System

Abstract

A system is provided.SOLUTION: A system comprising: means for automatically listing services suitable for disabled persons based on data input from a company; means for transmitting a list of services suitable for disabled persons to the company; means for listing candidates for disabled persons matching a desire of the company from a database; means for generating a customized training program based on training requirements of the company; means for answering questions related to disabled person employment in real time; and means for analyzing daily report data and detecting abnormalities.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Although companies are obligated to employ people with disabilities, many companies are unable to meet the legal employment rate. The main reasons for this include the difficulty of selecting work suitable for people with disabilities, a complicated recruitment process, a lack of appropriate training programs, and a lack of real-time support. It is also difficult to constantly keep track of the work progress and status of people with disabilities, which can make it difficult to take prompt action when an abnormality occurs. There is a need to resolve these issues. [Means for solving the problem]

[0005] The present invention solves the above problems by the following means. First, it provides a means for automatically creating a list of jobs suitable for people with disabilities using a generative AI model based on data input from companies. This list is sent to companies in real time. Next, it introduces a means for selecting candidates with disabilities from a database that match the company's preferences, reducing the complexity of recruiting. Furthermore, it adds a means for the generative AI model to generate customized training programs based on the company's training requirements, helping to improve the skills of people with disabilities. It also provides a means for an AI chatbot to answer questions about hiring people with disabilities in real time, strengthening support for company personnel and disabled workers. Finally, it introduces a means for analyzing daily report data and detecting anomalies, and by notifying company personnel of alerts based on the detected anomalies, it promotes early problem resolution.

[0006] "Input" refers to the data that a company enters into a system.

[0007] "Data-based" refers to processing based on information input by the company.

[0008] "Work suitable for people with disabilities" refers to work that is designed to allow disabled workers to engage in it appropriately.

[0009] "Means for automatically listing tasks" refers to a function that uses a generative AI model to select tasks suitable for people with disabilities and compile them into a list.

[0010] "Means for sending to the company" refers to the function of transmitting the generated business list to the company's person in charge.

[0011] "Disabled candidates who meet the company's requirements" are disabled people who meet the conditions and skills required by the company.

[0012] "Means of listing from a database" refers to the function of extracting candidates who meet the company's requirements from the data on disabled people in the database.

[0013] "Training requirements" refer to the skills and abilities that companies require from disabled workers.

[0014] A "customized training program" is an educational program individually designed by a generative AI model based on a company's training requirements.

[0015] "Real-time response means" refers to the ability of an AI chatbot to respond to user questions almost instantly.

[0016] "Daily report data" refers to data in which disabled workers report on the progress and work content of their daily work.

[0017] "Means for detecting anomalies" refers to the function of analyzing collected data and automatically detecting abnormal conditions or problems.

[0018] "Notifying company personnel of an alert" refers to a function that promptly notifies company personnel when an abnormality is detected. [Brief explanation of the drawings]

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

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

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

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

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

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

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

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

[0027] [First embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

[0040] This invention provides a total support system that enables companies to smoothly recruit and employ people with disabilities and provide continuous support. This system uses a generative AI model to automatically create a list of jobs suitable for people with disabilities based on data input from the company and sends the list to the company. It also includes a means for selecting candidates with disabilities who meet the company's requirements from a database and a means for the generative AI model to generate a customized training program based on the company's training requirements. Furthermore, the system has a means for using an AI chatbot to answer questions about the employment of people with disabilities in real time and a means for analyzing daily report data, detecting anomalies, and notifying company personnel.

[0041] Natural language description of the program

[0042] 1. The user (company representative) enters information such as an overview of their company's business, number of employees, required skill sets, and the purpose of employing people with disabilities on a dedicated terminal.

[0043] Example: A company employee types into a terminal, "We would like to hire one person to perform data entry work."

[0044] 2. The terminal formats the input data and sends it to the server, which stores it in a database.

[0045] Example: The terminal sends information such as "Data entry work, 1 position" to the server, which then stores it in a database.

[0046] 3. The server sends the received data to a generative AI model, which automatically generates a list of jobs suitable for people with disabilities. This list is then immediately sent to the company's representative.

[0047] Example: The AI ​​model creates a list of "the best candidates for data entry work are A, B, and C" and notifies the person in charge.

[0048] 4. The server searches a database of people with disabilities and lists candidates with disabilities who meet the company's requirements.

[0049] Example: The server creates a list of suitable candidates based on data such as "Person A needs visual assistance, Person B is fully visually capable, and Person C needs audio assistance."

[0050] 5. The server uses the generative AI model to generate a customized training program based on the company's training requirements, and sends the program to the company's personnel and disabled workers.

[0051] Example: AI generates training programs such as "basics of data entry, how to use visual support tools, and regular skill checks" and sends them to staff and people with disabilities.

[0052] 6. An AI chatbot will be available 24 hours a day to answer questions about employment for people with disabilities in real time.

[0053] Example: A company representative asks a chatbot, "What visual aid tools do you recommend?" and the chatbot immediately replies, "We recommend screen reader software."

[0054] 7. The server receives the daily report data entered by the disabled worker or the person in charge and analyzes the data using an anomaly detection algorithm. If an anomaly is detected, an alert is sent to the company's person in charge.

[0055] Example: A disabled worker writes in his daily report that "I was unable to work today due to poor health," and the server detects this information and alerts the person in charge that "urgent action is required."

[0056] This will enable companies to streamline the entire process of recruiting, training, and supporting people with disabilities, and provide ongoing support.

[0057] The processing flow will be explained below.

[0058] Step 1:

[0059] The user (company representative) operates the terminal to input information such as an overview of the company's business, number of employees, required skill sets, and the purpose of employing people with disabilities.

[0060] Example: A company employee types into a terminal, "We would like to hire one person to perform data entry work."

[0061] Step 2:

[0062] The terminal formats the data entered by the user and sends the data to the server.

[0063] Example: The terminal sends information such as "Data entry work, 1 position available" to the server.

[0064] Step 3:

[0065] The server stores the received data in a database.

[0066] Example: A server stores information such as "Data entry job, 1 position available" in a database.

[0067] Step 4:

[0068] The server sends the stored data to the generative AI model.

[0069] Example: The server sends the information "data entry work, number of positions available: 1" to the generative AI model.

[0070] Step 5:

[0071] The generative AI model analyzes the received data and automatically creates a list of tasks suitable for people with disabilities.

[0072] Example: The AI ​​model creates a list of candidates with disabilities who are best suited for data entry work: A, B, and C.

[0073] Step 6:

[0074] The server sends the generated list of tasks to the company representative.

[0075] Example: The server sends a list of information about "Mr. A, Mr. B, and Mr. C" to a company representative.

[0076] Step 7:

[0077] The server searches a database of people with disabilities and lists candidates with disabilities who meet the company's requirements.

[0078] Example: The server creates a list of suitable candidates based on data such as "Person A needs visual assistance, Person B is fully visually capable, and Person C needs audio assistance."

[0079] Step 8:

[0080] The server sends detailed information of the listed suitable candidates to the company representative.

[0081] Example: The server sends detailed information about "Mr. A, Mr. B, and Mr. C" to the person in charge.

[0082] Step 9:

[0083] The server generates a customized training program using a generative AI model based on the company's training requirements.

[0084] Example: AI generates customized training programs such as "basics of data entry, how to use visual support tools, and regular skill checks."

[0085] Step 10:

[0086] The server transmits the generated training program to the company personnel and the disabled workers.

[0087] Example: A server sends training programs to personnel and workers, such as "Basics of data entry, how to use visual aids, and regular skill checks."

[0088] Step 11:

[0089] The user (company representative or disabled worker) enters a question into the AI ​​chatbot.

[0090] Example: A company representative asks the chatbot, "What visual support tools do you recommend?"

[0091] Step 12:

[0092] The terminal transmits the entered question to the server.

[0093] Example: A device sends a question to a server: "What visual support tools do you recommend?"

[0094] Step 13:

[0095] The server analyzes the question and requests the appropriate answer from the generative AI model.

[0096] Example: The server sends the analysis results of a "question about visual support tools" to a generative AI model.

[0097] Step 14:

[0098] The generative AI model generates an appropriate answer based on the question and returns it to the server.

[0099] Example: An AI model generates the answer "Screen reader software is recommended."

[0100] Step 15:

[0101] The server generates a response and sends it back to the terminal.

[0102] Example: The server sends a response to the device saying "Screen reader software is recommended."

[0103] Step 16:

[0104] The device displays the answer on the screen.

[0105] Example: The device displays the response "Screen reader software recommended" on the screen.

[0106] Step 17:

[0107] The user (disabled worker or person in charge) enters the daily report data into the terminal.

[0108] Example: A disabled worker writes in his daily report, "I was unable to work today due to poor health."

[0109] Step 18:

[0110] The terminal transmits the input daily report data to the server.

[0111] Example: A terminal sends daily report data to a server stating, "I was unable to work today due to poor health."

[0112] Step 19:

[0113] The server analyzes the received daily report data using an anomaly detection algorithm.

[0114] Example: The server runs the "illness" information through an anomaly detection algorithm.

[0115] Step 20:

[0116] If the server detects an abnormality, it will send an alert to company personnel.

[0117] Example: A server sends an "urgent action required" alert to a company representative.

[0118] Example 1

[0119] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0120] The goal is to solve the many challenges that arise when companies hire and employ people with disabilities. Conventional methods require time and effort to create a list of jobs suitable for people with disabilities, identify suitable candidates, create training programs, and detect anomalies in daily report data, making these tasks inefficient. Furthermore, there are no adequate means to respond to questions about hiring people with disabilities in real time.

[0121] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0122] In this invention, the server includes means for automatically creating a list of jobs suitable for persons with disabilities based on data input from a terminal, means for sending the list of jobs suitable for persons with disabilities to a company, means for compiling a list of disabled candidates from a database that meets the company's preferences, means for using a generative AI model to create a customized training program based on the company's training requirements, means for using an AI chatbot to answer questions about the employment of persons with disabilities in real time, means for analyzing daily report data, detecting anomalies, and notifying company personnel, and means for formatting input data from the terminal and sending it to the server. This makes it possible to select jobs and candidates suitable for persons with disabilities based on data input from the terminal, provide customized training programs, respond to questions about the employment of persons with disabilities in real time, and detect and notify anomalies in daily report data.

[0123] A "terminal" is a hardware device for inputting and displaying data.

[0124] A "server" is a hardware and software configuration for storing, processing, sending and receiving data over a network.

[0125] A "generative AI model" is an algorithm that uses artificial intelligence technology to automate and optimize specific tasks.

[0126] A "list" is a collection of data that is organized and categorized based on specific criteria.

[0127] A "database" is a software system for efficiently storing, searching, and managing large amounts of data.

[0128] "Training Program" means an educational or training plan designed to acquire specific skills or knowledge.

[0129] An "AI chatbot" is a program that uses artificial intelligence technology to automatically hold conversations and provide answers to users' questions in real time.

[0130] "Daily report data" refers to information that records the progress of work and working conditions.

[0131] An "anomaly detection algorithm" is a computational method for analyzing data and detecting unusual patterns or anomalies.

[0132] An "alert" is a notification that notifies you of an abnormality or important information.

[0133] A "customized training program" is an education and training plan that is tailored to the requirements of a specific company or individual.

[0134] "Input data" refers to information entered into the system via a terminal.

[0135] "Real-time" refers to a state in which data processing and information provision are carried out immediately.

[0136] This is a total support system that enables companies to smoothly recruit, employ, and continuously support people with disabilities. The system is implemented using a server, terminals, a generative AI model, a database, and an AI chatbot.

[0137] First, the user (company representative) enters information such as the job summary, number of employees, required skill set, and purpose of hiring people with disabilities into a dedicated terminal. This information is necessary to clarify the skills and conditions that the company is looking for in people with disabilities. As a concrete example, the user might enter the following into the terminal: "We would like to hire one person to do data entry work. Visual assistance is required."

[0138] Next, the terminal formats the input data and sends it to the server. The formatted data is converted into a format that the server can easily accept, such as JSON. For example, the terminal converts information such as "Task: Data entry, Number of people: 1, Visual support: Required" into JSON format and sends it to the server.

[0139] The server stores the received data in a database. At the same time, it sends the data to the generative AI model and instructs it to analyze it. The generative AI model automatically creates a list of tasks suitable for people with disabilities based on the data entered from the device. This list includes specific tasks suitable for people with disabilities and candidates based on the company's requirements. As a concrete example, the generative AI model creates a list such as "The best candidates for data entry work are Person A, Person B, and Person C," and the server sends this list to the company employee's device.

[0140] The server then searches a database of people with disabilities and creates a list of candidates who meet the company's requirements. The list includes the skillsets and support required by each person with a disability. For example, the server creates a list based on data such as "Person A needs visual support, Person B needs voice support, and Person C needs physical support," and sends it to the company's representative.

[0141] The server also uses a generative AI model to generate a customized training program based on the company's training requirements. This program is tailored to each company's specific needs. The generated program is then sent to the company's personnel and disabled workers. For example, the AI ​​generates a training program titled "Basics of data entry, how to use visual aids, and regular skill checks," and sends it to the company's personnel and disabled workers via email.

[0142] An AI chatbot is available 24 hours a day to answer questions about the employment of people with disabilities in real time. This AI chatbot uses natural language processing technology to answer questions from users. For example, if a company representative asks the chatbot, "What visual assistance tools do you recommend?", the chatbot will immediately reply, "We recommend screen reader software."

[0143] Finally, the server analyzes the daily report data and notifies company personnel if an abnormality is detected. When disabled workers or personnel enter daily report data into their terminals, the server analyzes the data using an anomaly detection algorithm, and if an abnormality is detected, it notifies company personnel as an alert. For example, if a disabled worker enters in their daily report that "I was unable to work today due to poor health," the server analyzes the information and sends an alert to company personnel that "urgent action is required."

[0144] Prompt Sentence Examples

[0145] Job Listing: "Job Description: Data Entry. Position: 1. Please list suitable candidates."

[0146] Candidate Listing: "Company Request: Please list candidates who can handle data entry work."

[0147] Training Program Generation: "Training Requirements: Please generate a training program that includes training content on basic data entry skills and how to use visual aids."

[0148] Chatbot response example: "Question about employment for people with disabilities: What visual aids do you recommend?"

[0149] Anomaly detection: "Daily report data analysis: It is stated that the employee was unable to work today due to poor health. Please detect any anomalies and notify us."

[0150] These components enable companies to streamline the entire process of hiring, training, and supporting people with disabilities, and provide continuous support. By utilizing generative AI models and AI chatbots, the system achieves automation and real-time responses, contributing to companies' promotion of hiring people with disabilities.

[0151] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0152] Step 1:

[0153] The user (company representative) enters information such as the business overview, number of employees, required skill sets, and purpose of employing people with disabilities on a dedicated terminal.

[0154] Input: Details such as job description, number of employees, skill set, and employment objectives

[0155] Output: Formatted input data

[0156] Specific example of operation: A company representative enters detailed information into the input field on the terminal, such as "We would like to hire one person for data entry work. Visual assistance is required.", and presses the send button.

[0157] Step 2:

[0158] The terminal formats the input data and sends it to the server.

[0159] Input: Entered business information, number of employees, skill sets, employment purpose

[0160] Output: Formatted data such as JSON

[0161] Specific example of operation: The terminal converts the information "Task: Data entry, Number of people: 1, Visual support: Required" into JSON format and sends it to the server.

[0162] Step 3:

[0163] The server stores the received data in a database and simultaneously sends the data to the generative AI model, instructing it to analyze it.

[0164] Input: Formatted input data

[0165] Output: Data stored in a database, data sent to a generative AI model

[0166] Specific example of operation: The server records the data "Task: Data entry, Number of people: 1, Visual support: Required" in the database and requests the generative AI model to analyze it.

