

[1261] The server accumulates the knowledge and experience posted on the forum in a database. As input, it receives the knowledge and experience posted by the robots and stores it in the database. As data processing, it converts the information into an appropriate format and stores it in the database. As output, it obtains the accumulated knowledge and experience.

[1262] Step 7:

[1263] The robot improves work efficiency based on the knowledge and experience it gains from the forum. As input, it receives knowledge and experience acquired from the forum and applies it to the work. As data calculation, it optimizes the work procedure based on the knowledge and experience. As output, work efficiency is improved.

[1264] 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.

[1265] "Example 1"

[1266] One embodiment of the present invention is a system incorporating an emotion engine. This system accumulates employee information (department, skill set, project performance) as knowledge and suggests answers and organizations or people to consult with based on the content of the consultation entered. Furthermore, the emotion engine recognizes the user's emotions and suggests organizations or people to consult with based on those emotions. Specifically, if it recognizes that the user is feeling stressed, it suggests employees who are thought to be able to alleviate that stress.

[1267] "Example 2"

[1268] Another embodiment of the present invention is a system in which an emotion engine has the function of promoting communication between employees. This system recognizes the user's emotions and suggests communication methods based on those emotions. Specifically, if the system recognizes that the user is feeling joy, it encourages communication with employees who share that joy.

[1269] "Example 3"

[1270] Furthermore, as another embodiment of the present invention, there is a system in which an emotion engine suggests organizations or people to consult with based on employee information accumulated as knowledge and the user's emotions. This system combines the user's emotions and employee information to suggest the most appropriate person to consult with. Specifically, if it recognizes that the user is feeling anxious, it suggests experienced employees who are thought to be able to alleviate the anxiety.

[1271] The processing flow of each embodiment will be described below.

[1272] "Example 1"

[1273] Step 1: The system accumulates employee information (department, skill set, project performance) as knowledge.

[1274] Step 2: When the user inputs the content of their inquiry, the system will suggest answers and organizations or people to consult based on the content.

[1275] Step 3: The emotion engine recognizes the user's emotions and suggests organizations or people to consult with based on those emotions. Specifically, if the engine recognizes that the user is feeling stressed, it will suggest employees who are thought to be able to alleviate that stress.

[1276] "Example 2"

[1277] Step 1: The emotion engine recognizes the user's emotion.

[1278] Step 2: The emotion engine suggests ways to communicate based on the emotion. Specifically, if the engine recognizes that the user is feeling happy, it will encourage communication with employees who share that happiness.

[1279] "Example 3"

[1280] Step 1: The emotion engine combines the user's emotions with employee information to suggest the best person to consult.

[1281] Step 2: Specifically, if it is recognized that the user is feeling anxious, it will suggest experienced employees who may be able to alleviate that anxiety.

[1282] Example 1

[1283] Next, a description will be given of Example 1 of Form 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."

[1284] While conventional employee information management systems can manage employee skill sets and project performance, they lack the functionality to suggest appropriate consultations based on the user's emotions. Furthermore, they lack specific methods for promoting communication between employees, which means they are unable to fully reduce employee stress or improve work efficiency.

[1285] 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.

[1286] In this invention, the server includes means for accumulating employee information (department, skill set, project performance) as knowledge, means for suggesting answers and organizations or people to consult with based on the consultation content entered, means for recognizing the user's emotions using an emotion engine and suggesting organizations or people to consult with based on those emotions, and means for stimulating communication between employees. This makes it possible to suggest appropriate organizations or people to consult with based on the user's emotions, thereby reducing employee stress and improving work efficiency.

[1287] "Employee information" refers to information such as an employee's department, skill set, and project track record.

[1288] "Knowledge" refers to the accumulation of employee information and the knowledge and information shared within the organization.

[1289] An "emotion engine" refers to software or algorithms that analyze emotions from user input and suggest appropriate responses based on those emotions.

[1290] "Consultation content" refers to the content of the consultation or question that the user inputs into the system.

[1291] "Consultation destination" refers to an organization or person suggested based on the content of the user's consultation.

[1292] "Means to promote communication" refers to functions and methods for promoting interaction and information sharing among employees.

[1293] A "server" is a computer that is the central part of a system and performs processes such as data storage, analysis, and proposals.

[1294] "Terminal" refers to a device through which a user accesses the system to enter information and view results.

[1295] This invention is a system that stores employee information (department, skill set, project performance) in a database and suggests appropriate answers and consultations based on the content of the user's consultation. It also includes a function that uses an emotion engine to recognize the user's emotions and suggests consultations based on those emotions.

[1296] System configuration

[1297] The server stores employee information in a database. Specifically, the database is updated every time an employee acquires a new skill or participates in a new project. The database is also updated appropriately when an employee leaves the company or changes departments. The server can use, for example, MySQL or PostgreSQL as its database management system (DBMS).

[1298] The terminal accepts input from the user. When the user inputs the content of the consultation, the content is sent to the server. The terminal is often implemented as a web browser or a mobile application.

[1299] The server analyzes the received consultation content and recognizes the user's emotions using an emotion engine, which can use, for example, the Google Cloud Natural Language API or IBM Watson's emotion analysis function.

[1300] The server then searches the database for appropriate organizations or people to consult with based on the emotions it recognizes. For example, if it recognizes that the user is feeling stressed, it will suggest employees who can help alleviate that stress.

[1301] The terminal displays the suggestions received from the server to the user, who can then select an appropriate consultation provider based on the displayed information.

[1302] Specific examples

[1303] If a user types, "I've been feeling a lot of stress at work lately," the emotion engine will recognize the word "stress." The server will search its database for employees with skills that can help reduce stress and suggest them to the user.

[1304] Example prompt sentence:

[1305] "I've been feeling a lot of pressure at work lately and it's stressful. Who can I talk to?"

[1306] This system efficiently manages employee information and suggests appropriate consultation sources based on the user's emotions, thereby contributing to reducing employee stress and improving work efficiency.

[1307] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1308] Step 1:

[1309] The user inputs the consultation content from the terminal.

[1310] Specific actions: The user enters "I've been feeling a lot of pressure at work lately and it's stressful" into the input form displayed on the device screen.

[1311] Input: User's inquiry (text format)

[1312] Output: Consultation details entered into the terminal

[1313] Step 2:

[1314] The terminal transmits the input consultation content to the server.

[1315] Specific operation: The device converts the consultation content entered by the user into JSON format and sends it to the server using an HTTP POST request.

[1316] Input: Consultation details entered into the device (text format)

[1317] Output: Consultation details sent to the server (JSON format)

[1318] Step 3:

[1319] The server analyzes the consultation content and recognizes the user's emotions using an emotion engine.

[1320] Specific operation: The server parses the received JSON data and passes it to the emotion engine. The emotion engine extracts the emotion "stress" from the text and returns it to the server.

[1321] Input: Consultation content sent to the server (JSON format)

[1322] Output: Emotion recognized by the emotion engine (e.g., stress)

[1323] Step 4:

[1324] Based on the emotion recognized by the server, a search is made for appropriate organizations or people to consult from a database.

[1325] Specific operation: The server executes a database query to search for employees who have skills that can help reduce stress or who have received similar consultations in the past. For example, it searches for employees with the skill "stress management."

[1326] Input: Emotion recognized by the emotion engine (e.g., stress)

[1327] Output: Information on appropriate organizations and people to consult found in the database

[1328] Step 5:

[1329] The server sends the search results to the terminal.

[1330] Specific operation: The server converts the search results into JSON format and sends them to the terminal as an HTTP response.

[1331] Input: Information on appropriate organizations and people to consult found in the database

[1332] Output: Search results sent to the device (JSON format)

[1333] Step 6:

[1334] The terminal displays the search results to the user.

[1335] Specific operation: The device analyzes the received JSON data and displays to the user, "Please consult with employee A, who has stress management skills."

[1336] Input: Search results sent to the terminal (JSON format)

[1337] Output: Search results displayed to the user (in text format)

[1338] (Application example 1)

[1339] Next, a description will be given of Application Example 1 of Form 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."

[1340] Conventional employee information management systems have difficulty providing appropriate support and advice that takes into account employees' emotions. Furthermore, the robots working in factories lacked the functionality to recognize employees' emotions and suggest appropriate actions, preventing them from fully reducing stress and promoting efficient communication. This created challenges for improving employee satisfaction and productivity.

[1341] 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.

[1342] In this invention, the server includes means for accumulating employee information (department, skill set, project performance) as knowledge, means for suggesting answers and organizations or people to consult with based on the consultation content entered, means for stimulating communication between employees, means for recognizing the user's emotions using an emotion engine and suggesting appropriate actions based on those emotions, and means installed in robots working in factories to recognize the emotions of workers and suggest appropriate actions when stress is detected. This makes it possible to provide appropriate support and advice that takes employees' emotions into consideration, thereby reducing stress among workers and promoting efficient communication.

[1343] "Employee information" refers to information such as an employee's department, skill set, and project track record.

[1344] "Knowledge" refers to accumulated information and knowledge, including employee information in particular.

[1345] An "emotion engine" refers to a system that recognizes a user's emotions and suggests appropriate actions based on those emotions.

[1346] "Consultation content" refers to the question or matter of consultation entered by the user.

[1347] "Organizations and individuals" refers to appropriate departments and employees that are suggested as suitable contact points based on the content of the consultation.

[1348] "Means to promote communication" refers to functions that promote interaction and information sharing between employees.

[1349] "Robots working in factories" refers to automated machinery that performs work in factories.

[1350] "Workers" refers to human employees working in a factory.

[1351] "Stress" refers to the mental or physical strain felt by workers.

[1352] "Appropriate action" refers to specific actions or countermeasures suggested based on the user's feelings and the content of their inquiry.

[1353] To implement the present invention, the following system configuration is required.

[1354] System Configuration

[1355] 1. Hardware:

[1356] Robots working in a factory

[1357] Camera for emotion recognition

[1358] server

[1359] 2. Software:

[1360] Python

[1361] emotion_recognition library

[1362] database_connector library

[1363] Program processing explanation

[1364] The server stores employee information (department, skill set, project performance) in a database. The database is updated whenever an employee acquires a new skill or participates in a new project. It is also updated appropriately when an employee resigns or changes departments.

