system

Abstract

Provide a system. A means for a user to input his / her skill information and spare time schedule; A way for people from other departments to input request information about problems that need to be solved or skills that are needed, means for storing the skill information, spare time schedule and request information in a database; means for comparing the skill information and request information and selecting a suitable user; A means for checking the free time schedule of the selected user and proposing a feasible schedule; means for notifying a user of the proposed schedule and accepting approval; A means of communicating approved schedule and task details to the requesting party. A system including:

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 today's corporate environment, it is necessary to make the most of the diverse skills and experience of employees. However, there is a lack of systems in place to allow employees to find spare time to support work outside of their own department and to appropriately match their skills with the needs of other departments. This results in inefficient problem-solving and operational improvement in other departments, and the company's overall resources are not being fully utilized. [Means for solving the problem]

[0005] The present invention provides a system that includes a means for users to input their own skill information and spare-time schedules, a means for staff from other departments to input request information regarding problems that need solving or skills they require, a means for storing the skill information, spare-time schedules, and request information in a database, a means for collating the skill information and request information to select suitable users, a means for confirming the spare-time schedules of the selected users and proposing feasible schedules, a means for notifying the users of the proposed schedules and accepting their approval, and a means for notifying the staff from other departments who made the request of details of the approved schedules and tasks. The system also includes a means for collecting feedback from users and staff from other departments, storing it in a database for analysis, and a means for providing a means for reporting the progress of work. In this way, employees' spare time can be effectively utilized to quickly and effectively resolve issues in other departments.

[0006] "User" refers to an individual who utilizes the system to input their own skill information and spare time schedule.

[0007] "Other department personnel" refers to individuals who use the system to input request information about problems that need to be solved or skills that are needed.

[0008] "Skill information" refers to specific knowledge and skills possessed by a user, and is data entered into the system.

[0009] The "spare time schedule" refers to a time frame in which a user can support work during a specific time period, and is data entered into the system.

[0010] "Request information" refers to information related to problems that need to be solved or desired skills that is entered into the system by staff from other departments.

[0011] "Database" means an information system for storing and managing skill information, availability schedules, request information, and other related data.

[0012] "Matching" refers to the process by which the system matches a user's skill information with the request information.

[0013] "Notification" means an electronic message or alert used by the system to communicate information to users or other personnel.

[0014] "Approval" refers to the act of a user indicating their agreement with the schedule and tasks proposed by the system.

[0015] "Feedback" refers to opinions and evaluations from users and staff in other departments regarding business support activities.

[0016] "Progress" refers to the degree of completion or progress of a particular task or project and is reported data. [Brief explanation of the drawings]

[0017] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7]FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0018] 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.

[0019] First, the terms used in the following description will be explained.

[0020] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0021] 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.

[0022] 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.

[0023] 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.

[0024] 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."

[0025] [First embodiment]

[0026] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0027] 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.

[0028] 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).

[0029] 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.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0034] 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.

[0035] 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.

[0036] 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.

[0037] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0038] The system of the present invention supports problem solving in other departments by matching skills and spare time with the user and the person in charge of the other department, and compares the information entered by the user and the person in charge of the other department using a database. The following describes in detail how the system is implemented.

[0039] Registering and saving user information

[0040] The user accesses a special page. The device displays an input form, and the user enters their skill information and spare time schedule. For example, "Java (registered trademark) programming" and "data analysis" are registered as skills, and the spare time from 14:00 to 15:00 on Mondays is entered. The device sends this information to the server as JSON format data. The server analyzes the received data and saves the skill information and schedule information in a database.

[0041] Enter and save request information

[0042] A person in another department accesses a special page to enter a request for solving a problem. The terminal displays an input form, and the person in charge enters the problem that needs to be solved and the skills required. For example, "fix a bug in a Python program." The terminal sends this information to the server as JSON format data. The server analyzes the received data and saves the request information in a database.

[0043] Matching skills to requests

[0044] The server runs a skill matching algorithm periodically or when a request occurs to match the request information with the user skill information stored in the database. The server searches the database for users who have the skills corresponding to the request and lists them.

[0045] Check schedule and suggest possible times

[0046] The server compares the selected users' free time schedules and extracts available time slots for the request. Based on this information, the server generates a schedule to propose to the user and prepares a notification message.

[0047] Notifications and Scheduling

[0048] The server sends a notification of the matching proposal to the user. The user receives the notification and checks their own schedule. The terminal displays the notification content, and the user can choose to accept or reject. If the user accepts, the server notifies the person in the other department who made the request of the final schedule and task details.

[0049] Business support and progress reports

[0050] Users visit other departments at designated times or participate in online meetings to perform support tasks. During and after work, they report their progress from their terminal. The terminal displays a progress report form, and the user enters the required information. The progress report is sent to the server, which stores it in a database.

[0051] Feedback collection and analysis

[0052] After completing the task, the server notifies the user and staff from other departments of the feedback request. The terminal displays a feedback form, and the user and staff from other departments enter their evaluations and opinions. The feedback is sent to the server and stored in a database. The server analyzes the collected feedback and uses it as data to improve the accuracy of the next match.

[0053] This allows the system to efficiently utilize internal skills and resources and effectively support other departments in solving problems and improving operations.

[0054] The processing flow will be explained below.

[0055] Step 1:

[0056] Users access a special page and enter their skill information and spare time schedule.

[0057] Step 2:

[0058] The terminal displays an input form and accepts input from the user.

[0059] Step 3:

[0060] When the device presses the send button, the input content is sent to the server as JSON format data.

[0061] Step 4:

[0062] The server parses the received JSON format data and saves the skill information and schedule information in a database.

[0063] Step 5:

[0064] Staff from other departments can access a special page and enter requests for problems that need to be solved or skills they are looking for.

[0065] Step 6:

[0066] The terminal displays an input form and accepts request information from staff in other departments.

[0067] Step 7:

[0068] When the device presses the send button, the input content is sent to the server as JSON format data.

[0069] Step 8:

[0070] The server analyzes the received JSON format data and saves the request information in the database.

[0071] Step 9:

[0072] The server retrieves user and request information from a database and runs a skill matching algorithm.

[0073] Step 10:

[0074] The server lists users who have the skills to handle the request.

[0075] Step 11:

[0076] The server checks the free time schedule of the selected user and extracts a time slot in which the request can be executed.

[0077] Step 12:

[0078] The server generates match suggestion notifications for suitable users.

[0079] Step 13:

[0080] The server sends a notification to the user.

[0081] Step 14:

[0082] Users receive notifications and check their schedules.

[0083] Step 15:

[0084] The terminal provides the user with the option to accept or decline and accepts the input.

[0085] Step 16:

[0086] The server obtains the user's approval and notifies the person in charge of the other department who made the request of the final schedule and task details.

[0087] Step 17:

[0088] The user visits other departments at a specified time or participates in an online conference to perform support work.

[0089] Step 18:

[0090] The user reports progress from the terminal.

[0091] Step 19:

[0092] The terminal sends the report to the server.

[0093] Step 20:

[0094] The server stores the received work report in a database.

[0095] Step 21:

[0096] The server notifies the user and other department personnel of the feedback request.

[0097] Step 22:

[0098] Users and staff from other departments access and fill out the feedback form.

[0099] Step 23:

[0100] The device sends the feedback to the server.

[0101] Step 24:

[0102] The feedback received by the server is stored in a database and used as data to improve matching accuracy next time.

[0103] The above are the specific processing steps of a system that efficiently utilizes the skills and spare time of users to support problem solving in other departments.

[0104] Example 1

[0105] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0106] In modern companies, the sharing of skills and the utilization of resources between different departments is becoming increasingly important. However, because each department has different areas of expertise, it is not always possible to solve problems within one department, making it difficult to efficiently find personnel in other departments who have the necessary skills. Furthermore, there is a lack of systems for identifying the free time of personnel with those skills and providing efficient support for their work. Therefore, there is a need for a system that can effectively match users' skills with their spare time and efficiently solve problems.

[0107] 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.

[0108] In this invention, the server includes: means for a user to input their own ability information and free time schedule; means for a person in another department to input request information regarding problems that need to be solved and the abilities they desire; means for saving the ability information, free time schedule, and request information in a database; means for comparing the ability information and request information and selecting a suitable user; means for checking the free time schedule of the selected user and proposing a workable timetable; means for notifying the user of the proposed timetable and accepting approval; means for notifying the person in another department who made the request of the approved timetable and details of the work; means for inputting progress; means for transmitting the progress from the user to the server and saving it in the database; and means for inputting feedback to the user and the person in another department after the work is completed. This makes it possible to efficiently match users' skills and free time, and effectively support problem solving in other departments.

[0109] A "user" is an entity that accesses a special page and enters their own ability information and free time schedule.

[0110] A "terminal" is a device that allows a user or a person in charge of another department to input information and transmit the data to a server.

[0111] A "server" is a device that receives and analyzes data sent by users or staff from other departments, and stores the data in a database.

[0112] "Capability information" is information about the technical or specialized skills and knowledge possessed by a user.

[0113] The "available timetable" is information about the time slots that a user can provide to solve problems in other departments.

[0114] A "person in charge of another department" is an entity that inputs request information for a problem that is difficult to solve within one's own department.

[0115] "Request information" is information about problems that need to be solved or capabilities that are required by personnel in other departments.

[0116] "Database" is a system for storing analyzed capacity information, availability timetables and request information.

[0117] The "skill matching algorithm" is a program that compares the ability information and request information stored in the database and selects suitable users.

[0118] The "proposed timetable" is a schedule of feasible time slots created based on the free time of the selected users.

[0119] "Notification" is a message that informs the user or other department personnel of the proposed timetable, final schedule, and task details.

[0120] "Progress" is information about the process and results of the work the user has done to solve the problem.

[0121] "Feedback" refers to information about evaluations and opinions provided by users and staff from other departments after completing work.

[0122] A "generative AI model" is an artificial intelligence system that uses collected feedback and data to improve the accuracy of the next match.

[0123] A "prompt sentence" is an example of specific text to be input into a generative AI model.

[0124] The system of the present invention is a system for promoting the effective use of in-house skills and spare time, and for supporting problem solving in other departments. To implement this system, the following hardware and software are used.

[0125] Hardware and software used

[0126] 1. Server: Performs processes such as receiving, analyzing, storing, collating, and notifying data. Examples of use include web servers using Apache (registered trademark) or Nginx, and database servers using MySQL (registered trademark) or PostgreSQL.

[0127] 2. Terminal: A device that allows users or staff from other departments to input information and send the data to a server. This includes personal computers, tablets, smartphones, etc.

[0128] 3. Analysis tools: Use data analysis tools such as Survicate or Datadog to analyze the data.

[0129] 4. Information retrieval library: Use an information retrieval library such as ElasticSearch (registered trademark) or Apache Lucene to execute the skill matching algorithm.

[0130] 5. Generative AI model: An artificial intelligence system that uses collected feedback to improve the accuracy of the next match.

[0131] Example of a system

[0132] Registering and saving user information

[0133] Users access a special page and enter their own skill information (e.g., Java programming, data analysis) and available time slot (e.g., Mondays from 14:00 to 15:00). The device sends this information to the server as JSON format data, which is then stored in a database.

[0134] Enter and save request information

[0135] A person from another department accesses a special page and inputs the problem that needs to be solved or the required capabilities (e.g., fixing a bug in a Python program). The terminal sends this information to the server as JSON format data, which is then stored in a database.

[0136] Matching skills to requests

[0137] The server compares the user's ability information stored in the database with the request information using a skill matching algorithm (e.g., Elasticsearch or Apache Lucene) and lists matching users.

[0138] Check schedule and suggest possible times

[0139] The server checks the free time schedules of the matching users and extracts feasible time slots for the request. Based on this information, it generates a feasible schedule and prepares notification messages to propose it to the users.

[0140] Notifications and Scheduling

[0141] The server sends a notification of the matching proposal to the user. The user receives the notification, checks their own schedule, and selects whether to accept or reject. If the user accepts, the server notifies the person in charge of the other department who made the request of the final schedule and task details.

[0142] Business support and progress reports

[0143] Users can visit other departments at designated times or participate in online meetings to carry out support work. During and after work, users report their progress from their terminals, and the server stores this information in a database.

[0144] Feedback collection and analysis

[0145] After the task is completed, the server notifies the user and other departments of the feedback request. The user enters their evaluation and opinion into a feedback form, which the device then sends to the server and stores in a database. The server analyzes the collected feedback and reflects it in the generative AI model to improve matching accuracy next time.

[0146] Prompt Sentence Examples

[0147] Here are some example prompts for a generative AI model:

[0148] Design a system to register a user's skill list in a database and match it with requests from other departments. Explain the process, including the steps of registering a user's skills, inputting a request, matching skills with requests, notifications, and collecting feedback, and use specific names (e.g., JSON format, skill matching algorithm, database, etc.).

[0149] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0150] Step 1:

[0151] Users access a special page and enter their ability information and available timetable.

[0152] What it does: The device displays a special page and provides a form where you can enter your skills (e.g., "Java programming," "data analysis") and available time (e.g., Mondays from 2:00 PM to 3:00 PM).

[0153] Input: Skill information, available timetable

[0154] Output: The data entered in the form is retrieved.

[0155] Step 2:

[0156] The terminal converts the entered user information into JSON format data and sends it to the server.

[0157] Specific operation: The terminal parses the input data into JSON format and sends an HTTP request to the server.

[0158] Input: Data entered in a form

[0159] Output: User data in JSON format

[0160] Step 3:

[0161] The server analyzes the received JSON data and stores the ability information and free time schedule in a database.

[0162] Specific operation: The server analyzes the received data and inserts capability information and free time information into the database.

[0163] Input: User data in JSON format

[0164] Output: Capacity information and availability timetable stored in the database

[0165] Step 4:

[0166] Staff from other departments access a special page and enter request information about the problems that need to be solved and the skills they are looking for.

[0167] What it does: The terminal displays a special page and provides a form where you can enter your request information (e.g., "Fix a bug in a Python program").

[0168] Input: Request information

[0169] Output: The data entered in the form is retrieved.

[0170] Step 5:

[0171] The terminal converts the request information into JSON format data and sends it to the server.

[0172] Specific operation: The terminal parses the input data into JSON format and sends an HTTP request to the server.

[0173] Input: Data entered in a form

[0174] Output: Request data in JSON format

[0175] Step 6:

[0176] The server parses the received JSON data and saves the request information in a database.

[0177] Specific operation: The server analyzes the received data and inserts the request information into the database.

[0178] Input: Request data in JSON format

[0179] Output: Request information stored in the database

[0180] Step 7:

[0181] The server runs a skills matching algorithm to match the capability information with the request information.

[0182] How it works: The server uses libraries such as Elasticsearch or Apache Lucene to match the request information with the capability information in the database and select a matching user.

[0183] Input: Capability and request information stored in the database

[0184] Output: A list of matching users as a result of the matching algorithm.

[0185] Step 8:

[0186] The server checks the free time schedules of the selected users and proposes feasible schedules.

[0187] Specific operation: The server extracts the free / busy data of the selected users and generates a feasible schedule that corresponds to the request.

[0188] Input: list of matching users, free time schedule

[0189] Output: Proposed feasible schedule

[0190] Step 9:

[0191] The server notifies the user of the proposed schedule and accepts approval.

[0192] What happens: The server creates a notification message and sends it to the user, allowing the user to accept or decline.

[0193] Input: Proposed Schedule

[0194] Output: Approval or rejection result

[0195] Step 10:

[0196] The server notifies the requesting person in the other department of the approved schedule and task details.

[0197] Specific operation: The server creates a message containing the final schedule and work details and sends it to the person in charge in the other department.

[0198] Inputs: Approved schedule, task details

[0199] Output: Notification to other department personnel

[0200] Step 11:

[0201] Users can visit other departments at designated times or participate in online meetings to perform support tasks.

[0202] Specific actions: The user performs the work according to the proposed schedule.

[0203] Input: Final schedule, support details

[0204] Output: Support activities performed

[0205] Step 12:

[0206] The user reports the progress from the terminal while working and when the work is completed.

[0207] Specific operation: The terminal displays a progress report form, and the user enters the required information. The entered data is sent to the server.

[0208] Input: Progress data

[0209] Output: Progress saved in the database

[0210] Step 13:

[0211] After the work is completed, the server notifies the user and the person in charge of the other department of the feedback request.

[0212] Specific behavior: The server creates a notification message with a link to a feedback form and sends it to the user and other department personnel.

[0213] Input: Notice of business termination

[0214] Output: Feedback request notification

[0215] Step 14:

[0216] Users and staff from other departments enter their evaluations and opinions into a feedback form, and the terminal sends them to the server.

[0217] Specific operation: The terminal displays a feedback form and sends the data entered by the user and the person in charge to the server.

[0218] Input: Feedback data

[0219] Output: Feedback stored in a database

[0220] Step 15:

[0221] The server analyzes the collected feedback and reflects it in the generative AI model.

[0222] What it does: The server analyzes the feedback data and provides the results to the generative AI model to improve the accuracy of the next match.

[0223] Input: Collected feedback

[0224] Output: Update data for the generative AI model

[0225] Prompt Sentence Examples

[0226] Here are some example prompts for a generative AI model:

[0227] Design a system to register a user's skill list in a database and match it with requests from other departments. Explain the process, including the steps of registering a user's skills, inputting a request, matching skills with requests, notifications, and collecting feedback, and use specific names (e.g., JSON format, skill matching algorithm, database, etc.).

[0228] (Application example 1)

[0229] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0230] In factories, the inability to effectively utilize the skills and spare time of specific engineers often leads to reduced productivity and delays in problem resolution. Furthermore, with conventional technology, managing the schedules of factory robots and engineers is cumbersome, making it difficult to quickly secure the right support personnel. Therefore, there is a need for a system that can appropriately match engineers' skills and spare time to smoothly resolve problems.

[0231] 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.

[0232] In this invention, the server includes: means for users to input their own skill information and spare time schedules; means for personnel from other departments to input request information regarding problems that need to be solved or skills they are looking for; means for saving the skill information, spare time schedules, and request information in a database; means for comparing the skill information and request information to select suitable users; means for checking the spare time schedules of the selected users and proposing feasible schedules; means for notifying the users of the proposed schedules and accepting their approval; means for notifying the personnel from other departments who made the request of details of the approved schedules and tasks; means for reporting the progress of ongoing work to users and saving the results in a database; means for collecting feedback from the users and personnel from other departments and saving and analyzing the feedback in a database to improve the accuracy of next task matching; and means for inputting and saving the skill information and spare time schedules using display terminals equipped on factory robots and mobile terminals of engineers and comparing them with the request information. This enables the skills and spare time of engineers in the factory to be fully utilized to quickly and efficiently solve problems.

[0233] A "user" is a person or organization that can input skill information and a schedule of spare time to assist other departments in solving problems.

[0234] "Other department representative" refers to a person or organization whose role is to input request information regarding problems that need to be solved or skills that are needed within their own department.

[0235] "Skill information" is information about the specialized skills and knowledge possessed by the user.

[0236] The "free time schedule" is information about the time period when the user is free from the current work.

[0237] "Request information" is information about problems that need to be solved or skills that are required by staff from other departments.

[0238] A "database" is a storage system of pieces of information for storing skill information, spare time schedules, and request information.

[0239] "Matching" is the process of comparing the skill information stored in the database with the request information and selecting a suitable user.

[0240] A "feasible schedule" is a proposal regarding the time periods when the selected users are available to assist with requests.

[0241] "Notification" is the act of informing users and other departments of details of the proposed schedule and tasks.

[0242] "Progress" is information about the current progress and results of ongoing work.

[0243] "Feedback" refers to evaluations and opinions collected from users and staff in other departments after the work is completed.

[0244] A "factory robot" is a device that automatically performs specific tasks in a manufacturing site and may be equipped with a display terminal.

[0245] "Mobile terminal" means a portable device used by a technician to input and store skill information and spare time schedules.

[0246] A "generative AI model" is an artificial intelligence program that finds patterns in large amounts of data and makes predictions and classifications based on the input data.

[0247] A "prompt sentence" is a sentence that guides the user to enter information in a particular format.

[0248] This invention is a system for quickly and efficiently solving problems by effectively utilizing the skills and spare time of specific engineers in a factory. This system is implemented using a cloud server, a database, mobile devices of engineers, and display terminals equipped on factory robots.

[0249] Registering and saving user information

[0250] Engineers access a dedicated app from their mobile device (e.g., a smartphone) and enter their own skill information and schedule for spare time. For example, the following skill information and schedule are entered:

[0251] Skills: "Sensor Calibration", "Machine Maintenance"

[0252] Schedule: "Monday 14:00 to 15:00"

[0253] The device sends this information as JSON format data to the cloud server, which then analyzes the data and stores the skill and schedule information in a database.

[0254] Enter and save request information

[0255] Factory managers access a dedicated page from the display terminals installed on factory robots and input the support tasks required by the robots. For example, a request such as "Fix an abnormal sensor on Robot A" may be entered. The terminal sends this information to the cloud server as JSON format data. The cloud server analyzes the received data and stores the request information in a database.

[0256] Matching skills to requests

[0257] The cloud server periodically compares the request information with the technician skill information stored in the database. Generative AI models are used to improve the accuracy of the matching process. The optimal match is made and a list of suitable technicians is created.

[0258] Check schedule and suggest possible times

[0259] The cloud server checks the free time schedules of the selected engineers and extracts the available time slots for the request. Based on this information, the server generates a schedule to propose to the engineers and prepares a notification message.

[0260] Notifications and Scheduling

[0261] The cloud server notifies the engineer of the proposed schedule via their mobile device. The engineer can then review the notification and choose to approve or reject it. If approved, the cloud server notifies the factory manager of the final schedule and task details.

[0262] Business support and progress reports

[0263] The technician performs support tasks at the designated time, either on the factory robot or at the designated site. At the end of the task, the technician reports the progress to the cloud server from the mobile device. This progress report is also sent in JSON format and stored in the database.

[0264] Feedback collection and analysis

[0265] After completing a task, the cloud server notifies the engineer and factory manager of the feedback request. The engineer uses a mobile device, and the manager uses a display device to enter their evaluation and opinions into the feedback form. The collected feedback is sent to the cloud server, where it is stored in a database and analyzed to improve the accuracy of task matching next time.

[0266] Examples and prompts

[0267] Examples of specific prompts include the following:

[0268] "Enter Technician A's skills and schedule. Example: Skill: 'Sensor Calibration', Schedule: 'Monday 14:00 to 15:00'"

[0269] "Administrator B, please enter the support task for Robot A. Example: 'Fix the sensor abnormality of Robot A'."