[0167] Step 4:

[0168] The generative AI model automatically creates a list of jobs suitable for people with disabilities based on the data it receives, and the server sends that list to the company's representative.

[0169] Input: Data sent to the generative AI model

[0170] Output: List of jobs suitable for people with disabilities, notified list

[0171] Specific example of operation: The generative AI model creates a list of "the best candidates for data entry work are A, B, and C," and the server sends this to the company employee's device.

[0172] Step 5:

[0173] The server searches a database of people with disabilities and lists candidates with disabilities who meet the company's requirements.

[0174] Input: Company preferences and disability database

[0175] Output: A list of possible matching disabilities

[0176] Specific example of operation: The server creates a list based on data such as "Person A needs visual assistance, Person B needs audio assistance, and Person C needs physical assistance" and sends it to the company representative.

[0177] Step 6:

[0178] The server uses a generative AI model to generate a customized training program based on the company's training requirements and sends it to company personnel and disabled workers.

[0179] Input: Training requirements, analysis data for the generative AI model

[0180] Output: Customized training program, transmitted program

[0181] Specific example of how it works: The AI ​​generates a training program on "basics of data entry, how to use visual support tools, and regular skill checks" and sends it via email to company representatives and disabled workers.

[0182] Step 7:

[0183] An AI chatbot is available 24 hours a day to answer questions about employment for people with disabilities in real time.

[0184] Input: User question

[0185] Output: Answer by AI chatbot

[0186] A specific example of how it works: A company representative asks the chatbot, "What visual support tools do you recommend?" and the chatbot immediately replies, "We recommend screen reader software."

[0187] Step 8:

[0188] The server analyzes the daily report data and notifies company personnel if an abnormality is detected.

[0189] Input: Daily report data, anomaly detection algorithm

[0190] Output: Alert notification when an abnormality is detected

[0191] A concrete example of how it works: When a disabled worker enters in their daily report that "I was unable to work today due to poor health," the server analyzes the information and alerts company personnel that "urgent action is required."

[0192] (Application example 1)

[0193] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0194] In modern manufacturing, employing people with disabilities is important from the perspective of corporate social responsibility and diversity. However, many companies face the challenge of finding appropriate work and training programs to provide a safe and efficient working environment for people with disabilities. In particular, when employing people with disabilities in factories, support is required to ensure both safety and efficiency, but the reality is that the technological means to achieve this are not fully in place.

[0195] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0196] In this invention, the server includes means for automatically creating a list of jobs suitable for persons with disabilities based on data input from a company, means for sending the list of jobs suitable for persons with disabilities to the company, means for compiling a list of disabled candidates from a database that meets the company's preferences, means for creating a customized training program based on the company's training requirements, means for answering questions about the employment of persons with disabilities in real time, means for analyzing daily report data and detecting abnormalities, means for providing support for persons with disabilities to work safely and efficiently in factories, and means for displaying the created job list and training program on a smart device in real time. This enables companies to provide comprehensive support for persons with disabilities, from hiring to training and daily operations, enabling them to work safely and efficiently.

[0197] An "enterprise" is a corporation or individual that conducts economic activities as an organization and provides goods and services.

[0198] "Input data" refers to the information that companies enter into the system, including details of the business, number of employees, required skill sets, and the purpose of employing people with disabilities.

[0199] "Disabled persons" refers to people with physical, mental or sensory impairments who may require special assistance or accommodations.

[0200] "Means for automatically listing tasks" refers to a function that uses a generative AI model to analyze input data and automatically list tasks suitable for people with disabilities.

[0201] "Means for sending the list to the company" refers to a function for electronically notifying the person in charge at the company of the generated business list.

[0202] A "database" is a collection of information that stores information and manages it in an organized manner, allowing it to be searched and listed efficiently.

[0203] "Means for generating training programs" refers to the ability to automatically generate customized training programs using generative AI models based on a company's training requirements.

[0204] "Real-time response means" refers to the ability to instantly provide answers to questions about employment for people with disabilities using generative AI models.

[0205] "Daily report data" refers to records used by disabled workers or those in charge to report on their daily work status, health condition, etc.

[0206] "Means for detecting abnormalities" refers to the function of analyzing daily report data and automatically detecting abnormalities that differ from normal work or health conditions.

[0207] "Measures to provide support within the factory" refers to the technical and human support systems that provide an environment in which persons with disabilities can work safely and efficiently within the factory.

[0208] A "smart device" is a portable electronic device that is capable of connecting to the Internet and has advanced computing power and is capable of running applications, and includes smartphones, smart glasses, head-mounted displays, etc.

[0209] "A means to view generated work lists and training programs in real time" refers to the function that allows generated work lists and training programs to be instantly checked via a smart device.

[0210] The system of the present invention provides total support for companies to smoothly recruit and employ people with disabilities and provide continuous support. This system uses a generative AI model to automatically create a list of jobs suitable for people with disabilities based on data input from the company and transmits the list to the company. It also includes a database listing candidates with disabilities who meet the company's requirements, and a generative AI model to generate a customized training program based on the company's training requirements. Furthermore, the system provides real-time answers to questions about the employment of people with disabilities using an AI chatbot, and a means for analyzing daily report data, detecting abnormalities, and notifying company personnel. When applied to factories, the system supports people with disabilities in working safely and efficiently, allowing them to access necessary information in real time on smart devices.

[0211] The server receives information entered by companies, such as job descriptions, number of employees, required skill sets, and the purpose of hiring people with disabilities, formats it, and stores it in a database. This data is then sent to a generative AI model, which creates a list of jobs suitable for people with disabilities. The generated list of jobs is immediately notified to company personnel. Similarly, the system also has the function of listing candidates with disabilities from the database. This allows companies to quickly find suitable candidates with disabilities.

[0212] Based on the training requirements of the company, the server uses a generative AI model to generate a customized training program.An AI chatbot is also installed, which can provide instant answers to questions about disability employment from company personnel and disabled workers.

[0213] For daily report data, disabled workers or staff enter information about their daily work and health into a terminal and send it to a server. The server analyzes this data and notifies the company staff if it detects any abnormalities. This anomaly detection uses an algorithm that automatically detects abnormalities that differ from normal work or health conditions.

[0214] The system also includes a means to enable workers with disabilities to access generated job lists and training programs in real time using smart devices, enabling them to work safely and efficiently in factories.

[0215] As a concrete example, consider the case where a company employee inputs, "We would like to hire one worker with basic machine operation skills." This data is sent to the server, and the generative AI model generates a list of suitable tasks, such as "simple machine operation, parts assembly, and shipping preparation." This list is notified to the employee, who then generates a customized training program, such as "basic machine operation training, explanation of assembly procedures, and shipping preparation methods." The employee can also ask, "What visual support tools do you recommend?" and the AI ​​chatbot can respond, "Screen reader software is recommended."

[0216] Here are some examples of prompts to input to the generative AI model:

[0217] 1. Generate a list of tasks:

[0218] Company information: Major manufacturing company, 500 employees, required skill set is basic machine operation, purpose of employing people with disabilities is to promote diversity and contribute to society

[0219] Generate a suitable task list.

[0220] 2. Generating training programs:

[0221] Job List: Simple machine operation, parts assembly, shipping preparation

[0222] Generate a training program based on this.

[0223] 3. Real-time chat support:

[0224] Disability employment question: What visual aids do you recommend?

[0225] Please respond in real time.

[0226] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0227] Step 1:

[0228] A user uses a dedicated terminal to input company information, including a business overview, number of employees, required skill sets, and the purpose of hiring people with disabilities. This data is formatted by the terminal and sent to the server. The input data on the terminal is, "We would like to hire one worker who can operate basic machines."

[0229] Step 2:

[0230] The server stores the received company information in a database. Specifically, it converts the input data into an appropriate format and stores it in the database. For example, information such as "basic machine operation, number of employees: 1" is stored.

[0231] Step 3:

[0232] The server sends the saved company information to the generative AI model, which then analyzes the input data using prompts and generates a list of tasks suitable for people with disabilities. The generated list of tasks is called "simple machine operation, parts assembly, and shipping preparation."

[0233] Step 4:

[0234] The server receives the task list generated by the generative AI model and sends it to the company's personnel. This includes sending notifications containing the task list via email or notification system. The output is "Suitable task list: simple machine operation, parts assembly, and shipping preparation."

[0235] Step 5:

[0236] The server searches the database and lists candidates with disabilities who meet the company's requirements. The search results are a list of suitable candidates such as "Mr. A, Mr. B, Mr. C."

[0237] Step 6:

[0238] The server uses a generative AI model to generate a customized training program based on the company's training requirements. The training program generated by this prompt is "Training basic machine operation, explaining assembly procedures, and how to prepare for shipment."

[0239] Step 7:

[0240] The server sends the generated training program to company personnel and disabled workers. This includes sending notifications containing the training program details via email and notification systems. The output is "specific training program details."

[0241] Step 8:

[0242] A user inputs a question about employment for people with disabilities into the AI ​​chatbot, for example, "What visual assistive tools do you recommend?"

[0243] Step 9:

[0244] The AI ​​chatbot answers questions in real time, using a generative AI model to generate appropriate answers and provide them to the user. The output is an immediate response such as "Screen reader software recommended."

[0245] Step 10:

[0246] The user inputs daily report data into the terminal, and the server receives the data. For example, the daily report may include, "I was not feeling well today and was unable to work."

[0247] Step 11:

[0248] The server analyzes the daily report data and detects anomalies. If an anomaly is detected, the server sends a notification to the company's responsible person. The output is an alert stating "Anomaly detected: Notify responsible person."

[0249] Step 12:

[0250] Users can view the generated work lists and training programs in real time using smart devices such as smartphones, smart glasses, and head-mounted displays.

[0251] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0252] This invention provides a system that provides more effective support by combining an emotion engine with a total support system that enables companies to smoothly recruit, employ, and sustainably support people with disabilities. This system includes a means for automatically creating a list of tasks suitable for people with disabilities using a generative AI model based on data input from the company and sending that list to the company. It also includes a means for selecting candidates with disabilities who meet the company's requirements from a database and a means for generating a customized training program using the generative AI model based on the company's training requirements. Furthermore, it includes a means for using an AI chatbot to answer questions about the employment of people with disabilities in real time and a means for analyzing daily report data, detecting anomalies, and notifying company personnel. In addition, by incorporating an emotion engine, the system can recognize user emotions and use them for analysis and customizing support content.

[0253] Natural language description of the program

[0254] 1. The user (company representative) enters information such as an overview of their company's business, number of employees, required skill sets, and the purpose of employing people with disabilities on a dedicated terminal.

[0255] Example: A company employee types into a terminal, "We would like to hire one person to perform data entry work."

[0256] 2. The terminal formats the data entered by the user and sends the data to the server.

[0257] Example: The terminal sends information such as "Data entry work, 1 position available" to the server.

[0258] 3. The server stores the received data in a database.

[0259] Example: A server stores information such as "Data entry job, 1 position available" in a database.

[0260] 4. The server sends the stored data to the generative AI model.

[0261] Example: The server sends the information "data entry work, number of positions available: 1" to the generative AI model.

[0262] 5. The generative AI model analyzes the received data and automatically creates a list of tasks suitable for people with disabilities.

[0263] Example: The AI ​​model creates a list of candidates with disabilities who are best suited for data entry work: A, B, and C.

[0264] 6. The server sends the generated list of tasks to the company representative.

[0265] Example: The server sends a list of information about "Mr. A, Mr. B, and Mr. C" to a company representative.

[0266] 7. The server searches the database of disabled people and lists candidates with disabilities who meet the company's requirements.

[0267] Example: The server creates a list of suitable candidates based on data such as "Person A needs visual assistance, Person B is fully visually capable, and Person C needs audio assistance."

[0268] 8. The server sends the details of the listed matching candidates to the company representative.

[0269] Example: The server sends detailed information about "Mr. A, Mr. B, and Mr. C" to the person in charge.

[0270] 9. The server generates a customized training program using the generative AI model based on the company's training requirements.

[0271] Example: AI generates customized training programs such as "basics of data entry, how to use visual support tools, and regular skill checks."

[0272] 10. The server sends the generated training program to the company's personnel and the disabled worker.

[0273] Example: A server sends training programs to personnel and workers, such as "Basics of data entry, how to use visual aids, and regular skill checks."

[0274] 11. The user (company representative or disabled worker) enters a question into the AI ​​chatbot.

[0275] Example: A company representative asks the chatbot, "What visual support tools do you recommend?"

[0276] 12. The terminal sends the entered question to the server.

[0277] Example: A device sends a question to a server: "What visual support tools do you recommend?"

[0278] 13. The server analyzes the question and requests the appropriate answer from the generative AI model.

[0279] Example: The server sends the analysis results of a "question about visual support tools" to a generative AI model.

[0280] 14. The generative AI model generates an appropriate answer based on the question and returns it to the server.

[0281] Example: An AI model generates the answer "Screen reader software is recommended."

[0282] 15. The server generates a response and sends it back to the device.

[0283] Example: The server sends a response to the device saying "Screen reader software is recommended."

[0284] 16. The device will display the answer on the screen.

[0285] Example: The device displays the response "Screen reader software recommended" on the screen.

[0286] 17. The emotion engine automatically identifies emotions from user input data and dialogue.

[0287] Example: An emotion engine identifies emotions such as "joy" or "anxiety" from user input and dialogue history.

[0288] 18. The emotion engine sends the identified emotion data to the server, which uses the emotion data for analysis.

[0289] Example: An emotion engine identifies the emotion "anxiety" and sends that information to a server.

[0290] 19. The server will also take emotional data into account to customize more appropriate training programs and support content.

[0291] Example: A server customizes a training program for users who feel "anxious," including relaxation techniques and encouragement.

[0292] 20. The user (disabled worker or person in charge) enters the daily report data into the terminal.

[0293] Example: A disabled worker writes in his daily report, "I was unable to work today due to poor health."

[0294] 21. The terminal sends the entered daily report data to the server.

[0295] Example: A terminal sends daily report data to a server stating, "I was unable to work today due to poor health."

[0296] 22. The server analyzes the received daily report data using an anomaly detection algorithm.

[0297] Example: The server runs the "illness" information through an anomaly detection algorithm.

[0298] 23. If the server detects an abnormality, it will send an alert to the company representative.

[0299] Example: A server sends an "urgent action required" alert to a company representative.

[0300] 24. The emotion engine analyzes daily report data as well as user emotions and customizes alert content based on that.

[0301] Example: The emotion engine analyzes the information "I am feeling unwell and anxious today" and notifies the person in charge that "special consideration is required."

[0302] This will enable companies to streamline the entire process of recruiting, training, and supporting people with disabilities, and also provide ongoing support that takes users' emotions into consideration.

[0303] The processing flow will be explained below.

[0304] Step 1:

[0305] The user (company representative) enters information such as the company's business overview, number of employees, required skill sets, and purpose of employing people with disabilities on the terminal.

[0306] Example: A company employee types into a terminal, "We would like to hire one person to perform data entry work."

[0307] Step 2:

[0308] The terminal formats the data entered by the user and sends the data to the server.

[0309] Example: The terminal sends information such as "Data entry work, 1 position available" to the server.

[0310] Step 3:

[0311] The server stores the received data in a database.

[0312] Example: A server stores information such as "Data entry job, 1 position available" in a database.

[0313] Step 4:

[0314] The server sends the stored data to the generative AI model.

[0315] Example: The server sends the information "data entry work, number of positions available: 1" to the generative AI model.

[0316] Step 5:

[0317] The generative AI model analyzes the received data and automatically creates a list of tasks suitable for people with disabilities.