[1365] The emotion engine recognizes the user's emotions and suggests appropriate actions based on those emotions. Specifically, if a robot working in a factory recognizes the emotions of a worker and detects stress, it will suggest actions to reduce that stress.

[1366] Specific examples

[1367] For example, consider a system in which a robot working in a factory detects stress in a worker and suggests the worker take a break. In this system, an emotion recognition camera captures the worker's facial expressions and analyzes their emotions using the emotion_recognition library. Based on the analysis results, the server suggests appropriate actions.

[1368] Prompt Sentence Examples

[1369] Examples of prompts to be input to a generative AI model include:

[1370] "Design a system where a robot working in a factory can recognize the emotions of workers and suggest appropriate actions if it senses stress. Specifically, include a function that suggests a worker take a break if they are feeling stressed."

[1371] By using this prompt, the generative AI model is expected to propose a specific system design.

[1372] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1373] Step 1:

[1374] The server stores employee information (department, skill set, project performance) in a database. As input, basic employee information and project participation history are provided. This information is saved in the database and updated every time an employee acquires a new skill or participates in a new project. As output, the latest employee information is saved in the database.

[1375] Step 2:

[1376] The server receives facial expression data of the worker acquired from the emotion recognition camera. As input, the image data captured by the camera is provided. Using the emotion_recognition library, this image data is analyzed to recognize the worker's emotions. As output, the recognized emotion data is generated.

[1377] Step 3:

[1378] The server evaluates the worker's stress level based on the recognized emotion data. The emotion data is provided as input. The emotion engine is used to calculate the stress level and evaluate the result. The stress level evaluation result is generated as output.

[1379] Step 4:

[1380] The server proposes appropriate actions based on the stress level assessment results. As input, the stress level assessment results are provided. If the stress level is high, the server determines specific actions, such as suggesting a break to the worker. As output, the proposed actions are generated.

[1381] Step 5:

[1382] The terminal notifies the worker of the action proposed by the server. As input, the proposed action is provided. Using the notification system, a message suggesting a break is displayed to the worker. As output, the notification to the worker is complete.

[1383] Step 6:

[1384] The user (worker) receives the notification and follows the suggested action. As input, the notified message is provided. The worker performs the action, such as taking a break. As output, the worker's stress is reduced.

[1385] Example 2

[1386] Next, a description will be given of Example 2 of Form 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."

[1387] Conventional employee information management systems made it difficult for users to quickly find employees with specific skills or experience. They also lacked appropriate methods for encouraging communication between employees, and in particular did not promote communication based on users' emotions. This led to problems such as reduced project efficiency and employee satisfaction.

[1388] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1389] In this invention, the server includes means for accepting consultation details entered by the user, means for searching a database based on the accepted consultation details and suggesting relevant employees or organizations, means for recognizing the user's emotions and suggesting communication methods based on those emotions, and means for promoting communication with the suggested employees or organizations. This enables the user to quickly find appropriate employees or organizations and further promotes communication based on emotions.

[1390] A "user" is a person who uses the system to input the details of a consultation and provides information to find appropriate employees or organizations.

[1391] "Consultation content" is information that a user enters into the system about a particular skill or experience, or a problem they want to solve.

[1392] A "database" is a collection of information that stores information such as employee skills, experience, and department.

[1393] An "employee" is a member of an organization whose information is registered in the database and who possesses particular skills and experience.

[1394] An "organization" is a group such as a department or team to which employees belong.

[1395] "Emotion" refers to a psychological state that can be recognized from the user's facial expression, tone of voice, etc.

[1396] "Communication methods" are means of exchanging information and interacting with other employees or organizations that are suggested based on the user's feelings.

[1397] "Suggestions" are information about suitable employees, organizations, or communication methods that the system provides to the user.

[1398] "Knowledge" refers to information about employees' skills, experience, departments, etc. stored in a database.

[1399] "Searching" is the process of extracting information from a database based on specific criteria.

[1400] "Analysis" is the process of processing a user's emotional data and determining their psychological state.

[1401] "Facilitation" means providing support and encouragement to promote communication with the proposed employee or organization.

[1402] MODE FOR CARRYING OUT THE INVENTION

[1403] This invention is a system that searches a database based on the consultation content entered by the user and suggests relevant employees and organizations. It also includes a function to recognize the user's emotions, suggest communication methods based on those emotions, and promote communication between employees.

[1404] Hardware and software used

[1405] 1. Device:

[1406] A device that allows users to input their consultation details. Specifically, this includes PCs, smartphones, tablets, etc.

[1407] The device is equipped with a camera and microphone, which are used to collect the user's facial expressions and tone of voice.

[1408] 2. Server:

[1409] A central processing unit for database search, sentiment analysis, and suggestion generation.

[1410] The software used includes relational database management systems (RDBMS) such as MySQL and PostgreSQL, OpenCV (image processing library), Google Cloud Speech-to-Text (voice recognition service), and Emotion API (emotion analysis engine).

[1411] Program processing

[1412] 1. User enters the consultation details:

[1413] The user enters the details of their inquiry into an input form on the device. For example, they might enter, "I'm looking for an employee with expertise in data science."

[1414] 2. The device sends the input to the server:

[1415] The device sends the entered consultation details to the server as an HTTP request using the HTTPS protocol.

[1416] 3. The server searches the database:

[1417] The server analyzes the received consultation content and extracts keywords, such as "data science."

[1418] The server searches the MySQL database based on the extracted keywords and retrieves the corresponding employee information using an SQL query.

[1419] 4. The server generates the search results:

[1420] The server generates a list of employees that match the search results. For example, it generates a list of "Ichiro Sato (7 years of data science experience), Jiro Yamada (5 years of data science experience)."

[1421] 5. The server sends the results to the device:

[1422] The server sends the generated list to the terminal in JSON format.

[1423] 6. The terminal displays the results to the user:

[1424] The device displays the received search results to the user, who can check the results on the screen.

[1425] Communication promotion function using emotion engine

[1426] 1. Recognize user emotions:

[1427] The device's built-in camera and microphone are used to collect the user's facial expressions and tone of voice in real time.

[1428] 2. The device sends the emotion data to the server:

[1429] The device sends the collected emotion data to the server as an HTTP request using the HTTPS protocol.

[1430] 3. The server analyzes the emotion:

[1431] The server analyzes the received emotion data using software called Emotion API. For example, it analyzes whether the user is feeling happy.

[1432] 4. The server suggests a communication method:

[1433] The server then suggests appropriate communication methods based on the analysis results, such as "Would you like to set up a meeting with a colleague who shares your joy?"

[1434] 5. The server sends the proposal to the device:

[1435] The server sends the proposal to the terminal in JSON format.

[1436] 6. The device displays the suggestions to the user:

[1437] The device displays the received suggestions to the user, who can then check them on the screen.

[1438] 7. User accepts the suggestion:

[1439] If the user accepts the offer, the terminal sends the information to the server.

[1440] 8. The server sends notifications to the appropriate employees:

[1441] The server sends notifications to the appropriate employees and facilitates communication. Notifications are sent via email and chat tools.

[1442] Examples of specific examples and prompts

[1443] Examples:

[1444] Consultation details: "We are looking for an employee with expertise in data science."

[1445] Search results: "Ichiro Sato (7 years of data science experience), Jiro Yamada (5 years of data science experience)"

[1446] Example prompt sentence:

[1447] Looking for a Project Management employee?

[1448] We are looking for employees with project management experience. Please provide us with a list.

[1449] When using the Emotion Engine:

[1450] If the user is feeling happy, suggest communicating with an employee who shares that emotion.

[1451] The above is an embodiment of the present invention.

[1452] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1453] Program processing flow

[1454] Database search function

[1455] Step 1:

[1456] The user inputs the consultation content.

[1457] Input: The user enters the consultation details into the input form on the device.

[1458] What happens: The user types "We're looking for someone with expertise in data science" and clicks the submit button.

[1459] Output: The input is displayed on the terminal.

[1460] Step 2:

[1461] The device sends the input to the server.

[1462] Input: The consultation content entered by the user.

[1463] Specific operation: The device sends the input consultation details to the server as an HTTP request using the HTTPS protocol.

[1464] Output: The server receives the consultation content.

[1465] Step 3:

[1466] The server searches the database.

[1467] Input: Received consultation content.

[1468] Specific operation: The server analyzes the received consultation content and extracts keywords. For example, the keyword "data science" is extracted. The server searches the MySQL database based on the extracted keywords. It uses an SQL query to retrieve the relevant employee information.

[1469] Output: A list of matching employees.

[1470] Step 4:

[1471] The server generates the search results.

[1472] Input: Employee information retrieved from the database.

[1473] Specific operation: The server generates a list of employees that match the search results. For example, it generates a list of "Ichiro Sato (7 years of data science experience), Jiro Yamada (5 years of data science experience)."

[1474] Output: The generated employee list.

[1475] Step 5:

[1476] The server sends the results to the terminal.

[1477] Input: The generated employee list.

[1478] Specific operation: The server sends the generated list to the terminal in JSON format.

[1479] Output: The terminal receives the employee list.

[1480] Step 6:

[1481] The terminal displays the results to the user.

[1482] Input: Employee list received from the server.

[1483] Specific operation: The device displays the received search results to the user, who can check the results on the screen.

[1484] Output: User checks employee list.

[1485] Communication promotion function using emotion engine

[1486] Step 1:

[1487] Recognize user emotions.

[1488] Input: The user's facial expression and tone of voice.

[1489] What it does: It uses the device's built-in camera and microphone to collect the user's facial expressions and tone of voice in real time.

[1490] Output: Collected emotion data.

[1491] Step 2:

[1492] The device transmits the emotion data to the server.

[1493] Input: Collected emotion data.

[1494] Specific operation: The device sends the collected emotion data to the server as an HTTP request using the HTTPS protocol.

[1495] Output: The server receives the emotion data.

[1496] Step 3:

[1497] The server analyzes the emotions.

[1498] Input: Received emotion data.

[1499] Specific operation: The server analyzes the received emotion data using software called Emotion API. For example, it analyzes that the user is feeling joy.