[0270] This system makes it possible to make the most of the skills and spare time of factory engineers and resolve problems quickly and efficiently.

[0271] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0272] Step 1:

[0273] Technicians access a dedicated app from their mobile devices and input their skill information and spare time schedule. For example, inputs include skills such as "sensor calibration" and "machine maintenance," and a schedule such as "Monday 14:00 to 15:00." The input data is converted into JSON format and sent to the cloud server.

[0274] Step 2:

[0275] The cloud server parses the received JSON data, extracts the skill information and the spare time schedule, and then stores this information in a database for future reference.

[0276] Step 3:

[0277] The factory manager accesses a dedicated page from the display terminal equipped on the factory robot and inputs the task for which support is required. The input is request information such as "Fix the sensor abnormality of robot A." The data entered by the manager is also converted to JSON format and sent to the cloud server.

[0278] Step 4:

[0279] The cloud server analyzes the received request information, extracts the request content, and stores it in a database. This request information is then compared with the skill information of the technician.

[0280] Step 5:

[0281] The cloud server periodically compares the request information with the technician skill information stored in the database. It then uses a generative AI model to create a list of technicians who best match the request. The input is the information in the database, and the output is a list of the best technicians.

[0282] Step 6:

[0283] The cloud server again retrieves the optimal spare time schedule of the engineer from the database and extracts the time slots that can be executed for the request. This generates a feasible schedule and proposes the optimal time slots for the engineer.

[0284] Step 7:

[0285] The cloud server notifies the technician of the proposed schedule on his / her mobile device. The notification includes details of the possible schedules and tasks. The technician can then review the notification and choose to accept or reject it.

[0286] Step 8:

[0287] Once the technician approves, the cloud server notifies the factory manager of the final schedule and task details, who can then make adjustments.

[0288] Step 9:

[0289] Engineers perform support tasks at designated times on factory robots or at designated sites. When the task is completed, the engineers report the progress to the cloud server from their mobile devices. The progress reports, sent in JSON format, are stored in a database.

[0290] Step 10:

[0291] The cloud server collects feedback from engineers and factory managers by sending emails and push notifications requesting them to fill out a feedback form. The feedback is sent to the cloud server and stored in a database. This feedback data is analyzed to improve the accuracy of task matching for the next time.

[0292] 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.

[0293] The system of the present invention combines the basic function of matching a user's skills and spare time with the needs of other departments with an emotion engine that recognizes the user's emotions, thereby providing more appropriate schedule adjustments and business support. The following describes in detail how the system is implemented.

[0294] Registering and saving user information

[0295] The user accesses a special page and enters their own skill information and spare time schedule. The device displays an input form and accepts input from the user. For example, "Web design" and "Project management" are registered as skills, and spare time from 10:00 to 11:00 on Friday is entered. The device sends this information to the server as JSON format data. The server analyzes the received data and saves the skill information and schedule information in a database.

[0296] Enter and save request information

[0297] A person from another department accesses a special page and enters a request for a problem that needs to be solved or a skill they need. The device displays an input form and accepts the input. For example, the user enters "design review." The device sends this information to the server as JSON format data. The server analyzes the received data and saves the request information in a database.

[0298] Matching skills to requests

[0299] The server retrieves user information and request information from the database, runs a skill matching algorithm, and lists users who have the skills to match the request.

[0300] Check schedule and suggest possible times

[0301] The server checks the selected users' free time schedules and extracts available time slots for the request. Based on this information, the server generates a schedule to propose to the users and prepares a notification message.

[0302] Emotion recognition by emotion engine

[0303] For emotion recognition, the system incorporates an emotion engine. The device collects emotional data from the user's facial expressions, voice tone, and input. For example, if the user is determined to be "tired," that information is stored in a database. This allows the system to optimize matching and scheduling by taking the user's emotional state into account.

[0304] Notifications and Scheduling

[0305] The server sends a notification of the proposed match to the user. The user receives the notification and checks their schedule and the proposed work. The terminal provides the option to accept or reject the request and accepts input from the user. If the user accepts, the server notifies the person in the other department who made the request of the final schedule and task details.

[0306] Business support and progress reports

[0307] Users visit other departments at designated times or participate in online meetings to perform support tasks. During and after work, they report their progress from their terminal. The terminal displays a progress report form, and the user enters the required information. The progress report is sent to the server, which stores it in a database.

[0308] Feedback collection and analysis

[0309] After the work is completed, the server notifies the user and staff from other departments of the feedback request. The terminal displays a feedback form, and the user and staff from other departments enter their evaluations and opinions. The feedback is sent to the server, which stores it in a database. The collected feedback is analyzed and used as data to improve the accuracy of the next match.

[0310] In this way, the system can provide the most appropriate resource matching, taking into account the user's emotional state, thereby reducing the burden on the user and achieving optimal business support.

[0311] The processing flow will be explained below.

[0312] Step 1:

[0313] Users access a special page and enter their skill information and spare time schedule.

[0314] Step 2:

[0315] The terminal displays an input form and accepts input from the user.

[0316] Step 3:

[0317] When the device presses the send button, the input content is sent to the server as JSON format data.

[0318] Step 4:

[0319] The server parses the received JSON format data and saves the skill information and schedule information in a database.

[0320] Step 5:

[0321] Staff from other departments can access a special page and enter requests for problems that need to be solved or skills they are looking for.

[0322] Step 6:

[0323] The terminal displays an input form and accepts request information from staff in other departments.

[0324] Step 7:

[0325] When the device presses the send button, the input content is sent to the server as JSON format data.

[0326] Step 8:

[0327] The server analyzes the received JSON format data and saves the request information in the database.

[0328] Step 9:

[0329] The server retrieves user and request information from a database and runs a skill matching algorithm.

[0330] Step 10:

[0331] The server lists users who have the skills to handle the request.

[0332] Step 11:

[0333] The server checks the free time schedule of the selected user and extracts a time slot in which the request can be executed.

[0334] Step 12:

[0335] The server obtains the user's latest emotional state using an emotion engine, which generates emotion data by analyzing the user's facial expressions, tone of voice, input content, etc.

[0336] Step 13:

[0337] The device sends the user's facial expressions and voice to the emotion engine.

[0338] Step 14:

[0339] The emotion engine determines the user's emotion and sends the data to the server.

[0340] Step 15:

[0341] The server uses emotion data to optimize the time slots available for requests, including suggesting lighter tasks when the user is tired.

[0342] Step 16:

[0343] The server generates match suggestion notifications for suitable users.

[0344] Step 17:

[0345] The server sends a notification to the user.

[0346] Step 18:

[0347] Users receive notifications and review their schedules and proposed work.

[0348] Step 19:

[0349] The terminal displays the option to accept or decline and accepts input from the user.

[0350] Step 20:

[0351] The server obtains the user's approval and notifies the person in charge of the other department who made the request of the final schedule and task details.

[0352] Step 21:

[0353] The user visits other departments at a specified time or participates in an online conference to perform support work.

[0354] Step 22:

[0355] The user reports progress from the terminal.

[0356] Step 23:

[0357] The terminal sends the report to the server.

[0358] Step 24:

[0359] The server stores the received work report in a database.

[0360] Step 25:

[0361] The server notifies the user and other department personnel of the feedback request.

[0362] Step 26:

[0363] Users and staff from other departments access and fill out the feedback form.

[0364] Step 27:

[0365] The device sends the feedback to the server.

[0366] Step 28:

[0367] The feedback received by the server is stored in a database and used as data to improve matching accuracy next time.

[0368] This allows the system to provide appropriate resource matching and business support while taking into account the user's emotional state.

[0369] Example 2

[0370] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0371] Conventional task matching systems provide a function to match optimal resources based on the user's skill information and spare time schedule. However, these systems only perform simple matching without considering the user's emotional state, which can increase the user's psychological burden and reduce work efficiency. In addition, there are cases where requests are not handled appropriately or progress management is insufficient, resulting in insufficient comprehensive work support.

[0372] 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.

[0373] In this invention, the server includes a means for users to input their own skill information and spare time schedules, a means for personnel in other departments to input requirement information regarding problems that need to be solved or skills they are looking for, a means for saving the skill information, spare time schedules, and requirement information in a data storage device, a means for comparing the skill information and requirement information and selecting suitable users, a means for checking the spare time schedules of the selected users and proposing feasible schedules, a means for collecting emotional data from the user's facial expressions, tone of voice, input content, etc., and recognizing the emotional state, a means for notifying the user of the proposed schedule and accepting approval, and a means for notifying the personnel in other departments who made the request of details of the approved schedule and tasks. This enables optimal resource matching and business support that takes into account the user's emotional state.

[0374] "User" is a general term for individuals or groups who use this system to input their own skill information and spare time schedules, and provide resources to other departments.

[0375] "Skill information" is a general term for data that refers to the specialized knowledge, skills, experience, etc. that a user possesses.

[0376] The "schedule for spare time" refers to data for a free time period designated by the user that does not overlap with other work.

[0377] "Other department personnel" is a collective term for individuals or groups who use the system to request a problem that needs to be solved or a resource with specific skills.

[0378] "Requirements information" refers to information entered by personnel in other departments regarding problems that need to be solved or skills that are being sought.

[0379] "Data storage device" refers to a database or storage system for saving and managing various data for the entire system.

[0380] "Matching" refers to the process of comparing the user's skill information with the requirements information of other departments to find matching or compatible items.

[0381] "Schedule proposal" refers to a proposal of feasible time slots that the system makes to the user based on the user's free time and the request information of other departments.

[0382] "Emotional data" refers to data collected from the user's facial expressions, voice tone, input content, etc., that indicates the user's emotional state.

[0383] "Notification" refers to the process by which the system communicates information to users and other department personnel.

[0384] "Acceptance" refers to an action that indicates the user accepts the suggestion from the system.

[0385] The system of the present invention not only has the basic function of matching a user's skill information and spare time with the requirements of other departments, but also incorporates an emotion engine that recognizes the user's emotions, thereby providing more appropriate schedule adjustments and business support. Specific implementation methods of the system are described in detail below.

[0386] Registering and saving user information

[0387] The user accesses a special page and enters their own skill information and spare time schedule. The device displays an input form and accepts the user's input. For example, "Web design" and "Project management" are registered as skills, and the spare time from 10:00 to 11:00 on Friday is entered. The entered data is converted to JSON format and sent to the server. The server analyzes the received data and saves it in a database.

[0388] Enter and save request information

[0389] A person from another department accesses a special page and enters a request for a problem that needs to be solved or a skill they need. The device displays an input form and accepts the input. For example, the user enters "design review." The input is converted to JSON format and sent to the server. The server analyzes the received data and stores it in a database.

[0390] Matching skills to requests

[0391] The server retrieves user and request information from the database and runs a skill matching algorithm. The server creates a list of users with the skills required for the request. Specifically, the server matches a user with the skill "Web design" with a request for "design review."

[0392] Check schedule and suggest possible times

[0393] The server retrieves the matched users' free time schedules and extracts the time slots that fit the request. For example, it finds that free time is available from 10:00 to 11:00 on Friday. The server uses this information to generate a suggested schedule and prepares a notification message.

[0394] Emotion recognition by emotion engine

[0395] For emotion recognition, the system employs an emotion engine. The device collects emotion data from the user's facial expressions, voice tone, and input. For example, it uses a camera and microphone to analyze the user's facial expressions and voice. If the user is determined to be "tired," the information is stored in a database. Based on this emotion data, the system takes the user's emotional state into account and optimizes matching and scheduling.

[0396] Notifications and Scheduling

[0397] The server sends a notification of the matching proposal to the user. The user receives the notification and checks the proposed schedule and work content. The terminal provides the option to accept or reject and accepts input from the user. If the user accepts the proposal, the server notifies the person in charge of the other department of the final schedule and task details.

[0398] Business support and progress reports

[0399] Users can visit other departments at designated times or participate in online meetings to support their work. They report their progress during and after work. The terminal displays a progress report form, and the user enters the required information. The progress report is converted to JSON format, sent to the server, and stored in a database.

[0400] Feedback collection and analysis

[0401] After the workday is over, the server notifies the user and staff from other departments of the feedback request. The terminal displays a feedback form, and the user and staff from other departments enter their ratings and opinions. The feedback content is converted to JSON format, sent to the server, and stored in a database. The server analyzes the collected feedback and uses it as data to improve the accuracy of the next match.

[0402] As a concrete example, the following is an example of a prompt sentence to be input to a generative AI model:

[0403] "A user has registered the skills of 'Web Design' and 'Project Management', and a spare time slot on Fridays from 10:00 to 11:00. A request for a design review has come in from another department, and the skills match. The proposed schedule will be for this spare time slot. The user's emotional state is recognized as 'Tired'. Can this be approved?"

[0404] By using this prompt, you can clearly explain the system and its suggestions.

[0405] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0406] Program processing flow

[0407] Step 1: Register and save your user information

[0408] Input: Data that users enter when they access a special page and enter their skill information and free time schedule.

[0409] Operation: The device displays an input form and accepts input from the user. The user enters "Web Design" and "Project Management" as skills and their spare time between 10:00 and 11:00 on Friday.

[0410] Data processing: The device converts this information into JSON format.

[0411] Output: The converted JSON data is sent to the server, which parses it and stores the skill and schedule information in a database.

[0412] Step 2: Enter and save your request information

[0413] Input: Data that allows staff from other departments to access a special page and enter request information about the problem that needs to be solved or the skills they are looking for.

[0414] Action: The device displays the input form and accepts input. The person types "Design review."

[0415] Data processing: The terminal converts this request information into JSON format.

[0416] Output: The converted JSON data is sent to the server, which parses the received data and saves the request information in a database.

[0417] Step 3: Matching skills to requests

[0418] Input: User and request information retrieved from the database.

[0419] How it works: The server runs a skill matching algorithm that uses the user's skill information to select a user with the skills to fulfill the request.

[0420] Data processing: Match the skill information with the request information and list the matching users.

[0421] Output: Information about the matched users.

[0422] Step 4: Check the schedule and propose feasible times

[0423] Input: Matched user's free time schedule information.

[0424] Action: The server checks the user's schedule and finds available time slots. Friday from 10:00 to 11:00 is determined to be available.

[0425] Data processing: Generate a proposed schedule based on the extracted information.

[0426] Output: The proposed schedule is prepared as a notification message.

[0427] Step 5: Emotion Recognition with the Emotion Engine

[0428] Input: Emotional data such as the user's facial expressions, tone of voice, and input.

[0429] How it works: The device uses a camera and microphone to collect the user's facial expressions and voice, which are then analyzed by the emotion engine. The device determines that the user is "tired."

[0430] Data processing: Analyze the collected emotion data and store it in a database.

[0431] Output: The user's emotional state is recorded.

[0432] Step 6: Notifications and Scheduling

[0433] Input: Proposed schedule and task details.

[0434] How it works: The server sends a notification of a proposed match to the user. The user receives the notification and reviews the proposed schedule and work content. The device displays the option to accept or reject. Input is accepted from the user.

[0435] Data processing: Processing information that the user has approved or rejected.

[0436] Output: The approved schedule and task details are notified to the relevant department.

[0437] Step 7: Implementation of business support and progress reporting

[0438] Input: Work performed on a schedule.

[0439] Operation: The user visits another department at a specified time or participates in an online meeting to assist with work. The terminal displays a progress report form, and the user enters the required information.

[0440] Data processing: Convert the progress report into JSON format.

[0441] Output: Progress reports are sent to the server and stored in a database.

[0442] Step 8: Gather and analyze feedback

[0443] Input: Feedback information from users and other departments.

[0444] Operation: The server sends a feedback request notification after the work is completed. The terminal displays a feedback form, and the user and other department staff can enter their evaluations and opinions.

[0445] Data processing: Convert the feedback information into JSON format.

[0446] Output: The feedback information is sent to the server and stored in a database. The server analyzes the collected feedback and uses it to improve the accuracy of the next match.

[0447] (Application example 2)

[0448] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0449] Conventional systems were able to match resources based on the user's skills and schedule, but they did not perform appropriate resource matching and schedule optimization that took the user's emotional state into account. This resulted in the problem of not taking the user's stress and fatigue levels into account, making it difficult to provide optimal work support. This problem was particularly pronounced in high-load environments such as logistics centers. Furthermore, there was a lack of means to detect the user's emotional state in real time and effectively utilize that data.

[0450] 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.

[0451] In this invention, the server includes: a means for a user to input their own skill information and spare time schedule; a means for a person in another department to input request information regarding problems that need to be solved or skills that they are looking for; a means for saving the skill information, spare time schedule, and request information in a database; a means for comparing the skill information and request information and selecting a suitable user; a means for confirming the spare time schedule of the selected user and proposing a feasible schedule; a means for notifying the user of the proposed schedule and accepting approval; a means for notifying the person in another department who made the request of details of the approved schedule and tasks; a means for detecting the user's emotional state and optimizing the optimal matching and schedule based on the information; and a means for using a camera and microphone to detect the user's emotional state via a smart device, thereby enabling optimal resource matching and schedule adjustment that takes the user's emotional state into consideration.

[0452] A "user" is an individual or entity that utilizes the system to enter their skill information and schedule.

[0453] "Skill information" is information about the knowledge and skills required for a user to carry out a specific job or task.

[0454] A "spare time schedule" is a list of the free time a user has available within a specific period of time.

[0455] "Request information" is data about problems that need to be solved or skills required by staff in other departments.

[0456] "Database" means a system for storing and managing skill information, schedule information, and request information.

[0457] The "matching means" is a function for comparing the user's skill information with the request information and selecting a suitable user.

[0458] The "schedule suggestion means" is a function that checks the user's free time schedule and creates a schedule that can be implemented in response to requests.

[0459] The "notification means" is a function for informing the user of the proposed schedule and receiving approval.

[0460] The "emotion detection means" is a function that recognizes the user's emotional state as data, and stores and analyzes that information.

[0461] A "smart device" is a device equipped with sensors such as a camera and a microphone, which is used to detect the emotional state of the user.

[0462] The system of the present invention effectively manages user skill information and spare time schedules, and optimally matches these with the needs of other departments. This system aims to improve work efficiency, particularly in logistics centers. The following describes in detail how the system is implemented.

[0463] System programming and processing methods

[0464] Program Generation

[0465] The system includes programs to perform the following functions:

[0466] 1. User information registration: Allows users to enter their current skills and their free time schedule.

[0467] 2. Request information entry: Allows staff from other departments to enter the problems to be solved and the skills required.

[0468] 3. Database management: Save the entered skill information, schedule information and request information in the database.

[0469] 4. Skill matching: Match the user's skill information with the request information and select the most suitable user.

[0470] 5. Schedule proposal: Check the free time of the selected users and propose a feasible schedule.

[0471] 6. Notification: Notify users of the proposed schedule and accept approval.

[0472] 7. Emotion detection: Detects the user's emotional state using smart devices (camera, microphone), and optimizes matching and scheduling based on that information.

[0473] 8. Feedback collection: After the work is completed, feedback is collected from users and staff from other departments.

[0474] Detailed explanation of the process

[0475] The server receives the skill information and spare time schedule entered by the user, as well as the request information entered by staff in other departments, and stores this information in a database. A Python library is used for database management.

[0476] The server compares the user's skill information with the request information to find the best match. The skill matching algorithm uses a machine learning model. For example, the scikit-learn library can be used to implement an algorithm that improves matching accuracy.

[0477] The server checks the selected user's free time schedule and proposes an optimal execution schedule. This schedule proposal uses the Google (registered trademark) Calendar API to avoid the user's busy times and finds an appropriate time slot.

[0478] The device will notify the user of the proposed schedule and give them the option to accept or reject it, using Firebase Cloud Messaging for this notification function.

[0479] The device (e.g., smart glasses) uses a built-in camera and microphone to detect the user's emotional state from facial expressions and voice in real time, and sends the information to a server, which processes the emotional information using the OpenCV library and the Google Cloud Speech-to-Text API.

[0480] The server provides optimal matching and scheduling, taking into account the user's emotional state. Collected data is analyzed using an AI model, which makes it possible to make improvements.

[0481] Specific examples

[0482] For example, imagine a worker at a logistics center wearing smart glasses. If this worker has the skills of "packing" and "sorting" and enters their spare time between 9:00 AM and 12:00 PM, the system will use that information to receive requests from other departments to "help with packing" and suggest an optimal schedule. If the system detects that the user is feeling "tired," it will refer to that emotion data and adjust the schedule so that the work assignments do not become a burden. For example, it may suggest that "working between 10:00 AM and 11:00 AM would be optimal."

[0483] Prompt Sentence Examples

[0484] Here is an example of the prompt the system will execute:

[0485] "User ID: user123, Skills: Packing, Sorting, Free Time: 09:00 to 12:00, Emotional State: Tired, Proposed Time: 10:00 to 11:00"

[0486] As described above, the system of the present invention can achieve optimal matching and schedule adjustment based on the emotional state of the user. By introducing this system, it is possible to simultaneously improve work efficiency at logistics centers and reduce the burden on users.

[0487] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0488] Step 1:

[0489] User information registration

[0490] The user inputs their skill information and their free time schedule. The device receives this information and sends it to the server as JSON format data. The server analyzes the received data and stores the user's skill information and schedule information in a database.

[0491] Input: Skill information, spare time schedule

[0492] Output: User information stored in the database

[0493] Specific operation: The user operates the device, enters skills and schedule information into the input form, and clicks the submit button. The server analyzes the received data and saves it in the database.

[0494] Step 2:

[0495] Enter request information

[0496] A person from another department inputs request information about the problem they need to solve or the skills they need. The device receives this information and sends it to the server as JSON data. The server analyzes the received data and stores the request information in a database.

[0497] Input: Request information

[0498] Output: Request information stored in the database

[0499] Specific operation: A person in another department operates a terminal, enters the request information into the input form, and clicks the send button. The server analyzes the received data and saves it in the database.

[0500] Step 3:

[0501] Skill Matching

[0502] The server retrieves user information and request information from the database and runs a skill matching algorithm to list users who have the skills to match the request.

[0503] Input: User and request information in the database

[0504] Output: A list of users who matched the request

[0505] Specific operation: The server runs a skill matching algorithm to select suitable users and generate a list.

[0506] Step 4:

[0507] Schedule proposal

[0508] The server checks the selected users' free time schedules and extracts available time slots for the request. It uses the Google Calendar API to suggest the optimal schedule.

