system

Abstract

We provide the system. [Solution] A system for expanding education and training in the medical and welfare fields, A means of storing the latest training data in the medical and welfare fields in a database, A means for users to apply for training via their devices, A means of generating an optimal training plan that takes into account the user's skill level and schedule, A means for the device to notify the user of the training plan and report the training progress in real time, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, and includes steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance that responds to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] A serious shortage of manpower in the medical and welfare fields is predicted to reach as many as 960,000 by 2040. This problem may stagnate the provision of high-quality medical and welfare services and have a significant impact on the health and welfare of service beneficiaries. In addition, due to the shortage of manpower, on-site staff are forced to work excessive overtime, which deteriorates the working environment and leads to a vicious cycle of further manpower shortages. To solve this problem, a comprehensive approach combining technological innovation and efficiency improvement is necessary.

Means for Solving the Problems

[0005] In order to solve the manpower shortage problem in the medical and welfare fields, the present invention provides a system including the following means.

[0006] 1. As a means of enhancing education and training, the latest training data in the medical and welfare fields will be stored in a database. Users will apply for training via a terminal, an optimal training plan will be generated considering the user's skill level and schedule, the terminal will notify the user of the training plan, and training progress will be reported in real time.

[0007] 2. As a means of promoting the utilization of foreign workers, recruitment information for foreign workers will be collected in a database, users will submit recruitment requests for foreign workers from their terminals, the system will select and notify the most suitable candidates based on language skills, qualifications, experience, etc., and the terminal will provide the user with information and contact details of the selected candidates.

[0008] 3. As a means of effectively introducing and utilizing technology, we will monitor the status of technology use in medical and welfare settings, propose technology tools and applications to users according to their needs, evaluate whether users accept the proposals using their devices, introduce approved technologies, and monitor their usage in real time.

[0009] This will help alleviate labor shortages in the medical and welfare sectors, improve service quality, and support improved working conditions and efficient operations.

[0010] The "medical and welfare field" refers to the field that aims to provide medical and welfare services, and includes hospitals, clinics, nursing homes, home healthcare, and rehabilitation facilities.

[0011] "Training data" refers to educational content designed to help individuals acquire specific skills or knowledge, and is provided in various formats such as videos, text, quizzes, and simulations.

[0012] A "database" is a structured data storage system for efficiently storing, managing, and retrieving information.

[0013] A "user" refers to an individual or organization that uses the system to perform tasks, education, or training in the medical and welfare fields.

[0014] A "terminal" is a device that a user uses to access and operate a system, and includes personal computers, tablets, smartphones, and other similar devices.

[0015] "Skill level" is an indicator that represents the degree of ability to perform a specific task or job.

[0016] A "schedule" refers to a planned timetable for carrying out a specific task or activity.

[0017] A "training plan" is a set of educational and training procedures and content optimized based on the user's skill level and schedule.

[0018] "Foreign workers" refers to individuals employed in a country other than their home country, particularly those whose purpose is to work in the medical and welfare fields.

[0019] A "hiring request" is a formal application or request to hire workers who possess specific skills or qualifications.

[0020] "Language skills" refer to the ability to understand, read, write, and speak one or more languages.

[0021] "Qualifications" refer to official certifications or licenses required to perform a specific job or task.

[0022] "Experience" refers to the totality of past records of engaging in specific tasks or activities, and the knowledge and skills acquired through those experiences.

[0023] "Technology utilization status" refers to a collection of data that represents the actual usage and effectiveness of technological tools and applications in medical and welfare settings.

[0024] A "technical tool" refers to technical means and devices such as devices, software, and apparatuses aimed at improving work efficiency and quality in the medical and welfare fields.

[0025] An "application" is a computer program for providing specific functions and services.

[0026] "Monitoring" is a process of continuously observing, recording, and evaluating specific activities and states.

Brief Explanation of Drawings

[0027] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which multiple emotions are mapped. [Figure 10] It shows an emotion map to which multiple emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12]This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2, which combines an emotion engine. [Modes for carrying out the invention]

[0028] Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings.

[0029] First, let's explain the terminology used in the following explanation.

[0030] In the following embodiments, the signed processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Furthermore, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include CPU (Central Processing Unit), GPU (Graphics Processing Unit), GPGPU (General-Purpose computing on Graphics Processing Units), and APU (Accelerated Processing Unit).

[0031] In the following embodiments, signed RAM (Random Access Memory) is a memory that temporarily stores information and is used as work memory by the processor.

[0032] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0033] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0034] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0035] [First Embodiment]

[0036] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0037] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0038] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0039] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0040] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0041] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0042] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0043] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0044] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0045] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0046] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0047] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0048] This invention is a system that supports the resolution of labor shortages and efficient business operations in the medical and welfare fields. Specific embodiments for implementing this invention are described below.

[0049] 1. Expansion of education and training

[0050] The server stores the latest training data (videos, text, quizzes, etc.) in the medical and welfare fields in its database. Users apply via their terminals, specifying their skill level and desired training program. The server generates an optimal training plan considering the user's skill level and schedule. The generated training plan is notified to the user via their terminal, and the progress of each training session is reported to the server in real time. This provides individually optimized educational plans and efficiently supports skill development.

[0051] As a concrete example, suppose a user wishes to receive online training to improve their caregiving skills. The user submits a training request from their device. The server considers the user's current skill level and available time, and generates a training plan combining video materials on basic caregiving techniques and quiz-style tests, which is then provided to the user. The user proceeds with the training according to this plan, and their device reports their progress to the server.

[0052] 2. Utilization of foreign workers

[0053] The server collects recruitment information from global job sites and agencies into its database. Users submit recruitment requests for foreign workers with specific skills and qualifications from their terminals. Based on the collected data, the server selects the best candidates based on language skills, qualifications, and experience, and provides detailed information to the terminals.

[0054] As a concrete example, suppose a user wants to hire foreign workers as nursing staff. The user sends a recruitment request from their device, specifying language skills and particular qualifications. The server searches for the most suitable candidates based on its database and notifies the user of the profiles and contact information of the selected candidates. The user then conducts interviews based on the provided information and makes a hiring decision.

[0055] 3. Utilization of technology

[0056] The server continuously monitors the usage of technical tools and applications used in healthcare and welfare settings. Based on demand, the server suggests the latest technical tools and applications to users. Users evaluate the suggestions via their terminals and decide whether to accept them. Approved technologies are then deployed to the field by the server, and their usage is monitored in real time.

[0057] For example, if a medical facility requests the automation of nursing records, the server will monitor the current manual record-keeping situation and, based on that information, suggest an appropriate automated record-keeping tool. After the user approves this suggestion on their terminal, the server will install the automated record-keeping tool and monitor its usage and effectiveness.

[0058] 4. Improvement of working conditions

[0059] The server periodically collects and analyzes data on the working environment in medical and welfare facilities. Users can input requests for improvements to the working environment via a terminal. Based on the collected data and user requests, the server proposes efficient improvement measures and notifies the user via the terminal. When work environment improvement proposals are implemented, the progress is reported to the server, ensuring continuous improvement.

[0060] For example, if a request for improvements to reduce staff stress is made at a nursing care facility, the server collects survey and sensor data, and based on the analysis results, proposes specific improvement measures to the user, such as introducing a relaxation space or revising the shift system. The user then checks the proposed measures on their terminal and puts them into action.

[0061] 5. Promoting regional cooperation

[0062] The server integrates and manages information about local healthcare and welfare resources in a database. Users submit requests for collaboration with local resources through their terminals. The server searches for appropriate local resources, generates a specific and actionable collaboration plan, and notifies the terminal. The progress of each collaboration step is reported to the server in real time.

[0063] For example, if an organization providing home care services wishes to expand its operations in collaboration with a local government, the user submits a collaboration request via their terminal. The server searches for appropriate local governments and related organizations based on database information, creates a specific collaboration plan, and provides it to the user. The user then proceeds with the collaboration according to this plan.

[0064] Thus, the present invention provides a comprehensive system for resolving labor shortages in the medical and welfare fields and improving operational efficiency.

[0065] The following describes the processing flow.

[0066] 1. Expansion of education and training

[0067] Processing steps

[0068] Step 1:

[0069] The server stores the latest training data (videos, text, quizzes, etc.) for the medical and welfare fields in a database. Specifically, it uses web crawling and APIs to collect reliable training materials, organizes them, and stores them in the database.

[0070] Step 2:

[0071] Users apply for training through their devices. Specifically, users access a dedicated application or web portal, log in, and then enter their skill level and preferred training dates and times into the application form.

[0072] Step 3:

[0073] The server generates an optimal training plan considering the user's skill level and schedule. Specifically, it uses an AI algorithm to analyze user data and training materials to create a personalized training plan.

[0074] Step 4:

[0075] The device notifies the user of the training plan. Specifically, it sends the user the details of the training plan via push notification or email, and also sends periodic reminders for training sessions.

[0076] Step 5:

[0077] The device reports training progress to the server in real time. Specifically, it has a function that automatically sends progress to the server each time the user completes a training session, and the server records the progress in a database and provides feedback as needed.

[0078] 2. Utilization of foreign workers

[0079] Processing steps

[0080] Step 1:

[0081] The server collects recruitment information for foreign workers into a database. Specifically, it periodically collects the latest job postings from global job sites and recruitment agencies, organizes them, and stores them in the database.

[0082] Step 2:

[0083] The user submits a request to hire foreign workers from their device. Specifically, the user fills out a request form on their device specifying the hiring requirements for workers with particular skills and qualifications, and then submits it.

[0084] Step 3:

[0085] The server selects the most suitable foreign worker based on the request. Specifically, it analyzes the request content and collected recruitment information using a matching algorithm to generate a list of optimal candidates.

[0086] Step 4:

[0087] The device provides the user with information and contact details of the selected personnel. Specifically, it displays the selected candidate's profile, past experience, contact information, and other details on the user's device.

[0088] 3. Utilization of technology

[0089] Processing steps

[0090] Step 1:

[0091] The server monitors the use of technology in medical and welfare settings. Specifically, it periodically collects, integrates, and analyzes usage data for tools and applications used in each setting.

[0092] Step 2:

[0093] The server proposes technical tools and applications to the user based on their needs. Specifically, it selects the most suitable tools and applications based on usage data and information on new technologies in the market, generates a list of suggestions, and notifies the user.

[0094] Step 3:

[0095] The user evaluates whether to accept the proposal using their device. Specifically, the user reviews the proposed technology, judges its usefulness, and sends feedback.

[0096] Step 4:

[0097] The server deploys approved technologies to healthcare and welfare settings and monitors their usage in real time. Specifically, it remotely configures technical tools, continuously collects and analyzes usage data after deployment, and provides support and feedback as needed.

[0098] 4. Improvement of working conditions

[0099] Processing steps

[0100] Step 1:

[0101] The server collects and analyzes working environment data from medical and welfare facilities. Specifically, it acquires data from regular surveys and sensors, integrates it, and analyzes it.

[0102] Step 2:

[0103] Users input requests for improvements to their work environment via their device. Specifically, users enter their complaints and requests for improvements regarding their work environment into a dedicated form and submit it.

[0104] Step 3:

[0105] Based on the data collected by the server and user requests, the system proposes improvement measures. Specifically, it generates concrete improvement plans based on insights gained from data analysis and notifies the user.

[0106] Step 4:

[0107] The device notifies the user of the proposed solutions and provides an implementation plan. Specifically, it provides the user with a guide that explains in detail the steps and schedule for implementing the improvement measures, and has a function to track progress.

[0108] 5. Promoting regional cooperation

[0109] Processing steps

[0110] Step 1:

[0111] The server integrates regional medical and welfare resource information into a database. Specifically, it collects, organizes, and centralizes resource information from medical institutions, welfare facilities, NPO organizations, and other organizations in each region.

[0112] Step 2:

[0113] Users submit requests to connect with local resources using their devices. Specifically, users fill out the required information in the request form on the top page and submit it.

[0114] Step 3:

[0115] The server searches for the most suitable regional resources and generates a collaboration plan. Specifically, it analyzes the request content and resource information using a matching algorithm to create a concrete collaboration plan.

[0116] Step 4:

[0117] The device notifies the user of the integration plan and reports its progress to the server. Specifically, it has the function to notify the user of the details of the integration plan via push notification and to report the execution status of each step to the server in real time.

[0118] Through the specific processing steps described above, the present invention provides a system that helps to alleviate labor shortages in the medical and welfare fields and improves operational efficiency.

[0119] (Example 1)

[0120] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0121] In the medical and welfare sector, numerous challenges exist, including a lack of education and training, difficulties in effectively utilizing foreign workers, and the need to introduce new technologies and improve working conditions on-site. These problems, lacking appropriate solutions, are contributing to a decline in the operational efficiency and service quality of medical and welfare facilities. This invention aims to resolve these challenges and provide a comprehensive system that enables efficient and effective support for medical and welfare operations.

[0122] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0123] In this invention, the server includes means for storing the latest training data in the medical and welfare fields in a database, means for users to apply for training via a terminal, means for generating an optimal training plan considering the user's skill level and schedule, and means for optimizing this generated plan using a generation AI model, means for the terminal to notify the user of the training plan and report the training progress to the server in real time, means for collecting recruitment information for foreign workers in a database, means for users to submit recruitment requests for foreign workers via a terminal, means for selecting and notifying the user of the most suitable personnel based on language skills, qualifications, experience, etc., and means for this selection using a generation AI model, means for the terminal to provide the user with information and contact details of the selected personnel, means for monitoring the status of technology utilization in medical and welfare settings, means for proposing technology tools and applications to the user according to demand, means for the user to evaluate whether to accept the proposal using a terminal, and means for introducing approved technologies and monitoring their usage in real time. This makes it possible to alleviate labor shortages in the medical and welfare fields, improve the efficiency of education and training, effectively utilize foreign workers, appropriately introduce technology, and continuously improve the working environment.

[0124] The "medical and welfare field" refers to a broad range of operations and services related to medical care and welfare.

[0125] "Education and training" refers to training and learning activities aimed at improving skills and knowledge.

[0126] A "server" refers to a computer system that manages and processes data via a network.

[0127] A "database" refers to a structured collection of data that efficiently stores, searches, and manages large amounts of data.

[0128] "User" refers to an individual or group that operates or uses this system.

[0129] "Terminal" refers to a computer or smart device used by a user to access a system.

[0130] A "training plan" refers to a specific educational and training schedule designed to improve the user's skills.

[0131] A "generative AI model" refers to an algorithm that uses artificial intelligence to automatically generate optimal solutions and plans.

[0132] "Foreign workers" refers to people who come from outside the country to work.

[0133] "Recruitment information" refers to information about job seekers and employers, such as job advertisements and recruitment details.

[0134] "Technical tools" refer to technical devices and applications that help improve the efficiency and quality of work.

[0135] "Monitoring" refers to the act of continuously observing and recording specific situations or data.

[0136] "Notification" refers to the act of transmitting information or messages in real time.

[0137] A "progress report" refers to reporting on the progress of a specific task or project.

[0138] "Evaluation" refers to making a value judgment about a particular element or action.

[0139] "Real-time" refers to the processing of data and the transmission of information occurring almost simultaneously.

[0140] A "proposal" refers to the act of recommending a specific action or measure.

[0141] Modes for carrying out the invention

[0142] This invention is a comprehensive system that supports the resolution of labor shortages and the improvement of operational efficiency in the medical and welfare fields. The system of this invention utilizes the latest technology and has functions that enable the expansion of education and training, effective utilization of foreign workers, on-site technology introduction, and continuous improvement of the working environment.

[0143] System Configuration

[0144] 1. Expansion of education and training

[0145] The server stores the latest training data (videos, text, quizzes, etc.) in the medical and welfare fields in its database. This training data is obtained from reliable medical and educational institutions.

[0146] Users use their devices to apply for training programs based on their skill level and desired training program.

[0147] The server uses a generative AI model to consider the user's skill level and schedule to generate an optimal training plan.

[0148] The generated training plan is notified to the user via their device, and the progress of each training session is reported to the server in real time.

[0149] Example: Suppose a user wants online training to improve their caregiving skills. The user submits a training request from their device. The server considers the user's current skill level and available time, and uses a generative AI model to generate a training plan combining video materials on basic caregiving techniques and quiz-style tests, which is then provided to the user. The user follows this plan and the device reports their progress to the server.

[0150] Example of a prompt:

[0151] "Please describe a system to address the labor shortage in the medical and welfare sectors. Include the following five functions: expansion of education and training, utilization of foreign workers, utilization of technology, improvement of working conditions, and promotion of regional cooperation. Please explain each of these, including specific examples."

[0152] 2. Utilization of foreign workers

[0153] The server collects job postings from global job sites and agencies into its database.

[0154] Users submit recruitment requests for foreign workers with specific skills and qualifications from their devices.

[0155] The server uses a generative AI model to collect data and selects the most suitable candidates based on language skills, qualifications, experience, etc., and provides detailed information to the terminal.

[0156] Example: Suppose a user wants to hire foreign workers as nursing staff. The user sends a recruitment request from their device, specifying language skills and certain qualifications as requirements. The server uses a generative AI model to search the database for the most suitable candidates and notifies the user of the selected candidates' profiles and contact information. The user then conducts interviews based on the provided information and makes a hiring decision.

[0157] 3. Utilization of technology

[0158] The server constantly monitors the usage status of technical tools and applications used in medical and welfare settings.

[0159] The server proposes the latest technical tools and applications to users according to their needs.

[0160] Users evaluate proposals using their devices and decide whether to accept them. Approved technologies are deployed to the field by the server, and their usage is monitored in real time.

[0161] Specific example: If a medical facility requests to implement automated nursing record keeping, the server monitors the current manual record-keeping status and suggests an appropriate automated record-keeping tool based on that information. After the user approves this suggestion on their terminal, the server installs the automated record-keeping tool and monitors its usage and effectiveness.

[0162] 4. Improvement of working conditions

[0163] The server periodically collects and analyzes data related to the working environment in medical and welfare facilities.

[0164] Users input their requests for improvements to the work environment using a terminal.

[0165] The server proposes efficient improvement measures based on collected data and user requests, and notifies the user via the terminal. When improvements are implemented, progress is reported to the server, ensuring continuous improvement.

[0166] Specific example: If a request for improvements to reduce staff stress is made at a nursing care facility, the server collects data through surveys and sensors, and based on the analysis results, proposes specific improvement measures to the user, such as introducing a relaxation space or revising the shift system. The user checks the proposed measures on their terminal and puts them into action.

[0167] 5. Promoting regional cooperation

[0168] The server integrates and manages information about local healthcare and welfare resources in a database.

[0169] Users submit requests for integration with local resources through their devices.

[0170] The server searches for appropriate regional resources, generates a specific collaboration plan, and notifies the terminal. The progress of each collaboration step is reported to the server in real time.

[0171] Specific example: If an organization providing home care services wishes to expand its operations in collaboration with a local government, the user submits a collaboration request via their terminal. The server searches for appropriate local governments and related organizations based on database information, creates a specific collaboration plan, and provides it to the user. The user then proceeds with the collaboration according to this plan.

[0172] The system of this invention, by integrating these functions, effectively solves a wide range of problems in the medical and welfare fields, thereby reducing labor shortages and improving operational efficiency.

[0173] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0174] Expansion of education and training

[0175] Step 1:

[0176] The server stores the latest training data (videos, text, quizzes, etc.) for the medical and welfare fields in its database.

[0177] Input: Training data obtained from reliable medical or educational institutions.

[0178] Data processing: Converting data formats and registering them in databases.

[0179] Output: Training data stored in the database.

[0180] Step 2:

[0181] Users use their devices to apply for their skill level and desired training program.

[0182] Input: User's skill level information and desired training program.

[0183] Data processing: Standardize the input data from application forms.

[0184] Output: Training application data sent to the server.

[0185] Specific actions: After logging in, the user enters information into the training application form and clicks the "Submit" button.

[0186] Step 3:

[0187] The server uses a generative AI model to generate a training plan that takes into account the user's skill level and schedule.

[0188] Input: User skill level, schedule, and training data.

[0189] Data processing: Analysis and plan generation using generative AI models.

[0190] Output: Optimal training plan.

[0191] Specific operation: The server inputs the user's skill data and available time into the generated AI model and generates an optimal training plan.

[0192] Step 4:

[0193] The server notifies the user of the generated training plan via the terminal.

[0194] Input: Optimal training plan.

[0195] Data processing: Generating notification messages and sending them to the device.

[0196] Output: The training plan notified to the user's device.

[0197] Specific action: Send a push notification to the user's device and display the training plan.

[0198] Step 5:

[0199] The device reports training progress to the server in real time.

[0200] Input: User training progress information.

[0201] Data processing: Collection and transfer of progress data.

[0202] Output: Training progress data reported to the server.

[0203] Specific operation: When a user updates their progress during a training session, the device sends that information to the server.

[0204] Utilization of foreign workers

[0205] Step 1:

[0206] The server collects job postings from global job sites and agencies into its database.

[0207] Input: Job postings from global job sites and agencies.

[0208] Data processing: Data collection and registration into databases.

[0209] Output: Recruitment information stored in the database.

[0210] Step 2:

[0211] Users submit recruitment requests for foreign workers from their devices.

[0212] Input: Language skills and specific qualifications required by the user.

[0213] Data processing: Standardization and storage of recruitment requests.

[0214] Output: Recruitment request data sent to the server.

[0215] Specific operation: The user enters the hiring criteria and clicks the "Submit Request" button.

[0216] Step 3:

[0217] The server selects the most suitable candidate based on the data collected using a generative AI model.

[0218] Input: Recruitment request data and collected recruitment information.

[0219] Data processing: Candidate selection using generative AI models.

[0220] Output: A list of the best candidates.

[0221] Specific operation: The server executes a database query to search for candidates that match the criteria.

[0222] Step 4:

[0223] The server notifies the terminal of detailed information about the selected candidates.

[0224] Input: A list of the best candidates.

[0225] Data processing: Generating and forwarding notification messages for candidate information.

[0226] Output: Candidate information notified to the user's device.

[0227] Specific operation: Display candidate information on the user's device and provide a link to the details page.

[0228] Utilization of technology

[0229] Step 1:

[0230] The server monitors the usage of technical tools and applications used in medical and welfare settings.

[0231] Input: Data on technology usage from the field.

[0232] Data processing: Data analysis and storage.

[0233] Output: Monitoring report.

[0234] Specific actions: Collect sensor and log data to track usage.

[0235] Step 2:

[0236] The server proposes the latest technical tools and applications to users according to their needs.

[0237] Input: Monitoring data and latest technology data.

[0238] Data processing: Generating proposals based on analysis results.

[0239] Output: Proposal message.

[0240] Specific operation: Analyze usage data and select the appropriate tool using a generated AI model.

[0241] Step 3:

[0242] The user evaluates the proposal and decides whether to accept it.

[0243] Input: Suggestion message.

[0244] Data processing: Evaluation of proposals.

[0245] Output: Evaluation results.

[0246] Specific actions: View the proposal, fill out the evaluation form, and click the "Complete Evaluation" button.

[0247] Step 4:

[0248] The server deploys approved technologies to the field and monitors their usage in real time.

[0249] Input: Approved technical information.