[1500] Output: Emotional state as a result of the analysis.

[1501] Step 4:

[1502] The server suggests a communication method.

[1503] Input: Emotional state as the result of the analysis.

[1504] Specific operation: The server suggests appropriate communication methods based on the analysis results, for example, "Would you like to set up a meeting with a colleague who shares your joy?"

[1505] Output: Proposal.

[1506] Step 5:

[1507] The server sends the proposal to the device.

[1508] Input: Proposal.

[1509] Specific operation: The server sends the proposal content to the device in JSON format.

[1510] Output: The device receives the proposal.

[1511] Step 6:

[1512] The terminal displays the suggestions to the user.

[1513] Input: The proposal received from the server.

[1514] Specific operation: The device displays the received suggestions to the user, who can then check the suggestions on the screen.

[1515] Output: User confirms the suggestion.

[1516] Step 7:

[1517] The user accepts the suggestion.

[1518] Input: Proposal.

[1519] Specific behavior: When the user accepts the suggestion, the device sends the information to the server.

[1520] Output: The server receives the offer acceptance information.

[1521] Step 8:

[1522] The server sends notifications to the appropriate employees.

[1523] Input: Proposal acceptance information.

[1524] What it does: The server sends notifications to the appropriate employees and facilitates communication. Notifications are sent via email and chat tools.

[1525] Output: The appropriate employee receives a notification.

[1526] (Application example 2)

[1527] Next, a description will be given of Application Example 2 of Form 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."

[1528] Conventional factory systems have had limitations in improving work efficiency and stimulating communication between workers, making it difficult to quickly find workers or machines with specific skills. Furthermore, there was no system that recognized workers' emotions and suggested appropriate communication methods, preventing sufficient improvements to the work environment. This resulted in problems such as reduced work efficiency and increased worker stress.

[1529] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1530] In this invention, the server includes means for accumulating employee information (department, skill set, project performance) as knowledge, means for suggesting answers and organizations or people to consult with based on the consultation content entered, means for stimulating communication between employees, means for searching for and suggesting workers or machines with specific skills, and means for recognizing the emotions of workers using an emotion recognition engine and suggesting appropriate communication methods.This enables improved work efficiency in the factory and smoother communication between workers.

[1531] "Employee information" refers to data about employees, such as department, skill set, and project performance.

[1532] "Knowledge" refers to accumulated information and knowledge that can be used for specific purposes.

[1533] "Consultation content" refers to the content of the question or problem that the user inputs into the system.

[1534] An "organization" refers to a group or group formed with a specific purpose.

[1535] A "person" refers to an individual with particular skills or knowledge.

[1536] "Communication" refers to the act of exchanging information and emotions.

[1537] "Worker" refers to a worker who performs specific tasks in a factory or on a work site.

[1538] "Machine" refers to a device or robot that performs a specific task automatically.

[1539] An "emotion recognition engine" refers to technology that identifies human emotions from data such as images and audio.

[1540] "Appropriate communication method" refers to the most effective means of exchanging information depending on the other person's feelings and the situation.

[1541] A system for carrying out this invention is configured as follows: The server includes means for accumulating employee information (department, skill set, project performance) as knowledge, means for suggesting answers and organizations or people to consult with based on the consultation content entered, means for stimulating communication between employees, means for searching for and suggesting workers or machines with specific skills, and means for recognizing the emotions of workers using an emotion recognition engine and suggesting appropriate communication methods.

[1542] First, the server uses an SQLite database to store employee information, including each employee's department, skill set, project history, etc. When a user searches for workers or machines with a particular skill, the server searches this database and provides a list of matching workers or machines.

[1543] Next, an emotion recognition engine (e.g., EmotionRecognizer) is used to recognize emotions from the worker's image and voice data. Based on the recognized emotions, the server suggests appropriate communication methods. These suggestions include, for example, communication methods that help the worker relax if they are feeling stressed, or methods that allow them to share their joy if they are feeling happy.

[1544] For example, if welding work needs to be done in a factory, the user searches for workers and machines with the skill "welding." The server searches the database and provides a list of relevant workers and machines. It also recognizes emotions using images of workers, and if a worker is feeling stressed, it suggests communication methods to help them relax.

[1545] Examples of prompts to input to a generative AI model include:

[1546] "Search for workers and machines with welding skills to perform welding work in the factory. Also, recognize the emotions of workers and suggest appropriate ways to communicate."

[1547] This system will improve work efficiency within the factory and enable smooth communication between workers.

[1548] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1549] Step 1:

[1550] Users enter keywords to search for workers or machines with specific skills.

[1551] Input: The keyword entered by the user (e.g. "welding")

[1552] Output: The keyword is sent to the server

[1553] Step 2:

[1554] The server searches an SQLite database to retrieve a list of workers and machines that match the entered keywords.

[1555] Input: The keyword entered by the user

[1556] Data processing: Matching skillsets in the database with keywords

[1557] Output: List of applicable workers and machines

[1558] Step 3:

[1559] The server provides the user with a list of workers and machines acquired.

[1560] Input: List of applicable workers and machines

[1561] Output: The list is displayed to the user

[1562] Step 4:

[1563] The user sends image and audio data to the server to recognize the worker's emotions.

[1564] Input: User-supplied image and audio data

[1565] Output: Image and audio data is sent to the server

[1566] Step 5:

[1567] The server uses an emotion recognition engine (EmotionRecognizer) to recognize the worker's emotions from the transmitted image and audio data.

[1568] Input: image and audio data

[1569] Data calculation: Emotion recognition engine analyzes data and identifies emotions

[1570] Output: Recognized emotion (e.g., "stressed")

[1571] Step 6:

[1572] The server suggests an appropriate communication method based on the recognized emotion.

[1573] Input: Recognized emotion

[1574] Data processing: Selecting communication methods based on emotions

[1575] Output: Suggestion of appropriate communication methods (e.g., "How to relax")

[1576] Step 7:

[1577] The server provides the suggested communication methods to the user.

[1578] Input: Appropriate communication methods

[1579] Output: The user is shown the suggestion

[1580] Example 3

[1581] Next, a description will be given of Example 3 of Form Example 3. 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."

[1582] In modern companies, there are problems such as a lack of communication between employees and insufficient sharing of knowledge and experiences. There is also the challenge of employees finding it difficult to find appropriate counseling for emotional issues. These problems can have a negative impact on employee productivity and mental health, so effective solutions are needed.

[1583] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[1584] In this invention, the server includes means for accumulating employee information (department, skill set, project record) as knowledge, means for suggesting answers and organizations or people to consult with based on the consultation content entered, means for stimulating communication between employees, communication means for sending and receiving messages in real time, means for providing a forum function for sharing knowledge and experience, and means for analyzing user emotions and suggesting the most appropriate person to consult with. This promotes communication between employees, encourages the sharing of knowledge and experience, and makes it possible to suggest the most appropriate person to consult with based on the user's emotions.

[1585] "Employee information" refers to information such as an employee's department, skill set, and project track record.

[1586] "Knowledge" refers to accumulated employee information, knowledge, and experience.

[1587] "Consultation content" refers to questions, concerns, and matters for consultation entered by the user.

[1588] "Means of making suggestions" refers to the function of selecting and presenting appropriate answers and organizations or people to consult with based on the consultation content entered.

[1589] "Means to promote communication" refers to functions that enable employees to smoothly exchange information and opinions with each other.

[1590] "Communication methods" refers to the technologies and protocols used to send and receive messages in real time.

[1591] The "forum function" refers to an online platform where employees can share knowledge and experiences and exchange opinions.

[1592] "Means for analyzing emotions" refers to the technology or algorithms used to analyze and identify emotions from user input.

[1593] "Means to suggest people to consult" refers to the function of selecting and presenting appropriate organizations or people to consult with based on the analyzed emotions.

[1594] The present invention is a system that stimulates communication between employees, promotes the sharing of knowledge and experience, and suggests appropriate consultations based on the user's feelings. Specific embodiments of this system are described below.

[1595] Chat feature

[1596] The server provides a chat function that allows employees to send and receive messages in real time. This function is built using Node.js and Socket.IO. The terminal provides a chat client that runs on a browser, allowing users to exchange messages with other employees through the browser.

[1597] Examples:

[1598] The user types a message saying, "How's the project going?" and sends it.

[1599] The terminal sends this message to the server, which forwards it to the recipient.

[1600] The recipient's device displays the message and the recipient replies, "Everything is going well."

[1601] Forum feature

[1602] The server provides a forum function for employees to share knowledge and experience. The backend for this function is built using the Django framework and the database is PostgreSQL. The terminal provides a frontend built using React.js, and users can access the forum through a browser.

[1603] Examples:

[1604] A user creates a topic called "Opinions on a new technology wanted."

[1605] Another user posts a comment saying, "I used technology X on project Y and it was very useful."

[1606] Consultation suggestion function based on emotion engine

[1607] The server uses an emotion engine to suggest the best place to seek advice based on the user's emotions and employee information. This function uses NLTK, a Python natural language processing library, and an emotion analysis model. The server uses the Django framework to build the backend for the emotion engine and MySQL as the database. Users can access the emotion engine through their browser and receive suggestions for where to seek advice.

[1608] Examples:

[1609] The user types, "Recently, I've been feeling anxious about the pressure at work."

[1610] The server analyzes this input and identifies the emotion "anxiety."

[1611] The server searches the knowledge base for "experienced employee D who can alleviate the anxiety" and suggests it to the user.

[1612] This promotes communication between employees and encourages the sharing of knowledge and experiences. In addition, since appropriate consultations are suggested based on the user's feelings, it also contributes to the mental health care of employees. The flow of the identification process in the third embodiment will be described with reference to FIG. 21.

[1613] Chat feature

[1614] Step 1:

[1615] The user enters a message.

[1616] Specific behavior: The user accesses the chat interface on a browser and types "How's the project going?" in the message input field.

[1617] Input: The message entered by the user.

[1618] Output: The message is displayed in the input field.

[1619] Step 2:

[1620] The device sends a message to the server.

[1621] Specific operation: The terminal sends the input message to the server via WebSocket.

[1622] Input: The message entered by the user.

[1623] Output: The message is sent to the server.