[0509] Input: User's free time schedule, request information

[0510] Output: Proposed schedule

[0511] Specific operation: The server compares the user's schedule with the request, extracts the optimal time slot, and generates a proposed schedule.

[0512] Step 5:

[0513] notification

[0514] The device notifies the user of the proposed schedule and gives them the option to accept or reject it. Notifications are achieved using Firebase Cloud Messaging.

[0515] Input: Proposed Schedule

[0516] Output: Notification sent to the user

[0517] Specific operation: The server sends a notification via Firebase Cloud Messaging, and the device displays the notification to the user.

[0518] Step 6:

[0519] Emotion Detection

[0520] The device (e.g., smart glasses) uses a built-in camera and microphone to detect the user's facial expressions and voice, and collects their emotional state. The collected emotional data is then sent to a server.

[0521] Input: User's facial expression data, voice data

[0522] Output: Emotion data sent to the server

[0523] Specific operation: The camera captures the user's facial expressions, the microphone records audio, and these data are sent to the server.

[0524] Step 7:

[0525] Emotional data analysis and optimization

[0526] The server analyzes the collected emotional data and uses an emotion recognition engine and AI models to optimally match users and readjust their schedules, taking into account the burden on the users.

[0527] Input: Emotion data, existing schedule information

[0528] Output: Optimized matching and schedule

[0529] What it does: The server analyzes the emotion data, reevaluates the existing schedule, and optimizes it if necessary.

[0530] Step 8:

[0531] Feedback collection

[0532] After the task is completed, the server collects feedback from users and staff from other departments. The collected feedback is stored in a database and used to improve matching accuracy in the future.

[0533] Input: Feedback information

[0534] Output: Feedback data stored in a database

[0535] Specific operation: The terminal displays a feedback form, the user and the person in charge fill it out, and it is sent to the server, which analyzes the data and stores it in a database.

[0536] 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.

[0537] 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> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0538] 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.

[0539] [Second embodiment]

[0540] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0541] 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.

[0542] 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).

[0543] 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.

[0544] 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.

[0545] 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).

[0546] 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.

[0547] 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.

[0548] 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.

[0549] 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.

[0550] 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.

[0551] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0552] The system of the present invention supports problem solving in other departments by matching skills and spare time with the user and the person in charge of the other department, and compares the information entered by the user and the person in charge of the other department using a database. The following describes in detail how the system is implemented.

[0553] Registering and saving user information

[0554] The user accesses a special page. The device displays an input form, and the user enters their skill information and spare time schedule. For example, "Java programming" and "data analysis" are registered as skills, and the spare time from 14:00 to 15:00 on Mondays is entered. The device sends this information to the server as JSON format data. The server analyzes the received data and saves the skill information and schedule information in a database.

[0555] Enter and save request information

[0556] A person in another department accesses a special page to enter a request for solving a problem. The terminal displays an input form, and the person in charge enters the problem that needs to be solved and the skills required. For example, "fix a bug in a Python program." The terminal sends this information to the server as JSON format data. The server analyzes the received data and saves the request information in a database.

[0557] Matching skills to requests

[0558] The server runs a skill matching algorithm periodically or when a request occurs to match the request information with the user skill information stored in the database. The server searches the database for users who have the skills corresponding to the request and lists them.

[0559] Check schedule and suggest possible times

[0560] The server compares the selected users' free time schedules and extracts available time slots for the request. Based on this information, the server generates a schedule to propose to the user and prepares a notification message.

[0561] Notifications and Scheduling

[0562] The server sends a notification of the matching proposal to the user. The user receives the notification and checks their own schedule. The terminal displays the notification content, and the user can choose to accept or reject. If the user accepts, the server notifies the person in the other department who made the request of the final schedule and task details.

[0563] Business support and progress reports

[0564] Users visit other departments at designated times or participate in online meetings to perform support tasks. During and after work, they report their progress from their terminal. The terminal displays a progress report form, and the user enters the required information. The progress report is sent to the server, which stores it in a database.

[0565] Feedback collection and analysis

[0566] After completing the task, the server notifies the user and staff from other departments of the feedback request. The terminal displays a feedback form, and the user and staff from other departments enter their evaluations and opinions. The feedback is sent to the server and stored in a database. The server analyzes the collected feedback and uses it as data to improve the accuracy of the next match.

[0567] This allows the system to efficiently utilize internal skills and resources and effectively support other departments in solving problems and improving operations.

[0568] The processing flow will be explained below.

[0569] Step 1:

[0570] Users access a special page and enter their skill information and spare time schedule.

[0571] Step 2:

[0572] The terminal displays an input form and accepts input from the user.

[0573] Step 3:

[0574] When the device presses the send button, the input content is sent to the server as JSON format data.

[0575] Step 4:

[0576] The server parses the received JSON format data and saves the skill information and schedule information in a database.

[0577] Step 5:

[0578] Staff from other departments can access a special page and enter requests for problems that need to be solved or skills they are looking for.

[0579] Step 6:

[0580] The terminal displays an input form and accepts request information from staff in other departments.

[0581] Step 7:

[0582] When the device presses the send button, the input content is sent to the server as JSON format data.

[0583] Step 8:

[0584] The server analyzes the received JSON format data and saves the request information in the database.

[0585] Step 9:

[0586] The server retrieves user and request information from a database and runs a skill matching algorithm.

[0587] Step 10:

[0588] The server lists users who have the skills to handle the request.

[0589] Step 11:

[0590] The server checks the free time schedule of the selected user and extracts a time slot in which the request can be executed.

[0591] Step 12:

[0592] The server generates match suggestion notifications for suitable users.

[0593] Step 13:

[0594] The server sends a notification to the user.

[0595] Step 14:

[0596] Users receive notifications and check their schedules.

[0597] Step 15:

[0598] The terminal provides the user with the option to accept or decline and accepts the input.

[0599] Step 16:

[0600] The server obtains the user's approval and notifies the person in charge of the other department who made the request of the final schedule and task details.

[0601] Step 17:

[0602] The user visits other departments at a specified time or participates in an online conference to perform support work.

[0603] Step 18:

[0604] The user reports progress from the terminal.

[0605] Step 19:

[0606] The terminal sends the report to the server.

[0607] Step 20:

[0608] The server stores the received work report in a database.

[0609] Step 21:

[0610] The server notifies the user and other department personnel of the feedback request.

[0611] Step 22:

[0612] Users and staff from other departments access and fill out the feedback form.

[0613] Step 23:

[0614] The device sends the feedback to the server.

[0615] Step 24:

[0616] The feedback received by the server is stored in a database and used as data to improve matching accuracy next time.

[0617] The above are the specific processing steps of a system that efficiently utilizes the skills and spare time of users to support problem solving in other departments.

[0618] Example 1

[0619] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0620] In modern companies, the sharing of skills and the utilization of resources between different departments is becoming increasingly important. However, because each department has different areas of expertise, it is not always possible to solve problems within one department, making it difficult to efficiently find personnel in other departments who have the necessary skills. Furthermore, there is a lack of systems for identifying the free time of personnel with those skills and providing efficient support for their work. Therefore, there is a need for a system that can effectively match users' skills with their spare time and efficiently solve problems.

[0621] 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.

[0622] In this invention, the server includes: means for a user to input their own ability information and free time schedule; means for a person in another department to input request information regarding problems that need to be solved and the abilities they desire; means for saving the ability information, free time schedule, and request information in a database; means for comparing the ability information and request information and selecting a suitable user; means for checking the free time schedule of the selected user and proposing a workable timetable; means for notifying the user of the proposed timetable and accepting approval; means for notifying the person in another department who made the request of the approved timetable and details of the work; means for inputting progress; means for transmitting the progress from the user to the server and saving it in the database; and means for inputting feedback to the user and the person in another department after the work is completed. This makes it possible to efficiently match users' skills and free time, and effectively support problem solving in other departments.

[0623] A "user" is an entity that accesses a special page and enters their own ability information and free time schedule.

[0624] A "terminal" is a device that allows a user or a person in charge of another department to input information and transmit the data to a server.

[0625] A "server" is a device that receives and analyzes data sent by users or staff from other departments, and stores the data in a database.

[0626] "Capability information" is information about the technical or specialized skills and knowledge possessed by a user.

[0627] The "available timetable" is information about the time slots that a user can provide to solve problems in other departments.

[0628] A "person in charge of another department" is an entity that inputs request information for a problem that is difficult to solve within one's own department.

[0629] "Request information" is information about problems that need to be solved or capabilities that are required by personnel in other departments.

[0630] "Database" is a system for storing analyzed capacity information, availability timetables and request information.

[0631] The "skill matching algorithm" is a program that compares the ability information and request information stored in the database and selects suitable users.

[0632] The "proposed timetable" is a schedule of feasible time slots created based on the free time of the selected users.

[0633] "Notification" is a message that informs the user or other department personnel of the proposed timetable, final schedule, and task details.

[0634] "Progress" is information about the process and results of the work the user has done to solve the problem.

[0635] "Feedback" refers to information about evaluations and opinions provided by users and staff from other departments after completing work.

[0636] A "generative AI model" is an artificial intelligence system that uses collected feedback and data to improve the accuracy of the next match.

[0637] A "prompt sentence" is an example of specific text to be input into a generative AI model.

[0638] The system of the present invention is a system for promoting the effective use of in-house skills and spare time, and for supporting problem solving in other departments. To implement this system, the following hardware and software are used.

[0639] Hardware and software used

[0640] 1. Server: Performs processes such as receiving, analyzing, storing, collating, and notifying data. Examples of use include web servers using Apache or Nginx, and database servers using MySQL or PostgreSQL.

[0641] 2. Terminal: A device that allows users or staff from other departments to input information and send the data to a server. This includes personal computers, tablets, smartphones, etc.

[0642] 3. Analysis tools: Use data analysis tools such as Survicate or Datadog to analyze the data.

[0643] 4. Information retrieval library: Use an information retrieval library such as Elasticsearch or Apache Lucene to run the skill matching algorithm.

[0644] 5. Generative AI model: An artificial intelligence system that uses collected feedback to improve the accuracy of the next match.

[0645] Example of a system

[0646] Registering and saving user information

[0647] Users access a special page and enter their own skill information (e.g., Java programming, data analysis) and available time slot (e.g., Mondays from 14:00 to 15:00). The device sends this information to the server as JSON format data, which is then stored in a database.

[0648] Enter and save request information

[0649] A person from another department accesses a special page and inputs the problem that needs to be solved or the required capabilities (e.g., fixing a bug in a Python program). The terminal sends this information to the server as JSON format data, which is then stored in a database.

[0650] Matching skills to requests

[0651] The server compares the user's ability information stored in the database with the request information using a skill matching algorithm (e.g., Elasticsearch or Apache Lucene) and lists matching users.

[0652] Check schedule and suggest possible times

[0653] The server checks the free time schedules of the matching users and extracts feasible time slots for the request. Based on this information, it generates a feasible schedule and prepares notification messages to propose it to the users.

[0654] Notifications and Scheduling

[0655] The server sends a notification of the matching proposal to the user. The user receives the notification, checks their own schedule, and selects whether to accept or reject. If the user accepts, the server notifies the person in charge of the other department who made the request of the final schedule and task details.

[0656] Business support and progress reports

[0657] Users can visit other departments at designated times or participate in online meetings to carry out support work. During and after work, users report their progress from their terminals, and the server stores this information in a database.

[0658] Feedback collection and analysis

[0659] After the task is completed, the server notifies the user and other departments of the feedback request. The user enters their evaluation and opinion into a feedback form, which the device then sends to the server and stores in a database. The server analyzes the collected feedback and reflects it in the generative AI model to improve matching accuracy next time.

[0660] Prompt Sentence Examples

[0661] Here are some example prompts for a generative AI model:

[0662] Design a system to register a user's skill list in a database and match it with requests from other departments. Explain the process, including the steps of registering a user's skills, inputting a request, matching skills with requests, notifications, and collecting feedback, and use specific names (e.g., JSON format, skill matching algorithm, database, etc.).

[0663] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0664] Step 1:

[0665] Users access a special page and enter their ability information and available timetable.

[0666] What it does: The device displays a special page and provides a form where you can enter your skills (e.g., "Java programming," "data analysis") and available time (e.g., Mondays from 2:00 PM to 3:00 PM).

[0667] Input: Skill information, available timetable

[0668] Output: The data entered in the form is retrieved.

[0669] Step 2:

[0670] The terminal converts the entered user information into JSON format data and sends it to the server.

[0671] Specific operation: The terminal parses the input data into JSON format and sends an HTTP request to the server.

[0672] Input: Data entered in a form

[0673] Output: User data in JSON format

[0674] Step 3:

[0675] The server analyzes the received JSON data and stores the ability information and free time schedule in a database.

[0676] Specific operation: The server analyzes the received data and inserts capability information and free time information into the database.

[0677] Input: User data in JSON format

[0678] Output: Capacity information and availability timetable stored in the database

[0679] Step 4:

[0680] Staff from other departments access a special page and enter request information about the problems that need to be solved and the skills they are looking for.

[0681] What it does: The terminal displays a special page and provides a form where you can enter your request information (e.g., "Fix a bug in a Python program").

[0682] Input: Request information

[0683] Output: The data entered in the form is retrieved.

[0684] Step 5:

[0685] The terminal converts the request information into JSON format data and sends it to the server.

[0686] Specific operation: The terminal parses the input data into JSON format and sends an HTTP request to the server.

[0687] Input: Data entered in a form

[0688] Output: Request data in JSON format

[0689] Step 6:

[0690] The server parses the received JSON data and saves the request information in a database.

[0691] Specific operation: The server analyzes the received data and inserts the request information into the database.

[0692] Input: Request data in JSON format

[0693] Output: Request information stored in the database

[0694] Step 7:

[0695] The server runs a skills matching algorithm to match the capability information with the request information.

[0696] How it works: The server uses libraries such as Elasticsearch or Apache Lucene to match the request information with the capability information in the database and select a matching user.

[0697] Input: Capability and request information stored in the database

[0698] Output: A list of matching users as a result of the matching algorithm.

[0699] Step 8:

[0700] The server checks the free time schedules of the selected users and proposes feasible schedules.

[0701] Specific operation: The server extracts the free / busy data of the selected users and generates a feasible schedule that corresponds to the request.

[0702] Input: list of matching users, free time schedule

[0703] Output: Proposed feasible schedule

[0704] Step 9:

[0705] The server notifies the user of the proposed schedule and accepts approval.

[0706] What happens: The server creates a notification message and sends it to the user, allowing the user to accept or decline.

[0707] Input: Proposed Schedule

[0708] Output: Approval or rejection result

[0709] Step 10:

[0710] The server notifies the requesting person in the other department of the approved schedule and task details.

[0711] Specific operation: The server creates a message containing the final schedule and work details and sends it to the person in charge in the other department.

[0712] Inputs: Approved schedule, task details

[0713] Output: Notification to other department personnel

[0714] Step 11:

[0715] Users can visit other departments at designated times or participate in online meetings to perform support tasks.

[0716] Specific actions: The user performs the work according to the proposed schedule.

[0717] Input: Final schedule, support details

[0718] Output: Support activities performed

[0719] Step 12:

[0720] The user reports the progress from the terminal while working and when the work is completed.

[0721] Specific operation: The terminal displays a progress report form, and the user enters the required information. The entered data is sent to the server.

[0722] Input: Progress data

[0723] Output: Progress saved in the database

[0724] Step 13:

[0725] After the work is completed, the server notifies the user and the person in charge of the other department of the feedback request.

[0726] Specific behavior: The server creates a notification message with a link to a feedback form and sends it to the user and other department personnel.

[0727] Input: Notice of business termination

[0728] Output: Feedback request notification

[0729] Step 14:

[0730] Users and staff from other departments enter their evaluations and opinions into a feedback form, and the terminal sends them to the server.

[0731] Specific operation: The terminal displays a feedback form and sends the data entered by the user and the person in charge to the server.

[0732] Input: Feedback data

[0733] Output: Feedback stored in a database

[0734] Step 15:

[0735] The server analyzes the collected feedback and reflects it in the generative AI model.

[0736] What it does: The server analyzes the feedback data and provides the results to the generative AI model to improve the accuracy of the next match.

[0737] Input: Collected feedback

[0738] Output: Update data for the generative AI model

[0739] Prompt Sentence Examples

[0740] Here are some example prompts for a generative AI model:

[0741] Design a system to register a user's skill list in a database and match it with requests from other departments. Explain the process, including the steps of registering a user's skills, inputting a request, matching skills with requests, notifications, and collecting feedback, and use specific names (e.g., JSON format, skill matching algorithm, database, etc.).

[0742] (Application example 1)

[0743] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0744] In factories, the inability to effectively utilize the skills and spare time of specific engineers often leads to reduced productivity and delays in problem resolution. Furthermore, with conventional technology, managing the schedules of factory robots and engineers is cumbersome, making it difficult to quickly secure the right support personnel. Therefore, there is a need for a system that can appropriately match engineers' skills and spare time to smoothly resolve problems.

[0745] 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.

[0746] In this invention, the server includes: means for users to input their own skill information and spare time schedules; means for personnel from other departments to input request information regarding problems that need to be solved or skills they are looking for; means for saving the skill information, spare time schedules, and request information in a database; means for comparing the skill information and request information to select suitable users; means for checking the spare time schedules of the selected users and proposing feasible schedules; means for notifying the users of the proposed schedules and accepting their approval; means for notifying the personnel from other departments who made the request of details of the approved schedules and tasks; means for reporting the progress of ongoing work to users and saving the results in a database; means for collecting feedback from the users and personnel from other departments and saving and analyzing the feedback in a database to improve the accuracy of next task matching; and means for inputting and saving the skill information and spare time schedules using display terminals equipped on factory robots and mobile terminals of engineers and comparing them with the request information. This enables the skills and spare time of engineers in the factory to be fully utilized to quickly and efficiently solve problems.

[0747] A "user" is a person or organization that can input skill information and a schedule of spare time to assist other departments in solving problems.

[0748] "Other department representative" refers to a person or organization whose role is to input request information regarding problems that need to be solved or skills that are needed within their own department.

[0749] "Skill information" is information about the specialized skills and knowledge possessed by the user.

[0750] The "free time schedule" is information about the time period when the user is free from the current work.

[0751] "Request information" is information about problems that need to be solved or skills that are required by staff from other departments.

[0752] A "database" is a storage system of pieces of information for storing skill information, spare time schedules, and request information.

[0753] "Matching" is the process of comparing the skill information stored in the database with the request information and selecting a suitable user.

[0754] A "feasible schedule" is a proposal regarding the time periods when the selected users are available to assist with requests.

[0755] "Notification" is the act of informing users and other departments of details of the proposed schedule and tasks.

[0756] "Progress" is information about the current progress and results of ongoing work.

[0757] "Feedback" refers to evaluations and opinions collected from users and staff in other departments after the work is completed.

[0758] A "factory robot" is a device that automatically performs specific tasks in a manufacturing site and may be equipped with a display terminal.

[0759] "Mobile terminal" means a portable device used by a technician to input and store skill information and spare time schedules.

[0760] A "generative AI model" is an artificial intelligence program that finds patterns in large amounts of data and makes predictions and classifications based on the input data.

[0761] A "prompt sentence" is a sentence that guides the user to enter information in a particular format.

[0762] This invention is a system for quickly and efficiently solving problems by effectively utilizing the skills and spare time of specific engineers in a factory. This system is implemented using a cloud server, a database, mobile devices of engineers, and display terminals equipped on factory robots.

[0763] Registering and saving user information

[0764] Engineers access a dedicated app from their mobile device (e.g., a smartphone) and enter their own skill information and schedule for spare time. For example, the following skill information and schedule are entered:

[0765] Skills: "Sensor Calibration", "Machine Maintenance"

[0766] Schedule: "Monday 14:00 to 15:00"

[0767] The device sends this information as JSON format data to the cloud server, which then analyzes the data and stores the skill and schedule information in a database.

[0768] Enter and save request information

[0769] Factory managers access a dedicated page from the display terminals installed on factory robots and input the support tasks required by the robots. For example, a request such as "Fix an abnormal sensor on Robot A" may be entered. The terminal sends this information to the cloud server as JSON format data. The cloud server analyzes the received data and stores the request information in a database.

[0770] Matching skills to requests

[0771] The cloud server periodically compares the request information with the technician skill information stored in the database. Generative AI models are used to improve the accuracy of the matching process. The optimal match is made and a list of suitable technicians is created.

[0772] Check schedule and suggest possible times

[0773] The cloud server checks the free time schedules of the selected engineers and extracts the available time slots for the request. Based on this information, the server generates a schedule to propose to the engineers and prepares a notification message.

[0774] Notifications and Scheduling

[0775] The cloud server notifies the engineer of the proposed schedule via their mobile device. The engineer can then review the notification and choose to approve or reject it. If approved, the cloud server notifies the factory manager of the final schedule and task details.

[0776] Business support and progress reports

[0777] The technician performs support tasks at the designated time, either on the factory robot or at the designated site. At the end of the task, the technician reports the progress to the cloud server from the mobile device. This progress report is also sent in JSON format and stored in the database.

[0778] Feedback collection and analysis

[0779] After completing a task, the cloud server notifies the engineer and factory manager of the feedback request. The engineer uses a mobile device, and the manager uses a display device to enter their evaluation and opinions into the feedback form. The collected feedback is sent to the cloud server, where it is stored in a database and analyzed to improve the accuracy of task matching next time.

[0780] Examples and prompts

[0781] Examples of specific prompts include the following:

[0782] "Enter Technician A's skills and schedule. Example: Skill: 'Sensor Calibration', Schedule: 'Monday 14:00 to 15:00'"

[0783] "Administrator B, please enter the support task for Robot A. Example: 'Fix the sensor abnormality of Robot A'."

[0784] This system makes it possible to make the most of the skills and spare time of factory engineers and resolve problems quickly and efficiently.

[0785] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0786] Step 1:

[0787] Technicians access a dedicated app from their mobile devices and input their skill information and spare time schedule. For example, inputs include skills such as "sensor calibration" and "machine maintenance," and a schedule such as "Monday 14:00 to 15:00." The input data is converted into JSON format and sent to the cloud server.

[0788] Step 2:

[0789] The cloud server parses the received JSON data, extracts the skill information and the spare time schedule, and then stores this information in a database for future reference.