[0250] Data processing: Monitoring the deployment and usage of technical tools.

[0251] Output: Usage report.

[0252] Specific actions: Deploy new technical tools to the field and monitor their usage using sensors and log data.

[0253] Improvement of working conditions

[0254] Step 1:

[0255] The server periodically collects and analyzes data related to the working environment in medical and welfare facilities.

[0256] Input: Surveys and sensor data related to the working environment.

[0257] Data processing: Data collection and analysis.

[0258] Output: Labor environment analysis report.

[0259] Specific operation: Data is collected through surveys and sensors, and then processed using analysis software.

[0260] Step 2:

[0261] Users input their requests for improvements to the work environment using a terminal.

[0262] Input: Improvement request data.

[0263] Data processing: Standardization and storage of requested data.

[0264] Output: Improvement request data sent to the server.

[0265] Specific action: Fill out the improvement request form and click the "Submit" button.

[0266] Step 3:

[0267] The server proposes efficient improvement measures based on the collected data and user requests.

[0268] Input: Work environment data and improvement request data.

[0269] Data processing: Data analysis and proposal generation.

[0270] Output: Suggestion message for improvement.

[0271] Specific operation: Combine user requests and data analysis results to generate improvement measures and notify the device.

[0272] Step 4:

[0273] When proposed improvements to the working environment are implemented, progress is reported to the server, and continuous improvement is ensured.

[0274] Input: Progress data on improvement implementation.

[0275] Data processing: Collection and analysis of progress data.

[0276] Output: Progress report.

[0277] Specific actions: Regularly monitor the effectiveness of implemented improvement measures and generate reports.

[0278] Promotion of Regional Collaboration

[0279] Step 1:

[0280] The server integrates and manages information about regional medical and welfare resources in a database.

[0281] Input: Regional resource information.

[0282] Data processing: Collection and integration of data.

[0283] Output: Regional resource information integrated into the database.

[0284] Specific operation: Collect data using the API for regional resource information.

[0285] Step 2:

[0286] The user submits a collaboration request with regional resources through a terminal.

[0287] Input: Collaboration request data.

[0288] Data processing: Standardization and storage of data.

[0289] Output: Collaboration request data sent to the server.

[0290] Specific operation: Enter in the collaboration request form and click the "Send" button.

[0291] Step 3:

[0292] The server searches for appropriate regional resources and generates a specific collaboration plan.

[0293] Input: Regional resource information and collaboration request data.

[0294] Data processing: Analysis of data and plan generation.

[0295] Output: Collaboration plan.

[0296] Specific operation: Analyze the user's request, query the database, and generate a collaboration plan.

[0297] Step 4:

[0298] The server notifies the terminal of the generated collaboration plan.

[0299] Input: Collaboration plan.

[0300] Data processing: Generate and transfer the notification message of the plan.

[0301] Output: The collaboration plan notified to the user's terminal.

[0302] Specific operation: Send the notification of the collaboration plan to the user's terminal and display the details.

[0303] Step 5:

[0304] The progress of each collaboration step is reported to the server.

[0305] Input: Progress data of the collaboration step.

[0306] Data processing: Collect and integrate the progress data.

[0307] Output: Progress report.

[0308] Specific operation: Monitor the progress of the collaboration and update the progress status to the server.

[0309] Through the above procedures, this system provides comprehensive support to eliminate the shortage of manpower in the medical and welfare fields and realize the improvement of business efficiency.

[0310] (Application Example 1)

[0311] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0312] Labor shortages and operational inefficiencies in the healthcare and welfare sectors are serious challenges. To address these issues, improved education and training, effective utilization of foreign workers, and the introduction of cutting-edge technologies are essential. In particular, similar problems exist not only in the healthcare and welfare sectors but also in manufacturing sites such as factories, where a lack of knowledge and skills regarding robot operation and maintenance is a bottleneck. To solve this, a comprehensive education system and technical support system are required.

[0313] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0314] In this invention, the server includes means for storing the latest training data related to the operation of medical and welfare fields and factory robots in a database, means for users to apply for training via a terminal, means for generating an optimal training plan considering the user's skill level and schedule, means for notifying users through various training and reporting their progress in real time, means for providing videos and materials on factory robot operation procedures, means for generating and notifying robot maintenance schedules, means for monitoring the robot's status and diagnosing errors, and means for users to utilize training modes for skill improvement. This enables the efficient provision of technical education and training in both medical and welfare fields and factory settings, improving the efficiency of operation and maintenance, and solving the problems of labor shortages and operational inefficiencies.

[0315] The "medical and welfare field" refers to all fields that provide medical and welfare services.

[0316] "Training data" refers to digital information such as videos, texts, and quizzes used for educational and training purposes.

[0317] A "database" refers to a system for structuring, storing, and managing training data and other information.

[0318] "Terminal" refers to devices such as computers, smartphones, and tablets that users use to access servers.

[0319] "Skill level" refers to an indicator that evaluates the user's current level of knowledge and proficiency in skills.

[0320] A "training plan" refers to an educational and training program customized based on the user's skill level and schedule.

[0321] "Real-time" refers to processing and responding instantly without delay.

[0322] "Factory robots" refer to automated mechanical devices used in factories and manufacturing sites.

[0323] "Operation procedure videos" refer to video content created to demonstrate how to use and operate a robot.

[0324] "Documents" refers to papers and manuals created to explain operating procedures and maintenance details.

[0325] A "maintenance schedule" refers to a timetable or plan for systematically performing maintenance on a robot.

[0326] "Monitoring" refers to the act of continuously monitoring the status of a system or device.

[0327] "Error diagnosis" refers to the process of detecting abnormalities that occur in devices or systems, and identifying and analyzing their causes.

[0328] "Training Mode" refers to special educational and training features that users can use to improve their skills.

[0329] "Technical tools" refer to various technical devices and software used to efficiently perform specific tasks.

[0330] An "application" refers to a software program with a specific function or purpose.

[0331] This invention is a system for streamlining the operation and maintenance of robots in the medical and welfare fields and in factories. Specific embodiments for carrying out this invention are described below.

[0332] Program generation:

[0333] The system consists of components applicable to both the medical and welfare fields and factory robotics. This system includes the following:

[0334] 1. The server stores the latest training data related to the operation and maintenance of medical and welfare fields and factory robots in its database.

[0335] 2. Users apply for training through their device.

[0336] 3. The server generates an optimal training plan, taking into account the user's skill level and schedule.

[0337] 4. The device notifies the user of the training plan and reports the training progress in real time.

[0338] 5. The server provides operating procedure videos and materials for the factory robots.

[0339] 6. The server generates and notifies the robot of its maintenance schedule.

[0340] 7. The server monitors the robot's status and diagnoses errors.

[0341] 8. Users utilize training modes to improve their skills.

[0342] Hardware and software to be used:

[0343] Hardware: Smartphones, tablets, smart glasses, computers

[0344] Software: Database management systems (e.g., SQLite), programming languages ​​(e.g., Python)

[0345] Data processing and data calculations:

[0346] Data processing: Training data and operating procedure documents are stored in a database, and appropriate data is provided in response to user requests.

[0347] Data processing: Generate customized training plans based on the user's skill level and schedule, and monitor progress in real time. Generate robot maintenance schedules and analyze error logs.

[0348] Specific example:

[0349] For example, if a nursing staff member working at a medical facility wants to learn how to operate new medical equipment, they can submit a training request via a terminal. The server then considers the staff member's skill level and schedule to generate an optimal training plan. This plan includes video materials and quiz-style tests, which the nursing staff member follows as they progress through the training. Similarly, data regarding the operation and maintenance of robots used in factories is managed in the same way, allowing workers to receive efficient training.

[0350] Example of a prompt:

[0351] Design an application that provides basic instructional videos, maintenance procedures, and error logs for new engineers to operate factory robots.

[0352] It also includes real-time support functions to address labor shortages and improve operational efficiency.

[0353] In this way, the present invention enables the efficient provision of technical education and training in both medical and welfare settings, as well as in factory settings, thereby solving the problems of labor shortages and operational inefficiencies.

[0354] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0355] Step 1:

[0356] The server stores the latest training data related to the operation and maintenance of medical and welfare fields and factory robots in its database.

[0357] Input: Training data (videos, text, quizzes, etc.)

[0358] Data processing: Save training data to a database categorized by type.

[0359] Output: Training data stored in the database

[0360] Specific operation: The administrator uploads the latest training data, and the server categorizes and stores it in the database.

[0361] Step 2:

[0362] Users apply for training through their device.

[0363] Input: User's skill level and desired training content

[0364] Data processing: Receive user application details and save them to the database.

[0365] Output: User application data

[0366] Specific operation: The user uses the application to input their skill level and desired training content, and that data is sent to the server.

[0367] Step 3:

[0368] The server generates an optimal training plan, taking into account the user's skill level and schedule.

[0369] Input: User's skill level and schedule, training data stored in the database

[0370] Data processing: Select an appropriate training program based on the user's skill level and available time.

[0371] Output: Individually optimized training plan

[0372] Specific operation: The server matches training data in the database with user information to generate the optimal training plan.

[0373] Step 4:

[0374] The device notifies the user of the training plan and reports on training progress in real time.

[0375] Input: Training plan, user progress data

[0376] Data processing: Notification of training plans and real-time reporting of progress data.

[0377] Output: User notifications, progress report data

[0378] Specific operation: As the user checks the training plan on their device and progresses through the training, their progress is automatically reported to the server.

[0379] Step 5:

[0380] The server provides operating procedure videos and documents for factory robots.

[0381] Input: Operation procedure data (video, text)

[0382] Data processing: Providing operation procedure data to users in an appropriate format.

[0383] Output: User instruction videos and documentation

[0384] Specific operation: Video tutorials and materials necessary for operating the robot are delivered to the user's device.

[0385] Step 6:

[0386] The server generates and notifies users of the robot's maintenance schedule.

[0387] Input: Robot operation data, recommended maintenance cycle

[0388] Data calculation: Calculate maintenance requirements and create a schedule.

[0389] Output: Maintenance Schedule

[0390] Specific operation: Based on the robot's usage frequency and status, the system automatically generates a schedule for the next maintenance and notifies the user.

[0391] Step 7:

[0392] The server monitors the robot's status and diagnoses errors.

[0393] Input: Real-time robot operation data, error logs

[0394] Data processing: Log data analysis and error diagnosis

[0395] Output: Error report and suggested solutions

[0396] Specific operation: Based on the robot's sensors and log data, it monitors its status in real time, immediately diagnoses any abnormalities, and reports them to the user.

[0397] Step 8:

[0398] Users can utilize the training mode to improve their skills.

[0399] Input: Training mode selection, current skill level

[0400] Data Processing: Customize training modes according to skill level.

[0401] Output: Training content tailored to the user

[0402] Specific operation: Users can select a training mode within the application and receive training tailored to their skill level.

[0403] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0404] This invention provides a system that combines an emotion engine that recognizes user emotions in order to alleviate labor shortages and support efficient operations in the medical and welfare fields. This system is implemented in the following manner.

[0405] 1. Expansion of education and training

[0406] The server stores the latest training data (videos, text, quizzes, etc.) in the medical and welfare fields in its database. The server also includes an emotion engine that recognizes user emotions. When a user applies for training through their device, the emotion engine evaluates the user's emotional state in real time through facial recognition and voice analysis. This emotion data, along with the user's skill level and schedule, is used to generate an optimal training plan.

[0407] The server analyzes emotional data collected by the emotion engine and, if the user is feeling stressed or unmotivated, provides training content and feedback tailored to their current emotions. The device then notifies the user of a training plan based on this analysis and reports its progress to the server in real time.

[0408] For example, if a user requests online training to improve their caregiving skills, the emotion engine assesses their stress level based on their facial expression and tone of voice when they log in and submit a training request. Based on this information, the server generates a training plan that includes relaxing video materials and interactive quizzes, which are then delivered to the user via their device.

[0409] 2. Utilization of foreign workers

[0410] The server collects recruitment information for foreign workers into a database and uses an emotion engine to evaluate the emotional state of candidates during interviews. Users submit recruitment requests for foreign workers from their terminals, and the server selects the most suitable candidates based on language skills, qualifications, experience, and emotional state. The terminal then provides the user with information and contact details of the selected candidates.

[0411] As a concrete example, when a user hires foreign workers as nursing staff, the emotional engine evaluates the candidate's stress level and communication skills during the interview, helping to select a suitable candidate. The user can then review this data via their device and hire the most suitable personnel.

[0412] 3. Utilization of technology

[0413] The server monitors the usage of technology tools and applications used in healthcare and welfare settings and uses an emotion engine to evaluate users' emotions towards the use of these technologies. Based on this data, the server suggests technology tools and applications to users according to their needs. Users evaluate the suggestions via their terminals, and approved technologies are deployed to the field by the server, with their usage and emotion data monitored in real time.

[0414] As a concrete example, if a user is unfamiliar with a new nursing record application introduced at a medical facility, the emotion engine will detect the user's confusion or stress, and the server will suggest a simpler interface or provide additional training. This information is then communicated to the user via the terminal, aiming to improve user satisfaction.

[0415] 4. Improvement of working conditions

[0416] The server collects and analyzes work environment and emotional data from medical and welfare facilities. Users input requests for improvements to the work environment via a terminal, and their emotional state is recorded in real time. Based on the collected data and the user's emotions, the server proposes specific improvement measures and notifies the user via the terminal. Progress during implementation is reported to the server, and feedback is provided as needed.

[0417] For example, if a staff member at a nursing home is experiencing stress, the emotion engine detects this, and the server suggests measures to reduce stress, such as expanding relaxation spaces or changing shifts. The user then reviews the suggestions on their device and takes action.

[0418] 5. Promoting regional cooperation

[0419] The server integrates and manages information and emotional data about local healthcare and welfare resources in a database. Users submit requests for collaboration with local resources through their terminals, and their emotional state at the time is also recorded. The server generates appropriate local resources and specific collaboration plans, and adjusts the timing and content of the collaboration plan proposals to the user based on the emotional data. The user is notified of the proposals through their terminal, and the progress of each collaboration step is reported to the server in real time.

[0420] As a concrete example, when an organization providing home care services expands its operations in collaboration with a local government, the user's emotion engine monitors their emotional state in real time during the collaboration negotiations, and the server proposes approaches to reduce the user's stress and anxiety. The user can check this from their terminal, and is supported in ensuring the smooth progress of the collaboration.

[0421] Thus, the present invention provides a system that, by combining an emotion engine, evaluates the user's emotional state in real time and enables more effective and user-friendly implementation of processes in the medical and welfare fields, including education, utilization of foreign workers, introduction of technology, improvement of the working environment, and regional collaboration.

[0422] The following describes the processing flow.

[0423] 1. Expansion of education and training

[0424] Processing steps

[0425] Step 1:

[0426] The server stores the latest training data (videos, text, quizzes, etc.) for the medical and welfare fields in a database. Specifically, it uses web crawling and APIs to collect reliable training materials, organizes them, and stores them in the database.

[0427] Step 2:

[0428] Users apply for training through their devices. Specifically, users access a dedicated application or web portal, log in, and then enter their skill level and preferred training dates and times into the application form.

[0429] Step 3:

[0430] The server uses an emotion engine to recognize user emotions and evaluate the user's emotional state. Specifically, when a user submits a training request, the system analyzes their facial expressions and voice tone in real time via the camera and microphone.

[0431] Step 4:

[0432] The server generates an optimal training plan by considering the user's skill level, schedule, and sentiment data. Specifically, it uses AI algorithms to analyze this data and create a personalized training plan.

[0433] Step 5:

[0434] The device notifies the user of the training plan. Specifically, it sends the user the details of the training plan via push notification or email, and also sends periodic reminders for training sessions.

[0435] Step 6:

[0436] The device reports training progress and user sentiment data to the server in real time. Specifically, it has a function that automatically sends progress and sentiment status to the server each time the user completes a training session.

[0437] 2. Utilization of foreign workers

[0438] Processing steps

[0439] Step 1:

[0440] The server collects recruitment information for foreign workers into a database. Specifically, it periodically collects the latest job postings from global job sites and recruitment agencies, organizes them, and stores them in the database.

[0441] Step 2:

[0442] The user submits a request to hire foreign workers from their device. Specifically, the user fills out a request form on their device specifying the hiring requirements for workers with particular skills and qualifications, and then submits it.

[0443] Step 3:

[0444] The server selects the most suitable foreign worker based on the request. Specifically, it analyzes the request content and collected recruitment information using a matching algorithm to generate a list of optimal candidates.

[0445] Step 4:

[0446] The server uses an emotion engine to evaluate the candidate's emotional state during the interview. Specifically, it collects and analyzes the candidate's emotional data through the camera and microphone during the interview.

[0447] Step 5:

[0448] The device provides the user with information and contact details of the selected personnel. Specifically, it displays the selected candidate's profile, past experience, contact information, and other details on the user's device.

[0449] 3. Utilization of technology

[0450] Processing steps

[0451] Step 1:

[0452] The server monitors the use of technology in medical and welfare settings. Specifically, it periodically collects, integrates, and analyzes usage data for tools and applications used in each setting.

[0453] Step 2:

[0454] The server uses an emotion engine to evaluate the user's emotional state when using technology. Specifically, it collects and analyzes emotional data through the camera and microphone when the user uses tools or applications.

[0455] Step 3:

[0456] The server suggests technology tools and applications to users based on their technology usage and sentiment data, tailored to their needs. Specifically, it uses an AI algorithm to generate a list of optimal tools and applications and notifies the user.

[0457] Step 4:

[0458] The user evaluates whether to accept the proposal using their device. Specifically, the user reviews the proposed technology, judges its usefulness, and sends feedback.

[0459] Step 5:

[0460] The server deploys approved technologies to healthcare and welfare settings, monitoring usage and emotional data in real time. Specifically, it remotely configures technical tools, continuously collects and analyzes usage and emotional data after deployment, and provides support and feedback as needed.

[0461] 4. Improvement of working conditions

[0462] Processing steps

[0463] Step 1:

[0464] The server collects and analyzes work environment and emotional data from medical and welfare facilities. Specifically, it acquires and analyzes data from periodic surveys, sensors, and real-time emotional data generated by an emotional analysis engine.

[0465] Step 2:

[0466] Users input requests for improvements to their work environment via their device. Specifically, users enter their complaints and requests for improvements regarding their work environment into a dedicated form and submit it.

[0467] Step 3:

[0468] The system proposes improvement measures based on data collected by the server and user sentiment. Specifically, it generates concrete improvement suggestions based on insights gained from data analysis and notifies the user.

[0469] Step 4:

[0470] The device notifies the user of the proposed solutions and provides an implementation plan. Specifically, it provides the user with a guide that explains in detail the steps and schedule for implementing the improvement measures, and has a function to track progress.

[0471] 5. Promoting regional cooperation

[0472] Processing steps

[0473] Step 1:

[0474] The server integrates regional medical and welfare resource information and sentiment data into a database. Specifically, it collects, organizes, and centralizes resource information and sentiment data from medical institutions, welfare facilities, NPO organizations, and other organizations in each region.

[0475] Step 2:

[0476] Users submit requests to connect with local resources using their devices. Specifically, users fill out the necessary information in a request form from the top page, and their emotional state at that time is recorded in real time.

[0477] Step 3:

[0478] The server searches for the most suitable regional resources and generates a collaboration plan. Specifically, it analyzes the request content, resource information, and sentiment data using a matching algorithm to create a concrete collaboration plan.

[0479] Step 4:

[0480] The device notifies the user of the integration plan and reports progress and sentiment data to the server. Specifically, it notifies the user of the details of the integration plan via push notification and has the function to monitor the sentiment state during execution and report the progress of each step to the server in real time.

[0481] Through the specific processing steps described above, the present invention provides a system that helps alleviate labor shortages in the medical and welfare fields and improves operational efficiency. By using an emotion engine, the user's emotional state can be evaluated in real time, enabling the provision of more effective and user-friendly support.

[0482] (Example 2)

[0483] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0484] In the healthcare and welfare sector, challenges include improving operational efficiency and reducing the psychological burden on employees in areas such as education and training, the utilization of foreign workers, and the introduction of new technologies. Conventional systems have made it difficult to assess users' emotional states in real time and respond individually, leading to decreased operational efficiency and increased employee stress.

[0485] The identification processing performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for storing the latest training data in the medical and welfare field in a database, means for users to apply for training through a terminal, means for generating an optimal training plan considering the user's skill level and schedule, means for recognizing and collecting the user's emotional state, means for analyzing the emotional data and adjusting the training content based on the user's emotional state, and means for the terminal to notify the user of the training plan and report the progress of the training in real time. This enables flexible and individualized responses in accordance with the user's emotional state.

[0486] The "medical and welfare field" refers to all activities in the medical and welfare industries, including patient treatment and the provision of welfare services.

[0487] "Training data" refers to learning resources such as videos, text, and quizzes that are stored on a server for educational and training purposes.

[0488] A "database" refers to a system for efficiently storing, searching, and managing information.

[0489] "Users" refer to employees and related parties in the medical and welfare fields who use this system.

[0490] "Terminal" refers to the computer or mobile device that a user uses to access this system.

[0491] An "emotion engine" refers to technology that recognizes, collects, and analyzes a user's emotional state.

[0492] "Emotional data" refers to data about the user's emotional state collected by the emotion engine.

[0493] "Skill level" refers to the user's level of proficiency in skills and knowledge.

[0494] A "training plan" refers to the optimal learning and training program generated by the server based on the user's skill level and emotional state.

[0495] "Foreign workers" refers to workers of foreign origin who are employed in the medical and welfare fields.

[0496] "Recruitment information" refers to data including foreign workers' language skills, qualifications, and experience.

[0497] "Technical tools and applications" refer to software and systems used in medical and welfare settings.

[0498] This invention relates to a system that supports the expansion of education and training, the utilization of foreign workers, and the introduction of technology in the medical and welfare fields. This system can improve work efficiency and reduce the psychological burden on employees by recognizing the user's emotional state in real time and providing optimal support based on that recognition.

[0499] Expansion of education and training

[0500] The server collects the latest training data in the medical and welfare fields and stores it in a database. This training data includes videos, text, quizzes, and more. It also features an emotion engine that uses facial recognition technology and voice analysis to evaluate the user's emotional state in real time.

[0501] When a user submits a training request using their device, the emotion engine analyzes the user's facial expression and tone of voice to collect emotional data. The server then generates an optimal training plan based on this emotional data, the user's skill level, and their schedule information. The generated training plan is tailored to the user's emotional state.

[0502] For example, if a user requests training to improve their caregiving skills, the device's camera and microphone activate, and the emotion engine collects emotional data. The server then provides a training plan that includes relaxing video materials and interactive quizzes. This allows the user to learn without feeling stressed.

[0503] Example of a prompt: "Please propose a relaxing training plan to improve caregiving skills."

[0504] Utilization of foreign workers

[0505] The server collects recruitment information on foreign workers (language skills, qualifications, experience) and stores it in a database. When a user submits a recruitment request for a foreign worker from their terminal, the server uses an emotion engine to evaluate the candidate's emotional state and analyzes their stress level and communication skills.