[1624] Step 3:

[1625] The server receives the message and forwards it to the specified recipient.

[1626] Specific behavior: The server parses the received message and forwards it over the WebSocket connection to the specified recipient.

[1627] Input: Message sent from terminal.

[1628] Output: The message is forwarded to the recipient.

[1629] Step 4:

[1630] The recipient's device displays the message.

[1631] Specific operation: The recipient's device displays the message received from the server in the chat interface.

[1632] Input: The message forwarded from the server.

[1633] Output: The message appears in the recipient's chat interface.

[1634] Forum feature

[1635] Step 1:

[1636] A user creates a new topic.

[1637] Specific Action: A user accesses a forum interface and fills out a form to create a new topic with "I'm looking for opinions on a new technology."

[1638] Input: Topic information entered by the user.

[1639] Output: The topic information is displayed in a form.

[1640] Step 2:

[1641] The terminal transmits topic information to the server.

[1642] Specific operation: The terminal sends the entered topic information to the server via an HTTP POST request.

[1643] Input: Topic information entered by the user.

[1644] Output: The topic information is sent to the server.

[1645] Step 3:

[1646] The server stores the topic information in a database.

[1647] Specific operation: The server stores the received topic information in a database.

[1648] Input: Topic information sent from the device.

[1649] Output: Topic information is stored in the database.

[1650] Step 4:

[1651] Other users post comments to the topic.

[1652] Specific behavior: Other users enter comments on the topic through the forum interface, posting "I used technology X in project Y and found it very useful."

[1653] Input: Comments entered by other users.

[1654] Output: The comment is added to the topic.

[1655] Step 5:

[1656] The server saves the comment in a database and notifies the topic creator.

[1657] Specific operation: The server stores the received comment in a database and sends a notification to the topic creator.

[1658] Input: Comments submitted by other users.

[1659] Output: The comment is saved to the database and a notification is sent to the topic creator.

[1660] Consultation suggestion function based on emotion engine

[1661] Step 1:

[1662] The user inputs the emotion.

[1663] Specific actions: The user accesses the emotion engine interface and inputs, "Recently, I've been feeling anxious because of the pressure at work."

[1664] Input: Emotion information entered by the user.

[1665] Output: Emotion information is displayed in the input field.

[1666] Step 2:

[1667] The device transmits the emotion information to the server.

[1668] Specific operation: The device sends the input emotion information to the server via an HTTP POST request.

[1669] Input: Emotion information entered by the user.

[1670] Output: The emotion information is sent to the server.

[1671] Step 3:

[1672] The server analyzes the emotional information.

[1673] Specific operation: The server uses Python's NLTK library to analyze emotion information and identify the emotion "anxiety."

[1674] Input: Emotion information sent from the device.

[1675] Output: Parsed emotion information.

[1676] Step 4:

[1677] The server searches the knowledge base for an appropriate person to consult.

[1678] Specific operation: The server searches for "experienced employee D who can alleviate the anxiety" based on employee information stored in the knowledge base.

[1679] Input: Parsed sentiment information and knowledge-based employee information.

[1680] Output: Information on appropriate contacts.

[1681] Step 5:

[1682] The server returns the suggestions to the user.

[1683] Specific operation: The server returns the search results to the user and suggests that "Employee D is a good person to consult with to alleviate your concerns."

[1684] Input: appropriate consultation information.

[1685] Output: The proposed results are displayed to the user.

[1686] (Application example 3)

[1687] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[1688] Conventional factory communication systems often resulted in a lack of communication between workers, resulting in insufficient sharing of knowledge and experience. Furthermore, the system did not suggest appropriate places to seek advice based on the worker's feelings, which could delay problem resolution. This led to issues such as reduced work efficiency and employee satisfaction.

[1689] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[1690] In this invention, the server includes a means for accumulating employee information (department, skill set, project performance) as knowledge, a means for suggesting answers and organizations or people to consult with based on the input consultation content, a means for promoting communication between employees, a means for performing emotion analysis, and a means for suggesting the most appropriate person to consult with based on the results of the emotion analysis. This promotes communication between workers, makes it easier to share knowledge and experience, and makes it possible to suggest appropriate people to consult with based on emotions.

[1691] "Employee information" refers to data about employees, such as department, skill set, and project performance.

[1692] "Knowledge" refers to the collection of knowledge and experience accumulated within an organization.

[1693] "Consultation details" refers to the details of a question or problem that a user enters into the system.

[1694] "Answer" refers to the solution or information that the system provides in response to the user's inquiry.

[1695] "Consultation destination" refers to an organization or person suggested based on the content of the user's consultation.

[1696] "Means for promoting communication" refers to functions that allow employees to send messages to each other and share knowledge and experiences.

[1697] "Sentiment analysis" refers to the process of analyzing emotions from user input.

[1698] "Means for suggesting the most suitable person to consult" refers to a function that suggests the most suitable person to consult for the user based on the results of emotion analysis.

[1699] To implement this invention, a specific program must be installed on the robots used in the factory. This program stores employee information as knowledge and has the function of suggesting answers and organizations or people to consult based on the input consultation content. It also includes a function to perform emotion analysis and suggest the most appropriate consultation based on the results.

[1700] Hardware and software used

[1701] Hardware: Robots used in factories (e.g. KUKA, ABB)

[1702] Software: Python, TextBlob (sentiment analysis library)

[1703] Data processing and calculation

[1704] Accumulation of employee information

[1705] The server stores employee information (department, skill set, project performance) in a database, which is used to store employee knowledge and experience.

[1706] Input and analysis of consultation details

[1707] When a user inputs their question through the robot, the server analyzes the content and suggests appropriate answers and where to seek advice.To perform sentiment analysis, the TextBlob library is used to analyze emotions from the user's input.

[1708] Emotion analysis and consultation suggestions

[1709] Based on the results of the emotion analysis, the server will suggest the most appropriate counselor. For example, if a user enters "I'm worried because things haven't been going well at work recently," emotion analysis will determine this as "negative" and suggest an appropriate counselor.

[1710] Specific examples

[1711] Example prompt sentence:

[1712] "Recently, things haven't been going well at work and I'm worried."

[1713] "I'm having trouble figuring out how to operate this new machine."

[1714] "I'm glad the project is progressing well."

[1715] This will promote communication between workers, make it easier to share knowledge and experience, and make it possible to suggest appropriate consultation sources based on emotions.

[1716] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1717] Step 1:

[1718] The user inputs the consultation content through the robot.

[1719] Input: User's concerns (e.g., "Recently, things haven't been going well at work and I'm worried.")

[1720] Output: Text data of the consultation content

[1721] Specific operation: The user uses the robot's interface to input the content of their inquiry in text format.

[1722] Step 2:

[1723] The server receives the entered consultation content and performs emotion analysis.

[1724] Input: Text data of consultation content

[1725] Output: The result of the sentiment analysis (e.g. "negative")

[1726] Specific operation: The server uses the TextBlob library to analyze the text data of the consultation content and determine the emotion.

[1727] Step 3:

[1728] The server will suggest the most appropriate person to consult based on the results of emotion analysis.

[1729] Input: Sentiment analysis results (e.g., "negative"), employee information accumulated as knowledge

[1730] Output: Suggested contact (e.g., "Counselor")

[1731] Specific operation: The server compares the results of the emotion analysis with the knowledge database and selects the appropriate person to consult.

[1732] Step 4:

[1733] The server notifies the user of the suggested consultation destinations.

[1734] Input: Suggested contact (e.g., "Counselor")

[1735] Output: A message to inform the user

[1736] Specific operation: The server displays a message through the robot's interface to inform the user of the suggested consultation information.

[1737] Step 5:

[1738] The user initiates communication with the suggested contact.

[1739] Input: Proposed consultation information

[1740] Output: Start of communication

[1741] Specific behavior: The user uses the robot's interface to exchange messages with the suggested contacts.

[1742] 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.

[1743] 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> ) 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.

[1744] Another example of generative AI is Gemini (internet search engine). <url: https: gemini.google.com ?hl="ja">) are mentioned.

[1745] 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.

[1746] [Third embodiment]

[1747] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1748] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1749] 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).

[1750] 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.

[1751] 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.

[1752] 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).

[1753] 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.

[1754] 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.

[1755] 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.

[1756] 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.

[1757] 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.

[1758] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[1759] "Example 1"

[1760] The system of the present invention stores employee information (department, skill set, project performance) in a database. This database is updated whenever an employee acquires a new skill or participates in a new project. It is also updated appropriately when an employee resigns or changes departments.

[1761] "Example 2"

[1762] When the user enters the content of the consultation, the system searches the database and suggests the employees and organizations that are most suitable for the consultation. For example, if an employee needs to find employees with specific skills to start a new project, they can enter that skill as a keyword and the system will provide a list of employees with that skill.

[1763] "Example 3"

[1764] In addition, the system also provides functions to promote communication between employees. For example, the system has a chat function that allows employees to send messages to each other. The system also provides a forum function that allows employees to share their knowledge and experience with each other. This allows employees to share their knowledge and experience and receive feedback from other employees.

[1765] The processing flow of each embodiment will be described below.

[1766] "Example 1"

[1767] Step 1: Every time an employee learns a new skill or takes on a new project, enter that information into the system.

[1768] Step 2: The system stores the entered information in a database.

[1769] Step 3: If an employee leaves the company or changes departments, enter that information into the system and update the database.

[1770] "Example 2"

[1771] Step 1: Enter the consultation details into the system.

[1772] Step 2: The system searches the database and suggests employees and organizations that best fit the needs of the customer.

[1773] Step 3: Communicate with the proposed employees and organizations.

[1774] "Example 3"

[1775] Step 1: Employees use the system's chat function to exchange messages with other employees.

[1776] Step 2: Employees use the system's forum function to share their knowledge and experiences.

[1777] Step 3: Receive feedback from others and update your knowledge and experience as needed.

[1778] Example 1

[1779] Next, a description will be given of Example 1 of Form 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."

[1780] With conventional employee information management systems, updating employee skill sets and project achievements is done manually, making it difficult to keep information up to date. Furthermore, updating information when an employee leaves the company or changes departments is tedious, making it difficult to quickly search for employees with specific skill sets or project achievements. Furthermore, the lack of functionality to promote communication between employees hinders knowledge sharing within the organization.