[0790] Step 3:

[0791] The factory manager accesses a dedicated page from the display terminal equipped on the factory robot and inputs the task for which support is required. The input is request information such as "Fix the sensor abnormality of robot A." The data entered by the manager is also converted to JSON format and sent to the cloud server.

[0792] Step 4:

[0793] The cloud server analyzes the received request information, extracts the request content, and stores it in a database. This request information is then compared with the skill information of the technician.

[0794] Step 5:

[0795] The cloud server periodically compares the request information with the technician skill information stored in the database. It then uses a generative AI model to create a list of technicians who best match the request. The input is the information in the database, and the output is a list of the best technicians.

[0796] Step 6:

[0797] The cloud server again retrieves the optimal spare time schedule of the engineer from the database and extracts the time slots that can be executed for the request. This generates a feasible schedule and proposes the optimal time slots for the engineer.

[0798] Step 7:

[0799] The cloud server notifies the technician of the proposed schedule on his / her mobile device. The notification includes details of the possible schedules and tasks. The technician can then review the notification and choose to accept or reject it.

[0800] Step 8:

[0801] Once the technician approves, the cloud server notifies the factory manager of the final schedule and task details, who can then make adjustments.

[0802] Step 9:

[0803] Engineers perform support tasks at designated times on factory robots or at designated sites. When the task is completed, the engineers report the progress to the cloud server from their mobile devices. The progress reports, sent in JSON format, are stored in a database.

[0804] Step 10:

[0805] The cloud server collects feedback from engineers and factory managers by sending emails and push notifications requesting them to fill out a feedback form. The feedback is sent to the cloud server and stored in a database. This feedback data is analyzed to improve the accuracy of task matching for the next time.

[0806] 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.

[0807] The system of the present invention combines the basic function of matching a user's skills and spare time with the needs of other departments with an emotion engine that recognizes the user's emotions, thereby providing more appropriate schedule adjustments and business support. The following describes in detail how the system is implemented.

[0808] Registering and saving user information

[0809] The user accesses a special page and enters their own skill information and spare time schedule. The device displays an input form and accepts input from the user. For example, "Web design" and "Project management" are registered as skills, and spare time from 10:00 to 11:00 on Friday is entered. The device sends this information to the server as JSON format data. The server analyzes the received data and saves the skill information and schedule information in a database.

[0810] Enter and save request information

[0811] A person from another department accesses a special page and enters a request for a problem that needs to be solved or a skill they need. The device displays an input form and accepts the input. For example, the user enters "design review." The device sends this information to the server as JSON format data. The server analyzes the received data and saves the request information in a database.

[0812] Matching skills to requests

[0813] The server retrieves user information and request information from the database, runs a skill matching algorithm, and lists users who have the skills to match the request.

[0814] Check schedule and suggest possible times

[0815] The server checks the selected users' free time schedules and extracts available time slots for the request. Based on this information, the server generates a schedule to propose to the users and prepares a notification message.

[0816] Emotion recognition by emotion engine

[0817] For emotion recognition, the system incorporates an emotion engine. The device collects emotional data from the user's facial expressions, voice tone, and input. For example, if the user is determined to be "tired," that information is stored in a database. This allows the system to optimize matching and scheduling by taking the user's emotional state into account.

[0818] Notifications and Scheduling

[0819] The server sends a notification of the proposed match to the user. The user receives the notification and checks their schedule and the proposed work. The terminal provides the option to accept or reject the request and accepts input from the user. If the user accepts, the server notifies the person in the other department who made the request of the final schedule and task details.

[0820] Business support and progress reports

[0821] Users visit other departments at designated times or participate in online meetings to perform support tasks. During and after work, they report their progress from their terminal. The terminal displays a progress report form, and the user enters the required information. The progress report is sent to the server, which stores it in a database.

[0822] Feedback collection and analysis

[0823] After the work is completed, the server notifies the user and staff from other departments of the feedback request. The terminal displays a feedback form, and the user and staff from other departments enter their evaluations and opinions. The feedback is sent to the server, which stores it in a database. The collected feedback is analyzed and used as data to improve the accuracy of the next match.

[0824] In this way, the system can provide the most appropriate resource matching, taking into account the user's emotional state, thereby reducing the burden on the user and achieving optimal business support.

[0825] The processing flow will be explained below.

[0826] Step 1:

[0827] Users access a special page and enter their skill information and spare time schedule.

[0828] Step 2:

[0829] The terminal displays an input form and accepts input from the user.

[0830] Step 3:

[0831] When the device presses the send button, the input content is sent to the server as JSON format data.

[0832] Step 4:

[0833] The server parses the received JSON format data and saves the skill information and schedule information in a database.

[0834] Step 5:

[0835] Staff from other departments can access a special page and enter requests for problems that need to be solved or skills they are looking for.

[0836] Step 6:

[0837] The terminal displays an input form and accepts request information from staff in other departments.

[0838] Step 7:

[0839] When the device presses the send button, the input content is sent to the server as JSON format data.

[0840] Step 8:

[0841] The server analyzes the received JSON format data and saves the request information in the database.

[0842] Step 9:

[0843] The server retrieves user and request information from a database and runs a skill matching algorithm.

[0844] Step 10:

[0845] The server lists users who have the skills to handle the request.

[0846] Step 11:

[0847] The server checks the free time schedule of the selected user and extracts a time slot in which the request can be executed.

[0848] Step 12:

[0849] The server obtains the user's latest emotional state using an emotion engine, which generates emotion data by analyzing the user's facial expressions, tone of voice, input content, etc.

[0850] Step 13:

[0851] The device sends the user's facial expressions and voice to the emotion engine.

[0852] Step 14:

[0853] The emotion engine determines the user's emotion and sends the data to the server.

[0854] Step 15:

[0855] The server uses emotion data to optimize the time slots available for requests, including suggesting lighter tasks when the user is tired.

[0856] Step 16:

[0857] The server generates match suggestion notifications for suitable users.

[0858] Step 17:

[0859] The server sends a notification to the user.

[0860] Step 18:

[0861] Users receive notifications and review their schedules and proposed work.

[0862] Step 19:

[0863] The terminal displays the option to accept or decline and accepts input from the user.

[0864] Step 20:

[0865] The server obtains the user's approval and notifies the person in charge of the other department who made the request of the final schedule and task details.

[0866] Step 21:

[0867] The user visits other departments at a specified time or participates in an online conference to perform support work.

[0868] Step 22:

[0869] The user reports progress from the terminal.

[0870] Step 23:

[0871] The terminal sends the report to the server.

[0872] Step 24:

[0873] The server stores the received work report in a database.

[0874] Step 25:

[0875] The server notifies the user and other department personnel of the feedback request.

[0876] Step 26:

[0877] Users and staff from other departments access and fill out the feedback form.

[0878] Step 27:

[0879] The device sends the feedback to the server.

[0880] Step 28:

[0881] The feedback received by the server is stored in a database and used as data to improve matching accuracy next time.

[0882] This allows the system to provide appropriate resource matching and business support while taking into account the user's emotional state.

[0883] Example 2

[0884] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0885] Conventional task matching systems provide a function to match optimal resources based on the user's skill information and spare time schedule. However, these systems only perform simple matching without considering the user's emotional state, which can increase the user's psychological burden and reduce work efficiency. In addition, there are cases where requests are not handled appropriately or progress management is insufficient, resulting in insufficient comprehensive work support.

[0886] 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.

[0887] In this invention, the server includes a means for users to input their own skill information and spare time schedules, a means for personnel in other departments to input requirement information regarding problems that need to be solved or skills they are looking for, a means for saving the skill information, spare time schedules, and requirement information in a data storage device, a means for comparing the skill information and requirement information and selecting suitable users, a means for checking the spare time schedules of the selected users and proposing feasible schedules, a means for collecting emotional data from the user's facial expressions, tone of voice, input content, etc., and recognizing the emotional state, a means for notifying the user of the proposed schedule and accepting approval, and a means for notifying the personnel in other departments who made the request of details of the approved schedule and tasks. This enables optimal resource matching and business support that takes into account the user's emotional state.

[0888] "User" is a general term for individuals or groups who use this system to input their own skill information and spare time schedules, and provide resources to other departments.

[0889] "Skill information" is a general term for data that refers to the specialized knowledge, skills, experience, etc. that a user possesses.

[0890] The "schedule for spare time" refers to data for a free time period designated by the user that does not overlap with other work.

[0891] "Other department personnel" is a collective term for individuals or groups who use the system to request a problem that needs to be solved or a resource with specific skills.

[0892] "Requirements information" refers to information entered by personnel in other departments regarding problems that need to be solved or skills that are being sought.

[0893] "Data storage device" refers to a database or storage system for saving and managing various data for the entire system.

[0894] "Matching" refers to the process of comparing the user's skill information with the requirements information of other departments to find matching or compatible items.

[0895] "Schedule proposal" refers to a proposal of feasible time slots that the system makes to the user based on the user's free time and the request information of other departments.

[0896] "Emotional data" refers to data collected from the user's facial expressions, voice tone, input content, etc., that indicates the user's emotional state.

[0897] "Notification" refers to the process by which the system communicates information to users and other department personnel.

[0898] "Acceptance" refers to an action that indicates the user accepts the suggestion from the system.

[0899] The system of the present invention not only has the basic function of matching a user's skill information and spare time with the requirements of other departments, but also incorporates an emotion engine that recognizes the user's emotions, thereby providing more appropriate schedule adjustments and business support. Specific implementation methods of the system are described in detail below.

[0900] Registering and saving user information

[0901] The user accesses a special page and enters their own skill information and spare time schedule. The device displays an input form and accepts the user's input. For example, "Web design" and "Project management" are registered as skills, and the spare time from 10:00 to 11:00 on Friday is entered. The entered data is converted to JSON format and sent to the server. The server analyzes the received data and saves it in a database.

[0902] Enter and save request information

[0903] A person from another department accesses a special page and enters a request for a problem that needs to be solved or a skill they need. The device displays an input form and accepts the input. For example, the user enters "design review." The input is converted to JSON format and sent to the server. The server analyzes the received data and stores it in a database.

[0904] Matching skills to requests

[0905] The server retrieves user and request information from the database and runs a skill matching algorithm. The server creates a list of users with the skills required for the request. Specifically, the server matches a user with the skill "Web design" with a request for "design review."

[0906] Check schedule and suggest possible times

[0907] The server retrieves the matched users' free time schedules and extracts the time slots that fit the request. For example, it finds that free time is available from 10:00 to 11:00 on Friday. The server uses this information to generate a suggested schedule and prepares a notification message.

[0908] Emotion recognition by emotion engine

[0909] For emotion recognition, the system employs an emotion engine. The device collects emotion data from the user's facial expressions, voice tone, and input. For example, it uses a camera and microphone to analyze the user's facial expressions and voice. If the user is determined to be "tired," the information is stored in a database. Based on this emotion data, the system takes the user's emotional state into account and optimizes matching and scheduling.

[0910] Notifications and Scheduling

[0911] The server sends a notification of the matching proposal to the user. The user receives the notification and checks the proposed schedule and work content. The terminal provides the option to accept or reject and accepts input from the user. If the user accepts the proposal, the server notifies the person in charge of the other department of the final schedule and task details.

[0912] Business support and progress reports

[0913] Users can visit other departments at designated times or participate in online meetings to support their work. They report their progress during and after work. The terminal displays a progress report form, and the user enters the required information. The progress report is converted to JSON format, sent to the server, and stored in a database.

[0914] Feedback collection and analysis

[0915] After the workday is over, the server notifies the user and staff from other departments of the feedback request. The terminal displays a feedback form, and the user and staff from other departments enter their ratings and opinions. The feedback content is converted to JSON format, sent to the server, and stored in a database. The server analyzes the collected feedback and uses it as data to improve the accuracy of the next match.

[0916] As a concrete example, the following is an example of a prompt sentence to be input to a generative AI model:

[0917] "A user has registered the skills of 'Web Design' and 'Project Management', and a spare time slot on Fridays from 10:00 to 11:00. A request for a design review has come in from another department, and the skills match. The proposed schedule will be for this spare time slot. The user's emotional state is recognized as 'Tired'. Can this be approved?"

[0918] By using this prompt, you can clearly explain the system and its suggestions.

[0919] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0920] Program processing flow

[0921] Step 1: Register and save your user information

[0922] Input: Data that users enter when they access a special page and enter their skill information and free time schedule.

[0923] Operation: The device displays an input form and accepts input from the user. The user enters "Web Design" and "Project Management" as skills and their spare time between 10:00 and 11:00 on Friday.

[0924] Data processing: The device converts this information into JSON format.

[0925] Output: The converted JSON data is sent to the server, which parses it and stores the skill and schedule information in a database.

[0926] Step 2: Enter and save your request information

[0927] Input: Data that allows staff from other departments to access a special page and enter request information about the problem that needs to be solved or the skills they are looking for.

[0928] Action: The device displays the input form and accepts input. The person types "Design review."

[0929] Data processing: The terminal converts this request information into JSON format.

[0930] Output: The converted JSON data is sent to the server, which parses the received data and saves the request information in a database.

[0931] Step 3: Matching skills to requests

[0932] Input: User and request information retrieved from the database.

[0933] How it works: The server runs a skill matching algorithm that uses the user's skill information to select a user with the skills to fulfill the request.

[0934] Data processing: Match the skill information with the request information and list the matching users.

[0935] Output: Information about the matched users.

[0936] Step 4: Check the schedule and propose feasible times

[0937] Input: Matched user's free time schedule information.

[0938] Action: The server checks the user's schedule and finds available time slots. Friday from 10:00 to 11:00 is determined to be available.

[0939] Data processing: Generate a proposed schedule based on the extracted information.

[0940] Output: The proposed schedule is prepared as a notification message.

[0941] Step 5: Emotion Recognition with the Emotion Engine

[0942] Input: Emotional data such as the user's facial expressions, tone of voice, and input.

[0943] How it works: The device uses a camera and microphone to collect the user's facial expressions and voice, which are then analyzed by the emotion engine. The device determines that the user is "tired."

[0944] Data processing: Analyze the collected emotion data and store it in a database.

[0945] Output: The user's emotional state is recorded.

[0946] Step 6: Notifications and Scheduling

[0947] Input: Proposed schedule and task details.

[0948] How it works: The server sends a notification of a proposed match to the user. The user receives the notification and reviews the proposed schedule and work content. The device displays the option to accept or reject. Input is accepted from the user.

[0949] Data processing: Processing information that the user has approved or rejected.

[0950] Output: The approved schedule and task details are notified to the relevant department.

[0951] Step 7: Implementation of business support and progress reporting

[0952] Input: Work performed on a schedule.

[0953] Operation: The user visits another department at a specified time or participates in an online meeting to assist with work. The terminal displays a progress report form, and the user enters the required information.

[0954] Data processing: Convert the progress report into JSON format.

[0955] Output: Progress reports are sent to the server and stored in a database.

[0956] Step 8: Gather and analyze feedback

[0957] Input: Feedback information from users and other departments.

[0958] Operation: The server sends a feedback request notification after the work is completed. The terminal displays a feedback form, and the user and other department staff can enter their evaluations and opinions.

[0959] Data processing: Convert the feedback information into JSON format.

[0960] Output: The feedback information is sent to the server and stored in a database. The server analyzes the collected feedback and uses it to improve the accuracy of the next match.

[0961] (Application example 2)

[0962] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0963] Conventional systems were able to match resources based on the user's skills and schedule, but they did not perform appropriate resource matching and schedule optimization that took the user's emotional state into account. This resulted in the problem of not taking the user's stress and fatigue levels into account, making it difficult to provide optimal work support. This problem was particularly pronounced in high-load environments such as logistics centers. Furthermore, there was a lack of means to detect the user's emotional state in real time and effectively utilize that data.

[0964] 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.

[0965] In this invention, the server includes: a means for a user to input their own skill information and spare time schedule; a means for a person in another department to input request information regarding problems that need to be solved or skills that they are looking for; a means for saving the skill information, spare time schedule, and request information in a database; a means for comparing the skill information and request information and selecting a suitable user; a means for confirming the spare time schedule of the selected user and proposing a feasible schedule; a means for notifying the user of the proposed schedule and accepting approval; a means for notifying the person in another department who made the request of details of the approved schedule and tasks; a means for detecting the user's emotional state and optimizing the optimal matching and schedule based on the information; and a means for using a camera and microphone to detect the user's emotional state via a smart device, thereby enabling optimal resource matching and schedule adjustment that takes the user's emotional state into consideration.

[0966] A "user" is an individual or entity that utilizes the system to enter their skill information and schedule.

[0967] "Skill information" is information about the knowledge and skills required for a user to carry out a specific job or task.

[0968] A "spare time schedule" is a list of the free time a user has available within a specific period of time.

[0969] "Request information" is data about problems that need to be solved or skills required by staff in other departments.

[0970] "Database" means a system for storing and managing skill information, schedule information, and request information.

[0971] The "matching means" is a function for comparing the user's skill information with the request information and selecting a suitable user.

[0972] The "schedule suggestion means" is a function that checks the user's free time schedule and creates a schedule that can be implemented in response to requests.

[0973] The "notification means" is a function for informing the user of the proposed schedule and receiving approval.

[0974] The "emotion detection means" is a function that recognizes the user's emotional state as data, and stores and analyzes that information.

[0975] A "smart device" is a device equipped with sensors such as a camera and a microphone, which is used to detect the emotional state of the user.

[0976] The system of the present invention effectively manages user skill information and spare time schedules, and optimally matches these with the needs of other departments. This system aims to improve work efficiency, particularly in logistics centers. The following describes in detail how the system is implemented.

[0977] System programming and processing methods

[0978] Program Generation

[0979] The system includes programs to perform the following functions:

[0980] 1. User information registration: Allows users to enter their current skills and their free time schedule.

[0981] 2. Request information entry: Allows staff from other departments to enter the problems to be solved and the skills required.

[0982] 3. Database management: Save the entered skill information, schedule information and request information in the database.

[0983] 4. Skill matching: Match the user's skill information with the request information and select the most suitable user.

[0984] 5. Schedule proposal: Check the free time of the selected users and propose a feasible schedule.

[0985] 6. Notification: Notify users of the proposed schedule and accept approval.

[0986] 7. Emotion detection: Detects the user's emotional state using smart devices (camera, microphone), and optimizes matching and scheduling based on that information.

[0987] 8. Feedback collection: After the work is completed, feedback is collected from users and staff from other departments.

[0988] Detailed explanation of the process

[0989] The server receives the skill information and spare time schedule entered by the user, as well as the request information entered by staff in other departments, and stores this information in a database. A Python library is used for database management.

[0990] The server compares the user's skill information with the request information to find the best match. The skill matching algorithm uses a machine learning model. For example, the scikit-learn library can be used to implement an algorithm that improves matching accuracy.

[0991] The server checks the selected users' free time schedules and proposes the optimal execution schedule. This schedule proposal uses the Google Calendar API to avoid the user's busy times and finds the most suitable time slot.

[0992] The device will notify the user of the proposed schedule and give them the option to accept or reject it, using Firebase Cloud Messaging for this notification function.

[0993] The device (e.g., smart glasses) uses a built-in camera and microphone to detect the user's emotional state from facial expressions and voice in real time, and sends the information to a server, which processes the emotional information using the OpenCV library and the Google Cloud Speech-to-Text API.

[0994] The server provides optimal matching and scheduling, taking into account the user's emotional state. Collected data is analyzed using an AI model, which makes it possible to make improvements.

[0995] Specific examples

[0996] For example, imagine a worker at a logistics center wearing smart glasses. If this worker has the skills of "packing" and "sorting" and enters their spare time between 9:00 AM and 12:00 PM, the system will use that information to receive requests from other departments to "help with packing" and suggest an optimal schedule. If the system detects that the user is feeling "tired," it will refer to that emotion data and adjust the schedule so that the work assignments do not become a burden. For example, it may suggest that "working between 10:00 AM and 11:00 AM would be optimal."

[0997] Prompt Sentence Examples

[0998] Here is an example of the prompt the system will execute:

[0999] "User ID: user123, Skills: Packing, Sorting, Free Time: 09:00 to 12:00, Emotional State: Tired, Proposed Time: 10:00 to 11:00"

[1000] As described above, the system of the present invention can achieve optimal matching and schedule adjustment based on the emotional state of the user. By introducing this system, it is possible to simultaneously improve work efficiency at logistics centers and reduce the burden on users.

[1001] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1002] Step 1:

[1003] User information registration

[1004] The user inputs their skill information and their free time schedule. The device receives this information and sends it to the server as JSON format data. The server analyzes the received data and stores the user's skill information and schedule information in a database.

[1005] Input: Skill information, spare time schedule

[1006] Output: User information stored in the database

[1007] Specific operation: The user operates the device, enters skills and schedule information into the input form, and clicks the submit button. The server analyzes the received data and saves it in the database.

[1008] Step 2:

[1009] Enter request information

[1010] A person from another department inputs request information about the problem they need to solve or the skills they need. The device receives this information and sends it to the server as JSON data. The server analyzes the received data and stores the request information in a database.

[1011] Input: Request information

[1012] Output: Request information stored in the database

[1013] Specific operation: A person in another department operates a terminal, enters the request information into the input form, and clicks the send button. The server analyzes the received data and saves it in the database.

[1014] Step 3:

[1015] Skill Matching

[1016] The server retrieves user information and request information from the database and runs a skill matching algorithm to list users who have the skills to match the request.

[1017] Input: User and request information in the database

[1018] Output: A list of users who matched the request

[1019] Specific operation: The server runs a skill matching algorithm to select suitable users and generate a list.

[1020] Step 4:

[1021] Schedule proposal

[1022] The server checks the selected users' free time schedules and extracts available time slots for the request. It uses the Google Calendar API to suggest the optimal schedule.

[1023] Input: User's free time schedule, request information

[1024] Output: Proposed schedule

[1025] Specific operation: The server compares the user's schedule with the request, extracts the optimal time slot, and generates a proposed schedule.

[1026] Step 5:

[1027] notification

[1028] The device notifies the user of the proposed schedule and gives them the option to accept or reject it. Notifications are achieved using Firebase Cloud Messaging.

[1029] Input: Proposed Schedule

[1030] Output: Notification sent to the user

[1031] Specific operation: The server sends a notification via Firebase Cloud Messaging, and the device displays the notification to the user.

[1032] Step 6:

[1033] Emotion Detection

[1034] The device (e.g., smart glasses) uses a built-in camera and microphone to detect the user's facial expressions and voice, and collects their emotional state. The collected emotional data is then sent to a server.