[0318] Example: The AI ​​model creates a list of candidates with disabilities who are best suited for data entry work: A, B, and C.

[0319] Step 6:

[0320] The server sends the generated list of tasks to the company representative.

[0321] Example: The server sends a list of information about "Mr. A, Mr. B, and Mr. C" to a company representative.

[0322] Step 7:

[0323] The server searches a database of people with disabilities and lists candidates with disabilities who meet the company's requirements.

[0324] Example: The server creates a list of suitable candidates based on data such as "Person A needs visual assistance, Person B is fully visually capable, and Person C needs audio assistance."

[0325] Step 8:

[0326] The server sends detailed information of the listed suitable candidates to the company representative.

[0327] Example: The server sends detailed information about "Mr. A, Mr. B, and Mr. C" to the person in charge.

[0328] Step 9:

[0329] The server generates a customized training program using a generative AI model based on the company's training requirements.

[0330] Example: AI generates customized training programs such as "basics of data entry, how to use visual support tools, and regular skill checks."

[0331] Step 10:

[0332] The server transmits the generated training program to the company personnel and the disabled workers.

[0333] Example: A server sends training programs to personnel and workers, such as "Basics of data entry, how to use visual aids, and regular skill checks."

[0334] Step 11:

[0335] The user (company representative or disabled worker) enters a question into the AI ​​chatbot.

[0336] Example: A company representative asks the chatbot, "What visual support tools do you recommend?"

[0337] Step 12:

[0338] The terminal transmits the entered question to the server.

[0339] Example: A device sends a question to a server: "What visual support tools do you recommend?"

[0340] Step 13:

[0341] The server analyzes the question and requests the appropriate answer from the generative AI model.

[0342] Example: The server sends the analysis results of a "question about visual support tools" to a generative AI model.

[0343] Step 14:

[0344] The generative AI model generates an appropriate answer based on the question and returns it to the server.

[0345] Example: An AI model generates the answer "Screen reader software is recommended."

[0346] Step 15:

[0347] The server generates a response and sends it back to the terminal.

[0348] Example: The server sends a response to the device saying "Screen reader software is recommended."

[0349] Step 16:

[0350] The device displays the answer on the screen.

[0351] Example: The device displays the response "Screen reader software recommended" on the screen.

[0352] Step 17:

[0353] The emotion engine automatically identifies emotions from user input data and dialogue content.

[0354] Example: An emotion engine identifies emotions such as "joy" or "anxiety" from user input and dialogue history.

[0355] Step 18:

[0356] The emotion engine sends the identified emotion data to the server, which uses the emotion data for analysis.

[0357] Example: An emotion engine identifies the emotion "anxiety" and sends that information to a server.

[0358] Step 19:

[0359] The server also takes emotional data into account to customize more appropriate training programs and support content.

[0360] Example: A server customizes a training program for users who feel "anxious," including relaxation techniques and encouragement.

[0361] Step 20:

[0362] The user (disabled worker or person in charge) enters the daily report data into the terminal.

[0363] Example: A disabled worker writes in his daily report, "I was unable to work today due to poor health."

[0364] Step 21:

[0365] The terminal transmits the input daily report data to the server.

[0366] Example: A terminal sends daily report data to a server stating, "I was unable to work today due to poor health."

[0367] Step 22:

[0368] The server analyzes the received daily report data using an anomaly detection algorithm.

[0369] Example: The server runs the "illness" information through an anomaly detection algorithm.

[0370] Step 23:

[0371] If the server detects an abnormality, it will send an alert to company personnel.

[0372] Example: A server sends an "urgent action required" alert to a company representative.

[0373] Step 24:

[0374] The emotion engine analyzes daily report data as well as user emotions and customizes alert content based on that.

[0375] Example: The emotion engine analyzes the information "I am feeling unwell and anxious today" and notifies the person in charge that "special consideration is required."

[0376] Example 2

[0377] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0378] The current recruitment and hiring process for people with disabilities in companies is difficult to accommodate special needs and individual requirements, making it difficult to operate efficiently. Furthermore, there is insufficient support that takes into account the feelings and individual needs of people with disabilities, and there is no sustainable support system in place. This has led to a need for effective tools to facilitate the recruitment and hiring process for people with disabilities and provide continuous support.

[0379] The identification processing 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 automatically listing jobs suitable for persons with disabilities based on data input from a company, means for transmitting the list of jobs suitable for persons with disabilities to the company, means for listing disabled candidates who meet the company's preferences from a database, means for generating a customized training program based on the company's training requirements, emotion engine means for identifying and analyzing the user's emotions, means for providing customized support content using the emotion data, and means for customizing the content of alerts based on daily report data and emotion data. This enables companies to streamline the recruitment and employment process for persons with disabilities and provide continuous support that takes emotions into consideration.

[0380] A "company" refers to an organization that provides goods and services through business activities and aims to pursue profits.

[0381] "Input data" refers to information entered into the system by users, such as business overview, number of employees, required skill sets, and purpose of employing people with disabilities.

[0382] "Disabled person" refers to an employee or job applicant who has a physical or mental impairment and requires special assistance.

[0383] "Task list" refers to a list of specific tasks suitable for people with disabilities that is created through analysis by the generative AI model.

[0384] "Database" refers to structured data storage that allows a system to efficiently store, manage, and retrieve data.

[0385] A "generative AI model" refers to an artificial intelligence model that uses machine learning algorithms to analyze data and generate task lists and training programs.

[0386] "Customized training program" refers to training content that is tailored to meet the needs of specific individuals with disabilities based on the training requirements of the company.

[0387] "Real-time answers" refers to the ability to provide immediate responses to questions regarding employment of people with disabilities.

[0388] "Daily report data" refers to the data reported by disabled workers recording their daily work, physical condition, emotions, etc.

[0389] An "anomaly detection algorithm" refers to a calculation method for analyzing daily report data and detecting patterns that are out of the ordinary.

[0390] An "emotion engine" refers to technology or software for automatically identifying and analyzing emotions from user input data and dialogue content.

[0391] An "alert" refers to a warning message sent to notify users (company personnel) of abnormalities or important information detected by the system.

[0392] "Support content" refers to the specific advice, training and assistance provided to businesses and disabled workers.

[0393] This invention is a total support system that enables companies to smoothly recruit and employ people with disabilities and provide continuous support. This system uses a generative AI model to automatically create a list of jobs suitable for people with disabilities based on data input from the company and sends that list to the company. It also includes a means for selecting candidates with disabilities who meet the company's requirements from a database and a means for the generative AI model to generate a customized training program based on the company's training requirements. Furthermore, it provides a means for answering questions about the employment of people with disabilities in real time using an AI chatbot, and a means for analyzing daily report data, detecting anomalies, and notifying company personnel. In addition, by combining it with an emotion engine, the system can recognize user emotions and use them for analysis and customizing support content.

[0394] To implement this system, a server, a dedicated terminal, a generative AI model, a database, an anomaly detection algorithm, and an emotion engine are required. Below, we will explain in detail how the system works using these components.

[0395] The user, a company representative, first enters information on a dedicated terminal, such as an overview of the company's business, the number of employees, the required skill set, and the purpose of hiring people with disabilities. For example, a company representative might enter, "We would like to hire one person to perform data entry work."

[0396] The terminal formats the data entered by the user and sends it to the server. This data specifically indicates the content of "Data entry work, number of positions available: 1."

[0397] The server stores the received data in a database and sends it to the generative AI model. The generative AI model analyzes the received data and automatically creates a list of suitable tasks. For example, it might list "Person A, Person B, and Person C are the most suitable candidates for disabled people for data entry work."

[0398] The server sends the generated job list to the company's personnel, who then selects from a database a list of candidates with disabilities who meet the company's requirements. The company's personnel then receive detailed information about the list of "Mr. A, Mr. B, and Mr. C." For example, this information may include data such as "Mr. A requires visual assistance, Mr. B is fully visually-enabled, and Mr. C requires voice assistance."

[0399] Next, the server uses the generative AI model to generate a customized training program based on the company's training requirements. For example, the training program could include "basics of data entry, how to use visual aids, and regular skill checks." The server then sends the generated training program to company personnel and disabled workers.

[0400] Furthermore, users (business representatives or workers with disabilities) can use the AI ​​chatbot to ask questions. For example, if a business representative asks, "What visual aid tools do you recommend?", the server sends this question to the generative AI model to get an answer. The generative AI model generates the answer, "Screen reader software is recommended," which the server then sends to the device and displays to the user.

[0401] The emotion engine automatically identifies emotions from user input data and dialogue content and sends the results to the server, which then uses the emotional data for analysis to customize more appropriate training programs and support content.

[0402] The user (disabled worker or person in charge) enters daily report data into the terminal, which then sends the data to the server. The server analyzes the daily report data using an anomaly detection algorithm and sends an alert to the company's person in charge if an anomaly is detected. The emotion engine analyzes emotions along with the daily report data, and the content of the alert can be customized as needed.

[0403] In this way, the present invention can streamline the hiring and employment process for people with disabilities and provide continuous support that takes emotions into consideration. Specific examples of prompts provided include "We are looking to hire one person for data entry work" and "What visual support tools do you recommend?"

[0404] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0405] Step 1:

[0406] Users (company representatives) use dedicated terminals to input information such as their company's business overview, number of employees, required skill sets, and purpose of employing people with disabilities.

[0407] Input: Company information such as business overview and number of employees.

[0408] Output: Formatted company information data.

[0409] Operation: A company employee types into the terminal, "We would like to hire one person for data entry work," and presses the "Send" button.

[0410] Step 2:

[0411] The terminal formats the input data and sends it to the server.

[0412] Input: Company information data entered by the user.

[0413] Output: The data sent to the server in JSON format.

[0414] How it works: The device formats information such as "Data entry job, 1 position available" and sends it to the server via an HTTP request.

[0415] Step 3:

[0416] The server stores the received data in a database.

[0417] Input: Company information data in formatted JSON.

[0418] Output: Company information stored in a database.

[0419] How it works: The server uses a parser to break down the data and executes SQL queries to insert it into the database.

[0420] Step 4:

[0421] The server sends the data to the generative AI model.

[0422] Input: Company information stored in a database.

[0423] Output: The business data sent to the generative AI model.

[0424] How it works: The server sends company information to the generative AI model via an HTTP request.

[0425] Step 5:

[0426] A generative AI model analyzes the data and generates a list of tasks suitable for people with disabilities.

[0427] Input: Business data sent from the server.

[0428] Output: The generated job list.

[0429] How it works: The generative AI model analyzes the data and creates a list of "the most suitable candidates for data entry work who are disabled: A, B, and C."

[0430] Step 6:

[0431] The server sends the generated list of tasks to the company representative.

[0432] Input: The list of jobs returned by the generative AI model.

[0433] Output: A list of tasks sent to the company contact.

[0434] How it works: The server sends the list of tasks to the company representative's email address or a dedicated dashboard.

[0435] Step 7:

[0436] The server searches a database of people with disabilities and lists candidates with disabilities who meet the company's requirements.

[0437] Input: Job listing and company requirements.

[0438] Output: List of potential disabled people.

[0439] How it works: The server queries the database and generates a list of matching candidates.

[0440] Step 8:

[0441] The server sends the candidate's details to the company representative.

[0442] Input: A list of potential disabled people.

[0443] Output: Detailed information sent to company contact.

[0444] How it works: The server sends the details to the company representative via email or dashboard.

[0445] Step 9:

[0446] The server generates a training program using a generative AI model.

[0447] Input: Company training requirements.

[0448] Output: The generated customized training program.

[0449] How it works: A server sends a company's requirements to a generative AI model, which generates a customized training program.

[0450] Step 10:

[0451] The server transmits the training program to business personnel and disabled workers.

[0452] Input: The generated training program.

[0453] Output: The training program is sent via email and a dedicated dashboard.

[0454] How it works: The server sends training programs to company personnel and workers.

[0455] Step 11:

[0456] The user (company representative or disabled worker) enters a question into the AI ​​chatbot.

[0457] Input: The question.

[0458] Output: The question sent to the AI ​​chatbot.

[0459] How it works: A company representative asks the chatbot, "What visual aids do you recommend?"

[0460] Step 12:

[0461] The terminal transmits the entered question to the server.

[0462] Input: The question entered.

[0463] Output: The question sent to the server.

[0464] How it works: The device analyzes the question and sends it to the server.

[0465] Step 13:

[0466] The server sends the question to the generative AI model.

[0467] Input: The question sent from the terminal.

[0468] Output: The question sent to the generative AI model.

[0469] How it works: The server sends the question to the generative AI model and requests an answer.

[0470] Step 14:

[0471] The generative AI model generates an appropriate answer based on the question and returns it to the server.

[0472] Input: The question.

[0473] Output: The generated answer.

[0474] How it works: The generative AI model generates an answer such as "Screen reader software is recommended."

[0475] Step 15:

[0476] The server sends the generated response to the terminal.

[0477] Input: The answer from the generative AI model.

[0478] Output: The answer sent to the terminal.

[0479] Action: The server sends a response to the device.

[0480] Step 16:

[0481] The terminal displays the answer to the user.

[0482] Input: The response from the server.

[0483] Output: The answer displayed on the terminal.

[0484] Behavior: The device displays "Screen reader software recommended."

[0485] Step 17:

[0486] The emotion engine identifies emotions from user input data and dialogue content.

[0487] Input: Input data and dialogue.

[0488] Output: Identified emotion data.

[0489] How it works: The emotion engine automatically identifies emotions such as "joy" and "anxiety."

[0490] Step 18:

[0491] The emotion engine sends the emotion data to the server, which uses the data for analysis.

[0492] Input: Identified emotion data.

[0493] Output: Emotion data sent to the server.

[0494] How it works: The emotion engine sends emotions, such as "anxiety," to the server, which then analyzes the data.

[0495] Step 19:

[0496] The server takes emotional data into account to customize training programs and support content.

[0497] Input: Emotion data and existing training program information.

[0498] Output: Customized training programs and support.

[0499] What it does: The server tailors a training program for users who feel "anxious," including relaxation techniques and encouragement.

[0500] Step 20:

[0501] The user inputs the daily report data into the terminal.

[0502] Input: Daily report data.

[0503] Output: Daily report data entered into the terminal.

[0504] Action: A disabled worker writes in his daily report, "I was unable to work today due to poor health."

[0505] Step 21:

[0506] The terminal transmits the daily report data to the server.

[0507] Input: Daily report data entered.

[0508] Output: Daily report data sent to the server.

[0509] Operation: The device formats the daily report data and sends it to the server.

[0510] Step 22:

[0511] The server analyzes the daily report data using an anomaly detection algorithm.

[0512] Input: Daily report data sent to the server.

[0513] Output: Anomaly detection results.

[0514] Operation: The server analyzes the daily report data and detects any abnormalities.

[0515] Step 23:

[0516] If the server detects an abnormality, it will notify the company representative.

[0517] Input: Anomaly detection results.

[0518] Output: Anomaly alert.

[0519] How it works: The server detects an anomaly and sends an alert to company personnel that "urgent action is required."

[0520] Step 24:

[0521] The emotion engine analyzes daily report data as well as user emotions and customizes alert content based on that.

[0522] Input: Daily report data and emotion data.

[0523] Output: The customized alert content.

[0524] How it works: The emotion engine analyzes the information "I'm feeling unwell and anxious today" and sends a notification to the company representative, including an alert that special consideration is needed.

[0525] (Application example 2)

[0526] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0527] Traditionally, companies that employ people with disabilities have often lacked the precision to assign appropriate tasks or the ability to customize training programs for people with disabilities. Furthermore, the lack of a way to analyze workers' emotions in real time and provide support based on those emotions makes it difficult to create an environment where workers can work sustainably and safely. This has hindered efforts to increase the employment rate of people with disabilities and improve their workplace adaptation after employment.