[1781] The identification process by the identification processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means. In this invention, the server includes means for storing employee information (department, skill set, project performance) in a database, means for transmitting input information to the server, means for saving and updating information received by the server in the database, means for updating the database when an employee leaves the company or changes departments, means for searching for employees with specific skill sets or project performance, means for displaying search results to the user, and means for stimulating communication between employees. This enables rapid searches and information updates while keeping employee information up-to-date, thereby realizing knowledge sharing and stimulating communication within the organization.

[1782] "Employee information" refers to information such as an employee's department, skill set, and project track record.

[1783] "Database" refers to an information system for storing and managing employee information.

[1784] "Server" refers to a computer system for storing and updating information in a database.

[1785] "Terminal" refers to a device through which a user inputs information and transmits it to a server.

[1786] "User" means a person who utilizes the system to enter, retrieve, and display information.

[1787] A "skill set" refers to the collection of skills and knowledge that an employee possesses.

[1788] "Project performance" refers to the history and results of projects in which employees have participated.

[1789] "Search tools" refers to the ability to search the database for employees with specific skill sets or project experience.

[1790] "Means of communication" refers to functions that promote information exchange and contact between employees.

[1791] "Information update means" refers to the function for keeping the information in the database up to date when an employee leaves the company or changes departments.

[1792] This invention is a system that stores and manages employee information (department, skill set, project performance) in a database. The system consists of three main elements: a server, terminals, and users.

[1793] Hardware and software used

[1794] Server: Database server (e.g. MySQL, PostgreSQL)

[1795] Devices: PCs and mobile devices used by employees

[1796] Software: Web application (e.g., Django, Ruby on Rails)

[1797] Program processing flow

[1798] 1. Entering data

[1799] When a user acquires a new skill or participates in a new project, the user enters the required information into an input form in a web application.

[1800] Specifically, the user opens a web browser and enters "Python programming" into the skill addition form.

[1801] 2. Data transmission

[1802] The terminal transmits the information entered by the user to the server.

[1803] Specifically, the device sends "Python programming" skill information to the server using an HTTP POST request.

[1804] 3. Data storage

[1805] The server stores the received information in a database.

[1806] Specifically, the server adds a new record to the "skills" table in the database, saving "Python programming."

[1807] 4. Updating Data

[1808] The server updates the existing employee information.

[1809] Specifically, the server searches for the corresponding employee record and adds new skill information.

[1810] 5. Data Deletion

[1811] When a user leaves the company or changes departments, the administrator enters that information through a web application.

[1812] The terminal transmits the input information to the server.

[1813] The server updates the database based on the received information, deleting or changing the relevant employee information.

[1814] Specifically, the administrator clicks the "Resign" button, and the server deletes the corresponding employee record from the database.

[1815] 6. Searching for data

[1816] When a user wants to search for employees with a particular skill set or project experience, they enter a search query through the web application.

[1817] The terminal sends a search query to the server.

[1818] The server searches the database and returns the relevant employee information to the terminal.

[1819] Specifically, the user searches for employees with "Python programming" and the server returns a list of matching employees.

[1820] 7. Displaying Data

[1821] The terminal displays the returned information to the user.

[1822] Specifically, the terminal displays the search results on a web page, and the user sees a list of employees who have "Python programming."

[1823] Example prompts for generative AI models

[1824] "Generate a prompt statement to add newly acquired skills to the database."

[1825] "Generate a prompt to search for employees with specific project experience."

[1826] In this way, employee information can be kept up to date while enabling quick searches and updates, thereby stimulating knowledge sharing and communication within the organization.

[1827] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1828] Step 1: Enter your data

[1829] When a user acquires a new skill or participates in a new project, the user enters the required information into an input form in a web application.

[1830] Input: A user opens a web browser and types "Python programming" into the add skill form.

[1831] Output: The information entered is sent to the terminal.

[1832] Step 2: Sending data

[1833] The terminal transmits the information entered by the user to the server.

[1834] Input: User-entered "Python Programming" skill information.

[1835] Data processing: The device generates an HTTP POST request and creates a request containing the entered information.

[1836] Output: An HTTP POST request is sent to the server.

[1837] Step 3: Save your data

[1838] The server stores the received information in a database.

[1839] Input: "Python Programming" skill information sent from the device.

[1840] Data processing: The server adds a new record to the "skills" table in the database and saves the entered skill information.

[1841] Output: The new skill information is saved in the database.

[1842] Step 4: Update data

[1843] The server updates the existing employee information.

[1844] Input: A record in the database where the new skill information is saved.

[1845] Data processing: The server searches for the corresponding employee record and adds the new skill information.

[1846] Output: The updated employee information is saved in the database.

[1847] Step 5: Delete data

[1848] When a user leaves the company or changes departments, the administrator enters that information through a web application.

[1849] Input: The administrator clicks the "Resign" button and enters the relevant employee's information.

[1850] Data processing: The terminal sends the entered information to the server.

[1851] Output: The server deletes the corresponding employee record from the database.

[1852] Step 6: Search for data

[1853] When a user wants to search for employees with a particular skill set or project experience, they enter a search query through the web application.

[1854] Input: A user enters a query to search for employees with "Python programming."

[1855] Data processing: The device sends the search query to the server.

[1856] Output: The server searches the database and returns the relevant employee information to the terminal.

[1857] Step 7: View the data

[1858] The terminal displays the returned information to the user.

[1859] Input: Search results returned by the server.

[1860] Data processing: The device formats the search results for display on a web page.

[1861] Output: User sees a list of employees who have "Python Programming".

[1862] (Application example 1)

[1863] Next, a description will be given of Application Example 1 of Form 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."

[1864] With the conventional employee information management system, it was difficult to effectively utilize employees' skill sets and project achievements, making it difficult to assign optimal tasks. Furthermore, updating information every time an employee acquired a new skill or participated in a project was time-consuming, making efficient operation impossible. Furthermore, there was a lack of ways to promote communication between employees, making it difficult to improve productivity across the organization.

[1865] 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.

[1866] In this invention, the server includes a means for accumulating employee information (department, skill set, project performance) as knowledge, a means for suggesting answers and organizations or people to consult with based on the input consultation content, a means for stimulating communication between employees, a means for suggesting optimal tasks based on the employee's skill set and project performance, and a means for updating employee information. This makes it possible to effectively utilize employees' skill sets and project performance to assign optimal tasks. Furthermore, updating employee information is automated, enabling efficient operations. Furthermore, this stimulates communication between employees, which is expected to improve productivity throughout the organization.

[1867] "Employee information" refers to information such as an employee's department, skill set, and project track record.

[1868] "Knowledge" refers to accumulated knowledge and information, especially employee information stored in a database.

[1869] "Consultation content" refers to the content of questions or consultations entered by employees.

[1870] "Answer" refers to the solution or information provided in response to the inquiry.

[1871] "Consultation destination" refers to organizations or individuals suggested based on the content of the consultation.

[1872] "Organization" refers to a group such as a company or department.

[1873] "Person" refers to a specific employee or professional.

[1874] "Communication" refers to the exchange of information and dialogue between employees.

[1875] A "skill set" refers to the collection of skills and abilities that an employee possesses.

[1876] "Project performance" refers to the history and results of projects in which employees have participated in the past.

[1877] "Best-fit work" refers to the work that is best suited to an employee based on their skill set and project performance.

[1878] "Update" refers to employee information being changed based on new skills or project achievements.

[1879] The system for implementing this invention accumulates employee information (department, skill set, project performance) as knowledge and suggests answers and organizations or people to consult with based on the input consultation content. It also has the function of stimulating communication between employees and suggesting optimal work based on employees' skill sets and project performance. It also has the function of updating employee information.

[1880] Hardware and software used

[1881] Hardware: Servers, factory robots, user devices (PCs, smartphones)

[1882] Software: SQLite database, Python program

[1883] System configuration

[1884] 1. Employee information collection:

[1885] The server stores information about employees' departments, skill sets, and project achievements in a database, allowing for centralized management of information about employees' skills and achievements.

[1886] 2. Proposal based on consultation:

[1887] The server then suggests the most appropriate answers and organizations or people to consult based on the consultation details entered by the user, allowing the user to quickly obtain appropriate information and support.

[1888] 3. Increased communication:

[1889] The server provides functionality to facilitate communication between employees, including functionality to facilitate contact with suggested organizations and individuals for consultation.

[1890] 4. Optimal working suggestions:

[1891] The server suggests the most suitable tasks based on the employee's skill set and project performance, allowing the factory robot to automatically assign the most suitable tasks to employees.

[1892] 5. Updating Employee Information:

[1893] The server automatically updates employee information whenever they acquire new skills or take on new projects, ensuring the database is always up-to-date.

[1894] Specific examples of processing

[1895] For example, if an employee with employee ID 1 has the skills of "welding" and "assembly," the server will suggest the work that best suits these skills from the database. When a user enters "Please suggest the best work based on the skill set of employee ID 1," the server will search the database and suggest the best work.

[1896] Prompt Sentence Examples

[1897] "Please suggest the best tasks for employee ID 1 based on their skill set."

[1898] In this way, the system can effectively utilize employees' skill sets and project experience to optimally assign tasks. It also automates updating employee information, leading to efficient operations. It also promotes communication between employees, which is expected to improve productivity across the organization.

[1899] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1900] Step 1:

[1901] The server stores employee information (department, skill set, project performance) in a database.

[1902] Input: Employee's department, skill set, project performance

[1903] Output: Employee information stored in the database

[1904] What it does: The server adds information about employees to the database whenever they acquire new skills or join new projects. It also updates the database when employees leave the company or change departments.

[1905] Step 2:

[1906] The user inputs the consultation content from the terminal.

[1907] Input: Consultation details

[1908] Output: Consultation details sent to the server

[1909] Specific operation: The user uses a terminal (PC or smartphone) to input the consultation content and send it to the server.

[1910] Step 3:

[1911] The server suggests answers and organizations or people to consult based on the input consultation content.