[1035] Input: User's facial expression data, voice data

[1036] Output: Emotion data sent to the server

[1037] Specific operation: The camera captures the user's facial expressions, the microphone records audio, and these data are sent to the server.

[1038] Step 7:

[1039] Emotional data analysis and optimization

[1040] The server analyzes the collected emotional data and uses an emotion recognition engine and AI models to optimally match users and readjust their schedules, taking into account the burden on the users.

[1041] Input: Emotion data, existing schedule information

[1042] Output: Optimized matching and schedule

[1043] What it does: The server analyzes the emotion data, reevaluates the existing schedule, and optimizes it if necessary.

[1044] Step 8:

[1045] Feedback collection

[1046] After the task is completed, the server collects feedback from users and staff from other departments. The collected feedback is stored in a database and used to improve matching accuracy in the future.

[1047] Input: Feedback information

[1048] Output: Feedback data stored in a database

[1049] Specific operation: The terminal displays a feedback form, the user and the person in charge fill it out, and it is sent to the server, which analyzes the data and stores it in a database.

[1050] 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.

[1051] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1052] 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.

[1053] [Third embodiment]

[1054] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1055] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1056] 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).

[1057] 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.

[1058] 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.

[1059] 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).

[1060] 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.

[1061] 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.

[1062] 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.

[1063] 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.

[1064] 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.

[1065] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1066] The system of the present invention supports problem solving in other departments by matching skills and spare time with the user and the person in charge of the other department, and compares the information entered by the user and the person in charge of the other department using a database. The following describes in detail how the system is implemented.

[1067] Registering and saving user information

[1068] The user accesses a special page. The device displays an input form, and the user enters their skill information and spare time schedule. For example, "Java programming" and "data analysis" are registered as skills, and the spare time from 14:00 to 15:00 on Mondays is entered. The device sends this information to the server as JSON format data. The server analyzes the received data and saves the skill information and schedule information in a database.

[1069] Enter and save request information

[1070] A person in another department accesses a special page to enter a request for solving a problem. The terminal displays an input form, and the person in charge enters the problem that needs to be solved and the skills required. For example, "fix a bug in a Python program." The terminal sends this information to the server as JSON format data. The server analyzes the received data and saves the request information in a database.

[1071] Matching skills to requests

[1072] The server runs a skill matching algorithm periodically or when a request occurs to match the request information with the user skill information stored in the database. The server searches the database for users who have the skills corresponding to the request and lists them.

[1073] Check schedule and suggest possible times

[1074] The server compares the selected users' free time schedules and extracts available time slots for the request. Based on this information, the server generates a schedule to propose to the user and prepares a notification message.

[1075] Notifications and Scheduling

[1076] The server sends a notification of the matching proposal to the user. The user receives the notification and checks their own schedule. The terminal displays the notification content, and the user can choose to accept or reject. If the user accepts, the server notifies the person in the other department who made the request of the final schedule and task details.

[1077] Business support and progress reports

[1078] Users visit other departments at designated times or participate in online meetings to perform support tasks. During and after work, they report their progress from their terminal. The terminal displays a progress report form, and the user enters the required information. The progress report is sent to the server, which stores it in a database.

[1079] Feedback collection and analysis

[1080] After completing the task, the server notifies the user and staff from other departments of the feedback request. The terminal displays a feedback form, and the user and staff from other departments enter their evaluations and opinions. The feedback is sent to the server and stored in a database. The server analyzes the collected feedback and uses it as data to improve the accuracy of the next match.

[1081] This allows the system to efficiently utilize internal skills and resources and effectively support other departments in solving problems and improving operations.

[1082] The processing flow will be explained below.

[1083] Step 1:

[1084] Users access a special page and enter their skill information and spare time schedule.

[1085] Step 2:

[1086] The terminal displays an input form and accepts input from the user.

[1087] Step 3:

[1088] When the device presses the send button, the input content is sent to the server as JSON format data.

[1089] Step 4:

[1090] The server parses the received JSON format data and saves the skill information and schedule information in a database.

[1091] Step 5:

[1092] Staff from other departments can access a special page and enter requests for problems that need to be solved or skills they are looking for.

[1093] Step 6:

[1094] The terminal displays an input form and accepts request information from staff in other departments.

[1095] Step 7:

[1096] When the device presses the send button, the input content is sent to the server as JSON format data.

[1097] Step 8:

[1098] The server analyzes the received JSON format data and saves the request information in the database.

[1099] Step 9:

[1100] The server retrieves user and request information from a database and runs a skill matching algorithm.

[1101] Step 10:

[1102] The server lists users who have the skills to handle the request.

[1103] Step 11:

[1104] The server checks the free time schedule of the selected user and extracts a time slot in which the request can be executed.

[1105] Step 12:

[1106] The server generates match suggestion notifications for suitable users.

[1107] Step 13:

[1108] The server sends a notification to the user.

[1109] Step 14:

[1110] Users receive notifications and check their schedules.

[1111] Step 15:

[1112] The terminal provides the user with the option to accept or decline and accepts the input.

[1113] Step 16:

[1114] The server obtains the user's approval and notifies the person in charge of the other department who made the request of the final schedule and task details.

[1115] Step 17:

[1116] The user visits other departments at a specified time or participates in an online conference to perform support work.

[1117] Step 18:

[1118] The user reports progress from the terminal.

[1119] Step 19:

[1120] The terminal sends the report to the server.

[1121] Step 20:

[1122] The server stores the received work report in a database.

[1123] Step 21:

[1124] The server notifies the user and other department personnel of the feedback request.

[1125] Step 22:

[1126] Users and staff from other departments access and fill out the feedback form.

[1127] Step 23:

[1128] The device sends the feedback to the server.

[1129] Step 24:

[1130] The feedback received by the server is stored in a database and used as data to improve matching accuracy next time.

[1131] The above are the specific processing steps of a system that efficiently utilizes the skills and spare time of users to support problem solving in other departments.

[1132] Example 1

[1133] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1134] In modern companies, the sharing of skills and the utilization of resources between different departments is becoming increasingly important. However, because each department has different areas of expertise, it is not always possible to solve problems within one department, making it difficult to efficiently find personnel in other departments who have the necessary skills. Furthermore, there is a lack of systems for identifying the free time of personnel with those skills and providing efficient support for their work. Therefore, there is a need for a system that can effectively match users' skills with their spare time and efficiently solve problems.

[1135] 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.

[1136] In this invention, the server includes: means for a user to input their own ability information and free time schedule; means for a person in another department to input request information regarding problems that need to be solved and the abilities they desire; means for saving the ability information, free time schedule, and request information in a database; means for comparing the ability information and request information and selecting a suitable user; means for checking the free time schedule of the selected user and proposing a workable timetable; means for notifying the user of the proposed timetable and accepting approval; means for notifying the person in another department who made the request of the approved timetable and details of the work; means for inputting progress; means for transmitting the progress from the user to the server and saving it in the database; and means for inputting feedback to the user and the person in another department after the work is completed. This makes it possible to efficiently match users' skills and free time, and effectively support problem solving in other departments.

[1137] A "user" is an entity that accesses a special page and enters their own ability information and free time schedule.

[1138] A "terminal" is a device that allows a user or a person in charge of another department to input information and transmit the data to a server.

[1139] A "server" is a device that receives and analyzes data sent by users or staff from other departments, and stores the data in a database.

[1140] "Capability information" is information about the technical or specialized skills and knowledge possessed by a user.

[1141] The "available timetable" is information about the time slots that a user can provide to solve problems in other departments.

[1142] A "person in charge of another department" is an entity that inputs request information for a problem that is difficult to solve within one's own department.

[1143] "Request information" is information about problems that need to be solved or capabilities that are required by personnel in other departments.

[1144] "Database" is a system for storing analyzed capacity information, availability timetables and request information.

[1145] The "skill matching algorithm" is a program that compares the ability information and request information stored in the database and selects suitable users.

[1146] The "proposed timetable" is a schedule of feasible time slots created based on the free time of the selected users.

[1147] "Notification" is a message that informs the user or other department personnel of the proposed timetable, final schedule, and task details.

[1148] "Progress" is information about the process and results of the work the user has done to solve the problem.

[1149] "Feedback" refers to information about evaluations and opinions provided by users and staff from other departments after completing work.

[1150] A "generative AI model" is an artificial intelligence system that uses collected feedback and data to improve the accuracy of the next match.

[1151] A "prompt sentence" is an example of specific text to be input into a generative AI model.

[1152] The system of the present invention is a system for promoting the effective use of in-house skills and spare time, and for supporting problem solving in other departments. To implement this system, the following hardware and software are used.

[1153] Hardware and software used

[1154] 1. Server: Performs processes such as receiving, analyzing, storing, collating, and notifying data. Examples of use include web servers using Apache or Nginx, and database servers using MySQL or PostgreSQL.

[1155] 2. Terminal: A device that allows users or staff from other departments to input information and send the data to a server. This includes personal computers, tablets, smartphones, etc.

[1156] 3. Analysis tools: Use data analysis tools such as Survicate or Datadog to analyze the data.

[1157] 4. Information retrieval library: Use an information retrieval library such as Elasticsearch or Apache Lucene to run the skill matching algorithm.

[1158] 5. Generative AI model: An artificial intelligence system that uses collected feedback to improve the accuracy of the next match.

[1159] Example of a system

[1160] Registering and saving user information

[1161] Users access a special page and enter their own skill information (e.g., Java programming, data analysis) and available time slot (e.g., Mondays from 14:00 to 15:00). The device sends this information to the server as JSON format data, which is then stored in a database.

[1162] Enter and save request information

[1163] A person from another department accesses a special page and inputs the problem that needs to be solved or the required capabilities (e.g., fixing a bug in a Python program). The terminal sends this information to the server as JSON format data, which is then stored in a database.

[1164] Matching skills to requests

[1165] The server compares the user's ability information stored in the database with the request information using a skill matching algorithm (e.g., Elasticsearch or Apache Lucene) and lists matching users.

[1166] Check schedule and suggest possible times

[1167] The server checks the free time schedules of the matching users and extracts feasible time slots for the request. Based on this information, it generates a feasible schedule and prepares notification messages to propose it to the users.

[1168] Notifications and Scheduling

[1169] The server sends a notification of the matching proposal to the user. The user receives the notification, checks their own schedule, and selects whether to accept or reject. If the user accepts, the server notifies the person in charge of the other department who made the request of the final schedule and task details.

[1170] Business support and progress reports

[1171] Users can visit other departments at designated times or participate in online meetings to carry out support work. During and after work, users report their progress from their terminals, and the server stores this information in a database.

[1172] Feedback collection and analysis

[1173] After the task is completed, the server notifies the user and other departments of the feedback request. The user enters their evaluation and opinion into a feedback form, which the device then sends to the server and stores in a database. The server analyzes the collected feedback and reflects it in the generative AI model to improve matching accuracy next time.

[1174] Prompt Sentence Examples

[1175] Here are some example prompts for a generative AI model:

[1176] Design a system to register a user's skill list in a database and match it with requests from other departments. Explain the process, including the steps of registering a user's skills, inputting a request, matching skills with requests, notifications, and collecting feedback, and use specific names (e.g., JSON format, skill matching algorithm, database, etc.).

[1177] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1178] Step 1:

[1179] Users access a special page and enter their ability information and available timetable.

[1180] What it does: The device displays a special page and provides a form where you can enter your skills (e.g., "Java programming," "data analysis") and available time (e.g., Mondays from 2:00 PM to 3:00 PM).

[1181] Input: Skill information, available timetable

[1182] Output: The data entered in the form is retrieved.

[1183] Step 2:

[1184] The terminal converts the entered user information into JSON format data and sends it to the server.

[1185] Specific operation: The terminal parses the input data into JSON format and sends an HTTP request to the server.

[1186] Input: Data entered in a form

[1187] Output: User data in JSON format

[1188] Step 3:

[1189] The server analyzes the received JSON data and stores the ability information and free time schedule in a database.

[1190] Specific operation: The server analyzes the received data and inserts capability information and free time information into the database.

[1191] Input: User data in JSON format

[1192] Output: Capacity information and availability timetable stored in the database

[1193] Step 4:

[1194] Staff from other departments access a special page and enter request information about the problems that need to be solved and the skills they are looking for.

[1195] What it does: The terminal displays a special page and provides a form where you can enter your request information (e.g., "Fix a bug in a Python program").

[1196] Input: Request information

[1197] Output: The data entered in the form is retrieved.

[1198] Step 5:

[1199] The terminal converts the request information into JSON format data and sends it to the server.

[1200] Specific operation: The terminal parses the input data into JSON format and sends an HTTP request to the server.

[1201] Input: Data entered in a form

[1202] Output: Request data in JSON format

[1203] Step 6:

[1204] The server parses the received JSON data and saves the request information in a database.

[1205] Specific operation: The server analyzes the received data and inserts the request information into the database.

[1206] Input: Request data in JSON format

[1207] Output: Request information stored in the database

[1208] Step 7:

[1209] The server runs a skills matching algorithm to match the capability information with the request information.

[1210] How it works: The server uses libraries such as Elasticsearch or Apache Lucene to match the request information with the capability information in the database and select a matching user.

[1211] Input: Capability and request information stored in the database

[1212] Output: A list of matching users as a result of the matching algorithm.

[1213] Step 8:

[1214] The server checks the free time schedules of the selected users and proposes feasible schedules.

[1215] Specific operation: The server extracts the free / busy data of the selected users and generates a feasible schedule that corresponds to the request.

[1216] Input: list of matching users, free time schedule

[1217] Output: Proposed feasible schedule

[1218] Step 9:

[1219] The server notifies the user of the proposed schedule and accepts approval.

[1220] What happens: The server creates a notification message and sends it to the user, allowing the user to accept or decline.

[1221] Input: Proposed Schedule

[1222] Output: Approval or rejection result

[1223] Step 10:

[1224] The server notifies the requesting person in the other department of the approved schedule and task details.

[1225] Specific operation: The server creates a message containing the final schedule and work details and sends it to the person in charge in the other department.

[1226] Inputs: Approved schedule, task details

[1227] Output: Notification to other department personnel

[1228] Step 11:

[1229] Users can visit other departments at designated times or participate in online meetings to perform support tasks.

[1230] Specific actions: The user performs the work according to the proposed schedule.

[1231] Input: Final schedule, support details

[1232] Output: Support activities performed

[1233] Step 12:

[1234] The user reports the progress from the terminal while working and when the work is completed.

[1235] Specific operation: The terminal displays a progress report form, and the user enters the required information. The entered data is sent to the server.

[1236] Input: Progress data

[1237] Output: Progress saved in the database

[1238] Step 13:

[1239] After the work is completed, the server notifies the user and the person in charge of the other department of the feedback request.

[1240] Specific behavior: The server creates a notification message with a link to a feedback form and sends it to the user and other department personnel.

[1241] Input: Notice of business termination

[1242] Output: Feedback request notification

[1243] Step 14:

[1244] Users and staff from other departments enter their evaluations and opinions into a feedback form, and the terminal sends them to the server.

[1245] Specific operation: The terminal displays a feedback form and sends the data entered by the user and the person in charge to the server.

[1246] Input: Feedback data

[1247] Output: Feedback stored in a database

[1248] Step 15:

[1249] The server analyzes the collected feedback and reflects it in the generative AI model.

[1250] What it does: The server analyzes the feedback data and provides the results to the generative AI model to improve the accuracy of the next match.

[1251] Input: Collected feedback

[1252] Output: Update data for the generative AI model

[1253] Prompt Sentence Examples

[1254] Here are some example prompts for a generative AI model:

[1255] Design a system to register a user's skill list in a database and match it with requests from other departments. Explain the process, including the steps of registering a user's skills, inputting a request, matching skills with requests, notifications, and collecting feedback, and use specific names (e.g., JSON format, skill matching algorithm, database, etc.).

[1256] (Application example 1)

[1257] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1258] In factories, the inability to effectively utilize the skills and spare time of specific engineers often leads to reduced productivity and delays in problem resolution. Furthermore, with conventional technology, managing the schedules of factory robots and engineers is cumbersome, making it difficult to quickly secure the right support personnel. Therefore, there is a need for a system that can appropriately match engineers' skills and spare time to smoothly resolve problems.

[1259] 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.

[1260] In this invention, the server includes: means for users to input their own skill information and spare time schedules; means for personnel from other departments to input request information regarding problems that need to be solved or skills they are looking for; means for saving the skill information, spare time schedules, and request information in a database; means for comparing the skill information and request information to select suitable users; means for checking the spare time schedules of the selected users and proposing feasible schedules; means for notifying the users of the proposed schedules and accepting their approval; means for notifying the personnel from other departments who made the request of details of the approved schedules and tasks; means for reporting the progress of ongoing work to users and saving the results in a database; means for collecting feedback from the users and personnel from other departments and saving and analyzing the feedback in a database to improve the accuracy of next task matching; and means for inputting and saving the skill information and spare time schedules using display terminals equipped on factory robots and mobile terminals of engineers and comparing them with the request information. This enables the skills and spare time of engineers in the factory to be fully utilized to quickly and efficiently solve problems.

[1261] A "user" is a person or organization that can input skill information and a schedule of spare time to assist other departments in solving problems.

[1262] "Other department representative" refers to a person or organization whose role is to input request information regarding problems that need to be solved or skills that are needed within their own department.

[1263] "Skill information" is information about the specialized skills and knowledge possessed by the user.

[1264] The "free time schedule" is information about the time period when the user is free from the current work.

[1265] "Request information" is information about problems that need to be solved or skills that are required by staff from other departments.

[1266] A "database" is a storage system of pieces of information for storing skill information, spare time schedules, and request information.

[1267] "Matching" is the process of comparing the skill information stored in the database with the request information and selecting a suitable user.

[1268] A "feasible schedule" is a proposal regarding the time periods when the selected users are available to assist with requests.

[1269] "Notification" is the act of informing users and other departments of details of the proposed schedule and tasks.

[1270] "Progress" is information about the current progress and results of ongoing work.

[1271] "Feedback" refers to evaluations and opinions collected from users and staff in other departments after the work is completed.

[1272] A "factory robot" is a device that automatically performs specific tasks in a manufacturing site and may be equipped with a display terminal.

[1273] "Mobile terminal" means a portable device used by a technician to input and store skill information and spare time schedules.

[1274] A "generative AI model" is an artificial intelligence program that finds patterns in large amounts of data and makes predictions and classifications based on the input data.

[1275] A "prompt sentence" is a sentence that guides the user to enter information in a particular format.

[1276] This invention is a system for quickly and efficiently solving problems by effectively utilizing the skills and spare time of specific engineers in a factory. This system is implemented using a cloud server, a database, mobile devices of engineers, and display terminals equipped on factory robots.

[1277] Registering and saving user information

[1278] Engineers access a dedicated app from their mobile device (e.g., a smartphone) and enter their own skill information and schedule for spare time. For example, the following skill information and schedule are entered:

[1279] Skills: "Sensor Calibration", "Machine Maintenance"

[1280] Schedule: "Monday 14:00 to 15:00"

[1281] The device sends this information as JSON format data to the cloud server, which then analyzes the data and stores the skill and schedule information in a database.

[1282] Enter and save request information

[1283] Factory managers access a dedicated page from the display terminals installed on factory robots and input the support tasks required by the robots. For example, a request such as "Fix an abnormal sensor on Robot A" may be entered. The terminal sends this information to the cloud server as JSON format data. The cloud server analyzes the received data and stores the request information in a database.

[1284] Matching skills to requests

[1285] The cloud server periodically compares the request information with the technician skill information stored in the database. Generative AI models are used to improve the accuracy of the matching process. The optimal match is made and a list of suitable technicians is created.

[1286] Check schedule and suggest possible times

[1287] The cloud server checks the free time schedules of the selected engineers and extracts the available time slots for the request. Based on this information, the server generates a schedule to propose to the engineers and prepares a notification message.

[1288] Notifications and Scheduling

[1289] The cloud server notifies the engineer of the proposed schedule via their mobile device. The engineer can then review the notification and choose to approve or reject it. If approved, the cloud server notifies the factory manager of the final schedule and task details.

[1290] Business support and progress reports

[1291] The technician performs support tasks at the designated time, either on the factory robot or at the designated site. At the end of the task, the technician reports the progress to the cloud server from the mobile device. This progress report is also sent in JSON format and stored in the database.

[1292] Feedback collection and analysis

[1293] After completing a task, the cloud server notifies the engineer and factory manager of the feedback request. The engineer uses a mobile device, and the manager uses a display device to enter their evaluation and opinions into the feedback form. The collected feedback is sent to the cloud server, where it is stored in a database and analyzed to improve the accuracy of task matching next time.

[1294] Examples and prompts

[1295] Examples of specific prompts include the following:

[1296] "Enter Technician A's skills and schedule. Example: Skill: 'Sensor Calibration', Schedule: 'Monday 14:00 to 15:00'"

[1297] "Administrator B, please enter the support task for Robot A. Example: 'Fix the sensor abnormality of Robot A'."

[1298] This system makes it possible to make the most of the skills and spare time of factory engineers and resolve problems quickly and efficiently.

[1299] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1300] Step 1:

[1301] Technicians access a dedicated app from their mobile devices and input their skill information and spare time schedule. For example, inputs include skills such as "sensor calibration" and "machine maintenance," and a schedule such as "Monday 14:00 to 15:00." The input data is converted into JSON format and sent to the cloud server.

[1302] Step 2:

[1303] The cloud server parses the received JSON data, extracts the skill information and the spare time schedule, and then stores this information in a database for future reference.

[1304] Step 3:

[1305] The factory manager accesses a dedicated page from the display terminal equipped on the factory robot and inputs the task for which support is required. The input is request information such as "Fix the sensor abnormality of robot A." The data entered by the manager is also converted to JSON format and sent to the cloud server.

[1306] Step 4:

[1307] The cloud server analyzes the received request information, extracts the request content, and stores it in a database. This request information is then compared with the skill information of the technician.

[1308] Step 5:

[1309] The cloud server periodically compares the request information with the technician skill information stored in the database. It then uses a generative AI model to create a list of technicians who best match the request. The input is the information in the database, and the output is a list of the best technicians.

[1310] Step 6:

[1311] The cloud server again retrieves the optimal spare time schedule of the engineer from the database and extracts the time slots that can be executed for the request. This generates a feasible schedule and proposes the optimal time slots for the engineer.

[1312] Step 7:

[1313] The cloud server notifies the technician of the proposed schedule on his / her mobile device. The notification includes details of the possible schedules and tasks. The technician can then review the notification and choose to accept or reject it.