[0506] As a concrete example, when a user hires foreign workers as nursing staff, the emotion engine collects candidate emotional data during the interview, and the server selects the appropriate candidate. Once the best candidate is selected, their information and contact details are provided to the user via their device.

[0507] Example prompt: "Please tell me the criteria for selecting foreign workers who are suitable as nursing staff."

[0508] Utilization of technology

[0509] The server monitors the usage of technical tools and applications used in medical and welfare settings and evaluates the user's emotional state using an emotion engine. Based on the collected emotional data, the server suggests the most suitable technical tools and applications for the user.

[0510] As a concrete example, regarding a newly introduced nursing record app, if a user experiences confusion or stress while using it, the emotion engine detects this, and the server suggests a simpler interface or provides additional training. This makes it possible to improve user satisfaction.

[0511] Example prompt: "Please suggest ways to reduce the stress users experience with the new nursing record app."

[0512] Improvement of working conditions

[0513] The server can collect and analyze data on the working environment and emotional state of healthcare and welfare facilities. Users input requests for improvements to the working environment via a terminal, and their emotional state is recorded in real time. Based on the collected data, the server proposes specific improvement measures and notifies the user through the terminal.

[0514] For example, if staff at a nursing home are experiencing stress, the emotion engine detects this, and the server suggests measures to reduce stress (such as expanding relaxation spaces or changing shifts). This can reduce the psychological burden on staff and improve work efficiency.

[0515] Promoting regional cooperation

[0516] The server integrates and manages information and emotional data about local healthcare and welfare resources in a database. When a user submits a request to connect with local resources through their terminal, their emotional state is also recorded. The server generates appropriate local resources and specific connection plans, and optimizes suggestions for the user based on the emotional data.

[0517] As a concrete example, when an organization providing home care services collaborates with a local government, the emotion engine monitors the user's emotional state during negotiations, and the server proposes approaches to reduce the user's stress and anxiety. This helps to facilitate smooth collaboration.

[0518] Example prompt: "Please tell me about stress reduction measures for organizations providing home care services when collaborating with local governments."

[0519] Thus, the present invention is a system that effectively supports various processes in the medical and welfare fields by utilizing an emotion engine and recognizing the user's emotional state in real time.

[0520] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0521] Expansion of education and training

[0522] Step 1:

[0523] The server collects the latest training data in the medical and welfare fields and stores it in a database. This training data includes videos, text, quizzes, and more. Input training data is collected from diverse sources and neatly stored in the database. The output is a set of the latest available training data.

[0524] Step 2:

[0525] The user submits a training application using a terminal. The user's login information and training application details are sent as input. Upon receiving this information, the terminal activates its camera and microphone to send facial expression and voice tone to the emotion engine. The output is the transmission of audio and video data to the emotion engine.

[0526] Step 3:

[0527] The server analyzes the emotional data received from the emotion engine. Emotional data, user skill level, and schedule information are obtained as input. Data calculations are used to evaluate the user's stress level and motivation. Based on the results, an optimal training plan is generated. A personalized training plan is generated as output.

[0528] Step 4:

[0529] The server sends the generated training plan to the terminal. The generated training plan is the input, and the notification sent to the terminal is the output. The terminal notifies the user and simultaneously activates a system that reports the training progress to the server in real time.

[0530] Specific operation: For example, when a user applies for training to improve their caregiving skills, the device's camera and microphone automatically activate, and the emotion engine analyzes the user's facial expression and voice tone in real time. Based on the data collected in this way, the server generates a training plan that includes relaxing materials and interactive quizzes, and sends it to the device.

[0531] Utilization of foreign workers

[0532] Step 1:

[0533] The server collects recruitment information for foreign workers and stores it in a database. Inputs include information such as each candidate's language skills, qualifications, and experience. The output is a database of usable recruitment information.

[0534] Step 2:

[0535] The user submits a recruitment request for foreign workers from their terminal. The request details and the user's preferences are sent to the terminal as input. The output is the recruitment request information sent to the server.

[0536] Step 3:

[0537] The server uses an emotion engine to evaluate the candidate's emotional state during the interview. The candidate's facial expression and voice data are sent to the emotion engine as input, and analysis is performed. Output data includes evaluations of the candidate's stress level and communication skills.

[0538] Step 4:

[0539] The server integrates collected sentiment data with candidates' language skills, qualifications, and experience to select the most suitable candidates. The selected candidates' information is generated as output and notified to the terminal. The terminal then provides this information to the user.

[0540] Specific operation: For example, when a user hires a foreign worker as nursing staff, the device's camera and microphone are activated during the interview, and an emotion engine analyzes stress levels and communication skills. Based on the results, the server selects the most suitable candidate and sends the information to the device.

[0541] Utilization of technology

[0542] Step 1:

[0543] The server monitors the usage of technical tools and applications used in medical and welfare settings. The input is usage data for each tool and application. Data is then analyzed to determine usage frequency and effectiveness. The output is aggregated usage data.

[0544] Step 2:

[0545] The server uses an emotion engine to evaluate the user's emotional state regarding the use of technical tools. Real-time emotional data from the user is sent as input. The output is emotional evaluation data from the emotion engine.

[0546] Step 3:

[0547] The server suggests the most suitable technical tools and applications to the user based on the collected sentiment data. Sentiment data and usage data are used as input. The output is personalized suggestions.

[0548] Step 4:

[0549] Through the terminal, the user evaluates the proposal and notifies the server whether to accept or reject it. User feedback on the proposal is collected as input. The output is the server's approval or rejection data of the proposal.

[0550] Specific operation: For example, if a user feels confused or stressed by a new nursing record app, the emotion engine detects this, and the server suggests an alternative app with a simpler interface or additional training. If the user accepts this, their usage and emotional data are monitored in real time.

[0551] Improvement of working conditions

[0552] Step 1:

[0553] The server collects work environment and emotional data from healthcare and welfare facilities. Environmental sensor data and user emotional data are provided as input. The output is a report on the state of the work environment.

[0554] Step 2:

[0555] Users input requests for improvements to their work environment via a terminal, and real-time sentiment data is collected along with these requests. The input consists of user feedback and sentiment data. The output consists of request data and sentiment data sent to the server.

[0556] Step 3:

[0557] The server proposes specific improvement measures based on collected work environment data and the user's emotional state. Past improvement data and current emotional data are used as input. The output is improvement suggestions notified to the user.

[0558] Step 4:

[0559] Through the terminal, the user reviews the proposed improvements and sends their feedback to the server. The input is the user's approval or rejection feedback. The output is a list of improvements to be implemented on the server side.

[0560] Specific operation: For example, if a staff member at a nursing home is experiencing stress, the emotion engine detects this, and the server suggests measures such as expanding relaxation spaces or changing shifts. The user reviews and approves these suggestions on their terminal, and they are then implemented.

[0561] Promoting regional cooperation

[0562] Step 1:

[0563] The server integrates and manages information and sentiment data related to local healthcare and welfare resources into a database. Local resource information and sentiment data are collected as input. The output is the integrated and managed database.

[0564] Step 2:

[0565] Users submit requests to connect with local resources through their devices. Their emotional state is also recorded during this process. The input consists of the request content and emotional data. The output is the request data on the server side.

[0566] Step 3:

[0567] The server generates appropriate local resources and specific collaboration plans based on collected sentiment data. Sentiment data and local resource data are used as input. The output is a collaboration plan proposal for the user.

[0568] Step 4:

[0569] The terminal notifies the user of the integration plan details and reports the progress of each integration step to the server in real time. Inputs include user feedback and progress data. Outputs include feedback and adjustments to the proposed content based on the progress.

[0570] Specific operation: For example, when an organization providing home care services collaborates with a local government, the emotion engine monitors the emotional state during negotiations, and the server suggests measures to reduce stress and anxiety. The user can then view this on their device and take appropriate action to help the collaboration proceed smoothly.

[0571] (Application Example 2)

[0572] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0573] This invention relates to resolving labor shortages in the medical and welfare fields, improving operational efficiency, and providing a more appropriate work support system that takes into account the emotional state of workers. In particular, it aims to improve the working environment and enhance the quality of education by recognizing the emotional state of workers in real time and reflecting it in training and work support plans.

[0574] In Application Example 2, the specific processing performed by the specific processing unit 290 of the data processing device 12 is realized by the following means. In this invention, the server includes means for storing the latest training data in the medical and welfare field in a database, means for users to apply for training through a terminal, means for generating an optimal training plan considering the user's skill level, schedule, and emotional state, means for the terminal to notify the user of the training plan and report the progress of the training in real time, and means for evaluating the user's emotional state in real time using emotion recognition technology. This makes it possible to provide optimal training and work support that takes into account the user's emotional state.

[0575] "Education and training in the medical and welfare fields" refers to training and learning activities that provide the knowledge and skills necessary for medical and welfare-related jobs, and aim to improve employee capabilities and streamline operations.

[0576] "Training data" refers to information such as videos, texts, and quizzes used in educational and training programs, and is based on the latest medical and welfare technologies and knowledge.

[0577] "Terminal" refers to hardware devices such as computers, smartphones, and tablets that users operate.

[0578] "Training application" refers to the process of completing the necessary procedures and registrations required for a user to receive training.

[0579] A "training plan" refers to a learning plan that combines the most suitable educational content and methods, taking into account each user's individual skill level, schedule, and emotional state.

[0580] "Reporting progress in real time" refers to the process of continuously monitoring the progress of training or work and reporting it immediately.

[0581] "Emotion recognition technology" refers to technology that uses techniques such as facial recognition and voice analysis to evaluate a user's emotional state in real time.

[0582] "Foreign workers" refers to foreign nationals employed to work in medical and welfare facilities within Japan.

[0583] A "recruitment request" refers to an application or request made by a user to recruit foreign workers.

[0584] "Language skills, qualifications, and experience" refers to the language proficiency, professional qualifications, and past work experience possessed by foreign workers.

[0585] This invention provides a system that combines an emotion engine that recognizes user emotions in order to help alleviate labor shortages and improve operational efficiency in the medical and welfare fields. This system is implemented by the following specific method.

[0586] 1. System Configuration

[0587] The server stores the latest training data (videos, text, quizzes, etc.) in the medical and welfare fields in its database. Users apply for training through their terminals. The server generates an optimal training plan considering the user's skill level, schedule, and emotional state. The generated training plan is notified to the user through their terminal, and training progress is reported in real time.

[0588] 2. Use of emotion recognition technology

[0589] The server uses emotion recognition technology to evaluate the user's emotional state in real time. This technology uses a camera and microphone to analyze the user's facial expression and voice tone, acquiring emotional data such as whether the user is stressed or relaxed.

[0590] 3. Utilization of foreign workers

[0591] In the recruitment of foreign workers, the server collects recruitment information and the worker's emotional data into a database. Users submit recruitment requests for foreign workers from their terminals. The server selects the most suitable candidates based on language skills, qualifications, experience, and emotional status, and provides information and contact details of the selected candidates through the terminals.

[0592] 4. Introduction of technology

[0593] The server monitors the use of technology in healthcare and welfare settings and uses emotion recognition technology to evaluate users' feelings towards using that technology. The server suggests technology tools and applications to users according to their needs and evaluates whether users accept the suggestions using their devices. Once a technology is approved for use, the server deploys it to the field, and its usage and emotional data are monitored in real time.

[0594] The following scenarios are possible as specific examples of its use.

[0595] If some users are unfamiliar with a new nursing record application implemented at a medical facility, the emotion recognition engine detects their confusion or stress. The server then suggests a simpler interface and provides additional training. This information is communicated to the user via their device to improve user satisfaction.

[0596] The following are examples of prompt statements.

[0597] When writing feedback on a scenario where an operator is experiencing high stress while learning to operate a new machine, please generate a prompt using the following format:

[0598] 1. An emotion engine that recognizes the worker's emotions detects high stress.

[0599] 2. The system automatically suggests breaks and notifies workers with feedback.

[0600] The hardware used includes a camera, microphone, and terminal, while the software used includes OpenCV, Keras / TENSORFLOW®, SpeechRecognition (Python library), and others.

[0601] Such a system will streamline various processes related to education in the medical and welfare fields, recruitment of foreign workers, and introduction of technology, and will enable appropriate responses based on the user's emotional state.

[0602] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0603] Step 1:

[0604] The server stores the latest training data (videos, text, quizzes, etc.) in the medical and welfare fields into a database. This includes data collection, classification, and storage. The input is the latest training data, and the output is the data stored in the database. Specifically, it uploads the collected training data to the database in a specified format.

[0605] Step 2:

[0606] Users apply for training through their device. Input is the user's application information (skills, goals, schedule), and output is a confirmation message indicating that the application has been completed. Specifically, the user enters the required information into the application form via the device's user interface and sends it to the server.

[0607] Step 3:

[0608] The server generates an optimal training plan considering the user's skill level, schedule, and emotional state. The input is the user's application information and emotional data, and the output is the optimized training plan. Specifically, it uses emotion recognition technology to acquire the user's emotional data in real time and then uses an algorithm to calculate the optimal plan based on that data.

[0609] Step 4:

[0610] The terminal notifies the user of the generated training plan, and the user begins training based on that plan. The input is the training plan, and the output is the plan notified to the user and real-time feedback. Specifically, it displays the details of the plan on the user interface and reports the progress to the server in real time.

[0611] Step 5:

[0612] The server uses emotion recognition technology to evaluate the user's emotional state in real time. The input is data from the user's face and voice, and the output is the emotion evaluation result. Specifically, it analyzes data collected from the camera and microphone to determine the user's emotional state.

[0613] Step 6:

[0614] The server collects recruitment information and sentiment data of foreign workers into a database and processes recruitment requests from the user's terminal. Inputs are information about foreign workers and user requests, and output is the selection of the most suitable candidates. Specifically, it uses an algorithm to select candidates based on the collected information and provides that information to the user's terminal.

[0615] Step 7:

[0616] The server monitors the use of technology in medical and welfare settings and evaluates it using emotion recognition technology. Inputs are data on the technology being used and emotion data, while output is the evaluation result of the usage status. Specifically, it analyzes usage data and emotion data of the technology tools and monitors user responses in real time.

[0617] Step 8:

[0618] The server proposes technical tools and applications to the user based on their needs, and the user evaluates whether they accept the proposal using a terminal. Inputs are information about the technical tools and applications, as well as user feedback, while outputs are the adopted technology and its usage status. Specifically, it uses a matching algorithm to propose the most suitable technology and collects feedback on it.

[0619] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0620] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0621] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0622] [Second Embodiment]

[0623] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0624] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0625] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0626] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0627] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0628] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0629] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0630] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0631] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0632] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0633] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0634] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0635] This invention is a system that supports the resolution of labor shortages and efficient business operations in the medical and welfare fields. Specific embodiments for implementing this invention are described below.

[0636] 1. Expansion of education and training

[0637] The server stores the latest training data (videos, text, quizzes, etc.) in the medical and welfare fields in its database. Users apply via their terminals, specifying their skill level and desired training program. The server generates an optimal training plan considering the user's skill level and schedule. The generated training plan is notified to the user via their terminal, and the progress of each training session is reported to the server in real time. This provides individually optimized educational plans and efficiently supports skill development.

[0638] As a concrete example, suppose a user wishes to receive online training to improve their caregiving skills. The user submits a training request from their device. The server considers the user's current skill level and available time, and generates a training plan combining video materials on basic caregiving techniques and quiz-style tests, which is then provided to the user. The user proceeds with the training according to this plan, and their device reports their progress to the server.

[0639] 2. Utilization of foreign workers

[0640] The server collects recruitment information from global job sites and agencies into its database. Users submit recruitment requests for foreign workers with specific skills and qualifications from their terminals. Based on the collected data, the server selects the best candidates based on language skills, qualifications, and experience, and provides detailed information to the terminals.

[0641] As a concrete example, suppose a user wants to hire foreign workers as nursing staff. The user sends a recruitment request from their device, specifying language skills and particular qualifications. The server searches for the most suitable candidates based on its database and notifies the user of the profiles and contact information of the selected candidates. The user then conducts interviews based on the provided information and makes a hiring decision.

[0642] 3. Utilization of technology

[0643] The server continuously monitors the usage of technical tools and applications used in healthcare and welfare settings. Based on demand, the server suggests the latest technical tools and applications to users. Users evaluate the suggestions via their terminals and decide whether to accept them. Approved technologies are then deployed to the field by the server, and their usage is monitored in real time.

[0644] For example, if a medical facility requests the automation of nursing records, the server will monitor the current manual record-keeping situation and, based on that information, suggest an appropriate automated record-keeping tool. After the user approves this suggestion on their terminal, the server will install the automated record-keeping tool and monitor its usage and effectiveness.

[0645] 4. Improvement of working conditions

[0646] The server periodically collects and analyzes data on the working environment in medical and welfare facilities. Users can input requests for improvements to the working environment via a terminal. Based on the collected data and user requests, the server proposes efficient improvement measures and notifies the user via the terminal. When work environment improvement proposals are implemented, the progress is reported to the server, ensuring continuous improvement.

[0647] For example, if a request for improvements to reduce staff stress is made at a nursing care facility, the server collects survey and sensor data, and based on the analysis results, proposes specific improvement measures to the user, such as introducing a relaxation space or revising the shift system. The user then checks the proposed measures on their terminal and puts them into action.

[0648] 5. Promoting regional cooperation

[0649] The server integrates and manages information about local healthcare and welfare resources in a database. Users submit requests for collaboration with local resources through their terminals. The server searches for appropriate local resources, generates a specific and actionable collaboration plan, and notifies the terminal. The progress of each collaboration step is reported to the server in real time.

[0650] For example, if an organization providing home care services wishes to expand its operations in collaboration with a local government, the user submits a collaboration request via their terminal. The server searches for appropriate local governments and related organizations based on database information, creates a specific collaboration plan, and provides it to the user. The user then proceeds with the collaboration according to this plan.

[0651] Thus, the present invention provides a comprehensive system for resolving labor shortages in the medical and welfare fields and improving operational efficiency.

[0652] The following describes the processing flow.

[0653] 1. Expansion of education and training

[0654] Processing steps

[0655] Step 1:

[0656] The server stores the latest training data (videos, text, quizzes, etc.) for the medical and welfare fields in a database. Specifically, it uses web crawling and APIs to collect reliable training materials, organizes them, and stores them in the database.

[0657] Step 2:

[0658] Users apply for training through their devices. Specifically, users access a dedicated application or web portal, log in, and then enter their skill level and preferred training dates and times into the application form.

[0659] Step 3:

[0660] The server generates an optimal training plan considering the user's skill level and schedule. Specifically, it uses an AI algorithm to analyze user data and training materials to create a personalized training plan.

[0661] Step 4:

[0662] The device notifies the user of the training plan. Specifically, it sends the user the details of the training plan via push notification or email, and also sends periodic reminders for training sessions.

[0663] Step 5:

[0664] The device reports training progress to the server in real time. Specifically, it has a function that automatically sends progress to the server each time the user completes a training session, and the server records the progress in a database and provides feedback as needed.

[0665] 2. Utilization of foreign workers

[0666] Processing steps

[0667] Step 1:

[0668] The server collects recruitment information for foreign workers into a database. Specifically, it periodically collects the latest job postings from global job sites and recruitment agencies, organizes them, and stores them in the database.

[0669] Step 2:

[0670] The user submits a request to hire foreign workers from their device. Specifically, the user fills out a request form on their device specifying the hiring requirements for workers with particular skills and qualifications, and then submits it.

[0671] Step 3:

[0672] The server selects the most suitable foreign worker based on the request. Specifically, it analyzes the request content and collected recruitment information using a matching algorithm to generate a list of optimal candidates.

[0673] Step 4:

[0674] The device provides the user with information and contact details of the selected personnel. Specifically, it displays the selected candidate's profile, past experience, contact information, and other details on the user's device.

[0675] 3. Utilization of technology

[0676] Processing steps

[0677] Step 1:

[0678] The server monitors the use of technology in medical and welfare settings. Specifically, it periodically collects, integrates, and analyzes usage data for tools and applications used in each setting.

[0679] Step 2:

[0680] The server proposes technical tools and applications to the user based on their needs. Specifically, it selects the most suitable tools and applications based on usage data and information on new technologies in the market, generates a list of suggestions, and notifies the user.

[0681] Step 3:

[0682] The user evaluates whether to accept the proposal using their device. Specifically, the user reviews the proposed technology, judges its usefulness, and sends feedback.

[0683] Step 4:

[0684] The server deploys approved technologies to healthcare and welfare settings and monitors their usage in real time. Specifically, it remotely configures technical tools, continuously collects and analyzes usage data after deployment, and provides support and feedback as needed.

[0685] 4. Improvement of working conditions

[0686] Processing steps

[0687] Step 1:

[0688] The server collects and analyzes working environment data from medical and welfare facilities. Specifically, it acquires data from regular surveys and sensors, integrates it, and analyzes it.

[0689] Step 2:

[0690] Users input requests for improvements to their work environment via their device. Specifically, users enter their complaints and requests for improvements regarding their work environment into a dedicated form and submit it.

[0691] Step 3:

[0692] Based on the data collected by the server and user requests, the system proposes improvement measures. Specifically, it generates concrete improvement plans based on insights gained from data analysis and notifies the user.

[0693] Step 4:

[0694] The device notifies the user of the proposed solutions and provides an implementation plan. Specifically, it provides the user with a guide that explains in detail the steps and schedule for implementing the improvement measures, and has a function to track progress.

[0695] 5. Promoting regional cooperation

[0696] Processing steps

[0697] Step 1:

[0698] The server integrates regional medical and welfare resource information into a database. Specifically, it collects, organizes, and centralizes resource information from medical institutions, welfare facilities, NPO organizations, and other organizations in each region.

[0699] Step 2:

[0700] Users submit requests to connect with local resources using their devices. Specifically, users fill out the required information in the request form on the top page and submit it.

[0701] Step 3:

[0702] The server searches for the most suitable regional resources and generates a collaboration plan. Specifically, it analyzes the request content and resource information using a matching algorithm to create a concrete collaboration plan.

[0703] Step 4:

[0704] The device notifies the user of the integration plan and reports its progress to the server. Specifically, it has the function to notify the user of the details of the integration plan via push notification and to report the execution status of each step to the server in real time.

[0705] Through the specific processing steps described above, the present invention provides a system that helps to alleviate labor shortages in the medical and welfare fields and improves operational efficiency.

[0706] (Example 1)

[0707] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0708] In the medical and welfare sector, numerous challenges exist, including a lack of education and training, difficulties in effectively utilizing foreign workers, and the need to introduce new technologies and improve working conditions on-site. These problems, lacking appropriate solutions, are contributing to a decline in the operational efficiency and service quality of medical and welfare facilities. This invention aims to resolve these challenges and provide a comprehensive system that enables efficient and effective support for medical and welfare operations.