[1912] Input: Consultation details, employee information stored in the database

[1913] Output: Suggested answers and organizations or people to consult

[1914] Specific operation: The server analyzes the content of the consultation and refers to employee information stored in a database to select the most appropriate answer and the organization or person to consult.

[1915] Step 4:

[1916] The server provides functions to promote communication between employees.

[1917] Input: Suggested organization or person to consult

[1918] Output: A means of communication to facilitate communication

[1919] Specific operation: The server provides functions (e.g., chat functions and email notifications) to facilitate contact with the suggested organizations and people to consult with.

[1920] Step 5:

[1921] The server suggests the best work to do based on employees' skill sets and project experience.

[1922] Input: Employee skill sets, project performance

[1923] Output: Optimal work suggestions

[1924] Specific operation: The server refers to the employee's skill set and project track record stored in a database, and selects and proposes the most suitable work.

[1925] Step 6:

[1926] The server updates the employee information.

[1927] Input: New skills and project achievements

[1928] Output: Updated employee information

[1929] What it does: The server automatically updates employee information in the database whenever an employee acquires a new skill or takes on a new project.

[1930] Example 2

[1931] Next, a description will be given of Example 2 of Form 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."

[1932] With the previous system, it was difficult to find the right person to consult based on an employee's skills and experience, which led to problems with inactive communication between employees. Furthermore, there was a lack of a way to quickly and accurately suggest the right employee or organization based on the content of the consultation, which could lead to a decline in project efficiency.

[1933] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1934] In this invention, the server includes means for accumulating employee information (department, skill set, project performance) as knowledge, means for extracting keywords based on the input consultation content, means for searching the database based on the extracted keywords and generating a list of relevant employees and organizations, means for providing the generated list to the user, and means for stimulating communication between employees. This enables the user to quickly and accurately find the appropriate employee or organization, stimulating communication between employees and improving project efficiency.

[1935] "Employee information" refers to data about employees, such as department, skill set, and project performance.

[1936] "Knowledge" refers to accumulated information and knowledge, including employee information in particular.

[1937] "Consultation content" refers to the content of questions or requests that users input into the system.

[1938] "Keywords" refer to important words and phrases extracted from the content of the consultation.

[1939] A "database" refers to a system that stores data such as employee information in an organized manner and makes it searchable.

[1940] "List" refers to a list of relevant employees and organizations generated as search results.

[1941] "User" refers to a person who uses the system to input the details of a consultation and receive the results.

[1942] "Means to promote communication" refers to functions and methods for promoting information exchange and collaboration among employees.

[1943] This invention is a system that accumulates employee information as knowledge and suggests appropriate employees and organizations based on the content of an inquiry that has been input. A specific embodiment of this system will be described below.

[1944] System configuration

[1945] The system uses the following hardware and software:

[1946] Hardware: Servers (e.g., general-purpose servers), terminals (e.g., personal computers, smartphones)

[1947] Software: database management systems (e.g., MySQL), search algorithms (e.g., Elasticsearch)

[1948] Program processing

[1949] The server receives the consultation content from the user. The consultation content includes keywords for searching for employees with specific skills and experience. The server searches the database based on the received keywords and generates a list of relevant employees and organizations.

[1950] The system works as follows:

[1951] 1. The user enters the consultation content. For example, "We are looking for an employee with Python programming skills for a new project."

[1952] 2. The device sends the entered consultation details to the server. At this time, the device sends the data using an HTTP request.

[1953] 3. The server receives the consultation content and extracts keywords. For example, it extracts the keyword "Python programming."

[1954] 4. The server searches the database and generates a list of matching employees and organizations, using Elasticsearch for fast and efficient searching.

[1955] 5. The server sends the generated list to the device, again using an HTTP response to send the data.

[1956] 6. The terminal displays the list to the user, who can then select the appropriate employee or organization from the displayed list.

[1957] Specific examples

[1958] For example, a user may enter "I'm looking for an employee with Python programming skills for a new project" into a terminal. The terminal then sends this request to the server. The server receives the request and extracts the keyword "Python programming." The server then uses Elasticsearch to search the MySQL database and generate a list of employees with Python programming skills. The server then sends the generated list to the terminal, which then displays it to the user. The user can then select a suitable employee from the displayed list.

[1959] Example prompts to input to a generative AI model:

[1960] "We're looking for employees with Python programming skills for a new project. Can you suggest suitable candidates?"

[1961] After entering this prompt, the system will search the database and provide a list of employees who have Python programming skills.

[1962] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1963] Step 1:

[1964] The user inputs the consultation content.

[1965] The user inputs their inquiry into the device to find employees with specific skills and experience. For example, they might input "I'm looking for an employee with Python programming skills for a new project." The input inquiry is saved on the device.

[1966] Step 2:

[1967] The terminal transmits the input consultation content to the server.

[1968] The terminal sends the consultation details entered by the user to the server as an HTTP request. The input data is sent to the server in text format.

[1969] Step 3:

[1970] The server receives the consultation content and extracts keywords.

[1971] The server analyzes the consultation content received from the device and extracts important keywords. For example, the keyword "Python programming" is extracted. The extracted keywords are used in the next search process.

[1972] Step 4:

[1973] The server searches the database and generates a list of relevant employees and organizations.

[1974] The server uses Elasticsearch to search the MySQL database based on the extracted keywords, and generates a list of employees with Python programming skills. The list contains employee information retrieved from the database.

[1975] Step 5:

[1976] The server sends the generated list to the terminal.

[1977] The server sends the generated list of employees and organizations to the terminal as an HTTP response in text or JSON format.

[1978] Step 6:

[1979] The terminal displays the list to the user.

[1980] The terminal displays the list received from the server to the user, who can then select the appropriate employee or organization from the displayed list. The display format can be a list or a table.

[1981] (Application example 2)

[1982] Next, a description will be given of Application Example 2 of Form 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."

[1983] Conventional systems accumulate employee information as knowledge and can suggest appropriate organizations and individuals based on the content of the consultation, but they lack the functionality to quickly search for and suggest workers with specific skills. Furthermore, the means to stimulate communication between employees are limited, and the functionality to promote effective communication with the suggested consultation partners is insufficient. This makes it difficult to quickly find workers with the skills necessary to perform specific tasks within the factory, resulting in a decline in work efficiency.

[1984] The identification process by the identification 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 accumulating employee information (department, skill set, project performance) as knowledge, means for suggesting answers and organizations or people to consult with based on the input consultation content, means for stimulating communication between employees, and means for searching for and suggesting workers with specific skills. This makes it possible to quickly search for and suggest workers with specific skills, thereby improving work efficiency in the factory.

[1985] "Employee information" refers to information such as an employee's department, skill set, and project track record.

[1986] "Knowledge" refers to accumulated information and knowledge, including employee information in particular.

[1987] "Consultation content" refers to the questions or consultation content that users enter into the system.

[1988] An "organization" refers to a group or group formed with a specific purpose.

[1989] A "person" refers to an individual with particular skills or knowledge.

[1990] "Communication" refers to the act of exchanging information and opinions.

[1991] "Skills" refer to the abilities and techniques required to perform specific tasks or jobs.

[1992] "Worker" refers to a worker who performs specific tasks in a factory or on a work site.

[1993] "Search" refers to the act of finding specific information from a database or the like.

[1994] "Proposal" refers to the act of presenting a particular option or solution.

[1995] The system for implementing this invention includes means for accumulating employee information (department, skill set, project performance) as knowledge, means for suggesting answers and organizations or people to consult with based on the input consultation content, means for stimulating communication between employees, and means for searching for and suggesting workers with specific skills.

[1996] The server uses an SQLite database to store employee information, including department, skill set, project performance, etc. When a user searches for workers with specific skills, the server searches the database based on the entered skill keywords and generates a list of workers with the corresponding skills.

[1997] The system is implemented using a Python program. When a user inputs a skill keyword, the server executes a search query against the SQLite database to retrieve the corresponding worker information. The retrieved information is then displayed to the user in a list format.

[1998] As a concrete example, consider the case where a new welding machine is introduced in a factory and workers with the skills to operate that welding machine are needed. When a user enters "welding machine operation," the server searches the database and generates a list of workers with that skill. The user can then select an appropriate worker based on this list.

[1999] An example of a prompt is as follows:

[2000] "We are looking for employees with the skills to operate new welding machines. Please provide us with a list of employees with the skills to operate welding machines."

[2001] This system makes it possible to quickly search for and suggest workers with specific skills, thereby improving work efficiency within the factory.

[2002] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2003] Step 1:

[2004] A user uses a terminal to input keywords to search for workers with specific skills. The input keywords are sent to the server. The input data are keywords related to the skills the user is looking for.

[2005] Step 2:

[2006] The server searches the SQLite database based on the received keywords. It generates a search query and extracts workers with the corresponding skills from the employee information in the database (department, skill set, project history). The input data is the keyword entered by the user, and the output data is a list of workers with the corresponding skills.

[2007] Step 3:

[2008] The server formats the list of workers obtained as search results and converts it into a format for display to the user. Specifically, it compiles information such as the worker's name, department, skill set, and project performance into a list. The input data is the worker information obtained as search results, and the output data is the formatted list of workers.

[2009] Step 4:

[2010] The server sends the formatted list of workers to the user's terminal. The user can check the list of workers with the relevant skills on the terminal. The input data is the formatted list of workers, and the output data is the list of workers displayed on the user's terminal.

[2011] Step 5:

[2012] The user selects an appropriate worker based on the displayed list of workers. Specific work requests and communication can then be made to the selected worker. The input data is the list of workers confirmed by the user, and the output data is the content of the work requests and communication sent to the selected worker.

[2013] Example 3

[2014] Next, a third embodiment of the third embodiment will be described. 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."

[2015] Conventional employee information management systems have the problem of not encouraging active communication between employees and preventing sufficient sharing of knowledge and experience. Furthermore, the lack of real-time messaging and forum functionality means that information exchange between employees is not smooth. This can lead to a decline in employee productivity and cooperation.

[2016] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[2017] In this invention, the server includes means for accumulating employee information (department, skill set, project performance) as knowledge, means for suggesting answers and organizations or people to consult with based on the consultation content entered, means for stimulating communication between employees, means for sending and receiving messages in real time, and means for providing a forum for sharing knowledge and experience. This facilitates communication between employees and enables the smooth sharing of knowledge and experience.