[1314] Step 8:

[1315] Once the technician approves, the cloud server notifies the factory manager of the final schedule and task details, who can then make adjustments.

[1316] Step 9:

[1317] Engineers perform support tasks at designated times on factory robots or at designated sites. When the task is completed, the engineers report the progress to the cloud server from their mobile devices. The progress reports, sent in JSON format, are stored in a database.

[1318] Step 10:

[1319] The cloud server collects feedback from engineers and factory managers by sending emails and push notifications requesting them to fill out a feedback form. The feedback is sent to the cloud server and stored in a database. This feedback data is analyzed to improve the accuracy of task matching for the next time.

[1320] 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.

[1321] The system of the present invention combines the basic function of matching a user's skills and spare time with the needs of other departments with an emotion engine that recognizes the user's emotions, thereby providing more appropriate schedule adjustments and business support. The following describes in detail how the system is implemented.

[1322] Registering and saving user information

[1323] The user accesses a special page and enters their own skill information and spare time schedule. The device displays an input form and accepts input from the user. For example, "Web design" and "Project management" are registered as skills, and spare time from 10:00 to 11:00 on Friday is entered. The device sends this information to the server as JSON format data. The server analyzes the received data and saves the skill information and schedule information in a database.

[1324] Enter and save request information

[1325] A person from another department accesses a special page and enters a request for a problem that needs to be solved or a skill they need. The device displays an input form and accepts the input. For example, the user enters "design review." The device sends this information to the server as JSON format data. The server analyzes the received data and saves the request information in a database.

[1326] Matching skills to requests

[1327] The server retrieves user information and request information from the database, runs a skill matching algorithm, and lists users who have the skills to match the request.

[1328] Check schedule and suggest possible times

[1329] The server checks the selected users' free time schedules and extracts available time slots for the request. Based on this information, the server generates a schedule to propose to the users and prepares a notification message.

[1330] Emotion recognition by emotion engine

[1331] For emotion recognition, the system incorporates an emotion engine. The device collects emotional data from the user's facial expressions, voice tone, and input. For example, if the user is determined to be "tired," that information is stored in a database. This allows the system to optimize matching and scheduling by taking the user's emotional state into account.

[1332] Notifications and Scheduling

[1333] The server sends a notification of the proposed match to the user. The user receives the notification and checks their schedule and the proposed work. The terminal provides the option to accept or reject the request and accepts input from the user. If the user accepts, the server notifies the person in the other department who made the request of the final schedule and task details.

[1334] Business support and progress reports

[1335] Users visit other departments at designated times or participate in online meetings to perform support tasks. During and after work, they report their progress from their terminal. The terminal displays a progress report form, and the user enters the required information. The progress report is sent to the server, which stores it in a database.

[1336] Feedback collection and analysis

[1337] After the work is completed, the server notifies the user and staff from other departments of the feedback request. The terminal displays a feedback form, and the user and staff from other departments enter their evaluations and opinions. The feedback is sent to the server, which stores it in a database. The collected feedback is analyzed and used as data to improve the accuracy of the next match.

[1338] In this way, the system can provide the most appropriate resource matching, taking into account the user's emotional state, thereby reducing the burden on the user and achieving optimal business support.

[1339] The processing flow will be explained below.

[1340] Step 1:

[1341] Users access a special page and enter their skill information and spare time schedule.

[1342] Step 2:

[1343] The terminal displays an input form and accepts input from the user.

[1344] Step 3:

[1345] When the device presses the send button, the input content is sent to the server as JSON format data.

[1346] Step 4:

[1347] The server parses the received JSON format data and saves the skill information and schedule information in a database.

[1348] Step 5:

[1349] Staff from other departments can access a special page and enter requests for problems that need to be solved or skills they are looking for.

[1350] Step 6:

[1351] The terminal displays an input form and accepts request information from staff in other departments.

[1352] Step 7:

[1353] When the device presses the send button, the input content is sent to the server as JSON format data.

[1354] Step 8:

[1355] The server analyzes the received JSON format data and saves the request information in the database.

[1356] Step 9:

[1357] The server retrieves user and request information from a database and runs a skill matching algorithm.

[1358] Step 10:

[1359] The server lists users who have the skills to handle the request.

[1360] Step 11:

[1361] The server checks the free time schedule of the selected user and extracts a time slot in which the request can be executed.

[1362] Step 12:

[1363] The server obtains the user's latest emotional state using an emotion engine, which generates emotion data by analyzing the user's facial expressions, tone of voice, input content, etc.

[1364] Step 13:

[1365] The device sends the user's facial expressions and voice to the emotion engine.

[1366] Step 14:

[1367] The emotion engine determines the user's emotion and sends the data to the server.

[1368] Step 15:

[1369] The server uses emotion data to optimize the time slots available for requests, including suggesting lighter tasks when the user is tired.

[1370] Step 16:

[1371] The server generates match suggestion notifications for suitable users.

[1372] Step 17:

[1373] The server sends a notification to the user.

[1374] Step 18:

[1375] Users receive notifications and review their schedules and proposed work.

[1376] Step 19:

[1377] The terminal displays the option to accept or decline and accepts input from the user.

[1378] Step 20:

[1379] The server obtains the user's approval and notifies the person in charge of the other department who made the request of the final schedule and task details.

[1380] Step 21:

[1381] The user visits other departments at a specified time or participates in an online conference to perform support work.

[1382] Step 22:

[1383] The user reports progress from the terminal.

[1384] Step 23:

[1385] The terminal sends the report to the server.

[1386] Step 24:

[1387] The server stores the received work report in a database.

[1388] Step 25:

[1389] The server notifies the user and other department personnel of the feedback request.

[1390] Step 26:

[1391] Users and staff from other departments access and fill out the feedback form.

[1392] Step 27:

[1393] The device sends the feedback to the server.

[1394] Step 28:

[1395] The feedback received by the server is stored in a database and used as data to improve matching accuracy next time.

[1396] This allows the system to provide appropriate resource matching and business support while taking into account the user's emotional state.

[1397] Example 2

[1398] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1399] Conventional task matching systems provide a function to match optimal resources based on the user's skill information and spare time schedule. However, these systems only perform simple matching without considering the user's emotional state, which can increase the user's psychological burden and reduce work efficiency. In addition, there are cases where requests are not handled appropriately or progress management is insufficient, resulting in insufficient comprehensive work support.

[1400] 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.

[1401] In this invention, the server includes a means for users to input their own skill information and spare time schedules, a means for personnel in other departments to input requirement information regarding problems that need to be solved or skills they are looking for, a means for saving the skill information, spare time schedules, and requirement information in a data storage device, a means for comparing the skill information and requirement information and selecting suitable users, a means for checking the spare time schedules of the selected users and proposing feasible schedules, a means for collecting emotional data from the user's facial expressions, tone of voice, input content, etc., and recognizing the emotional state, a means for notifying the user of the proposed schedule and accepting approval, and a means for notifying the personnel in other departments who made the request of details of the approved schedule and tasks. This enables optimal resource matching and business support that takes into account the user's emotional state.

[1402] "User" is a general term for individuals or groups who use this system to input their own skill information and spare time schedules, and provide resources to other departments.

[1403] "Skill information" is a general term for data that refers to the specialized knowledge, skills, experience, etc. that a user possesses.

[1404] The "schedule for spare time" refers to data for a free time period designated by the user that does not overlap with other work.

[1405] "Other department personnel" is a collective term for individuals or groups who use the system to request a problem that needs to be solved or a resource with specific skills.

[1406] "Requirements information" refers to information entered by personnel in other departments regarding problems that need to be solved or skills that are being sought.

[1407] "Data storage device" refers to a database or storage system for saving and managing various data for the entire system.

[1408] "Matching" refers to the process of comparing the user's skill information with the requirements information of other departments to find matching or compatible items.

[1409] "Schedule proposal" refers to a proposal of feasible time slots that the system makes to the user based on the user's free time and the request information of other departments.

[1410] "Emotional data" refers to data collected from the user's facial expressions, voice tone, input content, etc., that indicates the user's emotional state.

[1411] "Notification" refers to the process by which the system communicates information to users and other department personnel.

[1412] "Acceptance" refers to an action that indicates the user accepts the suggestion from the system.

[1413] The system of the present invention not only has the basic function of matching a user's skill information and spare time with the requirements of other departments, but also incorporates an emotion engine that recognizes the user's emotions, thereby providing more appropriate schedule adjustments and business support. Specific implementation methods of the system are described in detail below.

[1414] Registering and saving user information

[1415] The user accesses a special page and enters their own skill information and spare time schedule. The device displays an input form and accepts the user's input. For example, "Web design" and "Project management" are registered as skills, and the spare time from 10:00 to 11:00 on Friday is entered. The entered data is converted to JSON format and sent to the server. The server analyzes the received data and saves it in a database.

[1416] Enter and save request information

[1417] A person from another department accesses a special page and enters a request for a problem that needs to be solved or a skill they need. The device displays an input form and accepts the input. For example, the user enters "design review." The input is converted to JSON format and sent to the server. The server analyzes the received data and stores it in a database.

[1418] Matching skills to requests

[1419] The server retrieves user and request information from the database and runs a skill matching algorithm. The server creates a list of users with the skills required for the request. Specifically, the server matches a user with the skill "Web design" with a request for "design review."

[1420] Check schedule and suggest possible times

[1421] The server retrieves the matched users' free time schedules and extracts the time slots that fit the request. For example, it finds that free time is available from 10:00 to 11:00 on Friday. The server uses this information to generate a suggested schedule and prepares a notification message.

[1422] Emotion recognition by emotion engine

[1423] For emotion recognition, the system employs an emotion engine. The device collects emotion data from the user's facial expressions, voice tone, and input. For example, it uses a camera and microphone to analyze the user's facial expressions and voice. If the user is determined to be "tired," the information is stored in a database. Based on this emotion data, the system takes the user's emotional state into account and optimizes matching and scheduling.

[1424] Notifications and Scheduling

[1425] The server sends a notification of the matching proposal to the user. The user receives the notification and checks the proposed schedule and work content. The terminal provides the option to accept or reject and accepts input from the user. If the user accepts the proposal, the server notifies the person in charge of the other department of the final schedule and task details.

[1426] Business support and progress reports

[1427] Users can visit other departments at designated times or participate in online meetings to support their work. They report their progress during and after work. The terminal displays a progress report form, and the user enters the required information. The progress report is converted to JSON format, sent to the server, and stored in a database.

[1428] Feedback collection and analysis

[1429] After the workday is over, the server notifies the user and staff from other departments of the feedback request. The terminal displays a feedback form, and the user and staff from other departments enter their ratings and opinions. The feedback content is converted to JSON format, sent to the server, and stored in a database. The server analyzes the collected feedback and uses it as data to improve the accuracy of the next match.

[1430] As a concrete example, the following is an example of a prompt sentence to be input to a generative AI model:

[1431] "A user has registered the skills of 'Web Design' and 'Project Management', and a spare time slot on Fridays from 10:00 to 11:00. A request for a design review has come in from another department, and the skills match. The proposed schedule will be for this spare time slot. The user's emotional state is recognized as 'Tired'. Can this be approved?"

[1432] By using this prompt, you can clearly explain the system and its suggestions.

[1433] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1434] Program processing flow

[1435] Step 1: Register and save your user information

[1436] Input: Data that users enter when they access a special page and enter their skill information and free time schedule.

[1437] Operation: The device displays an input form and accepts input from the user. The user enters "Web Design" and "Project Management" as skills and their spare time between 10:00 and 11:00 on Friday.

[1438] Data processing: The device converts this information into JSON format.

[1439] Output: The converted JSON data is sent to the server, which parses it and stores the skill and schedule information in a database.

[1440] Step 2: Enter and save your request information

[1441] Input: Data that allows staff from other departments to access a special page and enter request information about the problem that needs to be solved or the skills they are looking for.

[1442] Action: The device displays the input form and accepts input. The person types "Design review."

[1443] Data processing: The terminal converts this request information into JSON format.

[1444] Output: The converted JSON data is sent to the server, which parses the received data and saves the request information in a database.

[1445] Step 3: Matching skills to requests

[1446] Input: User and request information retrieved from the database.

[1447] How it works: The server runs a skill matching algorithm that uses the user's skill information to select a user with the skills to fulfill the request.

[1448] Data processing: Match the skill information with the request information and list the matching users.

[1449] Output: Information about the matched users.

[1450] Step 4: Check the schedule and propose feasible times

[1451] Input: Matched user's free time schedule information.

[1452] Action: The server checks the user's schedule and finds available time slots. Friday from 10:00 to 11:00 is determined to be available.

[1453] Data processing: Generate a proposed schedule based on the extracted information.

[1454] Output: The proposed schedule is prepared as a notification message.

[1455] Step 5: Emotion Recognition with the Emotion Engine

[1456] Input: Emotional data such as the user's facial expressions, tone of voice, and input.

[1457] How it works: The device uses a camera and microphone to collect the user's facial expressions and voice, which are then analyzed by the emotion engine. The device determines that the user is "tired."

[1458] Data processing: Analyze the collected emotion data and store it in a database.

[1459] Output: The user's emotional state is recorded.

[1460] Step 6: Notifications and Scheduling

[1461] Input: Proposed schedule and task details.

[1462] How it works: The server sends a notification of a proposed match to the user. The user receives the notification and reviews the proposed schedule and work content. The device displays the option to accept or reject. Input is accepted from the user.

[1463] Data processing: Processing information that the user has approved or rejected.

[1464] Output: The approved schedule and task details are notified to the relevant department.

[1465] Step 7: Implementation of business support and progress reporting

[1466] Input: Work performed on a schedule.

[1467] Operation: The user visits another department at a specified time or participates in an online meeting to assist with work. The terminal displays a progress report form, and the user enters the required information.

[1468] Data processing: Convert the progress report into JSON format.

[1469] Output: Progress reports are sent to the server and stored in a database.

[1470] Step 8: Gather and analyze feedback

[1471] Input: Feedback information from users and other departments.

[1472] Operation: The server sends a feedback request notification after the work is completed. The terminal displays a feedback form, and the user and other department staff can enter their evaluations and opinions.

[1473] Data processing: Convert the feedback information into JSON format.

[1474] Output: The feedback information is sent to the server and stored in a database. The server analyzes the collected feedback and uses it to improve the accuracy of the next match.

[1475] (Application example 2)

[1476] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1477] Conventional systems were able to match resources based on the user's skills and schedule, but they did not perform appropriate resource matching and schedule optimization that took the user's emotional state into account. This resulted in the problem of not taking the user's stress and fatigue levels into account, making it difficult to provide optimal work support. This problem was particularly pronounced in high-load environments such as logistics centers. Furthermore, there was a lack of means to detect the user's emotional state in real time and effectively utilize that data.

[1478] 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.

[1479] In this invention, the server includes: a means for a user to input their own skill information and spare time schedule; a means for a person in another department to input request information regarding problems that need to be solved or skills that they are looking for; a means for saving the skill information, spare time schedule, and request information in a database; a means for comparing the skill information and request information and selecting a suitable user; a means for confirming the spare time schedule of the selected user and proposing a feasible schedule; a means for notifying the user of the proposed schedule and accepting approval; a means for notifying the person in another department who made the request of details of the approved schedule and tasks; a means for detecting the user's emotional state and optimizing the optimal matching and schedule based on the information; and a means for using a camera and microphone to detect the user's emotional state via a smart device, thereby enabling optimal resource matching and schedule adjustment that takes the user's emotional state into consideration.

[1480] A "user" is an individual or entity that utilizes the system to enter their skill information and schedule.

[1481] "Skill information" is information about the knowledge and skills required for a user to carry out a specific job or task.

[1482] A "spare time schedule" is a list of the free time a user has available within a specific period of time.

[1483] "Request information" is data about problems that need to be solved or skills required by staff in other departments.

[1484] "Database" means a system for storing and managing skill information, schedule information, and request information.

[1485] The "matching means" is a function for comparing the user's skill information with the request information and selecting a suitable user.

[1486] The "schedule suggestion means" is a function that checks the user's free time schedule and creates a schedule that can be implemented in response to requests.

[1487] The "notification means" is a function for informing the user of the proposed schedule and receiving approval.

[1488] The "emotion detection means" is a function that recognizes the user's emotional state as data, and stores and analyzes that information.

[1489] A "smart device" is a device equipped with sensors such as a camera and a microphone, which is used to detect the emotional state of the user.

[1490] The system of the present invention effectively manages user skill information and spare time schedules, and optimally matches these with the needs of other departments. This system aims to improve work efficiency, particularly in logistics centers. The following describes in detail how the system is implemented.

[1491] System programming and processing methods

[1492] Program Generation

[1493] The system includes programs to perform the following functions:

[1494] 1. User information registration: Allows users to enter their current skills and their free time schedule.

[1495] 2. Request information entry: Allows staff from other departments to enter the problems to be solved and the skills required.

[1496] 3. Database management: Save the entered skill information, schedule information and request information in the database.

[1497] 4. Skill matching: Match the user's skill information with the request information and select the most suitable user.

[1498] 5. Schedule proposal: Check the free time of the selected users and propose a feasible schedule.

[1499] 6. Notification: Notify users of the proposed schedule and accept approval.

[1500] 7. Emotion detection: Detects the user's emotional state using smart devices (camera, microphone), and optimizes matching and scheduling based on that information.

[1501] 8. Feedback collection: After the work is completed, feedback is collected from users and staff from other departments.

[1502] Detailed explanation of the process

[1503] The server receives the skill information and spare time schedule entered by the user, as well as the request information entered by staff in other departments, and stores this information in a database. A Python library is used for database management.

[1504] The server compares the user's skill information with the request information to find the best match. The skill matching algorithm uses a machine learning model. For example, the scikit-learn library can be used to implement an algorithm that improves matching accuracy.

[1505] The server checks the selected users' free time schedules and proposes the optimal execution schedule. This schedule proposal uses the Google Calendar API to avoid the user's busy times and finds the most suitable time slot.

[1506] The device will notify the user of the proposed schedule and give them the option to accept or reject it, using Firebase Cloud Messaging for this notification function.

[1507] The device (e.g., smart glasses) uses a built-in camera and microphone to detect the user's emotional state from facial expressions and voice in real time, and sends the information to a server, which processes the emotional information using the OpenCV library and the Google Cloud Speech-to-Text API.

[1508] The server provides optimal matching and scheduling, taking into account the user's emotional state. Collected data is analyzed using an AI model, which makes it possible to make improvements.

[1509] Specific examples

[1510] For example, imagine a worker at a logistics center wearing smart glasses. If this worker has the skills of "packing" and "sorting" and enters their spare time between 9:00 AM and 12:00 PM, the system will use that information to receive requests from other departments to "help with packing" and suggest an optimal schedule. If the system detects that the user is feeling "tired," it will refer to that emotion data and adjust the schedule so that the work assignments do not become a burden. For example, it may suggest that "working between 10:00 AM and 11:00 AM would be optimal."

[1511] Prompt Sentence Examples

[1512] Here is an example of the prompt the system will execute:

[1513] "User ID: user123, Skills: Packing, Sorting, Free Time: 09:00 to 12:00, Emotional State: Tired, Proposed Time: 10:00 to 11:00"

[1514] As described above, the system of the present invention can achieve optimal matching and schedule adjustment based on the emotional state of the user. By introducing this system, it is possible to simultaneously improve work efficiency at logistics centers and reduce the burden on users.

[1515] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1516] Step 1:

[1517] User information registration

[1518] The user inputs their skill information and their free time schedule. The device receives this information and sends it to the server as JSON format data. The server analyzes the received data and stores the user's skill information and schedule information in a database.

[1519] Input: Skill information, spare time schedule

[1520] Output: User information stored in the database

[1521] Specific operation: The user operates the device, enters skills and schedule information into the input form, and clicks the submit button. The server analyzes the received data and saves it in the database.

[1522] Step 2:

[1523] Enter request information

[1524] A person from another department inputs request information about the problem they need to solve or the skills they need. The device receives this information and sends it to the server as JSON data. The server analyzes the received data and stores the request information in a database.

[1525] Input: Request information

[1526] Output: Request information stored in the database

[1527] Specific operation: A person in another department operates a terminal, enters the request information into the input form, and clicks the send button. The server analyzes the received data and saves it in the database.

[1528] Step 3:

[1529] Skill Matching

[1530] The server retrieves user information and request information from the database and runs a skill matching algorithm to list users who have the skills to match the request.

[1531] Input: User and request information in the database

[1532] Output: A list of users who matched the request

[1533] Specific operation: The server runs a skill matching algorithm to select suitable users and generate a list.

[1534] Step 4:

[1535] Schedule proposal

[1536] The server checks the selected users' free time schedules and extracts available time slots for the request. It uses the Google Calendar API to suggest the optimal schedule.

[1537] Input: User's free time schedule, request information

[1538] Output: Proposed schedule

[1539] Specific operation: The server compares the user's schedule with the request, extracts the optimal time slot, and generates a proposed schedule.

[1540] Step 5:

[1541] notification

[1542] The device notifies the user of the proposed schedule and gives them the option to accept or reject it. Notifications are achieved using Firebase Cloud Messaging.

[1543] Input: Proposed Schedule

[1544] Output: Notification sent to the user

[1545] Specific operation: The server sends a notification via Firebase Cloud Messaging, and the device displays the notification to the user.

[1546] Step 6:

[1547] Emotion Detection

[1548] The device (e.g., smart glasses) uses a built-in camera and microphone to detect the user's facial expressions and voice, and collects their emotional state. The collected emotional data is then sent to a server.

[1549] Input: User's facial expression data, voice data

[1550] Output: Emotion data sent to the server

[1551] Specific operation: The camera captures the user's facial expressions, the microphone records audio, and these data are sent to the server.

[1552] Step 7:

[1553] Emotional data analysis and optimization

[1554] The server analyzes the collected emotional data and uses an emotion recognition engine and AI models to optimally match users and readjust their schedules, taking into account the burden on the users.

[1555] Input: Emotion data, existing schedule information

[1556] Output: Optimized matching and schedule

[1557] What it does: The server analyzes the emotion data, reevaluates the existing schedule, and optimizes it if necessary.

[1558] Step 8:

[1559] Feedback collection

[1560] After the task is completed, the server collects feedback from users and staff from other departments. The collected feedback is stored in a database and used to improve matching accuracy in the future.