[0528] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for automatically listing tasks suitable for persons with disabilities based on data input from companies, means for formatting the data input from companies and sending it to the server, and means for analyzing the emotions of workers in real time and sending the emotion data to the server. This enables automatic listing of tasks based on the aptitudes of persons with disabilities and customized support based on real-time emotion analysis.

[0529] "Data input from companies" is a general term for information such as the type of work provided by companies, the required skill sets, number of employees, and the purpose of employing people with disabilities.

[0530] The "means for automatically listing jobs suitable for people with disabilities" is a function in which a generative AI model automatically identifies and lists jobs suitable for people with disabilities based on data provided by companies.

[0531] The "means of listing disabled candidates from a database who meet the company's requirements" is a process for extracting disabled candidates from a database based on the skills and requirements required by the company.

[0532] The "means for generating customized training programs" refers to the process by which a generative AI model creates training programs tailored to individual individuals with disabilities based on the training requirements set by the company.

[0533] The "means of answering questions about the employment of people with disabilities in real time" is a system in which an AI chatbot instantly responds to questions from company representatives and workers with disabilities.

[0534] The "means of analyzing daily report data and detecting abnormalities" refers to an algorithm that analyzes workers' daily report data and detects abnormalities, as well as a notification system for doing so.

[0535] "Means for analyzing workers' emotions in real time and sending emotional data to a server" refers to a function that uses an emotion engine to analyze the emotions of workers while they are working and sends the results to a server.

[0536] "Means for customizing training programs and support content based on emotional data" refers to the process of adjusting and optimizing the training programs and support content provided based on the emotional state of workers.

[0537] This invention is a total support system that enables companies to smoothly recruit, employ, and continuously support people with disabilities. The system is composed of the following:

[0538] System configuration

[0539] Hardware and Software

[0540] Hardware: Factory robots, general-purpose industrial tablets, servers

[0541] Software: Python, EmotionAnalyzer (emotion analysis engine), AIChatbot, generative AI model

[0542] Program Overview

[0543] 1. Data collection from companies:

[0544] Users (company personnel) use dedicated terminals to input information such as their company's business operations, number of employees, required skill sets, and purpose of employing people with disabilities. This input data is sent to the server.

[0545] 2. Formatting and listing the data:

[0546] The server then formats the data it receives and uses a generative AI model to automatically create a list of jobs suitable for people with disabilities. The list is then sent to the company's personnel.

[0547] 3. Database search and candidate list generation:

[0548] The server extracts from the database candidates with disabilities who meet the company's requirements, creates a list, and provides detailed information to the company's personnel.

[0549] 4. Customized training programs:

[0550] The server uses a generative AI model based on the company's training requirements to generate a training program tailored to each individual with a disability and sends it to company personnel and workers.

[0551] 5. Real-time response:

[0552] When a user (a company representative or a disabled worker) inputs a question into the AI ​​chatbot, the server analyzes the question and generates an appropriate answer using a generative AI model. The generated answer is then displayed on the device.

[0553] 6. Sentiment Analysis and Customization:

[0554] The emotion engine analyzes the worker's input data and dialogue in real time, and the resulting emotional data is sent to the server, which then analyzes the data and customizes training programs and support accordingly.

[0555] 7. Anomaly detection in daily report data:

[0556] When a user (a disabled worker or a person in charge) enters daily report data, the data is sent to the server and analyzed using an anomaly detection algorithm. If an anomaly is detected, the server sends an alert to the company's person in charge.

[0557] Examples and prompts

[0558] Company personnel enter data such as:

[0559] "I would like to hire one person to perform data entry work."

[0560] The server uses a generative AI model to generate a list of tasks, such as:

[0561] "The best candidates for disabled people for data entry work are A, B, and C."

[0562] Additionally, we create customized training programs for your company, such as:

[0563] "Data entry basics, how to use visual aids, and regular skill checks."

[0564] An example of how a chatbot can be used is to ask the following questions:

[0565] "What visual aids do you recommend?"

[0566] The server uses an AI chatbot and emotion engine to generate answers based on the following prompts:

[0567] Type of disability: Visual

[0568] Question: What are the best tools for an assembly line?

[0569] Context: Workers are anxious about new tasks

[0570] Tone of response: Encouraging

[0571] By generating specific answers using the above prompts, companies can provide support that takes into consideration the feelings of workers. This allows companies to streamline the entire process of hiring, training, and supporting people with disabilities, and also provides continuous support that takes into consideration the feelings of users.

[0572] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0573] Step 1:

[0574] The user (company representative) uses a dedicated terminal to input information such as the company's business overview, number of employees, required skill sets, and purpose of hiring people with disabilities. This input data is formatted and sent to the server. An example of input is "We would like to hire one person to perform data entry work." This information is formatted in JSON format.

[0575] Step 2:

[0576] The server analyzes the data it receives and stores it in a database, including job descriptions, number of employees, etc. The server then sends this data to a generative AI model.

[0577] Step 3:

[0578] The generative AI model analyzes the received data and automatically creates a list of suitable jobs. For example, it might list "The most suitable candidates for disabled people for data entry work are A, B, and C." The generated list is then sent back to the server.

[0579] Step 4:

[0580] The server sends the list of job information to the company's personnel. The output format is a list such as "Mr. A, Mr. B, Mr. C." The personnel will use this information to identify suitable candidates.

[0581] Step 5:

[0582] The server searches the database based on the company representative's requests and creates a list of candidates with disabilities. For example, it narrows down the candidates based on data such as "Person A needs visual assistance, Person B is fully visual, and Person C needs voice assistance." The resulting list is then sent to the company representative.

[0583] Step 6:

[0584] The server uses a generative AI model to generate a customized training program based on the company's training requirements. For example, a program might be generated that covers the basics of data entry, how to use visual support tools, and regular skill checks. The generated training program is then sent to company personnel and workers.

[0585] Step 7:

[0586] The user (a company representative or a worker with a disability) inputs a question into the AI ​​chatbot. For example, a question might be asked, "What visual support tools do you recommend?" The device then sends this question to the server.

[0587] Step 8:

[0588] The server receives and analyzes the question and generates an appropriate answer based on the generative AI model. For example, it might generate an answer such as "Screen reader software is recommended." The generated answer is sent to the device and displayed on the screen.

[0589] Step 9:

[0590] The emotion engine automatically identifies emotions from the user's input data and dialogue content. For example, it identifies emotions such as "joy" or "anxiety" from the user's input content and dialogue history. The identified emotion data is sent to the server.

[0591] Step 10:

[0592] The server analyzes the emotional data and customizes the training program and support content based on that data. For example, for a user who is feeling anxious, the server customizes the training program to include relaxation techniques and encouraging content, thereby providing more appropriate support.

[0593] Step 11:

[0594] The user (disabled worker or person in charge) inputs daily report data into the terminal. For example, the user may write in the daily report, "I was unable to work today due to poor health." The input daily report data is formatted and sent to the server.

[0595] Step 12:

[0596] The server analyzes the received daily report data using an anomaly detection algorithm. For example, information about "feeling unwell" is run through the algorithm, and if an abnormality is detected, an alert is sent to the company's responsible person.

[0597] Step 13:

[0598] The emotion engine analyzes the user's emotions along with the daily report data and customizes the alert content based on the results. For example, if the information is "I'm feeling unwell and anxious today," it will notify the person in charge that "special attention is required."

[0599] By taking these steps, companies can streamline the entire process of recruiting, training, and supporting people with disabilities, and provide ongoing support that takes users' emotions into consideration.

[0600] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0601] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0602] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0603] [Second embodiment]

[0604] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0605] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0606] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0607] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0608] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0609] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0610] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0611] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0612] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0613] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0614] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0615] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0616] This invention provides a total support system that enables companies to smoothly recruit and employ people with disabilities and provide continuous support. This system uses a generative AI model to automatically create a list of jobs suitable for people with disabilities based on data input from the company and sends the list to the company. It also includes a means for selecting candidates with disabilities who meet the company's requirements from a database and a means for the generative AI model to generate a customized training program based on the company's training requirements. Furthermore, the system has a means for using an AI chatbot to answer questions about the employment of people with disabilities in real time and a means for analyzing daily report data, detecting anomalies, and notifying company personnel.

[0617] Natural language description of the program

[0618] 1. The user (company representative) enters information such as an overview of their company's business, number of employees, required skill sets, and the purpose of employing people with disabilities on a dedicated terminal.

[0619] Example: A company employee types into a terminal, "We would like to hire one person to perform data entry work."

[0620] 2. The terminal formats the input data and sends it to the server, which stores it in a database.

[0621] Example: The terminal sends information such as "Data entry work, 1 position" to the server, which then stores it in a database.

[0622] 3. The server sends the received data to a generative AI model, which automatically generates a list of jobs suitable for people with disabilities. This list is then immediately sent to the company's representative.

[0623] Example: The AI ​​model creates a list of "the best candidates for data entry work are A, B, and C" and notifies the person in charge.

[0624] 4. The server searches a database of people with disabilities and lists candidates with disabilities who meet the company's requirements.

[0625] Example: The server creates a list of suitable candidates based on data such as "Person A needs visual assistance, Person B is fully visually capable, and Person C needs audio assistance."

[0626] 5. The server uses the generative AI model to generate a customized training program based on the company's training requirements, and sends the program to the company's personnel and disabled workers.

[0627] Example: AI generates training programs such as "basics of data entry, how to use visual support tools, and regular skill checks" and sends them to staff and people with disabilities.

[0628] 6. An AI chatbot will be available 24 hours a day to answer questions about employment for people with disabilities in real time.

[0629] Example: A company representative asks a chatbot, "What visual aid tools do you recommend?" and the chatbot immediately replies, "We recommend screen reader software."

[0630] 7. The server receives the daily report data entered by the disabled worker or the person in charge and analyzes the data using an anomaly detection algorithm. If an anomaly is detected, an alert is sent to the company's person in charge.

[0631] Example: A disabled worker writes in his daily report that "I was unable to work today due to poor health," and the server detects this information and alerts the person in charge that "urgent action is required."

[0632] This will enable companies to streamline the entire process of recruiting, training, and supporting people with disabilities, and provide ongoing support.

[0633] The processing flow will be explained below.

[0634] Step 1:

[0635] The user (company representative) operates the terminal to input information such as an overview of the company's business, number of employees, required skill sets, and the purpose of employing people with disabilities.

[0636] Example: A company employee types into a terminal, "We would like to hire one person to perform data entry work."

[0637] Step 2:

[0638] The terminal formats the data entered by the user and sends the data to the server.

[0639] Example: The terminal sends information such as "Data entry work, 1 position available" to the server.

[0640] Step 3:

[0641] The server stores the received data in a database.

[0642] Example: A server stores information such as "Data entry job, 1 position available" in a database.

[0643] Step 4:

[0644] The server sends the stored data to the generative AI model.

[0645] Example: The server sends the information "data entry work, number of positions available: 1" to the generative AI model.

[0646] Step 5:

[0647] The generative AI model analyzes the received data and automatically creates a list of tasks suitable for people with disabilities.

[0648] Example: The AI ​​model creates a list of candidates with disabilities who are best suited for data entry work: A, B, and C.

[0649] Step 6:

[0650] The server sends the generated list of tasks to the company representative.

[0651] Example: The server sends a list of information about "Mr. A, Mr. B, and Mr. C" to a company representative.

[0652] Step 7:

[0653] The server searches a database of people with disabilities and lists candidates with disabilities who meet the company's requirements.

[0654] Example: The server creates a list of suitable candidates based on data such as "Person A needs visual assistance, Person B is fully visually capable, and Person C needs audio assistance."

[0655] Step 8:

[0656] The server sends detailed information of the listed suitable candidates to the company representative.

[0657] Example: The server sends detailed information about "Mr. A, Mr. B, and Mr. C" to the person in charge.

[0658] Step 9:

[0659] The server generates a customized training program using a generative AI model based on the company's training requirements.

[0660] Example: AI generates customized training programs such as "basics of data entry, how to use visual support tools, and regular skill checks."

[0661] Step 10:

[0662] The server transmits the generated training program to the company personnel and the disabled workers.

[0663] Example: A server sends training programs to personnel and workers, such as "Basics of data entry, how to use visual aids, and regular skill checks."

[0664] Step 11:

[0665] The user (company representative or disabled worker) enters a question into the AI ​​chatbot.

[0666] Example: A company representative asks the chatbot, "What visual support tools do you recommend?"

[0667] Step 12:

[0668] The terminal transmits the entered question to the server.

[0669] Example: A device sends a question to a server: "What visual support tools do you recommend?"

[0670] Step 13:

[0671] The server analyzes the question and requests the appropriate answer from the generative AI model.

[0672] Example: The server sends the analysis results of a "question about visual support tools" to a generative AI model.

[0673] Step 14:

[0674] The generative AI model generates an appropriate answer based on the question and returns it to the server.

[0675] Example: An AI model generates the answer "Screen reader software is recommended."

[0676] Step 15:

[0677] The server generates a response and sends it back to the terminal.

[0678] Example: The server sends a response to the device saying "Screen reader software is recommended."

[0679] Step 16:

[0680] The device displays the answer on the screen.

[0681] Example: The device displays the response "Screen reader software recommended" on the screen.

[0682] Step 17:

[0683] The user (disabled worker or person in charge) enters the daily report data into the terminal.

[0684] Example: A disabled worker writes in his daily report, "I was unable to work today due to poor health."

[0685] Step 18:

[0686] The terminal transmits the input daily report data to the server.

[0687] Example: A terminal sends daily report data to a server stating, "I was unable to work today due to poor health."

[0688] Step 19:

[0689] The server analyzes the received daily report data using an anomaly detection algorithm.

[0690] Example: The server runs the "illness" information through an anomaly detection algorithm.

[0691] Step 20:

[0692] If the server detects an abnormality, it will send an alert to company personnel.

[0693] Example: A server sends an "urgent action required" alert to a company representative.

[0694] Example 1

[0695] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0696] The goal is to solve the many challenges that arise when companies hire and employ people with disabilities. Conventional methods require time and effort to create a list of jobs suitable for people with disabilities, identify suitable candidates, create training programs, and detect anomalies in daily report data, making these tasks inefficient. Furthermore, there are no adequate means to respond to questions about hiring people with disabilities in real time.

[0697] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0698] In this invention, the server includes means for automatically creating a list of jobs suitable for persons with disabilities based on data input from a terminal, means for sending the list of jobs suitable for persons with disabilities to a company, means for compiling a list of disabled candidates from a database that meets the company's preferences, means for using a generative AI model to create a customized training program based on the company's training requirements, means for using an AI chatbot to answer questions about the employment of persons with disabilities in real time, means for analyzing daily report data, detecting anomalies, and notifying company personnel, and means for formatting input data from the terminal and sending it to the server. This makes it possible to select jobs and candidates suitable for persons with disabilities based on data input from the terminal, provide customized training programs, respond to questions about the employment of persons with disabilities in real time, and detect and notify anomalies in daily report data.

[0699] A "terminal" is a hardware device for inputting and displaying data.

[0700] A "server" is a hardware and software configuration for storing, processing, sending and receiving data over a network.

[0701] A "generative AI model" is an algorithm that uses artificial intelligence technology to automate and optimize specific tasks.

[0702] A "list" is a collection of data that is organized and categorized based on specific criteria.

[0703] A "database" is a software system for efficiently storing, searching, and managing large amounts of data.

[0704] "Training Program" means an educational or training plan designed to acquire specific skills or knowledge.

[0705] An "AI chatbot" is a program that uses artificial intelligence technology to automatically hold conversations and provide answers to users' questions in real time.