[2018] "Employee information" refers to information such as an employee's department, skill set, and project track record.

[2019] "Knowledge" refers to the accumulation of employee information and data on knowledge and experience that is stored in a shareable format.

[2020] "Consultation content" refers to the questions and consultation content that employees enter into the system.

[2021] "Answer" refers to the solution or information provided in response to the inquiry.

[2022] "Consultation destination" refers to organizations or individuals suggested based on the content of the consultation.

[2023] "Means to promote communication" refers to functions that enable employees to smoothly exchange information and opinions with each other.

[2024] "Means of sending and receiving messages in real time" refers to the ability for employees to send and receive messages instantly.

[2025] "Forum" refers to an online message board where employees can share knowledge and experiences and exchange opinions.

[2026] "Server" refers to a computer system that manages the entire system and provides various functions.

[2027] "Terminal" refers to a device (e.g., PC, smartphone) used by an employee to access and operate the system.

[2028] This invention is a system for promoting communication among employees and sharing knowledge and experience. This system operates in cooperation with three parties: a server, a terminal, and a user.

[2029] Hardware and software used

[2030] Hardware:

[2031] High-performance servers (e.g., high-performance computer systems)

[2032] Device (e.g. PC, smartphone)

[2033] software:

[2034] Chat functionality: APIs for real-time messaging (e.g., messaging APIs)

[2035] Forum functionality: Online bulletin board software for sharing knowledge and experiences (e.g., forum software)

[2036] Specific operation of the system

[2037] server:

[2038] The server stores employee information (department, skill set, project track record) as knowledge. This allows it to suggest appropriate answers and organizations or people to consult with based on the consultation content entered. The server also provides a function for sending and receiving messages in real time, promoting active communication between employees. Furthermore, the server provides a forum function, providing a place for employees to share their knowledge and experience.

[2039] Device:

[2040] Terminals are devices that users use to access and operate the system. Users can use the terminals to send and receive messages in real time using the chat function, and can also use the forum function to share knowledge and experience and get feedback from other employees.

[2041] User:

[2042] Users are employees who use the system. They can use the chat and forum functions on their terminals to communicate with other employees. For example, if User A sends a message to User B saying, "Thank you for your hard work. Could you please send me the materials for today's meeting?", the message sent from User A's terminal is delivered to User B's terminal via the server. User B can receive the message and reply in real time.

[2043] Also, if user C posts a topic called "New Project Proposal" to the forum, the post sent from user C's device will be stored in the database via the server. Other users can view and comment on the topic.

[2044] Prompt Sentence Examples

[2045] "Design a system to facilitate communication between employees. The system should include real-time chat functionality and forum functionality for knowledge sharing. Use high-performance computer systems as the hardware and messaging APIs and forum software."

[2046] In this way, it is clearly explained how the server, terminal, and user cooperate to operate the system. The flow of the specific processing in the third embodiment will be explained with reference to FIG.

[2047] Step 1:

[2048] The user types a chat message.

[2049] A user opens a chat application on a terminal and enters text into a message input field, which is temporarily stored in the terminal's memory.

[2050] Step 2:

[2051] The device sends a message to the server.

[2052] The terminal sends the message entered by the user to the server using a messaging API. The message is sent as an HTTP request. The input is the user's message, and the output is an HTTP request to the server.

[2053] Step 3:

[2054] The server receives and processes the message.

[2055] The server parses the received HTTP request, extracts the message content and sender information, and processes the message to route it to the appropriate recipient. The input is the HTTP request, and the output is the recipient information and the message content.

[2056] Step 4:

[2057] The server sends the message to the recipient's terminal.

[2058] The server sends a message to the recipient's device. The recipient's device receives the message in real time via a messaging API. The input is recipient information and message content, and the output is an HTTP response to the recipient's device.

[2059] Step 5:

[2060] The recipient's device displays the message.

[2061] The receiver's device displays the received message in the chat application interface. The receiver can check the message and reply. The input is the HTTP response, and the output is the message displayed in the chat application interface.

[2062] Step 6:

[2063] A user creates a post in a forum.

[2064] A user opens a forum application on their device and enters a new topic or comment, which is temporarily stored in the device's memory.

[2065] Step 7:

[2066] The device sends the post to the server.

[2067] The terminal sends user-created posts to the server using the forum API. Posts are sent as HTTP requests. The input is the user post, and the output is an HTTP request to the server.

[2068] Step 8:

[2069] The server stores the posts in a database.

[2070] The server stores the received posts in a database. The database holds information such as the post content, author, and creation date. The input is an HTTP request, and the output is the post data stored in the database.

[2071] Step 9:

[2072] The server notifies other users of updates to the forum.

[2073] The server notifies other users when a new post has been made to the forum. The notification is done in real time. The input is the post data stored in the database, and the output is the notification to other users.

[2074] Step 10:

[2075] Other users' devices will display forum updates.

[2076] Other users' devices receive forum updates and display new posts in the application interface. Users can view and comment on new posts. The input is notifications, and the output is new posts displayed in the forum application interface.

[2077] (Application example 3)

[2078] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[2079] While conventional robots used in factories can perform individual tasks efficiently, they face the challenge of having difficulty sharing work progress and problems due to a lack of communication between robots. Furthermore, there is no way for robots to share the knowledge and experience they have gained with other robots, which can lead to a decline in overall work efficiency. To solve these issues, a system is needed that allows robots to communicate efficiently with each other and share knowledge and experience.

[2080] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[2081] In this invention, the server includes a means for accumulating employee information (department, skill set, project record) as knowledge, a means for suggesting answers and organizations or people to consult with based on the consultation content entered, a means for promoting communication between employees, a means for providing a chat function that allows robots to send messages to each other, and a means for providing a forum function for robots to share knowledge and experience. This enables robots to communicate with each other efficiently and quickly share work progress and problems. Furthermore, by sharing the knowledge and experience gained by robots with other robots, overall work efficiency can be improved.

[2082] "Employee information" refers to information about employees, such as department, skill set, and project performance.

[2083] "Knowledge" refers to accumulated information and knowledge, such as employee information and robot knowledge and experience.

[2084] "Consultation content" refers to questions or issues entered by employees or robots.

[2085] An "answer" is a solution or information provided in response to a question.

[2086] "Consultation destination" refers to an organization or person suggested based on the content of the consultation.

[2087] An "organization" is a group or group formed with a specific purpose.

[2088] A "person" is an individual with a specific role or skill.

[2089] "Communication" is the act of exchanging information and opinions.

[2090] The "chat function" allows robots and employees to send messages to each other.

[2091] The "forum function" is a function that allows robots and employees to share knowledge and experiences.

[2092] "Work efficiency" refers to the ability or degree to which work is performed efficiently.

[2093] "Progress" refers to the progress of a task or project.

[2094] A "problem" is a challenge or obstacle that arises in a task or project.

[2095] The system for implementing this invention aims to enable robots used in a factory to communicate with each other efficiently and share knowledge and experience. A specific embodiment of this system will be described below.

[2096] System Configuration

[2097] The system consists of the following main components:

[2098] 1. Server: Employee information (department, skill set, project track record) is accumulated as knowledge, and based on the inputted consultation content, answers and organizations or people to consult are suggested.

[2099] 2. Robot: A robot that works in a factory and has chat and forum functions.

[2100] 3. Network: A network for communication between the server and the robot.

[2101] Program processing

[2102] The server processes the data using the following means:

[2103] Employee information storage: The server stores employee information such as department, skill set, and project performance in a database. This data also includes the knowledge and experience gained by the robot during its work.

[2104] Analysis of consultation content: The server analyzes the consultation content entered by the robot or employee and suggests appropriate answers and organizations or people to consult.

[2105] Chat function: Robots can send messages to each other via the server, allowing them to share their work progress and problems in real time.

[2106] Forum function: Robots can post the knowledge and experience they gain during their work on the forum and share it with other robots.

[2107] Hardware and software used

[2108] Hardware: Robots, servers, and network equipment used in factories

[2109] Software: Python programs, database management systems (e.g., MySQL), thread libraries

[2110] Specific examples

[2111] For example, if a robot discovers a new, efficient work procedure in a factory, it can share that knowledge with other robots through the forum function, allowing other robots to adopt the same efficient procedure, improving overall work efficiency.

[2112] Example prompt sentence:

[2113] A robot in your factory has discovered a new, more efficient way to work. Think about how you can share this knowledge with other robots to improve their work efficiency.

[2114] In this way, robots can communicate with each other efficiently and share knowledge and experience, improving work efficiency throughout the factory and enabling quicker response when problems arise.

[2115] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[2116] Step 1:

[2117] The server accumulates employee information (department, skill set, project performance) in a database. As input, it receives information provided by each employee and robot and stores it in the database. As data processing, it converts the information into an appropriate format and stores it in the database. As output, it obtains the accumulated employee information.

[2118] Step 2:

[2119] The server receives the consultation content input from the robot or an employee. It receives the text data of the consultation content as input and analyzes it. As data processing, it uses natural language processing technology to analyze the consultation content and identify the appropriate answer or organization or person to consult. As output, it obtains a suggested answer or person to consult.

[2120] Step 3:

[2121] The server sends the suggested answers and information on where to consult to the robot. As input, it receives the answers and information on where to consult obtained in step 2 and sends this to the robot. As data processing, it converts the information into an appropriate format and sends it to the robot. As output, the robot receives the suggested answers and information on where to consult.

[2122] Step 4:

[2123] Based on the information received from the server, the robot exchanges messages with other robots using the chat function. As input, it generates a message based on the information received from the server and sends it to other robots. As data calculation, it generates and sends a message. As output, other robots receive the message.

[2124] Step 5:

[2125] Robots use the forum function to share the knowledge and experience they gain while working. As input, they post the knowledge and experience they gain while working to the forum. As data processing, the posted content is converted into an appropriate format and saved in the forum. As output, other robots can obtain the knowledge and experience from the forum.

[2126] Step 6:

[2127] The server accumulates the knowledge and experience posted on the forum in a database. As input, it receives the knowledge and experience posted by the robots and stores it in the database. As data processing, it converts the information into an appropriate format and stores it in the database. As output, it obtains the accumulated knowledge and experience.