[1561] Input: Feedback information

[1562] Output: Feedback data stored in a database

[1563] Specific operation: The terminal displays a feedback form, the user and the person in charge fill it out, and it is sent to the server, which analyzes the data and stores it in a database.

[1564] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1565] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1566] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1567] [Fourth embodiment]

[1568] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1569] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1570] 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).

[1571] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1572] 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.

[1573] 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).

[1574] 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.

[1575] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1576] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1577] 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.

[1578] 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.

[1579] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1580] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1581] The system of the present invention supports problem solving in other departments by matching skills and spare time with the user and the person in charge of the other department, and compares the information entered by the user and the person in charge of the other department using a database. The following describes in detail how the system is implemented.

[1582] Registering and saving user information

[1583] The user accesses a special page. The device displays an input form, and the user enters their skill information and spare time schedule. For example, "Java programming" and "data analysis" are registered as skills, and the spare time from 14:00 to 15:00 on Mondays is entered. The device sends this information to the server as JSON format data. The server analyzes the received data and saves the skill information and schedule information in a database.

[1584] Enter and save request information

[1585] A person in another department accesses a special page to enter a request for solving a problem. The terminal displays an input form, and the person in charge enters the problem that needs to be solved and the skills required. For example, "fix a bug in a Python program." The terminal sends this information to the server as JSON format data. The server analyzes the received data and saves the request information in a database.

[1586] Matching skills to requests

[1587] The server runs a skill matching algorithm periodically or when a request occurs to match the request information with the user skill information stored in the database. The server searches the database for users who have the skills corresponding to the request and lists them.

[1588] Check schedule and suggest possible times

[1589] The server compares the selected users' free time schedules and extracts available time slots for the request. Based on this information, the server generates a schedule to propose to the user and prepares a notification message.

[1590] Notifications and Scheduling

[1591] The server sends a notification of the matching proposal to the user. The user receives the notification and checks their own schedule. The terminal displays the notification content, and the user can choose to accept or reject. If the user accepts, the server notifies the person in the other department who made the request of the final schedule and task details.

[1592] Business support and progress reports

[1593] Users visit other departments at designated times or participate in online meetings to perform support tasks. During and after work, they report their progress from their terminal. The terminal displays a progress report form, and the user enters the required information. The progress report is sent to the server, which stores it in a database.

[1594] Feedback collection and analysis

[1595] After completing the task, the server notifies the user and staff from other departments of the feedback request. The terminal displays a feedback form, and the user and staff from other departments enter their evaluations and opinions. The feedback is sent to the server and stored in a database. The server analyzes the collected feedback and uses it as data to improve the accuracy of the next match.

[1596] This allows the system to efficiently utilize internal skills and resources and effectively support other departments in solving problems and improving operations.

[1597] The processing flow will be explained below.

[1598] Step 1:

[1599] Users access a special page and enter their skill information and spare time schedule.

[1600] Step 2:

[1601] The terminal displays an input form and accepts input from the user.

[1602] Step 3:

[1603] When the device presses the send button, the input content is sent to the server as JSON format data.

[1604] Step 4:

[1605] The server parses the received JSON format data and saves the skill information and schedule information in a database.

[1606] Step 5:

[1607] Staff from other departments can access a special page and enter requests for problems that need to be solved or skills they are looking for.

[1608] Step 6:

[1609] The terminal displays an input form and accepts request information from staff in other departments.

[1610] Step 7:

[1611] When the device presses the send button, the input content is sent to the server as JSON format data.

[1612] Step 8:

[1613] The server analyzes the received JSON format data and saves the request information in the database.

[1614] Step 9:

[1615] The server retrieves user and request information from a database and runs a skill matching algorithm.

[1616] Step 10:

[1617] The server lists users who have the skills to handle the request.

[1618] Step 11:

[1619] The server checks the free time schedule of the selected user and extracts a time slot in which the request can be executed.

[1620] Step 12:

[1621] The server generates match suggestion notifications for suitable users.

[1622] Step 13:

[1623] The server sends a notification to the user.

[1624] Step 14:

[1625] Users receive notifications and check their schedules.

[1626] Step 15:

[1627] The terminal provides the user with the option to accept or decline and accepts the input.

[1628] Step 16:

[1629] The server obtains the user's approval and notifies the person in charge of the other department who made the request of the final schedule and task details.

[1630] Step 17:

[1631] The user visits other departments at a specified time or participates in an online conference to perform support work.

[1632] Step 18:

[1633] The user reports progress from the terminal.

[1634] Step 19:

[1635] The terminal sends the report to the server.

[1636] Step 20:

[1637] The server stores the received work report in a database.

[1638] Step 21:

[1639] The server notifies the user and other department personnel of the feedback request.

[1640] Step 22:

[1641] Users and staff from other departments access and fill out the feedback form.

[1642] Step 23:

[1643] The device sends the feedback to the server.

[1644] Step 24:

[1645] The feedback received by the server is stored in a database and used as data to improve matching accuracy next time.

[1646] The above are the specific processing steps of a system that efficiently utilizes the skills and spare time of users to support problem solving in other departments.

[1647] Example 1

[1648] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1649] In modern companies, the sharing of skills and the utilization of resources between different departments is becoming increasingly important. However, because each department has different areas of expertise, it is not always possible to solve problems within one department, making it difficult to efficiently find personnel in other departments who have the necessary skills. Furthermore, there is a lack of systems for identifying the free time of personnel with those skills and providing efficient support for their work. Therefore, there is a need for a system that can effectively match users' skills with their spare time and efficiently solve problems.

[1650] 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.

[1651] In this invention, the server includes: means for a user to input their own ability information and free time schedule; means for a person in another department to input request information regarding problems that need to be solved and the abilities they desire; means for saving the ability information, free time schedule, and request information in a database; means for comparing the ability information and request information and selecting a suitable user; means for checking the free time schedule of the selected user and proposing a workable timetable; means for notifying the user of the proposed timetable and accepting approval; means for notifying the person in another department who made the request of the approved timetable and details of the work; means for inputting progress; means for transmitting the progress from the user to the server and saving it in the database; and means for inputting feedback to the user and the person in another department after the work is completed. This makes it possible to efficiently match users' skills and free time, and effectively support problem solving in other departments.

[1652] A "user" is an entity that accesses a special page and enters their own ability information and free time schedule.

[1653] A "terminal" is a device that allows a user or a person in charge of another department to input information and transmit the data to a server.

[1654] A "server" is a device that receives and analyzes data sent by users or staff from other departments, and stores the data in a database.

[1655] "Capability information" is information about the technical or specialized skills and knowledge possessed by a user.

[1656] The "available timetable" is information about the time slots that a user can provide to solve problems in other departments.

[1657] A "person in charge of another department" is an entity that inputs request information for a problem that is difficult to solve within one's own department.

[1658] "Request information" is information about problems that need to be solved or capabilities that are required by personnel in other departments.

[1659] "Database" is a system for storing analyzed capacity information, availability timetables and request information.

[1660] The "skill matching algorithm" is a program that compares the ability information and request information stored in the database and selects suitable users.

[1661] The "proposed timetable" is a schedule of feasible time slots created based on the free time of the selected users.

[1662] "Notification" is a message that informs the user or other department personnel of the proposed timetable, final schedule, and task details.

[1663] "Progress" is information about the process and results of the work the user has done to solve the problem.

[1664] "Feedback" refers to information about evaluations and opinions provided by users and staff from other departments after completing work.

[1665] A "generative AI model" is an artificial intelligence system that uses collected feedback and data to improve the accuracy of the next match.

[1666] A "prompt sentence" is an example of specific text to be input into a generative AI model.

[1667] The system of the present invention is a system for promoting the effective use of in-house skills and spare time, and for supporting problem solving in other departments. To implement this system, the following hardware and software are used.

[1668] Hardware and software used

[1669] 1. Server: Performs processes such as receiving, analyzing, storing, collating, and notifying data. Examples of use include web servers using Apache or Nginx, and database servers using MySQL or PostgreSQL.

[1670] 2. Terminal: A device that allows users or staff from other departments to input information and send the data to a server. This includes personal computers, tablets, smartphones, etc.

[1671] 3. Analysis tools: Use data analysis tools such as Survicate or Datadog to analyze the data.

[1672] 4. Information retrieval library: Use an information retrieval library such as Elasticsearch or Apache Lucene to run the skill matching algorithm.

[1673] 5. Generative AI model: An artificial intelligence system that uses collected feedback to improve the accuracy of the next match.

[1674] Example of a system

[1675] Registering and saving user information

[1676] Users access a special page and enter their own skill information (e.g., Java programming, data analysis) and available time slot (e.g., Mondays from 14:00 to 15:00). The device sends this information to the server as JSON format data, which is then stored in a database.

[1677] Enter and save request information

[1678] A person from another department accesses a special page and inputs the problem that needs to be solved or the required capabilities (e.g., fixing a bug in a Python program). The terminal sends this information to the server as JSON format data, which is then stored in a database.

[1679] Matching skills to requests

[1680] The server compares the user's ability information stored in the database with the request information using a skill matching algorithm (e.g., Elasticsearch or Apache Lucene) and lists matching users.

[1681] Check schedule and suggest possible times

[1682] The server checks the free time schedules of the matching users and extracts feasible time slots for the request. Based on this information, it generates a feasible schedule and prepares notification messages to propose it to the users.

[1683] Notifications and Scheduling

[1684] The server sends a notification of the matching proposal to the user. The user receives the notification, checks their own schedule, and selects whether to accept or reject. If the user accepts, the server notifies the person in charge of the other department who made the request of the final schedule and task details.

[1685] Business support and progress reports

[1686] Users can visit other departments at designated times or participate in online meetings to carry out support work. During and after work, users report their progress from their terminals, and the server stores this information in a database.

[1687] Feedback collection and analysis

[1688] After the task is completed, the server notifies the user and other departments of the feedback request. The user enters their evaluation and opinion into a feedback form, which the device then sends to the server and stores in a database. The server analyzes the collected feedback and reflects it in the generative AI model to improve matching accuracy next time.

[1689] Prompt Sentence Examples

[1690] Here are some example prompts for a generative AI model:

[1691] Design a system to register a user's skill list in a database and match it with requests from other departments. Explain the process, including the steps of registering a user's skills, inputting a request, matching skills with requests, notifications, and collecting feedback, and use specific names (e.g., JSON format, skill matching algorithm, database, etc.).

[1692] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1693] Step 1:

[1694] Users access a special page and enter their ability information and available timetable.

[1695] What it does: The device displays a special page and provides a form where you can enter your skills (e.g., "Java programming," "data analysis") and available time (e.g., Mondays from 2:00 PM to 3:00 PM).

[1696] Input: Skill information, available timetable

[1697] Output: The data entered in the form is retrieved.

[1698] Step 2:

[1699] The terminal converts the entered user information into JSON format data and sends it to the server.

[1700] Specific operation: The terminal parses the input data into JSON format and sends an HTTP request to the server.

[1701] Input: Data entered in a form

[1702] Output: User data in JSON format

[1703] Step 3:

[1704] The server analyzes the received JSON data and stores the ability information and free time schedule in a database.

[1705] Specific operation: The server analyzes the received data and inserts capability information and free time information into the database.

[1706] Input: User data in JSON format

[1707] Output: Capacity information and availability timetable stored in the database

[1708] Step 4:

[1709] Staff from other departments access a special page and enter request information about the problems that need to be solved and the skills they are looking for.

[1710] What it does: The terminal displays a special page and provides a form where you can enter your request information (e.g., "Fix a bug in a Python program").

[1711] Input: Request information

[1712] Output: The data entered in the form is retrieved.

[1713] Step 5:

[1714] The terminal converts the request information into JSON format data and sends it to the server.

[1715] Specific operation: The terminal parses the input data into JSON format and sends an HTTP request to the server.

[1716] Input: Data entered in a form

[1717] Output: Request data in JSON format

[1718] Step 6:

[1719] The server parses the received JSON data and saves the request information in a database.

[1720] Specific operation: The server analyzes the received data and inserts the request information into the database.

[1721] Input: Request data in JSON format

[1722] Output: Request information stored in the database

[1723] Step 7:

[1724] The server runs a skills matching algorithm to match the capability information with the request information.

[1725] How it works: The server uses libraries such as Elasticsearch or Apache Lucene to match the request information with the capability information in the database and select a matching user.

[1726] Input: Capability and request information stored in the database

[1727] Output: A list of matching users as a result of the matching algorithm.

[1728] Step 8:

[1729] The server checks the free time schedules of the selected users and proposes feasible schedules.

[1730] Specific operation: The server extracts the free / busy data of the selected users and generates a feasible schedule that corresponds to the request.

[1731] Input: list of matching users, free time schedule

[1732] Output: Proposed feasible schedule

[1733] Step 9:

[1734] The server notifies the user of the proposed schedule and accepts approval.

[1735] What happens: The server creates a notification message and sends it to the user, allowing the user to accept or decline.

[1736] Input: Proposed Schedule

[1737] Output: Approval or rejection result

[1738] Step 10:

[1739] The server notifies the requesting person in the other department of the approved schedule and task details.

[1740] Specific operation: The server creates a message containing the final schedule and work details and sends it to the person in charge in the other department.

[1741] Inputs: Approved schedule, task details

[1742] Output: Notification to other department personnel

[1743] Step 11:

[1744] Users can visit other departments at designated times or participate in online meetings to perform support tasks.

[1745] Specific actions: The user performs the work according to the proposed schedule.

[1746] Input: Final schedule, support details

[1747] Output: Support activities performed

[1748] Step 12:

[1749] The user reports the progress from the terminal while working and when the work is completed.

[1750] Specific operation: The terminal displays a progress report form, and the user enters the required information. The entered data is sent to the server.

[1751] Input: Progress data

[1752] Output: Progress saved in the database

[1753] Step 13:

[1754] After the work is completed, the server notifies the user and the person in charge of the other department of the feedback request.

[1755] Specific behavior: The server creates a notification message with a link to a feedback form and sends it to the user and other department personnel.

[1756] Input: Notice of business termination

[1757] Output: Feedback request notification

[1758] Step 14:

[1759] Users and staff from other departments enter their evaluations and opinions into a feedback form, and the terminal sends them to the server.

[1760] Specific operation: The terminal displays a feedback form and sends the data entered by the user and the person in charge to the server.

[1761] Input: Feedback data

[1762] Output: Feedback stored in a database

[1763] Step 15:

[1764] The server analyzes the collected feedback and reflects it in the generative AI model.

[1765] What it does: The server analyzes the feedback data and provides the results to the generative AI model to improve the accuracy of the next match.

[1766] Input: Collected feedback

[1767] Output: Update data for the generative AI model

[1768] Prompt Sentence Examples

[1769] Here are some example prompts for a generative AI model:

[1770] Design a system to register a user's skill list in a database and match it with requests from other departments. Explain the process, including the steps of registering a user's skills, inputting a request, matching skills with requests, notifications, and collecting feedback, and use specific names (e.g., JSON format, skill matching algorithm, database, etc.).

[1771] (Application example 1)

[1772] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1773] In factories, the inability to effectively utilize the skills and spare time of specific engineers often leads to reduced productivity and delays in problem resolution. Furthermore, with conventional technology, managing the schedules of factory robots and engineers is cumbersome, making it difficult to quickly secure the right support personnel. Therefore, there is a need for a system that can appropriately match engineers' skills and spare time to smoothly resolve problems.

[1774] 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.

[1775] In this invention, the server includes: means for users to input their own skill information and spare time schedules; means for personnel from other departments to input request information regarding problems that need to be solved or skills they are looking for; means for saving the skill information, spare time schedules, and request information in a database; means for comparing the skill information and request information to select suitable users; means for checking the spare time schedules of the selected users and proposing feasible schedules; means for notifying the users of the proposed schedules and accepting their approval; means for notifying the personnel from other departments who made the request of details of the approved schedules and tasks; means for reporting the progress of ongoing work to users and saving the results in a database; means for collecting feedback from the users and personnel from other departments and saving and analyzing the feedback in a database to improve the accuracy of next task matching; and means for inputting and saving the skill information and spare time schedules using display terminals equipped on factory robots and mobile terminals of engineers and comparing them with the request information. This enables the skills and spare time of engineers in the factory to be fully utilized to quickly and efficiently solve problems.

[1776] A "user" is a person or organization that can input skill information and a schedule of spare time to assist other departments in solving problems.

[1777] "Other department representative" refers to a person or organization whose role is to input request information regarding problems that need to be solved or skills that are needed within their own department.

[1778] "Skill information" is information about the specialized skills and knowledge possessed by the user.

[1779] The "free time schedule" is information about the time period when the user is free from the current work.

[1780] "Request information" is information about problems that need to be solved or skills that are required by staff from other departments.

[1781] A "database" is a storage system of pieces of information for storing skill information, spare time schedules, and request information.

[1782] "Matching" is the process of comparing the skill information stored in the database with the request information and selecting a suitable user.

[1783] A "feasible schedule" is a proposal regarding the time periods when the selected users are available to assist with requests.

[1784] "Notification" is the act of informing users and other departments of details of the proposed schedule and tasks.

[1785] "Progress" is information about the current progress and results of ongoing work.

[1786] "Feedback" refers to evaluations and opinions collected from users and staff in other departments after the work is completed.

[1787] A "factory robot" is a device that automatically performs specific tasks in a manufacturing site and may be equipped with a display terminal.

[1788] "Mobile terminal" means a portable device used by a technician to input and store skill information and spare time schedules.

[1789] A "generative AI model" is an artificial intelligence program that finds patterns in large amounts of data and makes predictions and classifications based on the input data.

[1790] A "prompt sentence" is a sentence that guides the user to enter information in a particular format.

[1791] This invention is a system for quickly and efficiently solving problems by effectively utilizing the skills and spare time of specific engineers in a factory. This system is implemented using a cloud server, a database, mobile devices of engineers, and display terminals equipped on factory robots.

[1792] Registering and saving user information

[1793] Engineers access a dedicated app from their mobile device (e.g., a smartphone) and enter their own skill information and schedule for spare time. For example, the following skill information and schedule are entered:

[1794] Skills: "Sensor Calibration", "Machine Maintenance"

[1795] Schedule: "Monday 14:00 to 15:00"

[1796] The device sends this information as JSON format data to the cloud server, which then analyzes the data and stores the skill and schedule information in a database.

[1797] Enter and save request information

[1798] Factory managers access a dedicated page from the display terminals installed on factory robots and input the support tasks required by the robots. For example, a request such as "Fix an abnormal sensor on Robot A" may be entered. The terminal sends this information to the cloud server as JSON format data. The cloud server analyzes the received data and stores the request information in a database.

[1799] Matching skills to requests

[1800] The cloud server periodically compares the request information with the technician skill information stored in the database. Generative AI models are used to improve the accuracy of the matching process. The optimal match is made and a list of suitable technicians is created.

[1801] Check schedule and suggest possible times

[1802] The cloud server checks the free time schedules of the selected engineers and extracts the available time slots for the request. Based on this information, the server generates a schedule to propose to the engineers and prepares a notification message.

[1803] Notifications and Scheduling

[1804] The cloud server notifies the engineer of the proposed schedule via their mobile device. The engineer can then review the notification and choose to approve or reject it. If approved, the cloud server notifies the factory manager of the final schedule and task details.

[1805] Business support and progress reports

[1806] The technician performs support tasks at the designated time, either on the factory robot or at the designated site. At the end of the task, the technician reports the progress to the cloud server from the mobile device. This progress report is also sent in JSON format and stored in the database.

[1807] Feedback collection and analysis

[1808] After completing a task, the cloud server notifies the engineer and factory manager of the feedback request. The engineer uses a mobile device, and the manager uses a display device to enter their evaluation and opinions into the feedback form. The collected feedback is sent to the cloud server, where it is stored in a database and analyzed to improve the accuracy of task matching next time.

[1809] Examples and prompts

[1810] Examples of specific prompts include the following:

[1811] "Enter Technician A's skills and schedule. Example: Skill: 'Sensor Calibration', Schedule: 'Monday 14:00 to 15:00'"

[1812] "Administrator B, please enter the support task for Robot A. Example: 'Fix the sensor abnormality of Robot A'."

[1813] This system makes it possible to make the most of the skills and spare time of factory engineers and resolve problems quickly and efficiently.

[1814] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1815] Step 1:

[1816] Technicians access a dedicated app from their mobile devices and input their skill information and spare time schedule. For example, inputs include skills such as "sensor calibration" and "machine maintenance," and a schedule such as "Monday 14:00 to 15:00." The input data is converted into JSON format and sent to the cloud server.

[1817] Step 2:

[1818] The cloud server parses the received JSON data, extracts the skill information and the spare time schedule, and then stores this information in a database for future reference.

[1819] Step 3:

[1820] The factory manager accesses a dedicated page from the display terminal equipped on the factory robot and inputs the task for which support is required. The input is request information such as "Fix the sensor abnormality of robot A." The data entered by the manager is also converted to JSON format and sent to the cloud server.

[1821] Step 4:

[1822] The cloud server analyzes the received request information, extracts the request content, and stores it in a database. This request information is then compared with the skill information of the technician.

[1823] Step 5:

[1824] The cloud server periodically compares the request information with the technician skill information stored in the database. It then uses a generative AI model to create a list of technicians who best match the request. The input is the information in the database, and the output is a list of the best technicians.

[1825] Step 6:

[1826] The cloud server again retrieves the optimal spare time schedule of the engineer from the database and extracts the time slots that can be executed for the request. This generates a feasible schedule and proposes the optimal time slots for the engineer.

[1827] Step 7:

[1828] The cloud server notifies the technician of the proposed schedule on his / her mobile device. The notification includes details of the possible schedules and tasks. The technician can then review the notification and choose to accept or reject it.

[1829] Step 8:

[1830] Once the technician approves, the cloud server notifies the factory manager of the final schedule and task details, who can then make adjustments.

[1831] Step 9:

[1832] Engineers perform support tasks at designated times on factory robots or at designated sites. When the task is completed, the engineers report the progress to the cloud server from their mobile devices. The progress reports, sent in JSON format, are stored in a database.

[1833] Step 10:

[1834] The cloud server collects feedback from engineers and factory managers by sending emails and push notifications requesting them to fill out a feedback form. The feedback is sent to the cloud server and stored in a database. This feedback data is analyzed to improve the accuracy of task matching for the next time.

[1835] 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.

[1836] The system of the present invention combines the basic function of matching a user's skills and spare time with the needs of other departments with an emotion engine that recognizes the user's emotions, thereby providing more appropriate schedule adjustments and business support. The following describes in detail how the system is implemented.