[0709] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0710] In this invention, the server includes means for storing the latest training data in the medical and welfare fields in a database, means for users to apply for training via a terminal, means for generating an optimal training plan considering the user's skill level and schedule, and means for optimizing this generated plan using a generation AI model, means for the terminal to notify the user of the training plan and report the training progress to the server in real time, means for collecting recruitment information for foreign workers in a database, means for users to submit recruitment requests for foreign workers via a terminal, means for selecting and notifying the user of the most suitable personnel based on language skills, qualifications, experience, etc., and means for this selection using a generation AI model, means for the terminal to provide the user with information and contact details of the selected personnel, means for monitoring the status of technology utilization in medical and welfare settings, means for proposing technology tools and applications to the user according to demand, means for the user to evaluate whether to accept the proposal using a terminal, and means for introducing approved technologies and monitoring their usage in real time. This makes it possible to alleviate labor shortages in the medical and welfare fields, improve the efficiency of education and training, effectively utilize foreign workers, appropriately introduce technology, and continuously improve the working environment.

[0711] The "medical and welfare field" refers to a broad range of operations and services related to medical care and welfare.

[0712] "Education and training" refers to training and learning activities aimed at improving skills and knowledge.

[0713] A "server" refers to a computer system that manages and processes data via a network.

[0714] A "database" refers to a structured collection of data that efficiently stores, searches, and manages large amounts of data.

[0715] "User" refers to an individual or group that operates or uses this system.

[0716] "Terminal" refers to a computer or smart device used by a user to access a system.

[0717] A "training plan" refers to a specific educational and training schedule designed to improve the user's skills.

[0718] A "generative AI model" refers to an algorithm that uses artificial intelligence to automatically generate optimal solutions and plans.

[0719] "Foreign workers" refers to people who come from outside the country to work.

[0720] "Recruitment information" refers to information about job seekers and employers, such as job advertisements and recruitment details.

[0721] "Technical tools" refer to technical devices and applications that help improve the efficiency and quality of work.

[0722] "Monitoring" refers to the act of continuously observing and recording specific situations or data.

[0723] "Notification" refers to the act of transmitting information or messages in real time.

[0724] A "progress report" refers to reporting on the progress of a specific task or project.

[0725] "Evaluation" refers to making a value judgment about a particular element or action.

[0726] "Real-time" refers to the processing of data and the transmission of information occurring almost simultaneously.

[0727] A "proposal" refers to the act of recommending a specific action or measure.

[0728] Modes for carrying out the invention

[0729] This invention is a comprehensive system that supports the resolution of labor shortages and the improvement of operational efficiency in the medical and welfare fields. The system of this invention utilizes the latest technology and has functions that enable the expansion of education and training, effective utilization of foreign workers, on-site technology introduction, and continuous improvement of the working environment.

[0730] System Configuration

[0731] 1. Expansion of education and training

[0732] The server stores the latest training data (videos, text, quizzes, etc.) in the medical and welfare fields in its database. This training data is obtained from reliable medical and educational institutions.

[0733] Users use their devices to apply for training programs based on their skill level and desired training program.

[0734] The server uses a generative AI model to consider the user's skill level and schedule to generate an optimal training plan.

[0735] The generated training plan is notified to the user via their device, and the progress of each training session is reported to the server in real time.

[0736] Example: Suppose a user wants online training to improve their caregiving skills. The user submits a training request from their device. The server considers the user's current skill level and available time, and uses a generative AI model to generate a training plan combining video materials on basic caregiving techniques and quiz-style tests, which is then provided to the user. The user follows this plan and the device reports their progress to the server.

[0737] Example of a prompt:

[0738] "Please describe a system to address the labor shortage in the medical and welfare sectors. Include the following five functions: expansion of education and training, utilization of foreign workers, utilization of technology, improvement of working conditions, and promotion of regional cooperation. Please explain each of these, including specific examples."

[0739] 2. Utilization of foreign workers

[0740] The server collects job postings from global job sites and agencies into its database.

[0741] Users submit recruitment requests for foreign workers with specific skills and qualifications from their devices.

[0742] The server uses a generative AI model to collect data and selects the most suitable candidates based on language skills, qualifications, experience, etc., and provides detailed information to the terminal.

[0743] Example: Suppose a user wants to hire foreign workers as nursing staff. The user sends a recruitment request from their device, specifying language skills and certain qualifications as requirements. The server uses a generative AI model to search the database for the most suitable candidates and notifies the user of the selected candidates' profiles and contact information. The user then conducts interviews based on the provided information and makes a hiring decision.

[0744] 3. Utilization of technology

[0745] The server constantly monitors the usage status of technical tools and applications used in medical and welfare settings.

[0746] The server proposes the latest technical tools and applications to users according to their needs.

[0747] Users evaluate proposals using their devices and decide whether to accept them. Approved technologies are deployed to the field by the server, and their usage is monitored in real time.

[0748] Specific example: If a medical facility requests to implement automated nursing record keeping, the server monitors the current manual record-keeping status and suggests an appropriate automated record-keeping tool based on that information. After the user approves this suggestion on their terminal, the server installs the automated record-keeping tool and monitors its usage and effectiveness.

[0749] 4. Improvement of working conditions

[0750] The server periodically collects and analyzes data related to the working environment in medical and welfare facilities.

[0751] Users input their requests for improvements to the work environment using a terminal.

[0752] The server proposes efficient improvement measures based on collected data and user requests, and notifies the user via the terminal. When improvements are implemented, progress is reported to the server, ensuring continuous improvement.

[0753] Specific example: If a request for improvements to reduce staff stress is made at a nursing care facility, the server collects data through surveys and sensors, and based on the analysis results, proposes specific improvement measures to the user, such as introducing a relaxation space or revising the shift system. The user checks the proposed measures on their terminal and puts them into action.

[0754] 5. Promoting regional cooperation

[0755] The server integrates and manages information about local healthcare and welfare resources in a database.

[0756] Users submit requests for integration with local resources through their devices.

[0757] The server searches for appropriate regional resources, generates a specific collaboration plan, and notifies the terminal. The progress of each collaboration step is reported to the server in real time.

[0758] Specific example: If an organization providing home care services wishes to expand its operations in collaboration with a local government, the user submits a collaboration request via their terminal. The server searches for appropriate local governments and related organizations based on database information, creates a specific collaboration plan, and provides it to the user. The user then proceeds with the collaboration according to this plan.

[0759] The system of this invention, by integrating these functions, effectively solves a wide range of problems in the medical and welfare fields, thereby reducing labor shortages and improving operational efficiency.

[0760] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0761] Expansion of education and training

[0762] Step 1:

[0763] The server stores the latest training data (videos, text, quizzes, etc.) for the medical and welfare fields in its database.

[0764] Input: Training data obtained from reliable medical or educational institutions.

[0765] Data processing: Converting data formats and registering them in databases.

[0766] Output: Training data stored in the database.

[0767] Step 2:

[0768] Users use their devices to apply for their skill level and desired training program.

[0769] Input: User's skill level information and desired training program.

[0770] Data processing: Standardize the input data from application forms.

[0771] Output: Training application data sent to the server.

[0772] Specific actions: After logging in, the user enters information into the training application form and clicks the "Submit" button.

[0773] Step 3:

[0774] The server uses a generative AI model to generate a training plan that takes into account the user's skill level and schedule.

[0775] Input: User skill level, schedule, and training data.

[0776] Data processing: Analysis and plan generation using generative AI models.

[0777] Output: Optimal training plan.

[0778] Specific operation: The server inputs the user's skill data and available time into the generated AI model and generates an optimal training plan.

[0779] Step 4:

[0780] The server notifies the user of the generated training plan via the terminal.

[0781] Input: Optimal training plan.

[0782] Data processing: Generating notification messages and sending them to the device.

[0783] Output: The training plan notified to the user's device.

[0784] Specific action: Send a push notification to the user's device and display the training plan.

[0785] Step 5:

[0786] The device reports training progress to the server in real time.

[0787] Input: User training progress information.

[0788] Data processing: Collection and transfer of progress data.

[0789] Output: Training progress data reported to the server.

[0790] Specific operation: When a user updates their progress during a training session, the device sends that information to the server.

[0791] Utilization of foreign workers

[0792] Step 1:

[0793] The server collects job postings from global job sites and agencies into its database.

[0794] Input: Job postings from global job sites and agencies.

[0795] Data processing: Data collection and registration into databases.

[0796] Output: Recruitment information stored in the database.

[0797] Step 2:

[0798] Users submit recruitment requests for foreign workers from their devices.

[0799] Input: Language skills and specific qualifications required by the user.

[0800] Data processing: Standardization and storage of recruitment requests.

[0801] Output: Recruitment request data sent to the server.

[0802] Specific operation: The user enters the hiring criteria and clicks the "Submit Request" button.

[0803] Step 3:

[0804] The server selects the most suitable candidate based on the data collected using a generative AI model.

[0805] Input: Recruitment request data and collected recruitment information.

[0806] Data processing: Candidate selection using generative AI models.

[0807] Output: A list of the best candidates.

[0808] Specific operation: The server executes a database query to search for candidates that match the criteria.

[0809] Step 4:

[0810] The server notifies the terminal of detailed information about the selected candidates.

[0811] Input: A list of the best candidates.

[0812] Data processing: Generating and forwarding notification messages for candidate information.

[0813] Output: Candidate information notified to the user's device.

[0814] Specific operation: Display candidate information on the user's device and provide a link to the details page.

[0815] Utilization of technology

[0816] Step 1:

[0817] The server monitors the usage of technical tools and applications used in medical and welfare settings.

[0818] Input: Data on technology usage from the field.

[0819] Data processing: Data analysis and storage.

[0820] Output: Monitoring report.

[0821] Specific actions: Collect sensor and log data to track usage.

[0822] Step 2:

[0823] The server proposes the latest technical tools and applications to users according to their needs.

[0824] Input: Monitoring data and latest technology data.

[0825] Data processing: Generating proposals based on analysis results.

[0826] Output: Proposal message.

[0827] Specific operation: Analyze usage data and select the appropriate tool using a generated AI model.

[0828] Step 3:

[0829] The user evaluates the proposal and decides whether to accept it.

[0830] Input: Suggestion message.

[0831] Data processing: Evaluation of proposals.

[0832] Output: Evaluation results.

[0833] Specific actions: View the proposal, fill out the evaluation form, and click the "Complete Evaluation" button.

[0834] Step 4:

[0835] The server deploys approved technologies to the field and monitors their usage in real time.

[0836] Input: Approved technical information.

[0837] Data processing: Monitoring the deployment and usage of technical tools.

[0838] Output: Usage report.

[0839] Specific actions: Deploy new technical tools to the field and monitor their usage using sensors and log data.

[0840] Improvement of working conditions

[0841] Step 1:

[0842] The server periodically collects and analyzes data related to the working environment in medical and welfare facilities.

[0843] Input: Surveys and sensor data related to the working environment.

[0844] Data processing: Data collection and analysis.

[0845] Output: Labor environment analysis report.

[0846] Specific operation: Data is collected through surveys and sensors, and then processed using analysis software.

[0847] Step 2:

[0848] Users input their requests for improvements to the work environment using a terminal.

[0849] Input: Improvement request data.

[0850] Data processing: Standardization and storage of requested data.

[0851] Output: Improvement request data sent to the server.

[0852] Specific action: Fill out the improvement request form and click the "Submit" button.

[0853] Step 3:

[0854] The server proposes efficient improvement measures based on the collected data and user requests.

[0855] Input: Work environment data and improvement request data.

[0856] Data processing: Data analysis and proposal generation.

[0857] Output: Suggestion message for improvement.

[0858] Specific operation: Combine user requests and data analysis results to generate improvement measures and notify the device.

[0859] Step 4:

[0860] When proposed improvements to the working environment are implemented, progress is reported to the server, and continuous improvement is ensured.

[0861] Input: Progress data on improvement implementation.

[0862] Data processing: Collection and analysis of progress data.

[0863] Output: Progress report.

[0864] Specific actions: Regularly monitor the effectiveness of implemented improvement measures and generate reports.

[0865] Promoting regional cooperation

[0866] Step 1:

[0867] The server integrates and manages information about local healthcare and welfare resources in a database.

[0868] Input: Local resource information.

[0869] Data processing: Data collection and integration.

[0870] Output: Regional resource information integrated into the database.

[0871] Specific actions: Collect data using the regional resource information API.

[0872] Step 2:

[0873] Users submit requests for integration with local resources through their devices.

[0874] Input: Integration request data.

[0875] Data processing: Standardization and storage of data.

[0876] Output: Integration request data sent to the server.

[0877] Specific action: Fill out the integration request form and click the "Submit" button.

[0878] Step 3:

[0879] The server searches for appropriate regional resources and generates a specific collaboration plan.

[0880] Input: Regional resource information and collaboration request data.

[0881] Data processing: Data analysis and plan generation.

[0882] Output: Integration plan.

[0883] Specific operation: Analyzes user requests, queries the database, and generates integration plans.

[0884] Step 4:

[0885] The server notifies the terminal of the generated integration plan.

[0886] Input: Integration plan.

[0887] Data processing: Generating and forwarding plan notification messages.

[0888] Output: The integration plan notified to the user's device.

[0889] Specific action: A notification about the integration plan is sent to the user's device, and details are displayed.

[0890] Step 5:

[0891] The progress of each integration step is reported to the server.

[0892] Input: Progress data for the integration steps.

[0893] Data processing: Collection and integration of progress data.

[0894] Output: Progress report.

[0895] Specific actions: Monitor the progress of the integration and update the progress status on the server.

[0896] Through the procedures outlined above, this system provides comprehensive support to address labor shortages in the medical and welfare sectors and improve operational efficiency.

[0897] (Application Example 1)

[0898] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0899] Labor shortages and operational inefficiencies in the healthcare and welfare sectors are serious challenges. To address these issues, improved education and training, effective utilization of foreign workers, and the introduction of cutting-edge technologies are essential. In particular, similar problems exist not only in the healthcare and welfare sectors but also in manufacturing sites such as factories, where a lack of knowledge and skills regarding robot operation and maintenance is a bottleneck. To solve this, a comprehensive education system and technical support system are required.

[0900] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0901] In this invention, the server includes means for storing the latest training data related to the operation of medical and welfare fields and factory robots in a database, means for users to apply for training via a terminal, means for generating an optimal training plan considering the user's skill level and schedule, means for notifying users through various training and reporting their progress in real time, means for providing videos and materials on factory robot operation procedures, means for generating and notifying robot maintenance schedules, means for monitoring the robot's status and diagnosing errors, and means for users to utilize training modes for skill improvement. This enables the efficient provision of technical education and training in both medical and welfare fields and factory settings, improving the efficiency of operation and maintenance, and solving the problems of labor shortages and operational inefficiencies.

[0902] The "medical and welfare field" refers to all fields that provide medical and welfare services.

[0903] "Training data" refers to digital information such as videos, texts, and quizzes used for educational and training purposes.

[0904] A "database" refers to a system for structuring, storing, and managing training data and other information.

[0905] "Terminal" refers to devices such as computers, smartphones, and tablets that users use to access servers.

[0906] "Skill level" refers to an indicator that evaluates the user's current level of knowledge and proficiency in skills.

[0907] A "training plan" refers to an educational and training program customized based on the user's skill level and schedule.

[0908] "Real-time" refers to processing and responding instantly without delay.

[0909] "Factory robots" refer to automated mechanical devices used in factories and manufacturing sites.

[0910] "Operation procedure videos" refer to video content created to demonstrate how to use and operate a robot.

[0911] "Documents" refers to papers and manuals created to explain operating procedures and maintenance details.

[0912] A "maintenance schedule" refers to a timetable or plan for systematically performing maintenance on a robot.

[0913] "Monitoring" refers to the act of continuously monitoring the status of a system or device.

[0914] "Error diagnosis" refers to the process of detecting abnormalities that occur in devices or systems, and identifying and analyzing their causes.

[0915] "Training Mode" refers to special educational and training features that users can use to improve their skills.

[0916] "Technical tools" refer to various technical devices and software used to efficiently perform specific tasks.

[0917] An "application" refers to a software program with a specific function or purpose.

[0918] This invention is a system for streamlining the operation and maintenance of robots in the medical and welfare fields and in factories. Specific embodiments for carrying out this invention are described below.

[0919] Program generation:

[0920] The system consists of components applicable to both the medical and welfare fields and factory robotics. This system includes the following:

[0921] 1. The server stores the latest training data related to the operation and maintenance of medical and welfare fields and factory robots in its database.

[0922] 2. Users apply for training through their device.

[0923] 3. The server generates an optimal training plan, taking into account the user's skill level and schedule.

[0924] 4. The device notifies the user of the training plan and reports the training progress in real time.

[0925] 5. The server provides operating procedure videos and materials for the factory robots.

[0926] 6. The server generates and notifies the robot of its maintenance schedule.

[0927] 7. The server monitors the robot's status and diagnoses errors.

[0928] 8. Users utilize training modes to improve their skills.

[0929] Hardware and software to be used:

[0930] Hardware: Smartphones, tablets, smart glasses, computers

[0931] Software: Database management systems (e.g., SQLite), programming languages ​​(e.g., Python)

[0932] Data processing and data calculations:

[0933] Data processing: Training data and operating procedure documents are stored in a database, and appropriate data is provided in response to user requests.

[0934] Data processing: Generate customized training plans based on the user's skill level and schedule, and monitor progress in real time. Generate robot maintenance schedules and analyze error logs.

[0935] Specific example:

[0936] For example, if a nursing staff member working at a medical facility wants to learn how to operate new medical equipment, they can submit a training request via a terminal. The server then considers the staff member's skill level and schedule to generate an optimal training plan. This plan includes video materials and quiz-style tests, which the nursing staff member follows as they progress through the training. Similarly, data regarding the operation and maintenance of robots used in factories is managed in the same way, allowing workers to receive efficient training.

[0937] Example of a prompt:

[0938] Design an application that provides basic instructional videos, maintenance procedures, and error logs for new engineers to operate factory robots.

[0939] It also includes real-time support functions to address labor shortages and improve operational efficiency.

[0940] In this way, the present invention enables the efficient provision of technical education and training in both medical and welfare settings, as well as in factory settings, thereby solving the problems of labor shortages and operational inefficiencies.

[0941] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0942] Step 1:

[0943] The server stores the latest training data related to the operation and maintenance of medical and welfare fields and factory robots in its database.

[0944] Input: Training data (videos, text, quizzes, etc.)

[0945] Data processing: Save training data to a database categorized by type.

[0946] Output: Training data stored in the database

[0947] Specific operation: The administrator uploads the latest training data, and the server categorizes and stores it in the database.

[0948] Step 2:

[0949] Users apply for training through their device.

[0950] Input: User's skill level and desired training content

[0951] Data processing: Receive user application details and save them to the database.

[0952] Output: User application data

[0953] Specific operation: The user uses the application to input their skill level and desired training content, and that data is sent to the server.

[0954] Step 3:

[0955] The server generates an optimal training plan, taking into account the user's skill level and schedule.

[0956] Input: User's skill level and schedule, training data stored in the database

[0957] Data processing: Select an appropriate training program based on the user's skill level and available time.

[0958] Output: Individually optimized training plan

[0959] Specific operation: The server matches training data in the database with user information to generate the optimal training plan.

[0960] Step 4:

[0961] The device notifies the user of the training plan and reports on training progress in real time.

[0962] Input: Training plan, user progress data

[0963] Data processing: Notification of training plans and real-time reporting of progress data.

[0964] Output: User notifications, progress report data

[0965] Specific operation: As the user checks the training plan on their device and progresses through the training, their progress is automatically reported to the server.

[0966] Step 5:

[0967] The server provides operating procedure videos and documents for factory robots.

[0968] Input: Operation procedure data (video, text)

[0969] Data processing: Providing operation procedure data to users in an appropriate format.

[0970] Output: User instruction videos and documentation

[0971] Specific operation: Video tutorials and materials necessary for operating the robot are delivered to the user's device.

[0972] Step 6:

[0973] The server generates and notifies users of the robot's maintenance schedule.

[0974] Input: Robot operation data, recommended maintenance cycle

[0975] Data calculation: Calculate maintenance requirements and create a schedule.

[0976] Output: Maintenance Schedule

[0977] Specific operation: Based on the robot's usage frequency and status, the system automatically generates a schedule for the next maintenance and notifies the user.

[0978] Step 7:

[0979] The server monitors the robot's status and diagnoses errors.

[0980] Input: Real-time robot operation data, error logs

[0981] Data processing: Log data analysis and error diagnosis

[0982] Output: Error report and suggested solutions

[0983] Specific operation: Based on the robot's sensors and log data, it monitors its status in real time, immediately diagnoses any abnormalities, and reports them to the user.

[0984] Step 8:

[0985] Users can utilize the training mode to improve their skills.

[0986] Input: Training mode selection, current skill level

[0987] Data Processing: Customize training modes according to skill level.

[0988] Output: Training content tailored to the user

[0989] Specific operation: Users can select a training mode within the application and receive training tailored to their skill level.

[0990] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0991] This invention provides a system that combines an emotion engine that recognizes user emotions in order to alleviate labor shortages and support efficient operations in the medical and welfare fields. This system is implemented in the following manner.

[0992] 1. Expansion of education and training

[0993] The server stores the latest training data (videos, text, quizzes, etc.) in the medical and welfare fields in its database. The server also includes an emotion engine that recognizes user emotions. When a user applies for training through their device, the emotion engine evaluates the user's emotional state in real time through facial recognition and voice analysis. This emotion data, along with the user's skill level and schedule, is used to generate an optimal training plan.

[0994] The server analyzes emotional data collected by the emotion engine and, if the user is feeling stressed or unmotivated, provides training content and feedback tailored to their current emotions. The device then notifies the user of a training plan based on this analysis and reports its progress to the server in real time.

[0995] For example, if a user requests online training to improve their caregiving skills, the emotion engine assesses their stress level based on their facial expression and tone of voice when they log in and submit a training request. Based on this information, the server generates a training plan that includes relaxing video materials and interactive quizzes, which are then delivered to the user via their device.

[0996] 2. Utilization of foreign workers

[0997] The server collects recruitment information for foreign workers into a database and uses an emotion engine to evaluate the emotional state of candidates during interviews. Users submit recruitment requests for foreign workers from their terminals, and the server selects the most suitable candidates based on language skills, qualifications, experience, and emotional state. The terminal then provides the user with information and contact details of the selected candidates.

[0998] As a concrete example, when a user hires foreign workers as nursing staff, the emotional engine evaluates the candidate's stress level and communication skills during the interview, helping to select a suitable candidate. The user can then review this data via their device and hire the most suitable personnel.

[0999] 3. Utilization of technology

[1000] The server monitors the usage of technology tools and applications used in healthcare and welfare settings and uses an emotion engine to evaluate users' emotions towards the use of these technologies. Based on this data, the server suggests technology tools and applications to users according to their needs. Users evaluate the suggestions via their terminals, and approved technologies are deployed to the field by the server, with their usage and emotion data monitored in real time.

[1001] As a concrete example, if a user is unfamiliar with a new nursing record application introduced at a medical facility, the emotion engine will detect the user's confusion or stress, and the server will suggest a simpler interface or provide additional training. This information is then communicated to the user via the terminal, aiming to improve user satisfaction.

[1002] 4. Improvement of working conditions

[1003] The server collects and analyzes work environment and emotional data from medical and welfare facilities. Users input requests for improvements to the work environment via a terminal, and their emotional state is recorded in real time. Based on the collected data and the user's emotions, the server proposes specific improvement measures and notifies the user via the terminal. Progress during implementation is reported to the server, and feedback is provided as needed.