[0706] "Daily report data" refers to information that records the progress of work and working conditions.

[0707] An "anomaly detection algorithm" is a computational method for analyzing data and detecting unusual patterns or anomalies.

[0708] An "alert" is a notification that notifies you of an abnormality or important information.

[0709] A "customized training program" is an education and training plan that is tailored to the requirements of a specific company or individual.

[0710] "Input data" refers to information entered into the system via a terminal.

[0711] "Real-time" refers to a state in which data processing and information provision are carried out immediately.

[0712] This is a total support system that enables companies to smoothly recruit, employ, and continuously support people with disabilities. The system is implemented using a server, terminals, a generative AI model, a database, and an AI chatbot.

[0713] First, the user (company representative) enters information such as the job summary, number of employees, required skill set, and purpose of hiring people with disabilities into a dedicated terminal. This information is necessary to clarify the skills and conditions that the company is looking for in people with disabilities. As a concrete example, the user might enter the following into the terminal: "We would like to hire one person to do data entry work. Visual assistance is required."

[0714] Next, the terminal formats the input data and sends it to the server. The formatted data is converted into a format that the server can easily accept, such as JSON. For example, the terminal converts information such as "Task: Data entry, Number of people: 1, Visual support: Required" into JSON format and sends it to the server.

[0715] The server stores the received data in a database. At the same time, it sends the data to the generative AI model and instructs it to analyze it. The generative AI model automatically creates a list of tasks suitable for people with disabilities based on the data entered from the device. This list includes specific tasks suitable for people with disabilities and candidates based on the company's requirements. As a concrete example, the generative AI model creates a list such as "The best candidates for data entry work are Person A, Person B, and Person C," and the server sends this list to the company employee's device.

[0716] The server then searches a database of people with disabilities and creates a list of candidates who meet the company's requirements. The list includes the skillsets and support required by each person with a disability. For example, the server creates a list based on data such as "Person A needs visual support, Person B needs voice support, and Person C needs physical support," and sends it to the company's representative.

[0717] The server also uses a generative AI model to generate a customized training program based on the company's training requirements. This program is tailored to each company's specific needs. The generated program is then sent to the company's personnel and disabled workers. For example, the AI ​​generates a training program titled "Basics of data entry, how to use visual aids, and regular skill checks," and sends it to the company's personnel and disabled workers via email.

[0718] An AI chatbot is available 24 hours a day to answer questions about the employment of people with disabilities in real time. This AI chatbot uses natural language processing technology to answer questions from users. For example, if a company representative asks the chatbot, "What visual assistance tools do you recommend?", the chatbot will immediately reply, "We recommend screen reader software."

[0719] Finally, the server analyzes the daily report data and notifies company personnel if an abnormality is detected. When disabled workers or personnel enter daily report data into their terminals, the server analyzes the data using an anomaly detection algorithm, and if an abnormality is detected, it notifies company personnel as an alert. For example, if a disabled worker enters in their daily report that "I was unable to work today due to poor health," the server analyzes the information and sends an alert to company personnel that "urgent action is required."

[0720] Prompt Sentence Examples

[0721] Job Listing: "Job Description: Data Entry. Position: 1. Please list suitable candidates."

[0722] Candidate Listing: "Company Request: Please list candidates who can handle data entry work."

[0723] Training Program Generation: "Training Requirements: Please generate a training program that includes training content on basic data entry skills and how to use visual aids."

[0724] Chatbot response example: "Question about employment for people with disabilities: What visual aids do you recommend?"

[0725] Anomaly detection: "Daily report data analysis: It is stated that the employee was unable to work today due to poor health. Please detect any anomalies and notify us."

[0726] These components enable companies to streamline the entire process of hiring, training, and supporting people with disabilities, and provide continuous support. By utilizing generative AI models and AI chatbots, the system achieves automation and real-time responses, contributing to companies' promotion of hiring people with disabilities.

[0727] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0728] Step 1:

[0729] The user (company representative) enters information such as the business overview, number of employees, required skill sets, and purpose of employing people with disabilities on a dedicated terminal.

[0730] Input: Details such as job description, number of employees, skill set, and employment objectives

[0731] Output: Formatted input data

[0732] Specific example of operation: A company representative enters detailed information into the input field on the terminal, such as "We would like to hire one person for data entry work. Visual assistance is required.", and presses the send button.

[0733] Step 2:

[0734] The terminal formats the input data and sends it to the server.

[0735] Input: Entered business information, number of employees, skill sets, employment purpose

[0736] Output: Formatted data such as JSON

[0737] Specific example of operation: The terminal converts the information "Task: Data entry, Number of people: 1, Visual support: Required" into JSON format and sends it to the server.

[0738] Step 3:

[0739] The server stores the received data in a database and simultaneously sends the data to the generative AI model, instructing it to analyze it.

[0740] Input: Formatted input data

[0741] Output: Data stored in a database, data sent to a generative AI model

[0742] Specific example of operation: The server records the data "Task: Data entry, Number of people: 1, Visual support: Required" in the database and requests the generative AI model to analyze it.

[0743] Step 4:

[0744] The generative AI model automatically creates a list of jobs suitable for people with disabilities based on the data it receives, and the server sends that list to the company's representative.

[0745] Input: Data sent to the generative AI model

[0746] Output: List of jobs suitable for people with disabilities, notified list

[0747] Specific example of operation: The generative AI model creates a list of "the best candidates for data entry work are A, B, and C," and the server sends this to the company employee's device.

[0748] Step 5:

[0749] The server searches a database of people with disabilities and lists candidates with disabilities who meet the company's requirements.

[0750] Input: Company preferences and disability database

[0751] Output: A list of possible matching disabilities

[0752] Specific example of operation: The server creates a list based on data such as "Person A needs visual assistance, Person B needs audio assistance, and Person C needs physical assistance" and sends it to the company representative.

[0753] Step 6:

[0754] The server uses a generative AI model to generate a customized training program based on the company's training requirements and sends it to company personnel and disabled workers.

[0755] Input: Training requirements, analysis data for the generative AI model

[0756] Output: Customized training program, transmitted program

[0757] Specific example of how it works: The AI ​​generates a training program on "basics of data entry, how to use visual support tools, and regular skill checks" and sends it via email to company representatives and disabled workers.

[0758] Step 7:

[0759] An AI chatbot is available 24 hours a day to answer questions about employment for people with disabilities in real time.

[0760] Input: User question

[0761] Output: Answer by AI chatbot

[0762] A specific example of how it works: A company representative asks the chatbot, "What visual support tools do you recommend?" and the chatbot immediately replies, "We recommend screen reader software."

[0763] Step 8:

[0764] The server analyzes the daily report data and notifies company personnel if an abnormality is detected.

[0765] Input: Daily report data, anomaly detection algorithm

[0766] Output: Alert notification when an abnormality is detected

[0767] A concrete example of how it works: When a disabled worker enters in their daily report that "I was unable to work today due to poor health," the server analyzes the information and alerts company personnel that "urgent action is required."

[0768] (Application example 1)

[0769] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0770] In modern manufacturing, employing people with disabilities is important from the perspective of corporate social responsibility and diversity. However, many companies face the challenge of finding appropriate work and training programs to provide a safe and efficient working environment for people with disabilities. In particular, when employing people with disabilities in factories, support is required to ensure both safety and efficiency, but the reality is that the technological means to achieve this are not fully in place.

[0771] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0772] In this invention, the server includes means for automatically creating a list of jobs suitable for persons with disabilities based on data input from a company, means for sending the list of jobs suitable for persons with disabilities to the company, means for compiling a list of disabled candidates from a database that meets the company's preferences, means for creating a customized training program based on the company's training requirements, means for answering questions about the employment of persons with disabilities in real time, means for analyzing daily report data and detecting abnormalities, means for providing support for persons with disabilities to work safely and efficiently in factories, and means for displaying the created job list and training program on a smart device in real time. This enables companies to provide comprehensive support for persons with disabilities, from hiring to training and daily operations, enabling them to work safely and efficiently.

[0773] An "enterprise" is a corporation or individual that conducts economic activities as an organization and provides goods and services.

[0774] "Input data" refers to the information that companies enter into the system, including details of the business, number of employees, required skill sets, and the purpose of employing people with disabilities.

[0775] "Disabled persons" refers to people with physical, mental or sensory impairments who may require special assistance or accommodations.

[0776] "Means for automatically listing tasks" refers to a function that uses a generative AI model to analyze input data and automatically list tasks suitable for people with disabilities.

[0777] "Means for sending the list to the company" refers to a function for electronically notifying the person in charge at the company of the generated business list.

[0778] A "database" is a collection of information that stores information and manages it in an organized manner, allowing it to be searched and listed efficiently.

[0779] "Means for generating training programs" refers to the ability to automatically generate customized training programs using generative AI models based on a company's training requirements.

[0780] "Real-time response means" refers to the ability to instantly provide answers to questions about employment for people with disabilities using generative AI models.

[0781] "Daily report data" refers to records used by disabled workers or those in charge to report on their daily work status, health condition, etc.

[0782] "Means for detecting abnormalities" refers to the function of analyzing daily report data and automatically detecting abnormalities that differ from normal work or health conditions.

[0783] "Measures to provide support within the factory" refers to the technical and human support systems that provide an environment in which persons with disabilities can work safely and efficiently within the factory.

[0784] A "smart device" is a portable electronic device that is capable of connecting to the Internet and has advanced computing power and is capable of running applications, and includes smartphones, smart glasses, head-mounted displays, etc.

[0785] "A means to view generated work lists and training programs in real time" refers to the function that allows generated work lists and training programs to be instantly checked via a smart device.

[0786] The system of the present invention provides total support for companies to smoothly recruit and employ people with disabilities and provide continuous support. This system uses a generative AI model to automatically create a list of jobs suitable for people with disabilities based on data input from the company and transmits the list to the company. It also includes a database listing candidates with disabilities who meet the company's requirements, and a generative AI model to generate a customized training program based on the company's training requirements. Furthermore, the system provides real-time answers to questions about the employment of people with disabilities using an AI chatbot, and a means for analyzing daily report data, detecting abnormalities, and notifying company personnel. When applied to factories, the system supports people with disabilities in working safely and efficiently, allowing them to access necessary information in real time on smart devices.

[0787] The server receives information entered by companies, such as job descriptions, number of employees, required skill sets, and the purpose of hiring people with disabilities, formats it, and stores it in a database. This data is then sent to a generative AI model, which creates a list of jobs suitable for people with disabilities. The generated list of jobs is immediately notified to company personnel. Similarly, the system also has the function of listing candidates with disabilities from the database. This allows companies to quickly find suitable candidates with disabilities.

[0788] Based on the training requirements of the company, the server uses a generative AI model to generate a customized training program.An AI chatbot is also installed, which can provide instant answers to questions about disability employment from company personnel and disabled workers.

[0789] For daily report data, disabled workers or staff enter information about their daily work and health into a terminal and send it to a server. The server analyzes this data and notifies the company staff if it detects any abnormalities. This anomaly detection uses an algorithm that automatically detects abnormalities that differ from normal work or health conditions.

[0790] The system also includes a means to enable workers with disabilities to access generated job lists and training programs in real time using smart devices, enabling them to work safely and efficiently in factories.

[0791] As a concrete example, consider the case where a company employee inputs, "We would like to hire one worker with basic machine operation skills." This data is sent to the server, and the generative AI model generates a list of suitable tasks, such as "simple machine operation, parts assembly, and shipping preparation." This list is notified to the employee, who then generates a customized training program, such as "basic machine operation training, explanation of assembly procedures, and shipping preparation methods." The employee can also ask, "What visual support tools do you recommend?" and the AI ​​chatbot can respond, "Screen reader software is recommended."

[0792] Here are some examples of prompts to input to the generative AI model:

[0793] 1. Generate a list of tasks:

[0794] Company information: Major manufacturing company, 500 employees, required skill set is basic machine operation, purpose of employing people with disabilities is to promote diversity and contribute to society

[0795] Generate a suitable task list.

[0796] 2. Generating training programs:

[0797] Job List: Simple machine operation, parts assembly, shipping preparation

[0798] Generate a training program based on this.

[0799] 3. Real-time chat support:

[0800] Disability employment question: What visual aids do you recommend?

[0801] Please respond in real time.

[0802] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0803] Step 1:

[0804] A user uses a dedicated terminal to input company information, including a business overview, number of employees, required skill sets, and the purpose of hiring people with disabilities. This data is formatted by the terminal and sent to the server. The input data on the terminal is, "We would like to hire one worker who can operate basic machines."

[0805] Step 2:

[0806] The server stores the received company information in a database. Specifically, it converts the input data into an appropriate format and stores it in the database. For example, information such as "basic machine operation, number of employees: 1" is stored.

[0807] Step 3:

[0808] The server sends the saved company information to the generative AI model, which then analyzes the input data using prompts and generates a list of tasks suitable for people with disabilities. The generated list of tasks is called "simple machine operation, parts assembly, and shipping preparation."

[0809] Step 4:

[0810] The server receives the task list generated by the generative AI model and sends it to the company's personnel. This includes sending notifications containing the task list via email or notification system. The output is "Suitable task list: simple machine operation, parts assembly, and shipping preparation."

[0811] Step 5:

[0812] The server searches the database and lists candidates with disabilities who meet the company's requirements. The search results are a list of suitable candidates such as "Mr. A, Mr. B, Mr. C."

[0813] Step 6:

[0814] The server uses a generative AI model to generate a customized training program based on the company's training requirements. The training program generated by this prompt is "Training basic machine operation, explaining assembly procedures, and how to prepare for shipment."

[0815] Step 7:

[0816] The server sends the generated training program to company personnel and disabled workers. This includes sending notifications containing the training program details via email and notification systems. The output is "specific training program details."

[0817] Step 8:

[0818] A user inputs a question about employment for people with disabilities into the AI ​​chatbot, for example, "What visual assistive tools do you recommend?"

[0819] Step 9:

[0820] The AI ​​chatbot answers questions in real time, using a generative AI model to generate appropriate answers and provide them to the user. The output is an immediate response such as "Screen reader software recommended."

[0821] Step 10:

[0822] The user inputs daily report data into the terminal, and the server receives the data. For example, the daily report may include, "I was not feeling well today and was unable to work."

[0823] Step 11:

[0824] The server analyzes the daily report data and detects anomalies. If an anomaly is detected, the server sends a notification to the company's responsible person. The output is an alert stating "Anomaly detected: Notify responsible person."

[0825] Step 12:

[0826] Users can view the generated work lists and training programs in real time using smart devices such as smartphones, smart glasses, and head-mounted displays.

[0827] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0828] This invention provides a system that provides more effective support by combining an emotion engine with a total support system that enables companies to smoothly recruit, employ, and sustainably support people with disabilities. This system includes a means for automatically creating a list of tasks suitable for people with disabilities using a generative AI model based on data input from the company and sending that list to the company. It also includes a means for selecting candidates with disabilities who meet the company's requirements from a database and a means for generating a customized training program using the generative AI model based on the company's training requirements. Furthermore, it includes a means for using an AI chatbot to answer questions about the employment of people with disabilities in real time and a means for analyzing daily report data, detecting anomalies, and notifying company personnel. In addition, by incorporating an emotion engine, the system can recognize user emotions and use them for analysis and customizing support content.

[0829] Natural language description of the program

[0830] 1. The user (company representative) enters information such as an overview of their company's business, number of employees, required skill sets, and the purpose of employing people with disabilities on a dedicated terminal.

[0831] Example: A company employee types into a terminal, "We would like to hire one person to perform data entry work."

[0832] 2. The terminal formats the data entered by the user and sends the data to the server.