[1837] Registering and saving user information

[1838] The user accesses a special page and enters their own skill information and spare time schedule. The device displays an input form and accepts input from the user. For example, "Web design" and "Project management" are registered as skills, and spare time from 10:00 to 11:00 on Friday is entered. The device sends this information to the server as JSON format data. The server analyzes the received data and saves the skill information and schedule information in a database.

[1839] Enter and save request information

[1840] A person from another department accesses a special page and enters a request for a problem that needs to be solved or a skill they need. The device displays an input form and accepts the input. For example, the user enters "design review." The device sends this information to the server as JSON format data. The server analyzes the received data and saves the request information in a database.

[1841] Matching skills to requests

[1842] The server retrieves user information and request information from the database, runs a skill matching algorithm, and lists users who have the skills to match the request.

[1843] Check schedule and suggest possible times

[1844] The server checks the selected users' free time schedules and extracts available time slots for the request. Based on this information, the server generates a schedule to propose to the users and prepares a notification message.

[1845] Emotion recognition by emotion engine

[1846] For emotion recognition, the system incorporates an emotion engine. The device collects emotional data from the user's facial expressions, voice tone, and input. For example, if the user is determined to be "tired," that information is stored in a database. This allows the system to optimize matching and scheduling by taking the user's emotional state into account.

[1847] Notifications and Scheduling

[1848] The server sends a notification of the proposed match to the user. The user receives the notification and checks their schedule and the proposed work. The terminal provides the option to accept or reject the request and accepts input from the user. If the user accepts, the server notifies the person in the other department who made the request of the final schedule and task details.

[1849] Business support and progress reports

[1850] Users visit other departments at designated times or participate in online meetings to perform support tasks. During and after work, they report their progress from their terminal. The terminal displays a progress report form, and the user enters the required information. The progress report is sent to the server, which stores it in a database.

[1851] Feedback collection and analysis

[1852] After the work is completed, the server notifies the user and staff from other departments of the feedback request. The terminal displays a feedback form, and the user and staff from other departments enter their evaluations and opinions. The feedback is sent to the server, which stores it in a database. The collected feedback is analyzed and used as data to improve the accuracy of the next match.

[1853] In this way, the system can provide the most appropriate resource matching, taking into account the user's emotional state, thereby reducing the burden on the user and achieving optimal business support.

[1854] The processing flow will be explained below.

[1855] Step 1:

[1856] Users access a special page and enter their skill information and spare time schedule.

[1857] Step 2:

[1858] The terminal displays an input form and accepts input from the user.

[1859] Step 3:

[1860] When the device presses the send button, the input content is sent to the server as JSON format data.

[1861] Step 4:

[1862] The server parses the received JSON format data and saves the skill information and schedule information in a database.

[1863] Step 5:

[1864] Staff from other departments can access a special page and enter requests for problems that need to be solved or skills they are looking for.

[1865] Step 6:

[1866] The terminal displays an input form and accepts request information from staff in other departments.

[1867] Step 7:

[1868] When the device presses the send button, the input content is sent to the server as JSON format data.

[1869] Step 8:

[1870] The server analyzes the received JSON format data and saves the request information in the database.

[1871] Step 9:

[1872] The server retrieves user and request information from a database and runs a skill matching algorithm.

[1873] Step 10:

[1874] The server lists users who have the skills to handle the request.

[1875] Step 11:

[1876] The server checks the free time schedule of the selected user and extracts a time slot in which the request can be executed.

[1877] Step 12:

[1878] The server obtains the user's latest emotional state using an emotion engine, which generates emotion data by analyzing the user's facial expressions, tone of voice, input content, etc.

[1879] Step 13:

[1880] The device sends the user's facial expressions and voice to the emotion engine.

[1881] Step 14:

[1882] The emotion engine determines the user's emotion and sends the data to the server.

[1883] Step 15:

[1884] The server uses emotion data to optimize the time slots available for requests, including suggesting lighter tasks when the user is tired.

[1885] Step 16:

[1886] The server generates match suggestion notifications for suitable users.

[1887] Step 17:

[1888] The server sends a notification to the user.

[1889] Step 18:

[1890] Users receive notifications and review their schedules and proposed work.

[1891] Step 19:

[1892] The terminal displays the option to accept or decline and accepts input from the user.

[1893] Step 20:

[1894] The server obtains the user's approval and notifies the person in charge of the other department who made the request of the final schedule and task details.

[1895] Step 21:

[1896] The user visits other departments at a specified time or participates in an online conference to perform support work.

[1897] Step 22:

[1898] The user reports progress from the terminal.

[1899] Step 23:

[1900] The terminal sends the report to the server.

[1901] Step 24:

[1902] The server stores the received work report in a database.

[1903] Step 25:

[1904] The server notifies the user and other department personnel of the feedback request.

[1905] Step 26:

[1906] Users and staff from other departments access and fill out the feedback form.

[1907] Step 27:

[1908] The device sends the feedback to the server.

[1909] Step 28:

[1910] The feedback received by the server is stored in a database and used as data to improve matching accuracy next time.

[1911] This allows the system to provide appropriate resource matching and business support while taking into account the user's emotional state.

[1912] Example 2

[1913] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1914] Conventional task matching systems provide a function to match optimal resources based on the user's skill information and spare time schedule. However, these systems only perform simple matching without considering the user's emotional state, which can increase the user's psychological burden and reduce work efficiency. In addition, there are cases where requests are not handled appropriately or progress management is insufficient, resulting in insufficient comprehensive work support.

[1915] 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.

[1916] In this invention, the server includes a means for users to input their own skill information and spare time schedules, a means for personnel in other departments to input requirement information regarding problems that need to be solved or skills they are looking for, a means for saving the skill information, spare time schedules, and requirement information in a data storage device, a means for comparing the skill information and requirement information and selecting suitable users, a means for checking the spare time schedules of the selected users and proposing feasible schedules, a means for collecting emotional data from the user's facial expressions, tone of voice, input content, etc., and recognizing the emotional state, a means for notifying the user of the proposed schedule and accepting approval, and a means for notifying the personnel in other departments who made the request of details of the approved schedule and tasks. This enables optimal resource matching and business support that takes into account the user's emotional state.

[1917] "User" is a general term for individuals or groups who use this system to input their own skill information and spare time schedules, and provide resources to other departments.

[1918] "Skill information" is a general term for data that refers to the specialized knowledge, skills, experience, etc. that a user possesses.

[1919] The "schedule for spare time" refers to data for a free time period designated by the user that does not overlap with other work.

[1920] "Other department personnel" is a collective term for individuals or groups who use the system to request a problem that needs to be solved or a resource with specific skills.

[1921] "Requirements information" refers to information entered by personnel in other departments regarding problems that need to be solved or skills that are being sought.

[1922] "Data storage device" refers to a database or storage system for saving and managing various data for the entire system.

[1923] "Matching" refers to the process of comparing the user's skill information with the requirements information of other departments to find matching or compatible items.

[1924] "Schedule proposal" refers to a proposal of feasible time slots that the system makes to the user based on the user's free time and the request information of other departments.

[1925] "Emotional data" refers to data collected from the user's facial expressions, voice tone, input content, etc., that indicates the user's emotional state.

[1926] "Notification" refers to the process by which the system communicates information to users and other department personnel.

[1927] "Acceptance" refers to an action that indicates the user accepts the suggestion from the system.

[1928] The system of the present invention not only has the basic function of matching a user's skill information and spare time with the requirements of other departments, but also incorporates an emotion engine that recognizes the user's emotions, thereby providing more appropriate schedule adjustments and business support. Specific implementation methods of the system are described in detail below.

[1929] Registering and saving user information

[1930] The user accesses a special page and enters their own skill information and spare time schedule. The device displays an input form and accepts the user's input. For example, "Web design" and "Project management" are registered as skills, and the spare time from 10:00 to 11:00 on Friday is entered. The entered data is converted to JSON format and sent to the server. The server analyzes the received data and saves it in a database.

[1931] Enter and save request information

[1932] A person from another department accesses a special page and enters a request for a problem that needs to be solved or a skill they need. The device displays an input form and accepts the input. For example, the user enters "design review." The input is converted to JSON format and sent to the server. The server analyzes the received data and stores it in a database.

[1933] Matching skills to requests

[1934] The server retrieves user and request information from the database and runs a skill matching algorithm. The server creates a list of users with the skills required for the request. Specifically, the server matches a user with the skill "Web design" with a request for "design review."

[1935] Check schedule and suggest possible times

[1936] The server retrieves the matched users' free time schedules and extracts the time slots that fit the request. For example, it finds that free time is available from 10:00 to 11:00 on Friday. The server uses this information to generate a suggested schedule and prepares a notification message.

[1937] Emotion recognition by emotion engine

[1938] For emotion recognition, the system employs an emotion engine. The device collects emotion data from the user's facial expressions, voice tone, and input. For example, it uses a camera and microphone to analyze the user's facial expressions and voice. If the user is determined to be "tired," the information is stored in a database. Based on this emotion data, the system takes the user's emotional state into account and optimizes matching and scheduling.

[1939] Notifications and Scheduling

[1940] The server sends a notification of the matching proposal to the user. The user receives the notification and checks the proposed schedule and work content. The terminal provides the option to accept or reject and accepts input from the user. If the user accepts the proposal, the server notifies the person in charge of the other department of the final schedule and task details.

[1941] Business support and progress reports

[1942] Users can visit other departments at designated times or participate in online meetings to support their work. They report their progress during and after work. The terminal displays a progress report form, and the user enters the required information. The progress report is converted to JSON format, sent to the server, and stored in a database.

[1943] Feedback collection and analysis

[1944] After the workday is over, the server notifies the user and staff from other departments of the feedback request. The terminal displays a feedback form, and the user and staff from other departments enter their ratings and opinions. The feedback content is converted to JSON format, sent to the server, and stored in a database. The server analyzes the collected feedback and uses it as data to improve the accuracy of the next match.

[1945] As a concrete example, the following is an example of a prompt sentence to be input to a generative AI model:

[1946] "A user has registered the skills of 'Web Design' and 'Project Management', and a spare time slot on Fridays from 10:00 to 11:00. A request for a design review has come in from another department, and the skills match. The proposed schedule will be for this spare time slot. The user's emotional state is recognized as 'Tired'. Can this be approved?"

[1947] By using this prompt, you can clearly explain the system and its suggestions.

[1948] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1949] Program processing flow

[1950] Step 1: Register and save your user information

[1951] Input: Data that users enter when they access a special page and enter their skill information and free time schedule.

[1952] Operation: The device displays an input form and accepts input from the user. The user enters "Web Design" and "Project Management" as skills and their spare time between 10:00 and 11:00 on Friday.

[1953] Data processing: The device converts this information into JSON format.

[1954] Output: The converted JSON data is sent to the server, which parses it and stores the skill and schedule information in a database.

[1955] Step 2: Enter and save your request information

[1956] Input: Data that allows staff from other departments to access a special page and enter request information about the problem that needs to be solved or the skills they are looking for.

[1957] Action: The device displays the input form and accepts input. The person types "Design review."

[1958] Data processing: The terminal converts this request information into JSON format.

[1959] Output: The converted JSON data is sent to the server, which parses the received data and saves the request information in a database.

[1960] Step 3: Matching skills to requests

[1961] Input: User and request information retrieved from the database.

[1962] How it works: The server runs a skill matching algorithm that uses the user's skill information to select a user with the skills to fulfill the request.

[1963] Data processing: Match the skill information with the request information and list the matching users.

[1964] Output: Information about the matched users.

[1965] Step 4: Check the schedule and propose feasible times

[1966] Input: Matched user's free time schedule information.

[1967] Action: The server checks the user's schedule and finds available time slots. Friday from 10:00 to 11:00 is determined to be available.

[1968] Data processing: Generate a proposed schedule based on the extracted information.

[1969] Output: The proposed schedule is prepared as a notification message.

[1970] Step 5: Emotion Recognition with the Emotion Engine

[1971] Input: Emotional data such as the user's facial expressions, tone of voice, and input.

[1972] How it works: The device uses a camera and microphone to collect the user's facial expressions and voice, which are then analyzed by the emotion engine. The device determines that the user is "tired."

[1973] Data processing: Analyze the collected emotion data and store it in a database.

[1974] Output: The user's emotional state is recorded.

[1975] Step 6: Notifications and Scheduling

[1976] Input: Proposed schedule and task details.

[1977] How it works: The server sends a notification of a proposed match to the user. The user receives the notification and reviews the proposed schedule and work content. The device displays the option to accept or reject. Input is accepted from the user.

[1978] Data processing: Processing information that the user has approved or rejected.

[1979] Output: The approved schedule and task details are notified to the relevant department.

[1980] Step 7: Implementation of business support and progress reporting

[1981] Input: Work performed on a schedule.

[1982] Operation: The user visits another department at a specified time or participates in an online meeting to assist with work. The terminal displays a progress report form, and the user enters the required information.

[1983] Data processing: Convert the progress report into JSON format.

[1984] Output: Progress reports are sent to the server and stored in a database.

[1985] Step 8: Gather and analyze feedback

[1986] Input: Feedback information from users and other departments.

[1987] Operation: The server sends a feedback request notification after the work is completed. The terminal displays a feedback form, and the user and other department staff can enter their evaluations and opinions.

[1988] Data processing: Convert the feedback information into JSON format.

[1989] Output: The feedback information is sent to the server and stored in a database. The server analyzes the collected feedback and uses it to improve the accuracy of the next match.

[1990] (Application example 2)

[1991] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1992] Conventional systems were able to match resources based on the user's skills and schedule, but they did not perform appropriate resource matching and schedule optimization that took the user's emotional state into account. This resulted in the problem of not taking the user's stress and fatigue levels into account, making it difficult to provide optimal work support. This problem was particularly pronounced in high-load environments such as logistics centers. Furthermore, there was a lack of means to detect the user's emotional state in real time and effectively utilize that data.

[1993] 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.

[1994] In this invention, the server includes: a means for a user to input their own skill information and spare time schedule; a means for a person in another department to input request information regarding problems that need to be solved or skills that they are looking for; a means for saving the skill information, spare time schedule, and request information in a database; a means for comparing the skill information and request information and selecting a suitable user; a means for confirming the spare time schedule of the selected user and proposing a feasible schedule; a means for notifying the user of the proposed schedule and accepting approval; a means for notifying the person in another department who made the request of details of the approved schedule and tasks; a means for detecting the user's emotional state and optimizing the optimal matching and schedule based on the information; and a means for using a camera and microphone to detect the user's emotional state via a smart device, thereby enabling optimal resource matching and schedule adjustment that takes the user's emotional state into consideration.

[1995] A "user" is an individual or entity that utilizes the system to enter their skill information and schedule.

[1996] "Skill information" is information about the knowledge and skills required for a user to carry out a specific job or task.

[1997] A "spare time schedule" is a list of the free time a user has available within a specific period of time.

[1998] "Request information" is data about problems that need to be solved or skills required by staff in other departments.

[1999] "Database" means a system for storing and managing skill information, schedule information, and request information.

[2000] The "matching means" is a function for comparing the user's skill information with the request information and selecting a suitable user.

[2001] The "schedule suggestion means" is a function that checks the user's free time schedule and creates a schedule that can be implemented in response to requests.

[2002] The "notification means" is a function for informing the user of the proposed schedule and receiving approval.

[2003] The "emotion detection means" is a function that recognizes the user's emotional state as data, and stores and analyzes that information.

[2004] A "smart device" is a device equipped with sensors such as a camera and a microphone, which is used to detect the emotional state of the user.

[2005] The system of the present invention effectively manages user skill information and spare time schedules, and optimally matches these with the needs of other departments. This system aims to improve work efficiency, particularly in logistics centers. The following describes in detail how the system is implemented.

[2006] System programming and processing methods

[2007] Program Generation

[2008] The system includes programs to perform the following functions:

[2009] 1. User information registration: Allows users to enter their current skills and their free time schedule.

[2010] 2. Request information entry: Allows staff from other departments to enter the problems to be solved and the skills required.

[2011] 3. Database management: Save the entered skill information, schedule information and request information in the database.

[2012] 4. Skill matching: Match the user's skill information with the request information and select the most suitable user.

[2013] 5. Schedule proposal: Check the free time of the selected users and propose a feasible schedule.

[2014] 6. Notification: Notify users of the proposed schedule and accept approval.

[2015] 7. Emotion detection: Detects the user's emotional state using smart devices (camera, microphone), and optimizes matching and scheduling based on that information.

[2016] 8. Feedback collection: After the work is completed, feedback is collected from users and staff from other departments.

[2017] Detailed explanation of the process

[2018] The server receives the skill information and spare time schedule entered by the user, as well as the request information entered by staff in other departments, and stores this information in a database. A Python library is used for database management.

[2019] The server compares the user's skill information with the request information to find the best match. The skill matching algorithm uses a machine learning model. For example, the scikit-learn library can be used to implement an algorithm that improves matching accuracy.

[2020] The server checks the selected users' free time schedules and proposes the optimal execution schedule. This schedule proposal uses the Google Calendar API to avoid the user's busy times and finds the most suitable time slot.

[2021] The device will notify the user of the proposed schedule and give them the option to accept or reject it, using Firebase Cloud Messaging for this notification function.

[2022] The device (e.g., smart glasses) uses a built-in camera and microphone to detect the user's emotional state from facial expressions and voice in real time, and sends the information to a server, which processes the emotional information using the OpenCV library and the Google Cloud Speech-to-Text API.

[2023] The server provides optimal matching and scheduling, taking into account the user's emotional state. Collected data is analyzed using an AI model, which makes it possible to make improvements.

[2024] Specific examples

[2025] For example, imagine a worker at a logistics center wearing smart glasses. If this worker has the skills of "packing" and "sorting" and enters their spare time between 9:00 AM and 12:00 PM, the system will use that information to receive requests from other departments to "help with packing" and suggest an optimal schedule. If the system detects that the user is feeling "tired," it will refer to that emotion data and adjust the schedule so that the work assignments do not become a burden. For example, it may suggest that "working between 10:00 AM and 11:00 AM would be optimal."

[2026] Prompt Sentence Examples

[2027] Here is an example of the prompt the system will execute:

[2028] "User ID: user123, Skills: Packing, Sorting, Free Time: 09:00 to 12:00, Emotional State: Tired, Proposed Time: 10:00 to 11:00"

[2029] As described above, the system of the present invention can achieve optimal matching and schedule adjustment based on the emotional state of the user. By introducing this system, it is possible to simultaneously improve work efficiency at logistics centers and reduce the burden on users.

[2030] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2031] Step 1:

[2032] User information registration

[2033] The user inputs their skill information and their free time schedule. The device receives this information and sends it to the server as JSON format data. The server analyzes the received data and stores the user's skill information and schedule information in a database.

[2034] Input: Skill information, spare time schedule

[2035] Output: User information stored in the database

[2036] Specific operation: The user operates the device, enters skills and schedule information into the input form, and clicks the submit button. The server analyzes the received data and saves it in the database.

[2037] Step 2:

[2038] Enter request information

[2039] A person from another department inputs request information about the problem they need to solve or the skills they need. The device receives this information and sends it to the server as JSON data. The server analyzes the received data and stores the request information in a database.

[2040] Input: Request information

[2041] Output: Request information stored in the database

[2042] Specific operation: A person in another department operates a terminal, enters the request information into the input form, and clicks the send button. The server analyzes the received data and saves it in the database.

[2043] Step 3:

[2044] Skill Matching

[2045] The server retrieves user information and request information from the database and runs a skill matching algorithm to list users who have the skills to match the request.

[2046] Input: User and request information in the database

[2047] Output: A list of users who matched the request

[2048] Specific operation: The server runs a skill matching algorithm to select suitable users and generate a list.

[2049] Step 4:

[2050] Schedule proposal

[2051] The server checks the selected users' free time schedules and extracts available time slots for the request. It uses the Google Calendar API to suggest the optimal schedule.

[2052] Input: User's free time schedule, request information

[2053] Output: Proposed schedule

[2054] Specific operation: The server compares the user's schedule with the request, extracts the optimal time slot, and generates a proposed schedule.

[2055] Step 5:

[2056] notification

[2057] The device notifies the user of the proposed schedule and gives them the option to accept or reject it. Notifications are achieved using Firebase Cloud Messaging.

[2058] Input: Proposed Schedule

[2059] Output: Notification sent to the user

[2060] Specific operation: The server sends a notification via Firebase Cloud Messaging, and the device displays the notification to the user.

[2061] Step 6:

[2062] Emotion Detection

[2063] The device (e.g., smart glasses) uses a built-in camera and microphone to detect the user's facial expressions and voice, and collects their emotional state. The collected emotional data is then sent to a server.

[2064] Input: User's facial expression data, voice data

[2065] Output: Emotion data sent to the server

[2066] Specific operation: The camera captures the user's facial expressions, the microphone records audio, and these data are sent to the server.

[2067] Step 7:

[2068] Emotional data analysis and optimization

[2069] The server analyzes the collected emotional data and uses an emotion recognition engine and AI models to optimally match users and readjust their schedules, taking into account the burden on the users.

[2070] Input: Emotion data, existing schedule information

[2071] Output: Optimized matching and schedule

[2072] What it does: The server analyzes the emotion data, reevaluates the existing schedule, and optimizes it if necessary.

[2073] Step 8:

[2074] Feedback collection

[2075] After the task is completed, the server collects feedback from users and staff from other departments. The collected feedback is stored in a database and used to improve matching accuracy in the future.

[2076] Input: Feedback information

[2077] Output: Feedback data stored in a database

[2078] Specific operation: The terminal displays a feedback form, the user and the person in charge fill it out, and it is sent to the server, which analyzes the data and stores it in a database.

[2079] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[2080] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[2081] In the above embodiment, an example was given in which the specific processing is performed by...

Claims

1. A means for a user to input his / her skill information and spare time schedule; A way for people from other departments to input request information about problems that need to be solved or skills that are needed, means for storing the skill information, spare time schedule and request information in a database; means for comparing the skill information and request information and selecting a suitable user; A means for checking the free time schedule of the selected user and proposing a feasible schedule; means for notifying a user of the proposed schedule and accepting approval; A means of communicating approved schedule and task details to the requesting party. A system including:

2. A means of collecting feedback from users and personnel from other departments, storing it in a database, and analyzing it. The system of claim 1 further comprising:

3. means for providing a means for reporting the progress of said work; The system of claim 1 further comprising:

Images