[2128] Step 7:

[2129] The robot improves work efficiency based on the knowledge and experience it gains from the forum. As input, it receives knowledge and experience acquired from the forum and applies it to the work. As data calculation, it optimizes the work procedure based on the knowledge and experience. As output, work efficiency is improved.

[2130] 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.

[2131] "Example 1"

[2132] One embodiment of the present invention is a system incorporating an emotion engine. This system accumulates employee information (department, skill set, project performance) as knowledge and suggests answers and organizations or people to consult with based on the content of the consultation entered. Furthermore, the emotion engine recognizes the user's emotions and suggests organizations or people to consult with based on those emotions. Specifically, if it recognizes that the user is feeling stressed, it suggests employees who are thought to be able to alleviate that stress.

[2133] "Example 2"

[2134] Another embodiment of the present invention is a system in which an emotion engine has the function of promoting communication between employees. This system recognizes the user's emotions and suggests communication methods based on those emotions. Specifically, if the system recognizes that the user is feeling joy, it encourages communication with employees who share that joy.

[2135] "Example 3"

[2136] Furthermore, as another embodiment of the present invention, there is a system in which an emotion engine suggests organizations or people to consult with based on employee information accumulated as knowledge and the user's emotions. This system combines the user's emotions and employee information to suggest the most appropriate person to consult with. Specifically, if it recognizes that the user is feeling anxious, it suggests experienced employees who are thought to be able to alleviate the anxiety.

[2137] The processing flow of each embodiment will be described below.

[2138] "Example 1"

[2139] Step 1: The system accumulates employee information (department, skill set, project performance) as knowledge.

[2140] Step 2: When the user inputs the content of their inquiry, the system will suggest answers and organizations or people to consult based on the content.

[2141] Step 3: The emotion engine recognizes the user's emotions and suggests organizations or people to consult with based on those emotions. Specifically, if the engine recognizes that the user is feeling stressed, it will suggest employees who are thought to be able to alleviate that stress.

[2142] "Example 2"

[2143] Step 1: The emotion engine recognizes the user's emotion.

[2144] Step 2: The emotion engine suggests ways to communicate based on the emotion. Specifically, if the engine recognizes that the user is feeling happy, it will encourage communication with employees who share that happiness.

[2145] "Example 3"

[2146] Step 1: The emotion engine combines the user's emotions with employee information to suggest the best person to consult.

[2147] Step 2: Specifically, if it is recognized that the user is feeling anxious, it will suggest experienced employees who may be able to alleviate that anxiety.

[2148] Example 1

[2149] Next, a description will be given of Example 1 of Form 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."

[2150] While conventional employee information management systems can manage employee skill sets and project performance, they lack the functionality to suggest appropriate consultations based on the user's emotions. Furthermore, they lack specific methods for promoting communication between employees, which means they are unable to fully reduce employee stress or improve work efficiency.

[2151] 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.

[2152] In this invention, the server includes means for accumulating employee information (department, skill set, project performance) as knowledge, means for suggesting answers and organizations or people to consult with based on the consultation content entered, means for recognizing the user's emotions using an emotion engine and suggesting organizations or people to consult with based on those emotions, and means for stimulating communication between employees. This makes it possible to suggest appropriate organizations or people to consult with based on the user's emotions, thereby reducing employee stress and improving work efficiency.

[2153] "Employee information" refers to information such as an employee's department, skill set, and project track record.

[2154] "Knowledge" refers to the accumulation of employee information and the knowledge and information shared within the organization.

[2155] An "emotion engine" refers to software or algorithms that analyze emotions from user input and suggest appropriate responses based on those emotions.

[2156] "Consultation content" refers to the content of the consultation or question that the user inputs into the system.

[2157] "Consultation destination" refers to an organization or person suggested based on the content of the user's consultation.

[2158] "Means to promote communication" refers to functions and methods for promoting interaction and information sharing among employees.

[2159] A "server" is a computer that is the central part of a system and performs processes such as data storage, analysis, and proposals.

[2160] "Terminal" refers to a device through which a user accesses the system to enter information and view results.

[2161] This invention is a system that stores employee information (department, skill set, project performance) in a database and suggests appropriate answers and consultations based on the content of the user's consultation. It also includes a function that uses an emotion engine to recognize the user's emotions and suggests consultations based on those emotions.

[2162] System configuration

[2163] The server stores employee information in a database. Specifically, the database is updated every time an employee acquires a new skill or participates in a new project. The database is also updated appropriately when an employee leaves the company or changes departments. The server can use, for example, MySQL or PostgreSQL as its database management system (DBMS).

[2164] The terminal accepts input from the user. When the user inputs the content of the consultation, the content is sent to the server. The terminal is often implemented as a web browser or a mobile application.

[2165] The server analyzes the received consultation content and recognizes the user's emotions using an emotion engine, which can use, for example, the Google Cloud Natural Language API or IBM Watson's emotion analysis function.

[2166] The server then searches the database for appropriate organizations or people to consult with based on the emotions it recognizes. For example, if it recognizes that the user is feeling stressed, it will suggest employees who can help alleviate that stress.

[2167] The terminal displays the suggestions received from the server to the user, who can then select an appropriate consultation provider based on the displayed information.

[2168] Specific examples

[2169] If a user types, "I've been feeling a lot of stress at work lately," the emotion engine will recognize the word "stress." The server will search its database for employees with skills that can help reduce stress and suggest them to the user.

[2170] Example prompt sentence:

[2171] "I've been feeling a lot of pressure at work lately and it's stressful. Who can I talk to?"

[2172] This system efficiently manages employee information and suggests appropriate consultation sources based on the user's emotions, thereby contributing to reducing employee stress and improving work efficiency.

[2173] The flow of the identification process in the first embodiment will be described with reference to FIG.

[2174] Step 1:

[2175] The user inputs the consultation content from the terminal.

[2176] Specific actions: The user enters "I've been feeling a lot of pressure at work lately and it's stressful" into the input form displayed on the device screen.

[2177] Input: User's inquiry (text format)

[2178] Output: Consultation details entered into the terminal

[2179] Step 2:

[2180] The terminal transmits the input consultation content to the server.

[2181] Specific operation: The device converts the consultation content entered by the user into JSON format and sends it to the server using an HTTP POST request.

[2182] Input: Consultation details entered into the device (text format)

[2183] Output: Consultation details sent to the server (JSON format)

[2184] Step 3:

[2185] The server analyzes the consultation content and recognizes the user's emotions using an emotion engine.

[2186] Specific operation: The server parses the received JSON data and passes it to the emotion engine. The emotion engine extracts the emotion "stress" from the text and returns it to the server.

[2187] Input: Consultation content sent to the server (JSON format)

[2188] Output: Emotion recognized by the emotion engine (e.g., stress)

[2189] Step 4:

[2190] Based on the emotion recognized by the server, a search is made for appropriate organizations or people to consult from a database.

[2191] Specific operation: The server executes a database query to search for employees who have skills that can help reduce stress or who have received similar consultations in the past. For example, it searches for employees with the skill "stress management."

[2192] Input: Emotion recognized by the emotion engine (e.g., stress)

[2193] Output: Information on appropriate organizations and people to consult found in the database

[2194] Step 5:

[2195] The server sends the search results to the terminal.

[2196] Specific operation: The server converts the search results into JSON format and sends them to the terminal as an HTTP response.

[2197] Input: Information on appropriate organizations and people to consult found in the database

[2198] Output: Search results sent to the device (JSON format)

[2199] Step 6:

[2200] The terminal displays the search results to the user.

[2201] Specific operation: The device analyzes the received JSON data and displays to the user, "Please consult with employee A, who has stress management skills."

[2202] Input: Search results sent to the terminal (JSON format)

[2203] Output: Search results displayed to the user (in text format)

[2204] (Application example 1)

[2205] Next, a description will be given of Application Example 1 of Form 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."

[2206] Conventional employee information management systems have difficulty providing appropriate support and advice that takes into account employees' emotions. Furthermore, the robots working in factories lacked the functionality to recognize employees' emotions and suggest appropriate actions, preventing them from fully reducing stress and promoting efficient communication. This created challenges for improving employee satisfaction and productivity.

[2207] 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.

[2208] In this invention, the server includes means for accumulating employee information (department, skill set, project performance) as knowledge, means for suggesting answers and organizations or people to consult with based on the consultation content entered, means for stimulating communication between employees, means for recognizing the user's emotions using an emotion engine and suggesting appropriate actions based on those emotions, and means installed in robots working in factories to recognize the emotions of workers and suggest appropriate actions when stress is detected. This makes it possible to provide appropriate support and advice that takes employees' emotions into consideration, thereby reducing stress among workers and promoting efficient communication.

[2209] "Employee information" refers to information such as an employee's department, skill set, and project track record.

[2210] "Knowledge" refers to accumulated information and knowledge, including employee information in particular.

[2211] An "emotion engine" refers to a system that recognizes a user's emotions and suggests appropriate actions based on those emotions.

[2212] "Consultation content" refers to the question or matter of consultation entered by the user.

[2213] "Organizations and individuals" refers to appropriate departments and employees that are suggested as suitable contact points based on the content of the consultation.

[2214] "Means to promote communication" refers to functions that promote interaction and information sharing between employees.

[2215] "Robots working in factories" refers to automated machinery that performs work in factories.

[2216] "Workers" refers to human employees working in a factory.

[2217] "Stress" refers to the mental or physical strain felt by workers.

[2218] "Appropriate action" refers to spec...

Claims

1. A means of accumulating employee information as knowledge, A means for suggesting answers or organizations or people to consult based on the input consultation content; A way to stimulate communication among employees, A means of communication for sending and receiving messages in real time; Means for providing a forum facility for sharing knowledge or experience; A means to analyze the user's emotions and suggest the best place to seek advice; A system including:

2. 2. The system according to claim 1, wherein organizations and individuals recommended for consultation based on the content of the consultation are selected based on employee information accumulated as knowledge.

3. 2. The system according to claim 1, wherein the means for promoting communication between employees includes a function for promoting communication with suggested organizations or persons for consultation.

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