[0833] Example: The terminal sends information such as "Data entry work, 1 position available" to the server.

[0834] 3. The server stores the received data in a database.

[0835] Example: A server stores information such as "Data entry job, 1 position available" in a database.

[0836] 4. The server sends the stored data to the generative AI model.

[0837] Example: The server sends the information "data entry work, number of positions available: 1" to the generative AI model.

[0838] 5. The generative AI model analyzes the received data and automatically creates a list of tasks suitable for people with disabilities.

[0839] Example: The AI ​​model creates a list of candidates with disabilities who are best suited for data entry work: A, B, and C.

[0840] 6. The server sends the generated list of tasks to the company representative.

[0841] Example: The server sends a list of information about "Mr. A, Mr. B, and Mr. C" to a company representative.

[0842] 7. The server searches the database of disabled people and lists candidates with disabilities who meet the company's requirements.

[0843] Example: The server creates a list of suitable candidates based on data such as "Person A needs visual assistance, Person B is fully visually capable, and Person C needs audio assistance."

[0844] 8. The server sends the details of the listed matching candidates to the company representative.

[0845] Example: The server sends detailed information about "Mr. A, Mr. B, and Mr. C" to the person in charge.

[0846] 9. The server generates a customized training program using the generative AI model based on the company's training requirements.

[0847] Example: AI generates customized training programs such as "basics of data entry, how to use visual support tools, and regular skill checks."

[0848] 10. The server sends the generated training program to the company's personnel and the disabled worker.

[0849] Example: A server sends training programs to personnel and workers, such as "Basics of data entry, how to use visual aids, and regular skill checks."

[0850] 11. The user (company representative or disabled worker) enters a question into the AI ​​chatbot.

[0851] Example: A company representative asks the chatbot, "What visual support tools do you recommend?"

[0852] 12. The terminal sends the entered question to the server.

[0853] Example: A device sends a question to a server: "What visual support tools do you recommend?"

[0854] 13. The server analyzes the question and requests the appropriate answer from the generative AI model.

[0855] Example: The server sends the analysis results of a "question about visual support tools" to a generative AI model.

[0856] 14. The generative AI model generates an appropriate answer based on the question and returns it to the server.

[0857] Example: An AI model generates the answer "Screen reader software is recommended."

[0858] 15. The server generates a response and sends it back to the device.

[0859] Example: The server sends a response to the device saying "Screen reader software is recommended."

[0860] 16. The device will display the answer on the screen.

[0861] Example: The device displays the response "Screen reader software recommended" on the screen.

[0862] 17. The emotion engine automatically identifies emotions from user input data and dialogue.

[0863] Example: An emotion engine identifies emotions such as "joy" or "anxiety" from user input and dialogue history.

[0864] 18. The emotion engine sends the identified emotion data to the server, which uses the emotion data for analysis.

[0865] Example: An emotion engine identifies the emotion "anxiety" and sends that information to a server.

[0866] 19. The server will also take emotional data into account to customize more appropriate training programs and support content.

[0867] Example: A server customizes a training program for users who feel "anxious," including relaxation techniques and encouragement.

[0868] 20. The user (disabled worker or person in charge) enters the daily report data into the terminal.

[0869] Example: A disabled worker writes in his daily report, "I was unable to work today due to poor health."

[0870] 21. The terminal sends the entered daily report data to the server.

[0871] Example: A terminal sends daily report data to a server stating, "I was unable to work today due to poor health."

[0872] 22. The server analyzes the received daily report data using an anomaly detection algorithm.

[0873] Example: The server runs the "illness" information through an anomaly detection algorithm.

[0874] 23. If the server detects an abnormality, it will send an alert to the company representative.

[0875] Example: A server sends an "urgent action required" alert to a company representative.

[0876] 24. The emotion engine analyzes daily report data as well as user emotions and customizes alert content based on that.

[0877] Example: The emotion engine analyzes the information "I am feeling unwell and anxious today" and notifies the person in charge that "special consideration is required."

[0878] This will enable companies to streamline the entire process of recruiting, training, and supporting people with disabilities, and also provide ongoing support that takes users' emotions into consideration.

[0879] The processing flow will be explained below.

[0880] Step 1:

[0881] The user (company representative) enters information such as the company's business overview, number of employees, required skill sets, and purpose of employing people with disabilities on the terminal.

[0882] Example: A company employee types into a terminal, "We would like to hire one person to perform data entry work."

[0883] Step 2:

[0884] The terminal formats the data entered by the user and sends the data to the server.

[0885] Example: The terminal sends information such as "Data entry work, 1 position available" to the server.

[0886] Step 3:

[0887] The server stores the received data in a database.

[0888] Example: A server stores information such as "Data entry job, 1 position available" in a database.

[0889] Step 4:

[0890] The server sends the stored data to the generative AI model.

[0891] Example: The server sends the information "data entry work, number of positions available: 1" to the generative AI model.

[0892] Step 5:

[0893] The generative AI model analyzes the received data and automatically creates a list of tasks suitable for people with disabilities.

[0894] Example: The AI ​​model creates a list of candidates with disabilities who are best suited for data entry work: A, B, and C.

[0895] Step 6:

[0896] The server sends the generated list of tasks to the company representative.

[0897] Example: The server sends a list of information about "Mr. A, Mr. B, and Mr. C" to a company representative.

[0898] Step 7:

[0899] The server searches a database of people with disabilities and lists candidates with disabilities who meet the company's requirements.

[0900] Example: The server creates a list of suitable candidates based on data such as "Person A needs visual assistance, Person B is fully visually capable, and Person C needs audio assistance."

[0901] Step 8:

[0902] The server sends detailed information of the listed suitable candidates to the company representative.

[0903] Example: The server sends detailed information about "Mr. A, Mr. B, and Mr. C" to the person in charge.

[0904] Step 9:

[0905] The server generates a customized training program using a generative AI model based on the company's training requirements.

[0906] Example: AI generates customized training programs such as "basics of data entry, how to use visual support tools, and regular skill checks."

[0907] Step 10:

[0908] The server transmits the generated training program to the company personnel and the disabled workers.

[0909] Example: A server sends training programs to personnel and workers, such as "Basics of data entry, how to use visual aids, and regular skill checks."

[0910] Step 11:

[0911] The user (company representative or disabled worker) enters a question into the AI ​​chatbot.

[0912] Example: A company representative asks the chatbot, "What visual support tools do you recommend?"

[0913] Step 12:

[0914] The terminal transmits the entered question to the server.

[0915] Example: A device sends a question to a server: "What visual support tools do you recommend?"

[0916] Step 13:

[0917] The server analyzes the question and requests the appropriate answer from the generative AI model.

[0918] Example: The server sends the analysis results of a "question about visual support tools" to a generative AI model.

[0919] Step 14:

[0920] The generative AI model generates an appropriate answer based on the question and returns it to the server.

[0921] Example: An AI model generates the answer "Screen reader software is recommended."

[0922] Step 15:

[0923] The server generates a response and sends it back to the terminal.

[0924] Example: The server sends a response to the device saying "Screen reader software is recommended."

[0925] Step 16:

[0926] The device displays the answer on the screen.

[0927] Example: The device displays the response "Screen reader software recommended" on the screen.

[0928] Step 17:

[0929] The emotion engine automatically identifies emotions from user input data and dialogue content.

[0930] Example: An emotion engine identifies emotions such as "joy" or "anxiety" from user input and dialogue history.

[0931] Step 18:

[0932] The emotion engine sends the identified emotion data to the server, which uses the emotion data for analysis.

[0933] Example: An emotion engine identifies the emotion "anxiety" and sends that information to a server.

[0934] Step 19:

[0935] The server also takes emotional data into account to customize more appropriate training programs and support content.

[0936] Example: A server customizes a training program for users who feel "anxious," including relaxation techniques and encouragement.

[0937] Step 20:

[0938] The user (disabled worker or person in charge) enters the daily report data into the terminal.

[0939] Example: A disabled worker writes in his daily report, "I was unable to work today due to poor health."

[0940] Step 21:

[0941] The terminal transmits the input daily report data to the server.

[0942] Example: A terminal sends daily report data to a server stating, "I was unable to work today due to poor health."

[0943] Step 22:

[0944] The server analyzes the received daily report data using an anomaly detection algorithm.

[0945] Example: The server runs the "illness" information through an anomaly detection algorithm.

[0946] Step 23:

[0947] If the server detects an abnormality, it will send an alert to company personnel.

[0948] Example: A server sends an "urgent action required" alert to a company representative.

[0949] Step 24:

[0950] The emotion engine analyzes daily report data as well as user emotions and customizes alert content based on that.

[0951] Example: The emotion engine analyzes the information "I am feeling unwell and anxious today" and notifies the person in charge that "special consideration is required."

[0952] Example 2

[0953] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0954] The current recruitment and hiring process for people with disabilities in companies is difficult to accommodate special needs and individual requirements, making it difficult to operate efficiently. Furthermore, there is insufficient support that takes into account the feelings and individual needs of people with disabilities, and there is no sustainable support system in place. This has led to a need for effective tools to facilitate the recruitment and hiring process for people with disabilities and provide continuous support.

[0955] The identification processing 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 automatically listing jobs suitable for persons with disabilities based on data input from a company, means for transmitting the list of jobs suitable for persons with disabilities to the company, means for listing disabled candidates who meet the company's preferences from a database, means for generating a customized training program based on the company's training requirements, emotion engine means for identifying and analyzing the user's emotions, means for providing customized support content using the emotion data, and means for customizing the content of alerts based on daily report data and emotion data. This enables companies to streamline the recruitment and employment process for persons with disabilities and provide continuous support that takes emotions into consideration.

[0956] A "company" refers to an organization that provides goods and services through business activities and aims to pursue profits.

[0957] "Input data" refers to information entered into the system by users, such as business overview, number of employees, required skill sets, and purpose of employing people with disabilities.

[0958] "Disabled person" refers to an employee or job applicant who has a physical or mental impairment and requires special assistance.

[0959] "Task list" refers to a list of specific tasks suitable for people with disabilities that is created through analysis by the generative AI model.

[0960] "Database" refers to structured data storage that allows a system to efficiently store, manage, and retrieve data.

[0961] A "generative AI model" refers to an artificial intelligence model that uses machine learning algorithms to analyze data and generate task lists and training programs.

[0962] "Customized training program" refers to training content that is tailored to meet the needs of specific individuals with disabilities based on the training requirements of the company.

[0963] "Real-time answers" refers to the ability to provide immediate responses to questions regarding employment of people with disabilities.

[0964] "Daily report data" refers to the data reported by disabled workers recording their daily work, physical condition, emotions, etc.

[0965] An "anomaly detection algorithm" refers to a calculation method for analyzing daily report data and detecting patterns that are out of the ordinary.

[0966] An "emotion engine" refers to technology or software for automatically identifying and analyzing emotions from user input data and dialogue content.

[0967] An "alert" refers to a warning message sent to notify users (company personnel) of abnormalities or important information detected by the system.

[0968] "Support content" refers to the specific advice, training and assistance provided to businesses and disabled workers.

[0969] This invention is a total support system that enables companies to smoothly recruit and employ people with disabilities and provide continuous support. This system uses a generative AI model to automatically create a list of jobs suitable for people with disabilities based on data input from the company and sends that list to the company. It also includes a means for selecting candidates with disabilities who meet the company's requirements from a database and a means for the generative AI model to generate a customized training program based on the company's training requirements. Furthermore, it provides a means for answering questions about the employment of people with disabilities in real time using an AI chatbot, and a means for analyzing daily report data, detecting anomalies, and notifying company personnel. In addition, by combining it with an emotion engine, the system can recognize user emotions and use them for analysis and customizing support content.

[0970] To implement this system, a server, a dedicated terminal, a generative AI model, a database, an anomaly detection algorithm, and an emotion engine are required. Below, we will explain in detail how the system works using these components.

[0971] The user, a company representative, first enters information on a dedicated terminal, such as an overview of the company's business, the number of employees, the required skill set, and the purpose of hiring people with disabilities. For example, a company representative might enter, "We would like to hire one person to perform data entry work."

[0972] The terminal formats the data entered by the user and sends it to the server. This data specifically indicates the content of "Data entry work, number of positions available: 1."

[0973] The server stores the received data in a database and sends it to the generative AI model. The generative AI model analyzes the received data and automatically creates a list of suitable tasks. For example, it might list "Person A, Person B, and Person C are the most suitable candidates for disabled people for data entry work."

[0974] The server sends the generated job list to the company's personnel, who then selects from a database a list of candidates with disabilities who meet the company's requirements. The company's personnel then receive detailed information about the list of "Mr. A, Mr. B, and Mr. C." For example, this information may include data such as "Mr. A requires visual assistance, Mr. B is fully visually-enabled, and Mr. C requires voice assistance."

[0975] Next, the server uses the generative AI model to generate a customized training program based on the company's training requirements. For example, the training program could include "basics of data entry, how to use visual aids, and regular skill checks." The server then sends the generated training program to company personnel and disabled workers.

[0976] Furthermore, users (business representatives or workers with disabilities) can use the AI ​​chatbot to ask questions. For example, if a business representative asks, "What visual aid tools do you recommend?", the server sends this question to the generative AI model to get an answer. The generative AI model generates the answer, "Screen reader software is recommended," which the server then sends to the device and displays to the user.

[0977] The emotion engine automatically identifies emotions from user input data and dialogue content and sends the results to the server, which then uses the emotional data for analysis to customize more appropriate training programs and support content.

[0978] The user (disabled worker or person in charge) enters daily report data into the terminal, which then sends the data to the server. The server analyzes the daily report data using an anomaly detection algorithm and sends an alert to the company's person in charge if an anomaly is detected. The emotion engine analyzes emotions along with the daily report data, and the content of the alert can be customized as needed.

[0979] In this way, the present invention can streamline the hiring and employment process for people with disabilities and provide continuous support that takes emotions into consideration. Specific examples of prompts provided include "We are looking to hire one person for data entry work" and "What visual support tools do you recommend?"

[0980] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0981] Step 1:

[0982] Users (company representatives) use dedicated terminals to input information such as their company's business overview, number of employees, required skill sets, and purpose of employing people with disabilities.

[0983] Input: Company information such as business overview and number of employees.

[0984] Output: Formatted company information data.

[0985] Operation: A company employee types into the terminal, "We would like to hire one person for data entry work," and presses the "Send" button.

[0986] Step 2:

[0987] The terminal formats the input data and sends it to the server.

[0988] Input: Company information data entered by the user.

[0989] Output: The data sent to the server in JSON format.

[0990] How it works: The device formats information such as "Data entry job, 1 position available" and sends it to the server via an HTTP request.

[0991] Step 3:

[0992] The server stores the received data in a database.

[0993] Input: Company information data in formatted JSON.

[0994] Output: Company information stored in a database.

[0995] How it works: The server uses a parser to break down the data and executes SQL queries to insert it into the database.

[0996] Step 4:

[0997] The server sends the data to the generative AI model.

[0998] Input: Company information stored in a database.

[0999] Output: The business data sent to the generative AI model.

[1000] How it works: The server sends company information to the generative AI model via an HTTP request.

[1001] Step 5:

[1002] A generative AI model analyzes the data and generates a list of tasks suitable for people with disabilities.

[1003] Input: Business data sent from the server.

[1004] Output: The generated job list.

[1005] How it works: The generative AI model analyzes the data and creates a list of "the most suitable candidates for data entry work who are disabled: A, B, and C."

[1006] Step 6:

[1007] The server sends the generated list of tasks to the company representative.

[1008] Input: The list of jobs returned by the generative AI model.

[1009] Output: A list of tasks sent to the company contact.

[1010] How it works: The server sends the list of tasks to the company representative's email address or a dedicated dashboard.