[1004] For example, if a staff member at a nursing home is experiencing stress, the emotion engine detects this, and the server suggests measures to reduce stress, such as expanding relaxation spaces or changing shifts. The user then reviews the suggestions on their device and takes action.

[1005] 5. Promoting regional cooperation

[1006] The server integrates and manages information and emotional data about local healthcare and welfare resources in a database. Users submit requests for collaboration with local resources through their terminals, and their emotional state at the time is also recorded. The server generates appropriate local resources and specific collaboration plans, and adjusts the timing and content of the collaboration plan proposals to the user based on the emotional data. The user is notified of the proposals through their terminal, and the progress of each collaboration step is reported to the server in real time.

[1007] As a concrete example, when an organization providing home care services expands its operations in collaboration with a local government, the user's emotion engine monitors their emotional state in real time during the collaboration negotiations, and the server proposes approaches to reduce the user's stress and anxiety. The user can check this from their terminal, and is supported in ensuring the smooth progress of the collaboration.

[1008] Thus, the present invention provides a system that, by combining an emotion engine, evaluates the user's emotional state in real time and enables more effective and user-friendly implementation of processes in the medical and welfare fields, including education, utilization of foreign workers, introduction of technology, improvement of the working environment, and regional collaboration.

[1009] The following describes the processing flow.

[1010] 1. Expansion of education and training

[1011] Processing steps

[1012] Step 1:

[1013] The server stores the latest training data (videos, text, quizzes, etc.) for the medical and welfare fields in a database. Specifically, it uses web crawling and APIs to collect reliable training materials, organizes them, and stores them in the database.

[1014] Step 2:

[1015] Users apply for training through their devices. Specifically, users access a dedicated application or web portal, log in, and then enter their skill level and preferred training dates and times into the application form.

[1016] Step 3:

[1017] The server uses an emotion engine to recognize user emotions and evaluate the user's emotional state. Specifically, when a user submits a training request, the system analyzes their facial expressions and voice tone in real time via the camera and microphone.

[1018] Step 4:

[1019] The server generates an optimal training plan by considering the user's skill level, schedule, and sentiment data. Specifically, it uses AI algorithms to analyze this data and create a personalized training plan.

[1020] Step 5:

[1021] The device notifies the user of the training plan. Specifically, it sends the user the details of the training plan via push notification or email, and also sends periodic reminders for training sessions.

[1022] Step 6:

[1023] The device reports training progress and user sentiment data to the server in real time. Specifically, it has a function that automatically sends progress and sentiment status to the server each time the user completes a training session.

[1024] 2. Utilization of foreign workers

[1025] Processing steps

[1026] Step 1:

[1027] The server collects recruitment information for foreign workers into a database. Specifically, it periodically collects the latest job postings from global job sites and recruitment agencies, organizes them, and stores them in the database.

[1028] Step 2:

[1029] The user submits a request to hire foreign workers from their device. Specifically, the user fills out a request form on their device specifying the hiring requirements for workers with particular skills and qualifications, and then submits it.

[1030] Step 3:

[1031] The server selects the most suitable foreign worker based on the request. Specifically, it analyzes the request content and collected recruitment information using a matching algorithm to generate a list of optimal candidates.

[1032] Step 4:

[1033] The server uses an emotion engine to evaluate the candidate's emotional state during the interview. Specifically, it collects and analyzes the candidate's emotional data through the camera and microphone during the interview.

[1034] Step 5:

[1035] The device provides the user with information and contact details of the selected personnel. Specifically, it displays the selected candidate's profile, past experience, contact information, and other details on the user's device.

[1036] 3. Utilization of technology

[1037] Processing steps

[1038] Step 1:

[1039] The server monitors the use of technology in medical and welfare settings. Specifically, it periodically collects, integrates, and analyzes usage data for tools and applications used in each setting.

[1040] Step 2:

[1041] The server uses an emotion engine to evaluate the user's emotional state when using technology. Specifically, it collects and analyzes emotional data through the camera and microphone when the user uses tools or applications.

[1042] Step 3:

[1043] The server suggests technology tools and applications to users based on their technology usage and sentiment data, tailored to their needs. Specifically, it uses an AI algorithm to generate a list of optimal tools and applications and notifies the user.

[1044] Step 4:

[1045] The user evaluates whether to accept the proposal using their device. Specifically, the user reviews the proposed technology, judges its usefulness, and sends feedback.

[1046] Step 5:

[1047] The server deploys approved technologies to healthcare and welfare settings, monitoring usage and emotional data in real time. Specifically, it remotely configures technical tools, continuously collects and analyzes usage and emotional data after deployment, and provides support and feedback as needed.

[1048] 4. Improvement of working conditions

[1049] Processing steps

[1050] Step 1:

[1051] The server collects and analyzes work environment and emotional data from medical and welfare facilities. Specifically, it acquires and analyzes data from periodic surveys, sensors, and real-time emotional data generated by an emotional analysis engine.

[1052] Step 2:

[1053] Users input requests for improvements to their work environment via their device. Specifically, users enter their complaints and requests for improvements regarding their work environment into a dedicated form and submit it.

[1054] Step 3:

[1055] The system proposes improvement measures based on data collected by the server and user sentiment. Specifically, it generates concrete improvement suggestions based on insights gained from data analysis and notifies the user.

[1056] Step 4:

[1057] The device notifies the user of the proposed solutions and provides an implementation plan. Specifically, it provides the user with a guide that explains in detail the steps and schedule for implementing the improvement measures, and has a function to track progress.

[1058] 5. Promoting regional cooperation

[1059] Processing steps

[1060] Step 1:

[1061] The server integrates regional medical and welfare resource information and sentiment data into a database. Specifically, it collects, organizes, and centralizes resource information and sentiment data from medical institutions, welfare facilities, NPO organizations, and other organizations in each region.

[1062] Step 2:

[1063] Users submit requests to connect with local resources using their devices. Specifically, users fill out the necessary information in a request form from the top page, and their emotional state at that time is recorded in real time.

[1064] Step 3:

[1065] The server searches for the most suitable regional resources and generates a collaboration plan. Specifically, it analyzes the request content, resource information, and sentiment data using a matching algorithm to create a concrete collaboration plan.

[1066] Step 4:

[1067] The device notifies the user of the integration plan and reports progress and sentiment data to the server. Specifically, it notifies the user of the details of the integration plan via push notification and has the function to monitor the sentiment state during execution and report the progress of each step to the server in real time.

[1068] Through the specific processing steps described above, the present invention provides a system that helps alleviate labor shortages in the medical and welfare fields and improves operational efficiency. By using an emotion engine, the user's emotional state can be evaluated in real time, enabling the provision of more effective and user-friendly support.

[1069] (Example 2)

[1070] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[1071] In the healthcare and welfare sector, challenges include improving operational efficiency and reducing the psychological burden on employees in areas such as education and training, the utilization of foreign workers, and the introduction of new technologies. Conventional systems have made it difficult to assess users' emotional states in real time and respond individually, leading to decreased operational efficiency and increased employee stress.

[1072] The identification processing performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for storing the latest training data in the medical and welfare field in a database, means for users to apply for training through a terminal, means for generating an optimal training plan considering the user's skill level and schedule, means for recognizing and collecting the user's emotional state, means for analyzing the emotional data and adjusting the training content based on the user's emotional state, and means for the terminal to notify the user of the training plan and report the progress of the training in real time. This enables flexible and individualized responses in accordance with the user's emotional state.

[1073] The "medical and welfare field" refers to all activities in the medical and welfare industries, including patient treatment and the provision of welfare services.

[1074] "Training data" refers to learning resources such as videos, text, and quizzes that are stored on a server for educational and training purposes.

[1075] A "database" refers to a system for efficiently storing, searching, and managing information.

[1076] "Users" refer to employees and related parties in the medical and welfare fields who use this system.

[1077] "Terminal" refers to the computer or mobile device that a user uses to access this system.

[1078] An "emotion engine" refers to technology that recognizes, collects, and analyzes a user's emotional state.

[1079] "Emotional data" refers to data about the user's emotional state collected by the emotion engine.

[1080] "Skill level" refers to the user's level of proficiency in skills and knowledge.

[1081] A "training plan" refers to the optimal learning and training program generated by the server based on the user's skill level and emotional state.

[1082] "Foreign workers" refers to workers of foreign origin who are employed in the medical and welfare fields.

[1083] "Recruitment information" refers to data including foreign workers' language skills, qualifications, and experience.

[1084] "Technical tools and applications" refer to software and systems used in medical and welfare settings.

[1085] This invention relates to a system that supports the expansion of education and training, the utilization of foreign workers, and the introduction of technology in the medical and welfare fields. This system can improve work efficiency and reduce the psychological burden on employees by recognizing the user's emotional state in real time and providing optimal support based on that recognition.

[1086] Expansion of education and training

[1087] The server collects the latest training data in the medical and welfare fields and stores it in a database. This training data includes videos, text, quizzes, and more. It also features an emotion engine that uses facial recognition technology and voice analysis to evaluate the user's emotional state in real time.

[1088] When a user submits a training request using their device, the emotion engine analyzes the user's facial expression and tone of voice to collect emotional data. The server then generates an optimal training plan based on this emotional data, the user's skill level, and their schedule information. The generated training plan is tailored to the user's emotional state.

[1089] For example, if a user requests training to improve their caregiving skills, the device's camera and microphone activate, and the emotion engine collects emotional data. The server then provides a training plan that includes relaxing video materials and interactive quizzes. This allows the user to learn without feeling stressed.

[1090] Example of a prompt: "Please propose a relaxing training plan to improve caregiving skills."

[1091] Utilization of foreign workers

[1092] The server collects recruitment information on foreign workers (language skills, qualifications, experience) and stores it in a database. When a user submits a recruitment request for a foreign worker from their terminal, the server uses an emotion engine to evaluate the candidate's emotional state and analyzes their stress level and communication skills.

[1093] As a concrete example, when a user hires foreign workers as nursing staff, the emotion engine collects candidate emotional data during the interview, and the server selects the appropriate candidate. Once the best candidate is selected, their information and contact details are provided to the user via their device.

[1094] Example prompt: "Please tell me the criteria for selecting foreign workers who are suitable as nursing staff."

[1095] Utilization of technology

[1096] The server monitors the usage of technical tools and applications used in medical and welfare settings and evaluates the user's emotional state using an emotion engine. Based on the collected emotional data, the server suggests the most suitable technical tools and applications for the user.

[1097] As a concrete example, regarding a newly introduced nursing record app, if a user experiences confusion or stress while using it, the emotion engine detects this, and the server suggests a simpler interface or provides additional training. This makes it possible to improve user satisfaction.

[1098] Example prompt: "Please suggest ways to reduce the stress users experience with the new nursing record app."

[1099] Improvement of working conditions

[1100] The server can collect and analyze data on the working environment and emotional state of healthcare and welfare facilities. Users input requests for improvements to the working environment via a terminal, and their emotional state is recorded in real time. Based on the collected data, the server proposes specific improvement measures and notifies the user through the terminal.

[1101] For example, if staff at a nursing home are experiencing stress, the emotion engine detects this, and the server suggests measures to reduce stress (such as expanding relaxation spaces or changing shifts). This can reduce the psychological burden on staff and improve work efficiency.

[1102] Promoting regional cooperation

[1103] The server integrates and manages information and emotional data about local healthcare and welfare resources in a database. When a user submits a request to connect with local resources through their terminal, their emotional state is also recorded. The server generates appropriate local resources and specific connection plans, and optimizes suggestions for the user based on the emotional data.

[1104] As a concrete example, when an organization providing home care services collaborates with a local government, the emotion engine monitors the user's emotional state during negotiations, and the server proposes approaches to reduce the user's stress and anxiety. This helps to facilitate smooth collaboration.

[1105] Example prompt: "Please tell me about stress reduction measures for organizations providing home care services when collaborating with local governments."

[1106] Thus, the present invention is a system that effectively supports various processes in the medical and welfare fields by utilizing an emotion engine and recognizing the user's emotional state in real time.

[1107] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1108] Expansion of education and training

[1109] Step 1:

[1110] The server collects the latest training data in the medical and welfare fields and stores it in a database. This training data includes videos, text, quizzes, and more. Input training data is collected from diverse sources and neatly stored in the database. The output is a set of the latest available training data.

[1111] Step 2:

[1112] The user submits a training application using a terminal. The user's login information and training application details are sent as input. Upon receiving this information, the terminal activates its camera and microphone to send facial expression and voice tone to the emotion engine. The output is the transmission of audio and video data to the emotion engine.

[1113] Step 3:

[1114] The server analyzes the emotional data received from the emotion engine. Emotional data, user skill level, and schedule information are obtained as input. Data calculations are used to evaluate the user's stress level and motivation. Based on the results, an optimal training plan is generated. A personalized training plan is generated as output.

[1115] Step 4:

[1116] The server sends the generated training plan to the terminal. The generated training plan is the input, and the notification sent to the terminal is the output. The terminal notifies the user and simultaneously activates a system that reports the training progress to the server in real time.

[1117] Specific operation: For example, when a user applies for training to improve their caregiving skills, the device's camera and microphone automatically activate, and the emotion engine analyzes the user's facial expression and voice tone in real time. Based on the data collected in this way, the server generates a training plan that includes relaxing materials and interactive quizzes, and sends it to the device.

[1118] Utilization of foreign workers

[1119] Step 1:

[1120] The server collects recruitment information for foreign workers and stores it in a database. Inputs include information such as each candidate's language skills, qualifications, and experience. The output is a database of usable recruitment information.

[1121] Step 2:

[1122] The user submits a recruitment request for foreign workers from their terminal. The request details and the user's preferences are sent to the terminal as input. The output is the recruitment request information sent to the server.

[1123] Step 3:

[1124] The server uses an emotion engine to evaluate the candidate's emotional state during the interview. The candidate's facial expression and voice data are sent to the emotion engine as input, and analysis is performed. Output data includes evaluations of the candidate's stress level and communication skills.

[1125] Step 4:

[1126] The server integrates collected sentiment data with candidates' language skills, qualifications, and experience to select the most suitable candidates. The selected candidates' information is generated as output and notified to the terminal. The terminal then provides this information to the user.

[1127] Specific operation: For example, when a user hires a foreign worker as nursing staff, the device's camera and microphone are activated during the interview, and an emotion engine analyzes stress levels and communication skills. Based on the results, the server selects the most suitable candidate and sends the information to the device.

[1128] Utilization of technology

[1129] Step 1:

[1130] The server monitors the usage of technical tools and applications used in medical and welfare settings. The input is usage data for each tool and application. Data is then analyzed to determine usage frequency and effectiveness. The output is aggregated usage data.

[1131] Step 2:

[1132] The server uses an emotion engine to evaluate the user's emotional state regarding the use of technical tools. Real-time emotional data from the user is sent as input. The output is emotional evaluation data from the emotion engine.

[1133] Step 3:

[1134] The server suggests the most suitable technical tools and applications to the user based on the collected sentiment data. Sentiment data and usage data are used as input. The output is personalized suggestions.

[1135] Step 4:

[1136] Through the terminal, the user evaluates the proposal and notifies the server whether to accept or reject it. User feedback on the proposal is collected as input. The output is the server's approval or rejection data of the proposal.

[1137] Specific operation: For example, if a user feels confused or stressed by a new nursing record app, the emotion engine detects this, and the server suggests an alternative app with a simpler interface or additional training. If the user accepts this, their usage and emotional data are monitored in real time.

[1138] Improvement of working conditions

[1139] Step 1:

[1140] The server collects work environment and emotional data from healthcare and welfare facilities. Environmental sensor data and user emotional data are provided as input. The output is a report on the state of the work environment.

[1141] Step 2:

[1142] Users input requests for improvements to their work environment via a terminal, and real-time sentiment data is collected along with these requests. The input consists of user feedback and sentiment data. The output consists of request data and sentiment data sent to the server.

[1143] Step 3:

[1144] The server proposes specific improvement measures based on collected work environment data and the user's emotional state. Past improvement data and current emotional data are used as input. The output is improvement suggestions notified to the user.

[1145] Step 4:

[1146] Through the terminal, the user reviews the proposed improvements and sends their feedback to the server. The input is the user's approval or rejection feedback. The output is a list of improvements to be implemented on the server side.

[1147] Specific operation: For example, if a staff member at a nursing home is experiencing stress, the emotion engine detects this, and the server suggests measures such as expanding relaxation spaces or changing shifts. The user reviews and approves these suggestions on their terminal, and they are then implemented.

[1148] Promoting regional cooperation

[1149] Step 1:

[1150] The server integrates and manages information and sentiment data related to local healthcare and welfare resources into a database. Local resource information and sentiment data are collected as input. The output is the integrated and managed database.

[1151] Step 2:

[1152] Users submit requests to connect with local resources through their devices. Their emotional state is also recorded during this process. The input consists of the request content and emotional data. The output is the request data on the server side.

[1153] Step 3:

[1154] The server generates appropriate local resources and specific collaboration plans based on collected sentiment data. Sentiment data and local resource data are used as input. The output is a collaboration plan proposal for the user.

[1155] Step 4:

[1156] The terminal notifies the user of the integration plan details and reports the progress of each integration step to the server in real time. Inputs include user feedback and progress data. Outputs include feedback and adjustments to the proposed content based on the progress.

[1157] Specific operation: For example, when an organization providing home care services collaborates with a local government, the emotion engine monitors the emotional state during negotiations, and the server suggests measures to reduce stress and anxiety. The user can then view this on their device and take appropriate action to help the collaboration proceed smoothly.

[1158] (Application Example 2)

[1159] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[1160] This invention relates to resolving labor shortages in the medical and welfare fields, improving operational efficiency, and providing a more appropriate work support system that takes into account the emotional state of workers. In particular, it aims to improve the working environment and enhance the quality of education by recognizing the emotional state of workers in real time and reflecting it in training and work support plans.

[1161] In Application Example 2, the specific processing performed by the specific processing unit 290 of the data processing device 12 is realized by the following means. In this invention, the server includes means for storing the latest training data in the medical and welfare field in a database, means for users to apply for training through a terminal, means for generating an optimal training plan considering the user's skill level, schedule, and emotional state, means for the terminal to notify the user of the training plan and report the progress of the training in real time, and means for evaluating the user's emotional state in real time using emotion recognition technology. This makes it possible to provide optimal training and work support that takes into account the user's emotional state.

[1162] "Education and training in the medical and welfare fields" refers to training and learning activities that provide the knowledge and skills necessary for medical and welfare-related jobs, and aim to improve employee capabilities and streamline operations.

[1163] "Training data" refers to information such as videos, texts, and quizzes used in educational and training programs, and is based on the latest medical and welfare technologies and knowledge.

[1164] "Terminal" refers to hardware devices such as computers, smartphones, and tablets that users operate.

[1165] "Training application" refers to the process of completing the necessary procedures and registrations required for a user to receive training.

[1166] A "training plan" refers to a learning plan that combines the most suitable educational content and methods, taking into account each user's individual skill level, schedule, and emotional state.

[1167] "Reporting progress in real time" refers to the process of continuously monitoring the progress of training or work and reporting it immediately.

[1168] "Emotion recognition technology" refers to technology that uses techniques such as facial recognition and voice analysis to evaluate a user's emotional state in real time.

[1169] "Foreign workers" refers to foreign nationals employed to work in medical and welfare facilities within Japan.

[1170] A "recruitment request" refers to an application or request made by a user to recruit foreign workers.

[1171] "Language skills, qualifications, and experience" refers to the language proficiency, professional qualifications, and past work experience possessed by foreign workers.

[1172] This invention provides a system that combines an emotion engine that recognizes user emotions in order to help alleviate labor shortages and improve operational efficiency in the medical and welfare fields. This system is implemented by the following specific method.

[1173] 1. System Configuration

[1174] The server stores the latest training data (videos, text, quizzes, etc.) in the medical and welfare fields in its database. Users apply for training through their terminals. The server generates an optimal training plan considering the user's skill level, schedule, and emotional state. The generated training plan is notified to the user through their terminal, and training progress is reported in real time.

[1175] 2. Use of emotion recognition technology

[1176] The server uses emotion recognition technology to evaluate the user's emotional state in real time. This technology uses a camera and microphone to analyze the user's facial expression and voice tone, acquiring emotional data such as whether the user is stressed or relaxed.

[1177] 3. Utilization of foreign workers

[1178] In the recruitment of foreign workers, the server collects recruitment information and the worker's emotional data into a database. Users submit recruitment requests for foreign workers from their terminals. The server selects the most suitable candidates based on language skills, qualifications, experience, and emotional status, and provides information and contact details of the selected candidates through the terminals.

[1179] 4. Introduction of technology

[1180] The server monitors the use of technology in healthcare and welfare settings and uses emotion recognition technology to evaluate users' feelings towards using that technology. The server suggests technology tools and applications to users according to their needs and evaluates whether users accept the suggestions using their devices. Once a technology is approved for use, the server deploys it to the field, and its usage and emotional data are monitored in real time.

[1181] The following scenarios are possible as specific examples of its use.

[1182] If some users are unfamiliar with a new nursing record application implemented at a medical facility, the emotion recognition engine detects their confusion or stress. The server then suggests a simpler interface and provides additional training. This information is communicated to the user via their device to improve user satisfaction.

[1183] The following are examples of prompt statements.

[1184] When writing feedback on a scenario where an operator is experiencing high stress while learning to operate a new machine, please generate a prompt using the following format:

[1185] 1. An emotion engine that recognizes the worker's emotions detects high stress.

[1186] 2. The system automatically suggests breaks and notifies workers with feedback.

[1187] The hardware used includes a camera, microphone, and terminal, while the software used includes OpenCV, Keras / TensorFlow, and SpeechRecognition (a Python library).

[1188] Such a system will streamline various processes related to education in the medical and welfare fields, recruitment of foreign workers, and introduction of technology, and will enable appropriate responses based on the user's emotional state.

[1189] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1190] Step 1:

[1191] The server stores the latest training data (videos, text, quizzes, etc.) in the medical and welfare fields into a database. This includes data collection, classification, and storage. The input is the latest training data, and the output is the data stored in the database. Specifically, it uploads the collected training data to the database in a specified format.

[1192] Step 2:

[1193] Users apply for training through their device. Input is the user's application information (skills, goals, schedule), and output is a confirmation message indicating that the application has been completed. Specifically, the user enters the required information into the application form via the device's user interface and sends it to the server.

[1194] Step 3:

[1195] The server generates an optimal training plan considering the user's skill level, schedule, and emotional state. The input is the user's application information and emotional data, and the output is the optimized training plan. Specifically, it uses emotion recognition technology to acquire the user's emotional data in real time and then uses an algorithm to calculate the optimal plan based on that data.

[1196] Step 4:

[1197] The terminal notifies the user of the generated training plan, and the user begins training based on that plan. The input is the training plan, and the output is the plan notified to the user and real-time feedback. Specifically, it displays the details of the plan on the user interface and reports the progress to the server in real time.