[1011] Step 7:

[1012] The server searches a database of people with disabilities and lists candidates with disabilities who meet the company's requirements.

[1013] Input: Job listing and company requirements.

[1014] Output: List of potential disabled people.

[1015] How it works: The server queries the database and generates a list of matching candidates.

[1016] Step 8:

[1017] The server sends the candidate's details to the company representative.

[1018] Input: A list of potential disabled people.

[1019] Output: Detailed information sent to company contact.

[1020] How it works: The server sends the details to the company representative via email or dashboard.

[1021] Step 9:

[1022] The server generates a training program using a generative AI model.

[1023] Input: Company training requirements.

[1024] Output: The generated customized training program.

[1025] How it works: A server sends a company's requirements to a generative AI model, which generates a customized training program.

[1026] Step 10:

[1027] The server transmits the training program to business personnel and disabled workers.

[1028] Input: The generated training program.

[1029] Output: The training program is sent via email and a dedicated dashboard.

[1030] How it works: The server sends training programs to company personnel and workers.

[1031] Step 11:

[1032] The user (company representative or disabled worker) enters a question into the AI ​​chatbot.

[1033] Input: The question.

[1034] Output: The question sent to the AI ​​chatbot.

[1035] How it works: A company representative asks the chatbot, "What visual aids do you recommend?"

[1036] Step 12:

[1037] The terminal transmits the entered question to the server.

[1038] Input: The question entered.

[1039] Output: The question sent to the server.

[1040] How it works: The device analyzes the question and sends it to the server.

[1041] Step 13:

[1042] The server sends the question to the generative AI model.

[1043] Input: The question sent from the terminal.

[1044] Output: The question sent to the generative AI model.

[1045] How it works: The server sends the question to the generative AI model and requests an answer.

[1046] Step 14:

[1047] The generative AI model generates an appropriate answer based on the question and returns it to the server.

[1048] Input: The question.

[1049] Output: The generated answer.

[1050] How it works: The generative AI model generates an answer such as "Screen reader software is recommended."

[1051] Step 15:

[1052] The server sends the generated response to the terminal.

[1053] Input: The answer from the generative AI model.

[1054] Output: The answer sent to the terminal.

[1055] Action: The server sends a response to the device.

[1056] Step 16:

[1057] The terminal displays the answer to the user.

[1058] Input: The response from the server.

[1059] Output: The answer displayed on the terminal.

[1060] Behavior: The device displays "Screen reader software recommended."

[1061] Step 17:

[1062] The emotion engine identifies emotions from user input data and dialogue content.

[1063] Input: Input data and dialogue.

[1064] Output: Identified emotion data.

[1065] How it works: The emotion engine automatically identifies emotions such as "joy" and "anxiety."

[1066] Step 18:

[1067] The emotion engine sends the emotion data to the server, which uses the data for analysis.

[1068] Input: Identified emotion data.

[1069] Output: Emotion data sent to the server.

[1070] How it works: The emotion engine sends emotions, such as "anxiety," to the server, which then analyzes the data.

[1071] Step 19:

[1072] The server takes emotional data into account to customize training programs and support content.

[1073] Input: Emotion data and existing training program information.

[1074] Output: Customized training programs and support.

[1075] What it does: The server tailors a training program for users who feel "anxious," including relaxation techniques and encouragement.

[1076] Step 20:

[1077] The user inputs the daily report data into the terminal.

[1078] Input: Daily report data.

[1079] Output: Daily report data entered into the terminal.

[1080] Action: A disabled worker writes in his daily report, "I was unable to work today due to poor health."

[1081] Step 21:

[1082] The terminal transmits the daily report data to the server.

[1083] Input: Daily report data entered.

[1084] Output: Daily report data sent to the server.

[1085] Operation: The device formats the daily report data and sends it to the server.

[1086] Step 22:

[1087] The server analyzes the daily report data using an anomaly detection algorithm.

[1088] Input: Daily report data sent to the server.

[1089] Output: Anomaly detection results.

[1090] Operation: The server analyzes the daily report data and detects any abnormalities.

[1091] Step 23:

[1092] If the server detects an abnormality, it will notify the company representative.

[1093] Input: Anomaly detection results.

[1094] Output: Anomaly alert.

[1095] How it works: The server detects an anomaly and sends an alert to company personnel that "urgent action is required."

[1096] Step 24:

[1097] The emotion engine analyzes daily report data as well as user emotions and customizes alert content based on that.

[1098] Input: Daily report data and emotion data.

[1099] Output: The customized alert content.

[1100] How it works: The emotion engine analyzes the information "I'm feeling unwell and anxious today" and sends a notification to the company representative, including an alert that special consideration is needed.

[1101] (Application example 2)

[1102] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1103] Traditionally, companies that employ people with disabilities have often lacked the precision to assign appropriate tasks or the ability to customize training programs for people with disabilities. Furthermore, the lack of a way to analyze workers' emotions in real time and provide support based on those emotions makes it difficult to create an environment where workers can work sustainably and safely. This has hindered efforts to increase the employment rate of people with disabilities and improve their workplace adaptation after employment.

[1104] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for automatically listing tasks suitable for persons with disabilities based on data input from companies, means for formatting the data input from companies and sending it to the server, and means for analyzing the emotions of workers in real time and sending the emotion data to the server. This enables automatic listing of tasks based on the aptitudes of persons with disabilities and customized support based on real-time emotion analysis.

[1105] "Data input from companies" is a general term for information such as the type of work provided by companies, the required skill sets, number of employees, and the purpose of employing people with disabilities.

[1106] The "means for automatically listing jobs suitable for people with disabilities" is a function in which a generative AI model automatically identifies and lists jobs suitable for people with disabilities based on data provided by companies.

[1107] The "means of listing disabled candidates from a database who meet the company's requirements" is a process for extracting disabled candidates from a database based on the skills and requirements required by the company.

[1108] The "means for generating customized training programs" refers to the process by which a generative AI model creates training programs tailored to individual individuals with disabilities based on the training requirements set by the company.

[1109] The "means of answering questions about the employment of people with disabilities in real time" is a system in which an AI chatbot instantly responds to questions from company representatives and workers with disabilities.

[1110] The "means of analyzing daily report data and detecting abnormalities" refers to an algorithm that analyzes workers' daily report data and detects abnormalities, as well as a notification system for doing so.

[1111] "Means for analyzing workers' emotions in real time and sending emotional data to a server" refers to a function that uses an emotion engine to analyze the emotions of workers while they are working and sends the results to a server.

[1112] "Means for customizing training programs and support content based on emotional data" refers to the process of adjusting and optimizing the training programs and support content provided based on the emotional state of workers.

[1113] This invention is a total support system that enables companies to smoothly recruit, employ, and continuously support people with disabilities. The system is composed of the following:

[1114] System configuration

[1115] Hardware and Software

[1116] Hardware: Factory robots, general-purpose industrial tablets, servers

[1117] Software: Python, EmotionAnalyzer (emotion analysis engine), AIChatbot, generative AI model

[1118] Program Overview

[1119] 1. Data collection from companies:

[1120] Users (company personnel) use dedicated terminals to input information such as their company's business operations, number of employees, required skill sets, and purpose of employing people with disabilities. This input data is sent to the server.

[1121] 2. Formatting and listing the data:

[1122] The server then formats the data it receives and uses a generative AI model to automatically create a list of jobs suitable for people with disabilities. The list is then sent to the company's personnel.

[1123] 3. Database search and candidate list generation:

[1124] The server extracts from the database candidates with disabilities who meet the company's requirements, creates a list, and provides detailed information to the company's personnel.

[1125] 4. Customized training programs:

[1126] The server uses a generative AI model based on the company's training requirements to generate a training program tailored to each individual with a disability and sends it to company personnel and workers.

[1127] 5. Real-time response:

[1128] When a user (a company representative or a disabled worker) inputs a question into the AI ​​chatbot, the server analyzes the question and generates an appropriate answer using a generative AI model. The generated answer is then displayed on the device.

[1129] 6. Sentiment Analysis and Customization:

[1130] The emotion engine analyzes the worker's input data and dialogue in real time, and the resulting emotional data is sent to the server, which then analyzes the data and customizes training programs and support accordingly.

[1131] 7. Anomaly detection in daily report data:

[1132] When a user (a disabled worker or a person in charge) enters daily report data, the data is sent to the server and analyzed using an anomaly detection algorithm. If an anomaly is detected, the server sends an alert to the company's person in charge.

[1133] Examples and prompts

[1134] Company personnel enter data such as:

[1135] "I would like to hire one person to perform data entry work."

[1136] The server uses a generative AI model to generate a list of tasks, such as:

[1137] "The best candidates for disabled people for data entry work are A, B, and C."

[1138] Additionally, we create customized training programs for your company, such as:

[1139] "Data entry basics, how to use visual aids, and regular skill checks."

[1140] An example of how a chatbot can be used is to ask the following questions:

[1141] "What visual aids do you recommend?"

[1142] The server uses an AI chatbot and emotion engine to generate answers based on the following prompts:

[1143] Type of disability: Visual

[1144] Question: What are the best tools for an assembly line?

[1145] Context: Workers are anxious about new tasks

[1146] Tone of response: Encouraging

[1147] By generating specific answers using the above prompts, companies can provide support that takes into consideration the feelings of workers. This allows companies to streamline the entire process of hiring, training, and supporting people with disabilities, and also provides continuous support that takes into consideration the feelings of users.

[1148] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1149] Step 1:

[1150] The user (company representative) uses a dedicated terminal to input information such as the company's business overview, number of employees, required skill sets, and purpose of hiring people with disabilities. This input data is formatted and sent to the server. An example of input is "We would like to hire one person to perform data entry work." This information is formatted in JSON format.

[1151] Step 2:

[1152] The server analyzes the data it receives and stores it in a database, including job descriptions, number of employees, etc. The server then sends this data to a generative AI model.

[1153] Step 3:

[1154] The generative AI model analyzes the received data and automatically creates a list of suitable jobs. For example, it might list "The most suitable candidates for disabled people for data entry work are A, B, and C." The generated list is then sent back to the server.

[1155] Step 4:

[1156] The server sends the list of job information to the company's personnel. The output format is a list such as "Mr. A, Mr. B, Mr. C." The personnel will use this information to identify suitable candidates.

[1157] Step 5:

[1158] The server searches the database based on the company representative's requests and creates a list of candidates with disabilities. For example, it narrows down the candidates based on data such as "Person A needs visual assistance, Person B is fully visual, and Person C needs voice assistance." The resulting list is then sent to the company representative.

[1159] Step 6:

[1160] The server uses a generative AI model to generate a customized training program based on the company's training requirements. For example, a program might be generated that covers the basics of data entry, how to use visual support tools, and regular skill checks. The generated training program is then sent to company personnel and workers.

[1161] Step 7:

[1162] The user (a company representative or a worker with a disability) inputs a question into the AI ​​chatbot. For example, a question might be asked, "What visual support tools do you recommend?" The device then sends this question to the server.

[1163] Step 8:

[1164] The server receives and analyzes the question and generates an appropriate answer based on the generative AI model. For example, it might generate an answer such as "Screen reader software is recommended." The generated answer is sent to the device and displayed on the screen.

[1165] Step 9:

[1166] The emotion engine automatically identifies emotions from the user's input data and dialogue content. For example, it identifies emotions such as "joy" or "anxiety" from the user's input content and dialogue history. The identified emotion data is sent to the server.

[1167] Step 10:

[1168] The server analyzes the emotional data and customizes the training program and support content based on that data. For example, for a user who is feeling anxious, the server customizes the training program to include relaxation techniques and encouraging content, thereby providing more appropriate support.

[1169] Step 11:

[1170] The user (disabled worker or person in charge) inputs daily report data into the terminal. For example, the user may write in the daily report, "I was unable to work today due to poor health." The input daily report data is formatted and sent to the server.

[1171] Step 12:

[1172] The server analyzes the received daily report data using an anomaly detection algorithm. For example, information about "feeling unwell" is run through the algorithm, and if an abnormality is detected, an alert is sent to the company's responsible person.

[1173] Step 13:

[1174] The emotion engine analyzes the user's emotions along with the daily report data and customizes the alert content based on the results. For example, if the information is "I'm feeling unwell and anxious today," it will notify the person in charge that "special attention is required."

[1175] By taking these steps, companies can streamline the entire process of recruiting, training, and supporting people with disabilities, and provide ongoing support that takes users' emotions into consideration.

[1176] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1177] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1178] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1179] [Third embodiment]

[1180] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1181] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1182] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1183] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1184] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1185] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1186] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1187] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1188] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1189] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1190] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1191] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1192] This invention provides a total support system that enables companies to smoothly recruit and employ people with disabilities and provide continuous support. This system uses a generative AI model to automatically create a list of jobs suitable for people with disabilities based on data input from the company and sends the list to the company. It also includes a means for selecting candidates with disabilities who meet the company's requirements from a database and a means for the generative AI model to generate a customized training program based on the company's training requirements. Furthermore, the system has a means for using an AI chatbot to answer questions about the employment of people with disabilities in real time and a means for analyzing daily report data, detecting anomalies, and notifying company personnel.

[1193] Natural language description of the program

[1194] 1. The user (company representative) enters information such as an overview of their company's business, number of employees, required skill sets, and the purpose of employing people with disabilities on a dedicated terminal.

[1195] Example: A company employee types into a terminal, "We would like to hire one person to perform data entry work."

[1196] 2. The terminal formats the input data and sends it to the server, which stores it in a database.

[1197] Example: The terminal sends information such as "Data entry work, 1 position" to the server, which then stores it in a database.

[1198] 3. The server sends the received data to a generative AI model, which automatically generates a list of jobs suitable for people with disabilities. This list is then immediately sent to the company's representative.

[1199] Example: The AI ​​model creates a list of "the best candidates for data entry work are A, B, and C" and notifies the person in charge.

[1200] 4. The server searches a database of people with disabilities and lists candidates with disabilities who meet the company's requirements.

[1201] Example: The server creates a list of suitable candidates based on data such as "Person A needs visual assistance, Person B is fully visually capable, and Person C needs audio assistance."

[1202] 5. The server uses the generative AI model to generate a customized training program based on the company's training requirements, and sends the program to the company's personnel and disabled workers.

[1203] Example: AI generates training programs such as "basics of data entry, how to use visual support tools, and regular skill checks" and sends them to staff and people with disabilities.

[1204] 6. An AI chatbot will be available 24 hours a day to answer questions about employment for people with disabilities in real time.

[1205] Example: A company representative asks a chatbot, "What visual aid tools do you recommend?" and the chatbot immediately replies, "We recommend screen reader software."

[1206] 7. The server receives the daily report data entered by the disabled worker or the person in charge and analyzes the data using an anomaly detection algorithm. If an anomaly is detected, an alert is sent to the company's person in charge.

[1207] Example: A disabled worker writes in his daily report that "I was unable to work today due to poor health," and the server detects this information and alerts the person in charge that "urgent action is required."

[1208] This will enable companies to streamline the entire process of recruiting, training, and supporting people with disabilities, and provide ongoing support.

[1209] The processing flow will be explained below.

[1210] Step 1:

[1211] The user (company representative) operates the terminal to input information such as an overview of the company's business, number of employees, required skill sets, and the purpose of employing people with disabilities.

[1212] Example: A company employee types into a terminal, "We would like to hire one person to perform data entry work."

[1213] Step 2:

[1214] The terminal formats the data entered by the user and sends the data to the server.

[1215] Example: The terminal sends information such as "Data entry work, 1 position available" to the server.

[1216] Step 3:

[1217] The server stores the received data in a database.

[1218] Example: A server stores information such as "Data entry job, 1 position available" in a database.