[1198] Step 5:

[1199] The server uses emotion recognition technology to evaluate the user's emotional state in real time. The input is data from the user's face and voice, and the output is the emotion evaluation result. Specifically, it analyzes data collected from the camera and microphone to determine the user's emotional state.

[1200] Step 6:

[1201] The server collects recruitment information and sentiment data of foreign workers into a database and processes recruitment requests from the user's terminal. Inputs are information about foreign workers and user requests, and output is the selection of the most suitable candidates. Specifically, it uses an algorithm to select candidates based on the collected information and provides that information to the user's terminal.

[1202] Step 7:

[1203] The server monitors the use of technology in medical and welfare settings and evaluates it using emotion recognition technology. Inputs are data on the technology being used and emotion data, while output is the evaluation result of the usage status. Specifically, it analyzes usage data and emotion data of the technology tools and monitors user responses in real time.

[1204] Step 8:

[1205] The server proposes technical tools and applications to the user based on their needs, and the user evaluates whether they accept the proposal using a terminal. Inputs are information about the technical tools and applications, as well as user feedback, while outputs are the adopted technology and its usage status. Specifically, it uses a matching algorithm to propose the most suitable technology and collects feedback on it.

[1206] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1207] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1208] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[1209] [Third Embodiment]

[1210] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[1211] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1212] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1213] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[1214] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1215] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1216] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1217] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1218] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1219] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1220] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1221] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[1222] This invention is a system that supports the resolution of labor shortages and efficient business operations in the medical and welfare fields. Specific embodiments for implementing this invention are described below.

[1223] 1. Expansion of education and training

[1224] The server stores the latest training data (videos, text, quizzes, etc.) in the medical and welfare fields in its database. Users apply via their terminals, specifying their skill level and desired training program. The server generates an optimal training plan considering the user's skill level and schedule. The generated training plan is notified to the user via their terminal, and the progress of each training session is reported to the server in real time. This provides individually optimized educational plans and efficiently supports skill development.

[1225] As a concrete example, suppose a user wishes to receive online training to improve their caregiving skills. The user submits a training request from their device. The server considers the user's current skill level and available time, and generates a training plan combining video materials on basic caregiving techniques and quiz-style tests, which is then provided to the user. The user proceeds with the training according to this plan, and their device reports their progress to the server.

[1226] 2. Utilization of foreign workers

[1227] The server collects recruitment information from global job sites and agencies into its database. Users submit recruitment requests for foreign workers with specific skills and qualifications from their terminals. Based on the collected data, the server selects the best candidates based on language skills, qualifications, and experience, and provides detailed information to the terminals.

[1228] As a concrete example, suppose a user wants to hire foreign workers as nursing staff. The user sends a recruitment request from their device, specifying language skills and particular qualifications. The server searches for the most suitable candidates based on its database and notifies the user of the profiles and contact information of the selected candidates. The user then conducts interviews based on the provided information and makes a hiring decision.

[1229] 3. Utilization of technology

[1230] The server continuously monitors the usage of technical tools and applications used in healthcare and welfare settings. Based on demand, the server suggests the latest technical tools and applications to users. Users evaluate the suggestions via their terminals and decide whether to accept them. Approved technologies are then deployed to the field by the server, and their usage is monitored in real time.

[1231] For example, if a medical facility requests the automation of nursing records, the server will monitor the current manual record-keeping situation and, based on that information, suggest an appropriate automated record-keeping tool. After the user approves this suggestion on their terminal, the server will install the automated record-keeping tool and monitor its usage and effectiveness.

[1232] 4. Improvement of working conditions

[1233] The server periodically collects and analyzes data on the working environment in medical and welfare facilities. Users can input requests for improvements to the working environment via a terminal. Based on the collected data and user requests, the server proposes efficient improvement measures and notifies the user via the terminal. When work environment improvement proposals are implemented, the progress is reported to the server, ensuring continuous improvement.

[1234] For example, if a request for improvements to reduce staff stress is made at a nursing care facility, the server collects survey and sensor data, and based on the analysis results, proposes specific improvement measures to the user, such as introducing a relaxation space or revising the shift system. The user then checks the proposed measures on their terminal and puts them into action.

[1235] 5. Promoting regional cooperation

[1236] The server integrates and manages information about local healthcare and welfare resources in a database. Users submit requests for collaboration with local resources through their terminals. The server searches for appropriate local resources, generates a specific and actionable collaboration plan, and notifies the terminal. The progress of each collaboration step is reported to the server in real time.

[1237] For example, if an organization providing home care services wishes to expand its operations in collaboration with a local government, the user submits a collaboration request via their terminal. The server searches for appropriate local governments and related organizations based on database information, creates a specific collaboration plan, and provides it to the user. The user then proceeds with the collaboration according to this plan.

[1238] Thus, the present invention provides a comprehensive system for resolving labor shortages in the medical and welfare fields and improving operational efficiency.

[1239] The following describes the processing flow.

[1240] 1. Expansion of education and training

[1241] Processing steps

[1242] Step 1:

[1243] The server stores the latest training data (videos, text, quizzes, etc.) for the medical and welfare fields in a database. Specifically, it uses web crawling and APIs to collect reliable training materials, organizes them, and stores them in the database.

[1244] Step 2:

[1245] Users apply for training through their devices. Specifically, users access a dedicated application or web portal, log in, and then enter their skill level and preferred training dates and times into the application form.

[1246] Step 3:

[1247] The server generates an optimal training plan considering the user's skill level and schedule. Specifically, it uses an AI algorithm to analyze user data and training materials to create a personalized training plan.

[1248] Step 4:

[1249] The device notifies the user of the training plan. Specifically, it sends the user the details of the training plan via push notification or email, and also sends periodic reminders for training sessions.

[1250] Step 5:

[1251] The device reports training progress to the server in real time. Specifically, it has a function that automatically sends progress to the server each time the user completes a training session, and the server records the progress in a database and provides feedback as needed.

[1252] 2. Utilization of foreign workers

[1253] Processing steps

[1254] Step 1:

[1255] The server collects recruitment information for foreign workers into a database. Specifically, it periodically collects the latest job postings from global job sites and recruitment agencies, organizes them, and stores them in the database.

[1256] Step 2:

[1257] The user submits a request to hire foreign workers from their device. Specifically, the user fills out a request form on their device specifying the hiring requirements for workers with particular skills and qualifications, and then submits it.

[1258] Step 3:

[1259] The server selects the most suitable foreign worker based on the request. Specifically, it analyzes the request content and collected recruitment information using a matching algorithm to generate a list of optimal candidates.

[1260] Step 4:

[1261] The device provides the user with information and contact details of the selected personnel. Specifically, it displays the selected candidate's profile, past experience, contact information, and other details on the user's device.

[1262] 3. Utilization of technology

[1263] Processing steps

[1264] Step 1:

[1265] The server monitors the use of technology in medical and welfare settings. Specifically, it periodically collects, integrates, and analyzes usage data for tools and applications used in each setting.

[1266] Step 2:

[1267] The server proposes technical tools and applications to the user based on their needs. Specifically, it selects the most suitable tools and applications based on usage data and information on new technologies in the market, generates a list of suggestions, and notifies the user.

[1268] Step 3:

[1269] The user evaluates whether to accept the proposal using their device. Specifically, the user reviews the proposed technology, judges its usefulness, and sends feedback.

[1270] Step 4:

[1271] The server deploys approved technologies to healthcare and welfare settings and monitors their usage in real time. Specifically, it remotely configures technical tools, continuously collects and analyzes usage data after deployment, and provides support and feedback as needed.

[1272] 4. Improvement of working conditions

[1273] Processing steps

[1274] Step 1:

[1275] The server collects and analyzes working environment data from medical and welfare facilities. Specifically, it acquires data from regular surveys and sensors, integrates it, and analyzes it.

[1276] Step 2:

[1277] Users input requests for improvements to their work environment via their device. Specifically, users enter their complaints and requests for improvements regarding their work environment into a dedicated form and submit it.

[1278] Step 3:

[1279] Based on the data collected by the server and user requests, the system proposes improvement measures. Specifically, it generates concrete improvement plans based on insights gained from data analysis and notifies the user.

[1280] Step 4:

[1281] The device notifies the user of the proposed solutions and provides an implementation plan. Specifically, it provides the user with a guide that explains in detail the steps and schedule for implementing the improvement measures, and has a function to track progress.

[1282] 5. Promoting regional cooperation

[1283] Processing steps

[1284] Step 1:

[1285] The server integrates regional medical and welfare resource information into a database. Specifically, it collects, organizes, and centralizes resource information from medical institutions, welfare facilities, NPO organizations, and other organizations in each region.

[1286] Step 2:

[1287] Users submit requests to connect with local resources using their devices. Specifically, users fill out the required information in the request form on the top page and submit it.

[1288] Step 3:

[1289] The server searches for the most suitable regional resources and generates a collaboration plan. Specifically, it analyzes the request content and resource information using a matching algorithm to create a concrete collaboration plan.

[1290] Step 4:

[1291] The device notifies the user of the integration plan and reports its progress to the server. Specifically, it has the function to notify the user of the details of the integration plan via push notification and to report the execution status of each step to the server in real time.

[1292] Through the specific processing steps described above, the present invention provides a system that helps to alleviate labor shortages in the medical and welfare fields and improves operational efficiency.

[1293] (Example 1)

[1294] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1295] In the medical and welfare sector, numerous challenges exist, including a lack of education and training, difficulties in effectively utilizing foreign workers, and the need to introduce new technologies and improve working conditions on-site. These problems, lacking appropriate solutions, are contributing to a decline in the operational efficiency and service quality of medical and welfare facilities. This invention aims to resolve these challenges and provide a comprehensive system that enables efficient and effective support for medical and welfare operations.

[1296] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1297] In this invention, the server includes means for storing the latest training data in the medical and welfare fields in a database, means for users to apply for training via a terminal, means for generating an optimal training plan considering the user's skill level and schedule, and means for optimizing this generated plan using a generation AI model, means for the terminal to notify the user of the training plan and report the training progress to the server in real time, means for collecting recruitment information for foreign workers in a database, means for users to submit recruitment requests for foreign workers via a terminal, means for selecting and notifying the user of the most suitable personnel based on language skills, qualifications, experience, etc., and means for this selection using a generation AI model, means for the terminal to provide the user with information and contact details of the selected personnel, means for monitoring the status of technology utilization in medical and welfare settings, means for proposing technology tools and applications to the user according to demand, means for the user to evaluate whether to accept the proposal using a terminal, and means for introducing approved technologies and monitoring their usage in real time. This makes it possible to alleviate labor shortages in the medical and welfare fields, improve the efficiency of education and training, effectively utilize foreign workers, appropriately introduce technology, and continuously improve the working environment.

[1298] The "medical and welfare field" refers to a broad range of operations and services related to medical care and welfare.

[1299] "Education and training" refers to training and learning activities aimed at improving skills and knowledge.

[1300] A "server" refers to a computer system that manages and processes data via a network.

[1301] A "database" refers to a structured collection of data that efficiently stores, searches, and manages large amounts of data.

[1302] "User" refers to an individual or group that operates or uses this system.

[1303] "Terminal" refers to a computer or smart device used by a user to access a system.

[1304] A "training plan" refers to a specific educational and training schedule designed to improve the user's skills.

[1305] A "generative AI model" refers to an algorithm that uses artificial intelligence to automatically generate optimal solutions and plans.

[1306] "Foreign workers" refers to people who come from outside the country to work.

[1307] "Recruitment information" refers to information about job seekers and employers, such as job advertisements and recruitment details.

[1308] "Technical tools" refer to technical devices and applications that help improve the efficiency and quality of work.

[1309] "Monitoring" refers to the act of continuously observing and recording specific situations or data.

[1310] "Notification" refers to the act of transmitting information or messages in real time.

[1311] A "progress report" refers to reporting on the progress of a specific task or project.

[1312] "Evaluation" refers to making a value judgment about a particular element or action.

[1313] "Real-time" refers to the processing of data and the transmission of information occurring almost simultaneously.

[1314] A "proposal" refers to the act of recommending a specific action or measure.

[1315] Modes for carrying out the invention

[1316] This invention is a comprehensive system that supports the resolution of labor shortages and the improvement of operational efficiency in the medical and welfare fields. The system of this invention utilizes the latest technology and has functions that enable the expansion of education and training, effective utilization of foreign workers, on-site technology introduction, and continuous improvement of the working environment.

[1317] System Configuration

[1318] 1. Expansion of education and training

[1319] The server stores the latest training data (videos, text, quizzes, etc.) in the medical and welfare fields in its database. This training data is obtained from reliable medical and educational institutions.

[1320] Users use their devices to apply for training programs based on their skill level and desired training program.

[1321] The server uses a generative AI model to consider the user's skill level and schedule to generate an optimal training plan.

[1322] The generated training plan is notified to the user via their device, and the progress of each training session is reported to the server in real time.

[1323] Example: Suppose a user wants online training to improve their caregiving skills. The user submits a training request from their device. The server considers the user's current skill level and available time, and uses a generative AI model to generate a training plan combining video materials on basic caregiving techniques and quiz-style tests, which is then provided to the user. The user follows this plan and the device reports their progress to the server.

[1324] Example of a prompt:

[1325] "Please describe a system to address the labor shortage in the medical and welfare sectors. Include the following five functions: expansion of education and training, utilization of foreign workers, utilization of technology, improvement of working conditions, and promotion of regional cooperation. Please explain each of these, including specific examples."

[1326] 2. Utilization of foreign workers

[1327] The server collects job postings from global job sites and agencies into its database.

[1328] Users submit recruitment requests for foreign workers with specific skills and qualifications from their devices.

[1329] The server uses a generative AI model to collect data and selects the most suitable candidates based on language skills, qualifications, experience, etc., and provides detailed information to the terminal.

[1330] Example: Suppose a user wants to hire foreign workers as nursing staff. The user sends a recruitment request from their device, specifying language skills and certain qualifications as requirements. The server uses a generative AI model to search the database for the most suitable candidates and notifies the user of the selected candidates' profiles and contact information. The user then conducts interviews based on the provided information and makes a hiring decision.

[1331] 3. Utilization of technology

[1332] The server constantly monitors the usage status of technical tools and applications used in medical and welfare settings.

[1333] The server proposes the latest technical tools and applications to users according to their needs.

[1334] Users evaluate proposals using their devices and decide whether to accept them. Approved technologies are deployed to the field by the server, and their usage is monitored in real time.

[1335] Specific example: If a medical facility requests to implement automated nursing record keeping, the server monitors the current manual record-keeping status and suggests an appropriate automated record-keeping tool based on that information. After the user approves this suggestion on their terminal, the server installs the automated record-keeping tool and monitors its usage and effectiveness.

[1336] 4. Improvement of working conditions

[1337] The server periodically collects and analyzes data related to the working environment in medical and welfare facilities.

[1338] Users input their requests for improvements to the work environment using a terminal.

[1339] The server proposes efficient improvement measures based on collected data and user requests, and notifies the user via the terminal. When improvements are implemented, progress is reported to the server, ensuring continuous improvement.

[1340] Specific example: If a request for improvements to reduce staff stress is made at a nursing care facility, the server collects data through surveys and sensors, and based on the analysis results, proposes specific improvement measures to the user, such as introducing a relaxation space or revising the shift system. The user checks the proposed measures on their terminal and puts them into action.

[1341] 5. Promoting regional cooperation

[1342] The server integrates and manages information about local healthcare and welfare resources in a database.

[1343] Users submit requests for integration with local resources through their devices.

[1344] The server searches for appropriate regional resources, generates a specific collaboration plan, and notifies the terminal. The progress of each collaboration step is reported to the server in real time.

[1345] Specific example: If an organization providing home care services wishes to expand its operations in collaboration with a local government, the user submits a collaboration request via their terminal. The server searches for appropriate local governments and related organizations based on database information, creates a specific collaboration plan, and provides it to the user. The user then proceeds with the collaboration according to this plan.

[1346] The system of this invention, by integrating these functions, effectively solves a wide range of problems in the medical and welfare fields, thereby reducing labor shortages and improving operational efficiency.

[1347] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1348] Expansion of education and training

[1349] Step 1:

[1350] The server stores the latest training data (videos, text, quizzes, etc.) for the medical and welfare fields in its database.

[1351] Input: Training data obtained from reliable medical or educational institutions.

[1352] Data processing: Converting data formats and registering them in databases.

[1353] Output: Training data stored in the database.

[1354] Step 2:

[1355] Users use their devices to apply for their skill level and desired training program.

[1356] Input: User's skill level information and desired training program.

[1357] Data processing: Standardize the input data from application forms.

[1358] Output: Training application data sent to the server.

[1359] Specific actions: After logging in, the user enters information into the training application form and clicks the "Submit" button.

[1360] Step 3:

[1361] The server uses a generative AI model to generate a training plan that takes into account the user's skill level and schedule.

[1362] Input: User skill level, schedule, and training data.

[1363] Data processing: Analysis and plan generation using generative AI models.

[1364] Output: Optimal training plan.

[1365] Specific operation: The server inputs the user's skill data and available time into the generated AI model and generates an optimal training plan.

[1366] Step 4:

[1367] The server notifies the user of the generated training plan via the terminal.

[1368] Input: Optimal training plan.

[1369] Data processing: Generating notification messages and sending them to the device.

[1370] Output: The training plan notified to the user's device.

[1371] Specific action: Send a push notification to the user's device and display the training plan.

[1372] Step 5:

[1373] The device reports training progress to the server in real time.

[1374] Input: User training progress information.

[1375] Data processing: Collection and transfer of progress data.

[1376] Output: Training progress data reported to the server.

[1377] Specific operation: When a user updates their progress during a training session, the device sends that information to the server.

[1378] Utilization of foreign workers

[1379] Step 1:

[1380] The server collects job postings from global job sites and agencies into its database.

[1381] Input: Job postings from global job sites and agencies.

[1382] Data processing: Data collection and registration into databases.

[1383] Output: Recruitment information stored in the database.

[1384] Step 2:

[1385] Users submit recruitment requests for foreign workers from their devices.

[1386] Input: Language skills and specific qualifications required by the user.

[1387] Data processing: Standardization and storage of recruitment requests.

[1388] Output: Recruitment request data sent to the server.

[1389] Specific operation: The user enters the hiring criteria and clicks the "Submit Request" button.

[1390] Step 3:

[1391] The server selects the most suitable candidate based on the data collected using a generative AI model.

[1392] Input: Recruitment request data and collected recruitment information.

[1393] Data processing: Candidate selection using generative AI models.

[1394] Output: A list of the best candidates.

[1395] Specific operation: The server executes a database query to search for candidates that match the criteria.

[1396] Step 4:

[1397] The server notifies the terminal of detailed information about the selected candidates.

[1398] Input: A list of the best candidates.

[1399] Data processing: Generating and forwarding notification messages for candidate information.

[1400] Output: Candidate information notified to the user's device.

[1401] Specific operation: Display candidate information on the user's device and provide a link to the details page.

[1402] Utilization of technology

[1403] Step 1:

[1404] The server monitors the usage of technical tools and applications used in medical and welfare settings.

[1405] Input: Data on technology usage from the field.

[1406] Data processing: Data analysis and storage.

[1407] Output: Monitoring report.

[1408] Specific actions: Collect sensor and log data to track usage.

[1409] Step 2:

[1410] The server proposes the latest technical tools and applications to users according to their needs.

[1411] Input: Monitoring data and latest technology data.

[1412] Data processing: Generating proposals based on analysis results.

[1413] Output: Proposal message.

[1414] Specific operation: Analyze usage data and select the appropriate tool using a generated AI model.

[1415] Step 3:

[1416] The user evaluates the proposal and decides whether to accept it.

[1417] Input: Suggestion message.

[1418] Data processing: Evaluation of proposals.

[1419] Output: Evaluation results.

[1420] Specific actions: View the proposal, fill out the evaluation form, and click the "Complete Evaluation" button.

[1421] Step 4:

[1422] The server deploys approved technologies to the field and monitors their usage in real time.

[1423] Input: Approved technical information.

[1424] Data processing: Monitoring the deployment and usage of technical tools.

[1425] Output: Usage report.

[1426] Specific actions: Deploy new technical tools to the field and monitor their usage using sensors and log data.

[1427] Improvement of working conditions

[1428] Step 1:

[1429] The server periodically collects and analyzes data related to the working environment in medical and welfare facilities.

[1430] Input: Surveys and sensor data related to the working environment.

[1431] Data processing: Data collection and analysis.

[1432] Output: Labor environment analysis report.

[1433] Specific operation: Data is collected through surveys and sensors, and then processed using analysis software.

[1434] Step 2:

[1435] Users input their requests for improvements to the work environment using a terminal.

[1436] Input: Improvement request data.

[1437] Data processing: Standardization and storage of requested data.

[1438] Output: Improvement request data sent to the server.

[1439] Specific action: Fill out the improvement request form and click the "Submit" button.

[1440] Step 3:

[1441] The server proposes efficient improvement measures based on the collected data and user requests.

[1442] Input: Work environment data and improvement request data.

[1443] Data processing: Data analysis and proposal generation.

[1444] Output: Suggestion message for improvement.

[1445] Specific operation: Combine user requests and data analysis results to generate improvement measures and notify the device.

[1446] Step 4:

[1447] When proposed improvements to the working environment are implemented, progress is reported to the server, and continuous improvement is ensured.

[1448] Input: Progress data on improvement implementation.

[1449] Data processing: Collection and analysis of progress data.

[1450] Output: Progress report.

[1451] Specific actions: Regularly monitor the effectiveness of implemented improvement measures and generate reports.

[1452] Promoting regional cooperation

[1453] Step 1:

[1454] The server integrates and manages information about local healthcare and welfare resources in a database.

[1455] Input: Local resource information.

[1456] Data processing: Data collection and integration.

[1457] Output: Regional resource information integrated into the database.

[1458] Specific actions: Collect data using the regional resource information API.

[1459] Step 2:

[1460] Users submit requests for integration with local resources through their devices.

[1461] Input: Integration request data.

[1462] Data processing: Standardization and storage of data.

[1463] Output: Integration request data sent to the server.

[1464] Specific action: Fill out the integration request form and click the "Submit" button.

[1465] Step 3:

[1466] The server searches for appropriate regional resources and generates a specific collaboration plan.

[1467] Input: Regional resource information and collaboration request data.

[1468] Data processing: Data analysis and plan generation.

[1469] Output: Integration plan.

[1470] Specific operation: Analyzes user requests, queries the database, and generates integration plans.

[1471] Step 4:

[1472] The server notifies the terminal of the generated integration plan.

[1473] Input: Integration plan.

[1474] Data processing: Generating and forwarding plan notification messages.

[1475] Output: The integration plan notified to the user's device.

[1476] Specific action: A notification about the integration plan is sent to the user's device, and details are displayed.

[1477] Step 5:

[1478] The progress of each integration step is reported to the server.

[1479] Input: Progress data for the integration steps.

[1480] Data processing: Collection and integration of progress data.

[1481] Output: Progress report.

[1482] Specific actions: Monitor the progress of the integration and update the progress status on the server.

[1483] Through the procedures outlined above, this system provides comprehensive support to address labor shortages in the medical and welfare sectors and improve operational efficiency.

[1484] (Application Example 1)

[1485] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1486] Labor shortages and operational inefficiencies in the healthcare and welfare sectors are serious challenges. To address these issues, improved education and training, effective utilization of foreign workers, and the introduction of cutting-edge technologies are essential. In particular, similar problems exist not only in the healthcare and welfare sectors but also in manufacturing sites such as factories, where a lack of knowledge and skills regarding robot operation and maintenance is a bottleneck. To solve this, a comprehensive education system and technical support system are required.

[1487] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1488] In this invention, the server includes means for storing the latest training data related to the operation of medical and welfare fields and factory robots in a database, means for users to apply for training via a terminal, means for generating an optimal training plan considering the user's skill level and schedule, means for notifying users through various training and reporting their progress in real time, means for providing videos and materials on factory robot operation procedures, means for generating and notifying robot maintenance schedules, means for monitoring the robot's status and diagnosing errors, and means for users to utilize training modes for skill improvement. This enables the efficient provision of technical education and training in both medical and welfare fields and factory settings, improving the efficiency of operation and maintenance, and solving the problems of labor shortages and operational inefficiencies.

[1489] The "medical and welfare field" refers to all fields that provide medical and welfare services.

[1490] "Training data" refers to digital information such as videos, texts, and quizzes used for educational and training purposes.

[1491] A "database" refers to a system for structuring, storing, and managing training data and other information.

[1492] "Terminal" refers to devices such as computers, smartphones, and tablets that users use to access servers.

[1493] "Skill level" refers to an indicator that evaluates the user's current level of knowledge and proficiency in skills.

[1494] A "training plan" refers to an educational and training program customized based on the user's skill level and schedule.

[1495] "Real-time" refers to processing and responding instantly without delay.

[1496] "Factory robots" refer to automated mechanical devices used in factories and manufacturing sites.

[1497] "Operation procedure videos" refer to video content created to demonstrate how to use and operate a robot.

[1498] "Documents" refers to papers and manuals created to explain operating procedures and maintenance details.

[1499] A "maintenance schedule" refers to a timetable or plan for systematically performing maintenance on a robot.

[1500] "Monitoring" refers to the act of continuously monitoring the status of a system or device.

[1501] "Error diagnosis" refers to the process of detecting abnormalities that occur in devices or systems, and identifying and analyzing their causes.

[1502] "Training Mode" refers to special educational and training features that users can use to improve their skills.

[1503] "Technical tools" refer to various technical devices and software used to efficiently perform specific tasks.

[1504] An "application" refers to a software program with a specific function or purpose.

[1505] This invention is a system for streamlining the operation and maintenance of robots in the medical and welfare fields and in factories. Specific embodiments for carrying out this invention are described below.

[1506] Program generation:

[1507] The system consists of components applicable to both the medical and welfare fields and factory robotics. This system includes the following:

[1508] 1. The server stores the latest training data related to the operation and maintenance of medical and welfare fields and factory robots in its database.

[1509] 2. Users apply for training through their device.

[1510] 3. The server generates an optimal training plan, taking into account the user's skill level and schedule.

[1511] 4. The device notifies the user of the training plan and reports the training progress in real time.

[1512] 5. The server provides operating procedure videos and materials for the factory robots.

[1513] 6. The server generates and notifies the robot of its maintenance schedule.

[1514] 7. The server monitors the robot's status and diagnoses errors.

[1515] 8. Users utilize training modes to improve their skills.

[1516] Hardware and software to be used:

[1517] Hardware: Smartphones, tablets, smart glasses, computers

[1518] Software: Database management systems (e.g., SQLite), programming languages ​​(e.g., Python)

[1519] Data processing and data calculations:

[1520] Data processing: Training data and operating procedure documents are stored in a database, and appropriate data is provided in response to user requests.

[1521] Data processing: Generate customized training plans based on the user's skill level and schedule, and monitor progress in real time. Generate robot maintenance schedules and analyze error logs.

[1522] Specific example:

[1523] For example, if a nursing staff member working at a medical facility wants to learn how to operate new medical equipment, they can submit a training request via a terminal. The server then considers the staff member's skill level and schedule to generate an optimal training plan. This plan includes video materials and quiz-style tests, which the nursing staff member follows as they progress through the training. Similarly, data regarding the operation and maintenance of robots used in factories is managed in the same way, allowing workers to receive efficient training.

[1524] Example of a prompt:

[1525] Design an application that provides basic instructional videos, maintenance procedures, and error logs for new engineers to operate factory robots.

[1526] It also includes real-time support functions to address labor shortages and improve operational efficiency.

[1527] In this way, the present invention enables the efficient provision of technical education and training in both medical and welfare settings, as well as in factory settings, thereby solving the problems of labor shortages and operational inefficiencies.

[1528] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1529] Step 1:

[1530] The server stores the latest training data related to the operation and maintenance of medical and welfare fields and factory robots in its database.

[1531] Input: Training data (videos, text, quizzes, etc.)

[1532] Data processing: Save training data to a database categorized by type.

[1533] Output: Training data stored in the database

[1534] Specific operation: The administrator uploads the latest training data, and the server categorizes and stores it in the database.

[1535] Step 2:

[1536] Users apply for training through their device.

[1537] Input: User's skill level and desired training content

[1538] Data processing: Receive user application details and save them to the database.

[1539] Output: User application data

[1540] Specific operation: The user uses the application to input their skill level and desired training content, and that data is sent to the server.

[1541] Step 3:

[1542] The server generates an optimal training plan, taking into account the user's skill level and schedule.

[1543] Input: User's skill level and schedule, training data stored in the database

[1544] Data processing: Select an appropriate training program based on the user's skill level and available time.

[1545] Output: Individually optimized training plan

[1546] Specific operation: The server matches training data in the database with user information to generate the optimal training plan.

[1547] Step 4:

[1548] The device notifies the user of the training plan and reports on training progress in real time.

[1549] Input: Training plan, user progress data

[1550] Data processing: Notification of training plans and real-time reporting of progress data.

[1551] Output: User notifications, progress report data

[1552] Specific operation: As the user checks the training plan on their device and progresses through the training, their progress is automatically reported to the server.

[1553] Step 5:

[1554] The server provides operating procedure videos and documents for factory robots.

[1555] Input: Operation procedure data (video, text)

[1556] Data processing: Providing operation procedure data to users in an appropriate format.

[1557] Output: User instruction videos and documentation

[1558] Specific operation: Video tutorials and materials necessary for operating the robot are delivered to the user's device.

[1559] Step 6:

[1560] The server generates and notifies users of the robot's maintenance schedule.

[1561] Input: Robot operation data, recommended maintenance cycle

[1562] Data calculation: Calculate maintenance requirements and create a schedule.

[1563] Output: Maintenance Schedule

[1564] Specific operation: Based on the robot's usage frequency and status, the system automatically generates a schedule for the next maintenance and notifies the user.

[1565] Step 7:

[1566] The server monitors the robot's status and diagnoses errors.

[1567] Input: Real-time robot operation data, error logs

[1568] Data processing: Log data analysis and error diagnosis

[1569] Output: Error report and suggested solutions

[1570] Specific operation: Based on the robot's sensors and log data, it monitors its status in real time, immediately diagnoses any abnormalities, and reports them to the user.

[1571] Step 8:

[1572] Users can utilize the training mode to improve their skills.

[1573] Input: Training mode selection, current skill level

[1574] Data Processing: Customize training modes according to skill level.

[1575] Output: Training content tailored to the user

[1576] Specific operation: Users can select a training mode within the application and receive training tailored to their skill level.

[1577] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1578] This invention provides a system that combines an emotion engine that recognizes user emotions in order to alleviate labor shortages and support efficient operations in the medical and welfare fields. This system is implemented in the following manner.

[1579] 1. Expansion of education and training

[1580] The server stores the latest training data (videos, text, quizzes, etc.) in the medical and welfare fields in its database. The server also includes an emotion engine that recognizes user emotions. When a user applies for training through their device, the emotion engine evaluates the user's emotional state in real time through facial recognition and voice analysis. This emotion data, along with the user's skill level and schedule, is used to generate an optimal training plan.

[1581] The server analyzes emotional data collected by the emotion engine and, if the user is feeling stressed or unmotivated, provides training content and feedback tailored to their current emotions. The device then notifies the user of a training plan based on this analysis and reports its progress to the server in real time.

[1582] For example, if a user requests online training to improve their caregiving skills, the emotion engine assesses their stress level based on their facial expression and tone of voice when they log in and submit a training request. Based on this information, the server generates a training plan that includes relaxing video materials and interactive quizzes, which are then delivered to the user via their device.

[1583] 2. Utilization of foreign workers

[1584] The server collects recruitment information for foreign workers into a database and uses an emotion engine to evaluate the emotional state of candidates during interviews. Users submit recruitment requests for foreign workers from their terminals, and the server selects the most suitable candidates based on language skills, qualifications, experience, and emotional state. The terminal then provides the user with information and contact details of the selected candidates.

[1585] As a concrete example, when a user hires foreign workers as nursing staff, the emotional engine evaluates the candidate's stress level and communication skills during the interview, helping to select a suitable candidate. The user can then review this data via their device and hire the most suitable personnel.

[1586] 3. Utilization of technology

[1587] The server monitors the usage of technology tools and applications used in healthcare and welfare settings and uses an emotion engine to evaluate users' emotions towards the use of these technologies. Based on this data, the server suggests technology tools and applications to users according to their needs. Users evaluate the suggestions via their terminals, and approved technologies are deployed to the field by the server, with their usage and emotion data monitored in real time.

[1588] As a concrete example, if a user is unfamiliar with a new nursing record application introduced at a medical facility, the emotion engine will detect the user's confusion or stress, and the server will suggest a simpler interface or provide additional training. This information is then communicated to the user via the terminal, aiming to improve user satisfaction.

[1589] 4. Improvement of working conditions

[1590] The server collects and analyzes work environment and emotional data from medical and welfare facilities. Users input requests for improvements to the work environment via a terminal, and their emotional state is recorded in real time. Based on the collected data and the user's emotions, the server proposes specific improvement measures and notifies the user via the terminal. Progress during implementation is reported to the server, and feedback is provided as needed.

[1591] For example, if a staff member at a nursing home is experiencing stress, the emotion engine detects this, and the server suggests measures to reduce stress, such as expanding relaxation spaces or changing shifts. The user then reviews the suggestions on their device and takes action.

[1592] 5. Promoting regional cooperation

[1593] The server integrates and manages information and emotional data about local healthcare and welfare resources in a database. Users submit requests for collaboration with local resources through their terminals, and their emotional state at the time is also recorded. The server generates appropriate local resources and specific collaboration plans, and adjusts the timing and content of the collaboration plan proposals to the user based on the emotional data. The user is notified of the proposals through their terminal, and the progress of each collaboration step is reported to the server in real time.

[1594] As a concrete example, when an organization providing home care services expands its operations in collaboration with a local government, the user's emotion engine monitors their emotional state in real time during the collaboration negotiations, and the server proposes approaches to reduce the user's stress and anxiety. The user can check this from their terminal, and is supported in ensuring the smooth progress of the collaboration.

[1595] Thus, the present invention provides a system that, by combining an emotion engine, evaluates the user's emotional state in real time and enables more effective and user-friendly implementation of processes in the medical and welfare fields, including education, utilization of foreign workers, introduction of technology, improvement of the working environment, and regional collaboration.

[1596] The following describes the processing flow.

[1597] 1. Expansion of education and training

[1598] Processing steps

[1599] Step 1:

[1600] The server stores the latest training data (videos, text, quizzes, etc.) for the medical and welfare fields in a database. Specifically, it uses web crawling and APIs to collect reliable training materials, organizes them, and stores them in the database.

[1601] Step 2:

[1602] Users apply for training through their devices. Specifically, users access a dedicated application or web portal, log in, and then enter their skill level and preferred training dates and times into the application form.

[1603] Step 3:

[1604] The server uses an emotion engine to recognize user emotions and evaluate the user's emotional state. Specifically, when a user submits a training request, the system analyzes their facial expressions and voice tone in real time via the camera and microphone.

[1605] Step 4:

[1606] The server generates an optimal training plan by considering the user's skill level, schedule, and sentiment data. Specifically, it uses AI algorithms to analyze this data and create a personalized training plan.

[1607] Step 5:

[1608] The device notifies the user of the training plan. Specifically, it sends the user the details of the training plan via push notification or email, and also sends periodic reminders for training sessions.

[1609] Step 6:

[1610] The device reports training progress and user sentiment data to the server in real time. Specifically, it has a function that automatically sends progress and sentiment status to the server each time the user completes a training session.

[1611] 2. Utilization of foreign workers

[1612] Processing steps

[1613] Step 1:

[1614] The server collects recruitment information for foreign workers into a database. Specifically, it periodically collects the latest job postings from global job sites and recruitment agencies, organizes them, and stores them in the database.

[1615] Step 2:

[1616] The user submits a request to hire foreign workers from their device. Specifically, the user fills out a request form on their device specifying the hiring requirements for workers with particular skills and qualifications, and then submits it.

[1617] Step 3:

[1618] The server selects the most suitable foreign worker based on the request. Specifically, it analyzes the request content and collected recruitment information using a matching algorithm to generate a list of optimal candidates.

[1619] Step 4:

[1620] The server uses an emotion engine to evaluate the candidate's emotional state during the interview. Specifically, it collects and analyzes the candidate's emotional data through the camera and microphone during the interview.

[1621] Step 5:

[1622] The device provides the user with information and contact details of the selected personnel. Specifically, it displays the selected candidate's profile, past experience, contact information, and other details on the user's device.

[1623] 3. Utilization of technology

[1624] Processing steps

[1625] Step 1:

[1626] The server monitors the use of technology in medical and welfare settings. Specifically, it periodically collects, integrates, and analyzes usage data for tools and applications used in each setting.

[1627] Step 2:

[1628] The server uses an emotion engine to evaluate the user's emotional state when using technology. Specifically, it collects and analyzes emotional data through the camera and microphone when the user uses tools or applications.

[1629] Step 3:

[1630] The server suggests technology tools and applications to users based on their technology usage and sentiment data, tailored to their needs. Specifically, it uses an AI algorithm to generate a list of optimal tools and applications and notifies the user.

[1631] Step 4:

[1632] The user evaluates whether to accept the proposal using their device. Specifically, the user reviews the proposed technology, judges its usefulness, and sends feedback.

[1633] Step 5:

[1634] The server deploys approved technologies to healthcare and welfare settings, monitoring usage and emotional data in real time. Specifically, it remotely configures technical tools, continuously collects and analyzes usage and emotional data after deployment, and provides support and feedback as needed.

[1635] 4. Improvement of working conditions

[1636] Processing steps

[1637] Step 1:

[1638] The server collects and analyzes work environment and emotional data from medical and welfare facilities. Specifically, it acquires and analyzes data from periodic surveys, sensors, and real-time emotional data generated by an emotional analysis engine.

[1639] Step 2:

[1640] Users input requests for improvements to their work environment via their device. Specifically, users enter their complaints and requests for improvements regarding their work environment into a dedicated form and submit it.

[1641] Step 3:

[1642] The system proposes improvement measures based on data collected by the server and user sentiment. Specifically, it generates concrete improvement suggestions based on insights gained from data analysis and notifies the user.

[1643] Step 4:

[1644] The device notifies the user of the proposed solutions and provides an implementation plan. Specifically, it provides the user with a guide that explains in detail the steps and schedule for implementing the improvement measures, and has a function to track progress.

[1645] 5. Promoting regional cooperation

[1646] Processing steps

[1647] Step 1:

[1648] The server integrates regional medical and welfare resource information and sentiment data into a database. Specifically, it collects, organizes, and centralizes resource information and sentiment data from medical institutions, welfare facilities, NPO organizations, and other organizations in each region.

[1649] Step 2:

[1650] Users submit requests to connect with local resources using their devices. Specifically, users fill out the necessary information in a request form from the top page, and their emotional state at that time is recorded in real time.

[1651] Step 3:

[1652] The server searches for the most suitable regional resources and generates a collaboration plan. Specifically, it analyzes the request content, resource information, and sentiment data using a matching algorithm to create a concrete collaboration plan.

[1653] Step 4:

[1654] The device notifies the user of the integration plan and reports progress and sentiment data to the server. Specifically, it notifies the user of the details of the integration plan via push notification and has the function to monitor the sentiment state during execution and report the progress of each step to the server in real time.

[1655] Through the specific processing steps described above, the present invention provides a system that helps alleviate labor shortages in the medical and welfare fields and improves operational efficiency. By using an emotion engine, the user's emotional state can be evaluated in real time, enabling the provision of more effective and user-friendly support.

[1656] (Example 2)

[1657] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1658] In the healthcare and welfare sector, challenges include improving operational efficiency and reducing the psychological burden on employees in areas such as education and training, the utilization of foreign workers, and the introduction of new technologies. Conventional systems have made it difficult to assess users' emotional states in real time and respond individually, leading to decreased operational efficiency and increased employee stress.

[1659] The identification processing performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for storing the latest training data in the medical and welfare field in a database, means for users to apply for training through a terminal, means for generating an optimal training plan considering the user's skill level and schedule, means for recognizing and collecting the user's emotional state, means for analyzing the emotional data and adjusting the training content based on the user's emotional state, and means for the terminal to notify the user of the training plan and report the progress of the training in real time. This enables flexible and individualized responses in accordance with the user's emotional state.

[1660] The "medical and welfare field" refers to all activities in the medical and welfare industries, including patient treatment and the provision of welfare services.

[1661] "Training data" refers to learning resources such as videos, text, and quizzes that are stored on a server for educational and training purposes.

[1662] A "database" refers to a system for efficiently storing, searching, and managing information.

[1663] "Users" refer to employees and related parties in the medical and welfare fields who use this system.

[1664] "Terminal" refers to the computer or mobile device that a user uses to access this system.

[1665] An "emotion engine" refers to technology that recognizes, collects, and analyzes a user's emotional state.

[1666] "Emotional data" refers to data about the user's emotional state collected by the emotion engine.

[1667] "Skill level" refers to the user's level of proficiency in skills and knowledge.

[1668] A "training plan" refers to the optimal learning and training program generated by the server based on the user's skill level and emotional state.

[1669] "Foreign workers" refers to workers of foreign origin who are employed in the medical and welfare fields.

[1670] "Recruitment information" refers to data including foreign workers' language skills, qualifications, and experience.

[1671] "Technical tools and applications" refer to software and systems used in medical and welfare settings.

[1672] This invention relates to a system that supports the expansion of education and training, the utilization of foreign workers, and the introduction of technology in the medical and welfare fields. This system can improve work efficiency and reduce the psychological burden on employees by recognizing the user's emotional state in real time and providing optimal support based on that recognition.

[1673] Expansion of education and training

[1674] The server collects the latest training data in the medical and welfare fields and stores it in a database. This training data includes videos, text, quizzes, and more. It also features an emotion engine that uses facial recognition technology and voice analysis to evaluate the user's emotional state in real time.

[1675] When a user submits a training request using their device, the emotion engine analyzes the user's facial expression and tone of voice to collect emotional data. The server then generates an optimal training plan based on this emotional data, the user's skill level, and their schedule information. The generated training plan is tailored to the user's emotional state.

[1676] For example, if a user requests training to improve their caregiving skills, the device's camera and microphone activate, and the emotion engine collects emotional data. The server then provides a training plan that includes relaxing video materials and interactive quizzes. This allows the user to learn without feeling stressed.

[1677] Example of a prompt: "Please propose a relaxing training plan to improve caregiving skills."

[1678] Utilization of foreign workers

[1679] The server collects recruitment information on foreign workers (language skills, qualifications, experience) and stores it in a database. When a user submits a recruitment request for a foreign worker from their terminal, the server uses an emotion engine to evaluate the candidate's emotional state and analyzes their stress level and communication skills.

[1680] As a concrete example, when a user hires foreign workers as nursing staff, the emotion engine collects candidate emotional data during the interview, and the server selects the appropriate candidate. Once the best candidate is selected, their information and contact details are provided to the user via their device.

[1681] Example prompt: "Please tell me the criteria for selecting foreign workers who are suitable as nursing staff."

[1682] Utilization of technology

[1683] The server monitors the usage of technical tools and applications used in medical and welfare settings and evaluates the user's emotional state using an emotion engine. Based on the collected emotional data, the server suggests the most suitable technical tools and applications for the user.

[1684] As a concrete example, regarding a newly introduced nursing record app, if a user experiences confusion or stress while using it, the emotion engine detects this, and the server suggests a simpler interface or provides additional training. This makes it possible to improve user satisfaction.

[1685] Example prompt: "Please suggest ways to reduce the stress users experience with the new nursing record app."

[1686] Improvement of working conditions

[1687] The server can collect and analyze data on the working environment and emotional state of healthcare and welfare facilities. Users input requests for improvements to the working environment via a terminal, and their emotional state is recorded in real time. Based on the collected data, the server proposes specific improvement measures and notifies the user through the terminal.

[1688] For example, if staff at a nursing home are experiencing stress, the emotion engine detects this, and the server suggests measures to reduce stress (such as expanding relaxation spaces or changing shifts). This can reduce the psychological burden on staff and improve work efficiency.

[1689] Promoting regional cooperation

[1690] The server integrates and manages information and emotional data about local healthcare and welfare resources in a database. When a user submits a request to connect with local resources through their terminal, their emotional state is also recorded. The server generates appropriate local resources and specific connection plans, and optimizes suggestions for the user based on the emotional data.

[1691] As a concrete example, when an organization providing home care services collaborates with a local government, the emotion engine monitors the user's emotional state during negotiations, and the server proposes approaches to reduce the user's stress and anxiety. This helps to facilitate smooth collaboration.

[1692] Example prompt: "Please tell me about stress reduction measures for organizations providing home care services when collaborating with local governments."

[1693] Thus, the present invention is a system that effectively supports various processes in the medical and welfare fields by utilizing an emotion engine and recognizing the user's emotional state in real time.

[1694] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1695] Expansion of education and training

[1696] Step 1:

[1697] The server collects the latest training data in the medical and welfare fields and stores it in a database. This training data includes videos, text, quizzes, and more. Input training data is collected from diverse sources and neatly stored in the database. The output is a set of the latest available training data.

[1698] Step 2:

[1699] The user submits a training application using a terminal. The user's login information and training application details are sent as input. Upon receiving this information, the terminal activates its camera and microphone to send facial expression and voice tone to the emotion engine. The output is the transmission of audio and video data to the emotion engine.

[1700] Step 3:

[1701] The server analyzes the emotional data received from the emotion engine. Emotional data, user skill level, and schedule information are obtained as input. Data calculations are used to evaluate the user's stress level and motivation. Based on the results, an optimal training plan is generated. A personalized training plan is generated as output.

[1702] Step 4:

[1703] The server sends the generated training plan to the terminal. The generated training plan is the input, and the notification sent to the terminal is the output. The terminal notifies the user and simultaneously activates a system that reports the training progress to the server in real time.

[1704] Specific operation: For example, when a user applies for training to improve their caregiving skills, the device's camera and microphone automatically activate, and the emotion engine analyzes the user's facial expression and voice tone in real time. Based on the data collected in this way, the server generates a training plan that includes relaxing materials and interactive quizzes, and sends it to the device.

[1705] Utilization of foreign workers

[1706] Step 1:

[1707] The server collects recruitment information for foreign workers and stores it in a database. Inputs include information such as each candidate's language skills, qualifications, and experience. The output is a database of usable recruitment information.

[1708] Step 2:

[1709] The user submits a recruitment request for foreign workers from their terminal. The request details and the user's preferences are sent to the terminal as input. The output is the recruitment request information sent to the server.

[1710] Step 3:

[1711] The server uses an emotion engine to evaluate the candidate's emotional state during the interview. The candidate's facial expression and voice data are sent to the emotion engine as input, and analysis is performed. Output data includes evaluations of the candidate's stress level and communication skills.

[1712] Step 4:

[1713] The server integrates collected sentiment data with candidates' language skills, qualifications, and experience to select the most suitable candidates. The selected candidates' information is generated as output and notified to the terminal. The terminal then provides this information to the user.

[1714] Specific operation: For example, when a user hires a foreign worker as nursing staff, the device's camera and microphone are activated during the interview, and an emotion engine analyzes stress levels and communication skills. Based on the results, the server selects the most suitable candidate and sends the information to the device.

[1715] Utilization of technology

[1716] Step 1:

[1717] The server monitors the usage of technical tools and applications used in medical and welfare settings. The input is usage data for each tool and application. Data is then analyzed to determine usage frequency and effectiveness. The output is aggregated usage data.

[1718] Step 2:

[1719] The server uses an emotion engine to evaluate the user's emotional state regarding the use of technical tools. Real-time emotional data from the user is sent as input. The output is emotional evaluation data from the emotion engine.

[1720] Step 3:

[1721] The server suggests the most suitable technical tools and applications to the user based on the collected sentiment data. Sentiment data and usage data are used as input. The output is personalized suggestions.

[1722] Step 4:

[1723] Through the terminal, the user evaluates the proposal and notifies the server whether to accept or reject it. User feedback on the proposal is collected as input. The output is the server's approval or rejection data of the proposal.

[1724] Specific operation: For example, if a user feels confused or stressed by a new nursing record app, the emotion engine detects this, and the server suggests an alternative app with a simpler interface or additional training. If the user accepts this, their usage and emotional data are monitored in real time.

[1725] Improvement of working conditions

[1726] Step 1:

[1727] The server collects work environment and emotional data from healthcare and welfare facilities. Environmental sensor data and user emotional data are provided as input. The output is a report on the state of the work environment.

[1728] Step 2:

[1729] Users input requests for improvements to their work environment via a terminal, and real-time sentiment data is collected along with these requests. The input consists of user feedback and sentiment data. The output consists of request data and sentiment data sent to the server.

[1730] Step 3:

[1731] The server proposes specific improvement measures based on collected work environment data and the user's emotional state. Past improvement data and current emotional data are used as input. The output is improvement suggestions notified to the user.

[1732] Step 4:

[1733] Through the terminal, the user reviews the proposed improvements and sends their feedback to the server. The input is the user's approval or rejection feedback. The output is a list of improvements to be implemented on the server side.

[1734] Specific operation: For example, if a staff member at a nursing home is experiencing stress, the emotion engine detects this, and the server suggests measures such as expanding relaxation spaces or changing shifts. The user reviews and approves these suggestions on their terminal, and they are then implemented.

[1735] Promoting regional cooperation

[1736] Step 1:

[1737] The server integrates and manages information and sentiment data related to local healthcare and welfare resources into a database. Local resource information and sentiment data are collected as input. The output is the integrated and managed database.

[1738] Step 2:

[1739] Users submit requests to connect with local resources through their devices. Their emotional state is also recorded during this process. The input consists of the request content and emotional data. The output is the request data on the server side.

[1740] Step 3:

[1741] The server generates appropriate local resources and specific collaboration plans based on collected sentiment data. Sentiment data and local resource data are used as input. The output is a collaboration plan proposal for the user.

[1742] Step 4:

[1743] The terminal notifies the user of the integration plan details and reports the progress of each integration step to the server in real time. Inputs include user feedback and progress data. Outputs include feedback and adjustments to the proposed content based on the progress.

[1744] Specific operation: For example, when an organization providing home care services collaborates with a local government, the emotion engine monitors the emotional state during negotiations, and the server suggests measures to reduce stress and anxiety. The user can then view this on their device and take appropriate action to help the collaboration proceed smoothly.

[1745] (Application Example 2)

[1746] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1747] This invention relates to resolving labor shortages in the medical and welfare fields, improving operational efficiency, and providing a more appropriate work support system that takes into account the emotional state of workers. In particular, it aims to improve the working environment and enhance the quality of education by recognizing the emotional state of workers in real time and reflecting it in training and work support plans.

[1748] In Application Example 2, the specific processing performed by the specific processing unit 290 of the data processing device 12 is realized by the following means. In this invention, the server includes means for storing the latest training data in the medical and welfare field in a database, means for users to apply for training through a terminal, means for generating an optimal training plan considering the user's skill level, schedule, and emotional state, means for the terminal to notify the user of the training plan and report the progress of the training in real time, and means for evaluating the user's emotional state in real time using emotion recognition technology. This makes it possible to provide optimal training and work support that takes into account the user's emotional state.

[1749] "Education and training in the medical and welfare fields" refers to training and learning activities that provide the knowledge and skills necessary for medical and welfare-related jobs, and aim to improve employee capabilities and streamline operations.

[1750] "Training data" refers to information such as videos, texts, and quizzes used in educational and training programs, and is based on the latest medical and welfare technologies and knowledge.

[1751] "Terminal" refers to hardware devices such as computers, smartphones, and tablets that users operate.

[1752] "Training application" refers to the process of completing the necessary procedures and registrations required for a user to receive training.

[1753] A "training plan" refers to a learning plan that combines the most suitable educational content and methods, taking into account each user's individual skill level, schedule, and emotional state.

[1754] "Reporting progress in real time" refers to the process of continuously monitoring the progress of training or work and reporting it immediately.

[1755] "Emotion recognition technology" refers to technology that uses techniques such as facial recognition and voice analysis to evaluate a user's emotional state in real time.

[1756] "Foreign workers" refers to foreign nationals employed to work in medical and welfare facilities within Japan.

[1757] A "recruitment request" refers to an application or request made by a user to recruit foreign workers.

[1758] "Language skills, qualifications, and experience" refers to the language proficiency, professional qualifications, and past work experience possessed by foreign workers.

[1759] This invention provides a system that combines an emotion engine that recognizes user emotions in order to help alleviate labor shortages and improve operational efficiency in the medical and welfare fields. This system is implemented by the following specific method.

[1760] 1. System Configuration

[1761] The server stores the latest training data (videos, text, quizzes, etc.) in the medical and welfare fields in its database. Users apply for training through their terminals. The server generates an optimal training plan considering the user's skill level, schedule, and emotional state. The generated training plan is notified to the user through their terminal, and training progress is reported in real time.

[1762] 2. Use of emotion recognition technology

[1763] The server uses emotion recognition technology to evaluate the user's emotional state in real time. This technology uses a camera and microphone to analyze the user's facial expression and voice tone, acquiring emotional data such as whether the user is stressed or relaxed.

[1764] 3. Utilization of foreign workers

[1765] In the recruitment of foreign workers, the server collects recruitment information and the worker's emotional data into a database. Users submit recruitment requests for foreign workers from their terminals. The server selects the most suitable candidates based on language skills, qualifications, experience, and emotional status, and provides information and contact details of the selected candidates through the terminals.

[1766] 4. Introduction of technology

[1767] The server monitors the use of technology in healthcare and welfare settings and uses emotion recognition technology to evaluate users' feelings towards using that technology. The server suggests technology tools and applications to users according to their needs and evaluates whether users accept the suggestions using their devices. Once a technology is approved for use, the server deploys it to the field, and its usage and emotional data are monitored in real time.

[1768] The following scenarios are possible as specific examples of its use.

[1769] If some users are unfamiliar with a new nursing record application implemented at a medical facility, the emotion recognition engine detects their confusion or stress. The server then suggests a simpler interface and provides additional training. This information is communicated to the user via their device to improve user satisfaction.

[1770] The following are examples of prompt statements.

[1771] When writing feedback on a scenario where an operator is experiencing high stress while learning to operate a new machine, please generate a prompt using the following format:

[1772] 1. An emotion engine that recognizes the worker's emotions detects high stress.

[1773] 2. The system automatically suggests breaks and notifies workers with feedback.

[1774] The hardware used includes a camera, microphone, and terminal, while the software used includes OpenCV, Keras / TensorFlow, and SpeechRecognition (a Python library).

[1775] Such a system will streamline various processes related to education in the medical and welfare fields, recruitment of foreign workers, and introduction of technology, and will enable appropriate responses based on the user's emotional state.

[1776] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1777] Step 1:

[1778] The server stores the latest training data (videos, text, quizzes, etc.) in the medical and welfare fields into a database. This includes data collection, classification, and storage. The input is the latest training data, and the output is the data stored in the database. Specifically, it uploads the collected training data to the database in a specified format.

[1779] Step 2:

[1780] Users apply for training through their device. Input is the user's application information (skills, goals, schedule), and output is a confirmation message indicating that the application has been completed. Specifically, the user enters the required information into the application form via the device's user interface and sends it to the server.

[1781] Step 3:

[1782] The server generates an optimal training plan considering the user's skill level, schedule, and emotional state. The input is the user's application information and emotional data, and the output is the optimized training plan. Specifically, it uses emotion recognition technology to acquire the user's emotional data in real time and then uses an algorithm to calculate the optimal plan based on that data.

[1783] Step 4:

[1784] The terminal notifies the user of the generated training plan, and the user begins training based on that plan. The input is the training plan, and the output is the plan notified to the user and real-time feedback. Specifically, it displays the details of the plan on the user interface and reports the progress to the server in real time.

[1785] Step 5:

[1786] The server uses emotion recognition technology to evaluate the user's emotional state in real time. The input is data from the user's face and voice, and the output is the emotion evaluation result. Specifically, it analyzes data collected from the camera and microphone to determine the user's emotional state.

[1787] Step 6:

[1788] The server collects recruitment information and sentiment data of foreign workers into a database and processes recruitment requests from the user's terminal. Inputs are information about foreign workers and user requests, and output is the selection of the most suitable candidates. Specifically, it uses an algorithm to select candidates based on the collected information and provides that information to the user's terminal.

[1789] Step 7:

[1790] The server monitors the use of technology in medical and welfare settings and evaluates it using emotion recognition technology. Inputs are data on the technology being used and emotion data, while output is the evaluation result of the usage status. Specifically, it analyzes usage data and emotion data of the technology tools and monitors user responses in real time.

[1791] Step 8:

[1792] The server proposes technical tools and applications to the user based on their needs, and the user evaluates whether they accept the proposal using a terminal. Inputs are information about the technical tools and applications, as well as user feedback, while outputs are the adopted technology and its usage status. Specifically, it uses a matching algorithm to propose the most suitable technology and collects feedback on it.

[1793] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1794] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1795] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[1796] [Fourth Embodiment]

[1797] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1798] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1799] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1800] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[1801] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1802] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1803] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1804] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[1805] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1806] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1807] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1808] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1809] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1810] This invention is a system that supports the resolution of labor shortages and efficient business operations in the medical and welfare fields. Specific embodiments for implementing this invention are described below.

[1811] 1. Expansion of education and training

[1812] The server stores the latest training data (videos, text, quizzes, etc.) in the medical and welfare fields in its database. Users apply via their terminals, specifying their skill level and desired training program. The server generates an optimal training plan considering the user's skill level and schedule. The generated training plan is notified to the user via their terminal, and the progress of each training session is reported to the server in real time. This provides individually optimized educational plans and efficiently supports skill development.

[1813] As a concrete example, suppose a user wishes to receive online training to improve their caregiving skills. The user submits a training request from their device. The server considers the user's current skill level and available time, and generates a training plan combining video materials on basic caregiving techniques and quiz-style tests, which is then provided to the user. The user proceeds with the training according to this plan, and their device reports their progress to the server.

[1814] 2. Utilization of foreign workers

[1815] The server collects recruitment information from global job sites and agencies into its database. Users submit recruitment requests for foreign workers with specific skills and qualifications from their terminals. Based on the collected data, the server selects the best candidates based on language skills, qualifications, and experience, and provides detailed information to the terminals.

[1816] As a concrete example, suppose a user wants to hire foreign workers as nursing staff. The user sends a recruitment request from their device, specifying language skills and particular qualifications. The server searches for the most suitable candidates based on its database and notifies the user of the profiles and contact information of the selected candidates. The user then conducts interviews based on the provided information and makes a hiring decision.

[1817] 3. Utilization of technology

[1818] The server continuously monitors the usage of technical tools and applications used in healthcare and welfare settings. Based on demand, the server suggests the latest technical tools and applications to users. Users evaluate the suggestions via their terminals and decide whether to accept them. Approved technologies are then deployed to the field by the server, and their usage is monitored in real time.

[1819] For example, if a medical facility requests the automation of nursing records, the server will monitor the current manual record-keeping situation and, based on that information, suggest an appropriate automated record-keeping tool. After the user approves this suggestion on their terminal, the server will install the automated record-keeping tool and monitor its usage and effectiveness.

[1820] 4. Improvement of working conditions

[1821] The server periodically collects and analyzes data on the working environment in medical and welfare facilities. Users can input requests for improvements to the working environment via a terminal. Based on the collected data and user requests, the server proposes efficient improvement measures and notifies the user via the terminal. When work environment improvement proposals are implemented, the progress is reported to the server, ensuring continuous improvement.

[1822] For example, if a request for improvements to reduce staff stress is made at a nursing care facility, the server collects survey and sensor data, and based on the analysis results, proposes specific improvement measures to the user, such as introducing a relaxation space or revising the shift system. The user then checks the proposed measures on their terminal and puts them into action.

[1823] 5. Promoting regional cooperation

[1824] The server integrates and manages information about local healthcare and welfare resources in a database. Users submit requests for collaboration with local resources through their terminals. The server searches for appropriate local resources, generates a specific and actionable collaboration plan, and notifies the terminal. The progress of each collaboration step is reported to the server in real time.

[1825] For example, if an organization providing home care services wishes to expand its operations in collaboration with a local government, the user submits a collaboration request via their terminal. The server searches for appropriate local governments and related organizations based on database information, creates a specific collaboration plan, and provides it to the user. The user then proceeds with the collaboration according to this plan.

[1826] Thus, the present invention provides a comprehensive system for resolving labor shortages in the medical and welfare fields and improving operational efficiency.

[1827] The following describes the processing flow.

[1828] 1. Expansion of education and training

[1829] Processing steps

[1830] Step 1:

[1831] The server stores the latest training data (videos, text, quizzes, etc.) for the medical and welfare fields in a database. Specifically, it uses web crawling and APIs to collect reliable training materials, organizes them, and stores them in the database.

[1832] Step 2:

[1833] Users apply for training through their devices. Specifically, users access a dedicated application or web portal, log in, and then enter their skill level and preferred training dates and times into the application form.

[1834] Step 3:

[1835] The server generates an optimal training plan considering the user's skill level and schedule. Specifically, it uses an AI algorithm to analyze user data and training materials to create a personalized training plan.

[1836] Step 4:

[1837] The device notifies the user of the training plan. Specifically, it sends the user the details of the training plan via push notification or email, and also sends periodic reminders for training sessions.

[1838] Step 5:

[1839] The device reports training progress to the server in real time. Specifically, it has a function that automatically sends progress to the server each time the user completes a training session, and the server records the progress in a database and provides feedback as needed.

[1840] 2. Utilization of foreign workers

[1841] Processing steps

[1842] Step 1:

[1843] The server collects recruitment information for foreign workers into a database. Specifically, it periodically collects the latest job postings from global job sites and recruitment agencies, organizes them, and stores them in the database.

[1844] Step 2:

[1845] The user submits a request to hire foreign workers from their device. Specifically, the user fills out a request form on their device specifying the hiring requirements for workers with particular skills and qualifications, and then submits it.

[1846] Step 3:

[1847] The server selects the most suitable foreign worker based on the request. Specifically, it analyzes the request content and collected recruitment information using a matching algorithm to generate a list of optimal candidates.

[1848] Step 4:

[1849] The device provides the user with information and contact details of the selected personnel. Specifically, it displays the selected candidate's profile, past experience, contact information, and other details on the user's device.

[1850] 3. Utilization of technology

[1851] Processing steps

[1852] Step 1:

[1853] The server monitors the use of technology in medical and welfare settings. Specifically, it periodically collects, integrates, and analyzes usage data for tools and applications used in each setting.

[1854] Step 2:

[1855] The server proposes technical tools and applications to the user based on their needs. Specifically, it selects the most suitable tools and applications based on usage data and information on new technologies in the market, generates a list of suggestions, and notifies the user.

[1856] Step 3:

[1857] The user evaluates whether to accept the proposal using their device. Specifically, the user reviews the proposed technology, judges its usefulness, and sends feedback.

[1858] Step 4:

[1859] The server deploys approved technologies to healthcare and welfare settings and monitors their usage in real time. Specifically, it remotely configures technical tools, continuously collects and analyzes usage data after deployment, and provides support and feedback as needed.

[1860] 4. Improvement of working conditions

[1861] Processing steps

[1862] Step 1:

[1863] The server collects and analyzes working environment data from medical and welfare facilities. Specifically, it acquires data from regular surveys and sensors, integrates it, and analyzes it.

[1864] Step 2:

[1865] Users input requests for improvements to their work environment via their device. Specifically, users enter their complaints and requests for improvements regarding their work environment into a dedicated form and submit it.

[1866] Step 3:

[1867] Based on the data collected by the server and user requests, the system proposes improvement measures. Specifically, it generates concrete improvement plans based on insights gained from data analysis and notifies the user.

[1868] Step 4:

[1869] The device notifies the user of the proposed solutions and provides an implementation plan. Specifically, it provides the user with a guide that explains in detail the steps and schedule for implementing the improvement measures, and has a function to track progress.

[1870] 5. Promoting regional cooperation

[1871] Processing steps

[1872] Step 1:

[1873] The server integrates regional medical and welfare resource information into a database. Specifically, it collects, organizes, and centralizes resource information from medical institutions, welfare facilities, NPO organizations, and other organizations in each region.

[1874] Step 2:

[1875] Users submit requests to connect with local resources using their devices. Specifically, users fill out the required information in the request form on the top page and submit it.

[1876] Step 3:

[1877] The server searches for the most suitable regional resources and generates a collaboration plan. Specifically, it analyzes the request content and resource information using a matching algorithm to create a concrete collaboration plan.

[1878] Step 4:

[1879] The device notifies the user of the integration plan and reports its progress to the server. Specifically, it has the function to notify the user of the details of the integration plan via push notification and to report the execution status of each step to the server in real time.

[1880] Through the specific processing steps described above, the present invention provides a system that helps to alleviate labor shortages in the medical and welfare fields and improves operational efficiency.

[1881] (Example 1)

[1882] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1883] In the medical and welfare sector, numerous challenges exist, including a lack of education and training, difficulties in effectively utilizing foreign workers, and the need to introduce new technologies and improve working conditions on-site. These problems, lacking appropriate solutions, are contributing to a decline in the operational efficiency and service quality of medical and welfare facilities. This invention aims to resolve these challenges and provide a comprehensive system that enables efficient and effective support for medical and welfare operations.

[1884] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1885] In this invention, the server includes means for storing the latest training data in the medical and welfare fields in a database, means for users to apply for training via a terminal, means for generating an optimal training plan considering the user's skill level and schedule, and means for optimizing this generated plan using a generation AI model, means for the terminal to notify the user of the training plan and report the training progress to the server in real time, means for collecting recruitment information for foreign workers in a database, means for users to submit recruitment requests for foreign workers via a terminal, means for selecting and notifying the user of the most suitable personnel based on language skills, qualifications, experience, etc., and means for this selection using a generation AI model, means for the terminal to provide the user with information and contact details of the selected personnel, means for monitoring the status of technology utilization in medical and welfare settings, means for proposing technology tools and applications to the user according to demand, means for the user to evaluate whether to accept the proposal using a terminal, and means for introducing approved technologies and monitoring their usage in real time. This makes it possible to alleviate labor shortages in the medical and welfare fields, improve the efficiency of education and training, effectively utilize foreign workers, appropriately introduce technology, and continuously improve the working environment.

[1886] The "medical and welfare field" refers to a broad range of operations and services related to medical care and welfare.

[1887] "Education and training" refers to training and learning activities aimed at improving skills and knowledge.

[1888] A "server" refers to a computer system that manages and processes data via a network.

[1889] A "database" refers to a structured collection of data that efficiently stores, searches, and manages large amounts of data.

[1890] "User" refers to an individual or group that operates or uses this system.

[1891] "Terminal" refers to a computer or smart device used by a user to access a system.

[1892] A "training plan" refers to a specific educational and training schedule designed to improve the user's skills.

[1893] A "generative AI model" refers to an algorithm that uses artificial intelligence to automatically generate optimal solutions and plans.

[1894] "Foreign workers" refers to people who come from outside the country to work.

[1895] "Recruitment information" refers to information about job seekers and employers, such as job advertisements and recruitment details.

[1896] "Technical tools" refer to technical devices and applications that help improve the efficiency and quality of work.

[1897] "Monitoring" refers to the act of continuously observing and recording specific situations or data.

[1898] "Notification" refers to the act of transmitting information or messages in real time.

[1899] A "progress report" refers to reporting on the progress of a specific task or project.

[1900] "Evaluation" refers to making a value judgment about a particular element or action.

[1901] "Real-time" refers to the processing of data and the transmission of information occurring almost simultaneously.

[1902] A "proposal" refers to the act of recommending a specific action or measure.

[1903] Modes for carrying out the invention

[1904] This invention is a comprehensive system that supports the resolution of labor shortages and the improvement of operational efficiency in the medical and welfare fields. The system of this invention utilizes the latest technology and has functions that enable the expansion of education and training, effective utilization of foreign workers, on-site technology introduction, and continuous improvement of the working environment.

[1905] System Configuration

[1906] 1. Expansion of education and training

[1907] The server stores the latest training data (videos...

Claims

1. This is a system to expand education and training in the medical and welfare fields. A means of storing the latest training data in the medical and welfare fields in a database, A means for users to apply for training via their devices, A means of generating an optimal training plan that takes into account the user's skill level and schedule, A means for the device to notify the user of the training plan and report the training progress in real time, A system that includes this.

2. A system for utilizing foreign workers, A means of collecting information on the employment of foreign workers into a database, A means for users to submit requests for hiring foreign workers from their devices, A means of selecting and notifying the most suitable personnel based on language skills, qualifications, experience, etc. A means of providing users with information and contact details of selected personnel, The system according to claim 1, including the following:

3. This is a system for utilizing technology in the medical and welfare fields. A means of monitoring the status of technology use in medical and welfare settings, A means of proposing technical tools and applications to users that meet their needs, A means for users to evaluate whether they accept the proposal using their device, The system implements approved technologies and provides a means to monitor their usage in real time. The system according to claim 1, including the following:

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