[1219] Step 4:

[1220] The server sends the stored data to the generative AI model.

[1221] Example: The server sends the information "data entry work, number of positions available: 1" to the generative AI model.

[1222] Step 5:

[1223] The generative AI model analyzes the received data and automatically creates a list of tasks suitable for people with disabilities.

[1224] Example: The AI ​​model creates a list of candidates with disabilities who are best suited for data entry work: A, B, and C.

[1225] Step 6:

[1226] The server sends the generated list of tasks to the company representative.

[1227] Example: The server sends a list of information about "Mr. A, Mr. B, and Mr. C" to a company representative.

[1228] Step 7:

[1229] The server searches a database of people with disabilities and lists candidates with disabilities who meet the company's requirements.

[1230] Example: The server creates a list of suitable candidates based on data such as "Person A needs visual assistance, Person B is fully visually capable, and Person C needs audio assistance."

[1231] Step 8:

[1232] The server sends detailed information of the listed suitable candidates to the company representative.

[1233] Example: The server sends detailed information about "Mr. A, Mr. B, and Mr. C" to the person in charge.

[1234] Step 9:

[1235] The server generates a customized training program using a generative AI model based on the company's training requirements.

[1236] Example: AI generates customized training programs such as "basics of data entry, how to use visual support tools, and regular skill checks."

[1237] Step 10:

[1238] The server transmits the generated training program to the company personnel and the disabled workers.

[1239] Example: A server sends training programs to personnel and workers, such as "Basics of data entry, how to use visual aids, and regular skill checks."

[1240] Step 11:

[1241] The user (company representative or disabled worker) enters a question into the AI ​​chatbot.

[1242] Example: A company representative asks the chatbot, "What visual support tools do you recommend?"

[1243] Step 12:

[1244] The terminal transmits the entered question to the server.

[1245] Example: A device sends a question to a server: "What visual support tools do you recommend?"

[1246] Step 13:

[1247] The server analyzes the question and requests the appropriate answer from the generative AI model.

[1248] Example: The server sends the analysis results of a "question about visual support tools" to a generative AI model.

[1249] Step 14:

[1250] The generative AI model generates an appropriate answer based on the question and returns it to the server.

[1251] Example: An AI model generates the answer "Screen reader software is recommended."

[1252] Step 15:

[1253] The server generates a response and sends it back to the terminal.

[1254] Example: The server sends a response to the device saying "Screen reader software is recommended."

[1255] Step 16:

[1256] The device displays the answer on the screen.

[1257] Example: The device displays the response "Screen reader software recommended" on the screen.

[1258] Step 17:

[1259] The user (disabled worker or person in charge) enters the daily report data into the terminal.

[1260] Example: A disabled worker writes in his daily report, "I was unable to work today due to poor health."

[1261] Step 18:

[1262] The terminal transmits the input daily report data to the server.

[1263] Example: A terminal sends daily report data to a server stating, "I was unable to work today due to poor health."

[1264] Step 19:

[1265] The server analyzes the received daily report data using an anomaly detection algorithm.

[1266] Example: The server runs the "illness" information through an anomaly detection algorithm.

[1267] Step 20:

[1268] If the server detects an abnormality, it will send an alert to company personnel.

[1269] Example: A server sends an "urgent action required" alert to a company representative.

[1270] Example 1

[1271] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1272] The goal is to solve the many challenges that arise when companies hire and employ people with disabilities. Conventional methods require time and effort to create a list of jobs suitable for people with disabilities, identify suitable candidates, create training programs, and detect anomalies in daily report data, making these tasks inefficient. Furthermore, there are no adequate means to respond to questions about hiring people with disabilities in real time.

[1273] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1274] In this invention, the server includes means for automatically creating a list of jobs suitable for persons with disabilities based on data input from a terminal, means for sending the list of jobs suitable for persons with disabilities to a company, means for compiling a list of disabled candidates from a database that meets the company's preferences, means for using a generative AI model to create a customized training program based on the company's training requirements, means for using an AI chatbot to answer questions about the employment of persons with disabilities in real time, means for analyzing daily report data, detecting anomalies, and notifying company personnel, and means for formatting input data from the terminal and sending it to the server. This makes it possible to select jobs and candidates suitable for persons with disabilities based on data input from the terminal, provide customized training programs, respond to questions about the employment of persons with disabilities in real time, and detect and notify anomalies in daily report data.

[1275] A "terminal" is a hardware device for inputting and displaying data.

[1276] A "server" is a hardware and software configuration for storing, processing, sending and receiving data over a network.

[1277] A "generative AI model" is an algorithm that uses artificial intelligence technology to automate and optimize specific tasks.

[1278] A "list" is a collection of data that is organized and categorized based on specific criteria.

[1279] A "database" is a software system for efficiently storing, searching, and managing large amounts of data.

[1280] "Training Program" means an educational or training plan designed to acquire specific skills or knowledge.

[1281] An "AI chatbot" is a program that uses artificial intelligence technology to automatically hold conversations and provide answers to users' questions in real time.

[1282] "Daily report data" refers to information that records the progress of work and working conditions.

[1283] An "anomaly detection algorithm" is a computational method for analyzing data and detecting unusual patterns or anomalies.

[1284] An "alert" is a notification that notifies you of an abnormality or important information.

[1285] A "customized training program" is an education and training plan that is tailored to the requirements of a specific company or individual.

[1286] "Input data" refers to information entered into the system via a terminal.

[1287] "Real-time" refers to a state in which data processing and information provision are carried out immediately.

[1288] This is a total support system that enables companies to smoothly recruit, employ, and continuously support people with disabilities. The system is implemented using a server, terminals, a generative AI model, a database, and an AI chatbot.

[1289] First, the user (company representative) enters information such as the job summary, number of employees, required skill set, and purpose of hiring people with disabilities into a dedicated terminal. This information is necessary to clarify the skills and conditions that the company is looking for in people with disabilities. As a concrete example, the user might enter the following into the terminal: "We would like to hire one person to do data entry work. Visual assistance is required."

[1290] Next, the terminal formats the input data and sends it to the server. The formatted data is converted into a format that the server can easily accept, such as JSON. For example, the terminal converts information such as "Task: Data entry, Number of people: 1, Visual support: Required" into JSON format and sends it to the server.

[1291] The server stores the received data in a database. At the same time, it sends the data to the generative AI model and instructs it to analyze it. The generative AI model automatically creates a list of tasks suitable for people with disabilities based on the data entered from the device. This list includes specific tasks suitable for people with disabilities and candidates based on the company's requirements. As a concrete example, the generative AI model creates a list such as "The best candidates for data entry work are Person A, Person B, and Person C," and the server sends this list to the company employee's device.

[1292] The server then searches a database of people with disabilities and creates a list of candidates who meet the company's requirements. The list includes the skillsets and support required by each person with a disability. For example, the server creates a list based on data such as "Person A needs visual support, Person B needs voice support, and Person C needs physical support," and sends it to the company's representative.

[1293] The server also uses a generative AI model to generate a customized training program based on the company's training requirements. This program is tailored to each company's specific needs. The generated program is then sent to the company's personnel and disabled workers. For example, the AI ​​generates a training program titled "Basics of data entry, how to use visual aids, and regular skill checks," and sends it to the company's personnel and disabled workers via email.

[1294] An AI chatbot is available 24 hours a day to answer questions about the employment of people with disabilities in real time. This AI chatbot uses natural language processing technology to answer questions from users. For example, if a company representative asks the chatbot, "What visual assistance tools do you recommend?", the chatbot will immediately reply, "We recommend screen reader software."

[1295] Finally, the server analyzes the daily report data and notifies company personnel if an abnormality is detected. When disabled workers or personnel enter daily report data into their terminals, the server analyzes the data using an anomaly detection algorithm, and if an abnormality is detected, it notifies company personnel as an alert. For example, if a disabled worker enters in their daily report that "I was unable to work today due to poor health," the server analyzes the information and sends an alert to company personnel that "urgent action is required."

[1296] Prompt Sentence Examples

[1297] Job Listing: "Job Description: Data Entry. Position: 1. Please list suitable candidates."

[1298] Candidate Listing: "Company Request: Please list candidates who can handle data entry work."

[1299] Training Program Generation: "Training Requirements: Please generate a training program that includes training content on basic data entry skills and how to use visual aids."

[1300] Chatbot response example: "Question about employment for people with disabilities: What visual aids do you recommend?"

[1301] Anomaly detection: "Daily report data analysis: It is stated that the employee was unable to work today due to poor health. Please detect any anomalies and notify us."

[1302] These components enable companies to streamline the entire process of hiring, training, and supporting people with disabilities, and provide continuous support. By utilizing generative AI models and AI chatbots, the system achieves automation and real-time responses, contributing to companies' promotion of hiring people with disabilities.

[1303] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1304] Step 1:

[1305] The user (company representative) enters information such as the business overview, number of employees, required skill sets, and purpose of employing people with disabilities on a dedicated terminal.

[1306] Input: Details such as job description, number of employees, skill set, and employment objectives

[1307] Output: Formatted input data

[1308] Specific example of operation: A company representative enters detailed information into the input field on the terminal, such as "We would like to hire one person for data entry work. Visual assistance is required.", and presses the send button.

[1309] Step 2:

[1310] The terminal formats the input data and sends it to the server.

[1311] Input: Entered business information, number of employees, skill sets, employment purpose

[1312] Output: Formatted data such as JSON

[1313] Specific example of operation: The terminal converts the information "Task: Data entry, Number of people: 1, Visual support: Required" into JSON format and sends it to the server.

[1314] Step 3:

[1315] The server stores the received data in a database and simultaneously sends the data to the generative AI model, instructing it to analyze it.

[1316] Input: Formatted input data

[1317] Output: Data stored in a database, data sent to a generative AI model

[1318] Specific example of operation: The server records the data "Task: Data entry, Number of people: 1, Visual support: Required" in the database and requests the generative AI model to analyze it.

[1319] Step 4:

[1320] The generative AI model automatically creates a list of jobs suitable for people with disabilities based on the data it receives, and the server sends that list to the company's representative.

[1321] Input: Data sent to the generative AI model

[1322] Output: List of jobs suitable for people with disabilities, notified list

[1323] Specific example of operation: The generative AI model creates a list of "the best candidates for data entry work are A, B, and C," and the server sends this to the company employee's device.

[1324] Step 5:

[1325] The server searches a database of people with disabilities and lists candidates with disabilities who meet the company's requirements.

[1326] Input: Company preferences and disability database

[1327] Output: A list of possible matching disabilities

[1328] Specific example of operation: The server creates a list based on data such as "Person A needs visual assistance, Person B needs audio assistance, and Person C needs physical assistance" and sends it to the company representative.

[1329] Step 6:

[1330] The server uses a generative AI model to generate a customized training program based on the company's training requirements and sends it to company personnel and disabled workers.

[1331] Input: Training requirements, analysis data for the generative AI model

[1332] Output: Customized training program, transmitted program

[1333] Specific example of how it works: The AI ​​generates a training program on "basics of data entry, how to use visual support tools, and regular skill checks" and sends it via email to company representatives and disabled workers.

[1334] Step 7:

[1335] An AI chatbot is available 24 hours a day to answer questions about employment for people with disabilities in real time.

[1336] Input: User question

[1337] Output: Answer by AI chatbot

[1338] A specific example of how it works: A company representative asks the chatbot, "What visual support tools do you recommend?" and the chatbot immediately replies, "We recommend screen reader software."

[1339] Step 8:

[1340] The server analyzes the daily report data and notifies company personnel if an abnormality is detected.

[1341] Input: Daily report data, anomaly detection algorithm

[1342] Output: Alert notification when an abnormality is detected

[1343] A concrete example of how it works: When a disabled worker enters in their daily report that "I was unable to work today due to poor health," the server analyzes the information and alerts company personnel that "urgent action is required."

[1344] (Application example 1)

[1345] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1346] In modern manufacturing, employing people with disabilities is important from the perspective of corporate social responsibility and diversity. However, many companies face the challenge of finding appropriate work and training programs to provide a safe and efficient working environment for people with disabilities. In particular, when employing people with disabilities in factories, support is required to ensure both safety and efficiency, but the reality is that the technological means to achieve this are not fully in place.

[1347] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1348] In this invention, the server includes means for automatically creating a list of jobs suitable for persons with disabilities based on data input from a company, means for sending the list of jobs suitable for persons with disabilities to the company, means for compiling a list of disabled candidates from a database that meets the company's preferences, means for creating a customized training program based on the company's training requirements, means for answering questions about the employment of persons with disabilities in real time, means for analyzing daily report data and detecting abnormalities, means for providing support for persons with disabilities to work safely and efficiently in factories, and means for displaying the created job list and training program on a smart device in real time. This enables companies to provide comprehensive support for persons with disabilities, from hiring to training and daily operations, enabling them to work safely and efficiently.

[1349] An "enterprise" is a corporation or individual that conducts economic activities as an organization and provides goods and services.

[1350] "Input data" refers to the information that companies enter into the system, including details of the business, number of employees, required skill sets, and the purpose of employing people with disabilities.

[1351] "Disabled persons" refers to people with physical, mental or sensory impairments who may require special assistance or accommodations.

[1352] "Means for automatically listing tasks" refers to a function that uses a generative AI model to analyze input data and automatically list tasks suitable for people with disabilities.

[1353] "Means for sending the list to the company" refers to a function for electronically notifying the person in charge at the company of the generated business list.

[1354] A "database" is a collection of information that stores information and manages it in an organized manner, allowing it to be searched and listed efficiently.

[1355] "Means for generating training programs" refers to the ability to automatically generate customized training programs using generative AI models based on a company's training requirements.

[1356] "Real-time response means" refers to the ability to instantly provide answers to questions about employment for people with disabilities using generative AI models.

[1357] "Daily report data" refers to records used by disabled workers or those in charge to report on their daily work status, health condition, etc.

[1358] "Means for detecting abnormalities" refers to the function of analyzing daily report data and automatically detecting abnormalities that differ from normal work or health conditions.

[1359] "Measures to provide support within the factory" refers to the technical and human support systems that provide an environment in which persons with disabilities can work safely and efficiently within the factory.

[1360] A "smart device" is a portable electronic device that is capable of connecting to the Internet and has advanced computing power and is capable of running applications, and includes smartphones, smart glasses, head-mounted displays, etc.

[1361] "A means to view generated work lists and training programs in real time" refers to the function that allows generated work lists and training programs to be instantly checked via a smart device.

[1362] The system of the present invention provides total support for companies to smoothly recruit and employ people with disabilities and provide continuous support. This system uses a generative AI model to automatically create a list of jobs suitable for people with disabilities based on data input from the company and transmits the list to the company. It also includes a database listing candidates with disabilities who meet the company's requirements, and a generative AI model to generate a customized training program based on the company's training requirements. Furthermore, the system provides real-time answers to questions about the employment of people with disabilities using an AI chatbot, and a means for analyzing daily report data, detecting abnormalities, and notifying company personnel. When applied to factories, the system supports people with disabilities in working safely and efficiently, allowing them to access necessary information in real time on smart devices.

[1363] The server receives information entered by companies, such as job descriptions, number of employees, required skill sets, and the purpose of hiring people with disabilities, formats it, and stores it in a database. This data is then sent to a generative AI model, which creates a list of jobs suitable for people with disabilities. The generated list of jobs is immediately notified to company personnel. Similarly, the system also has the function of listing candidates with disabilities from the database. This allows companies to quickly find suitable candidates with disabilities.

[1364] Based on the training requirements of the company, the server uses a generative AI model to generate a customized training program.An AI chatbot is also installed, which can provide instant answers to questions about disability employment from company personnel and disabled workers.

[1365] For daily report data, disabled workers or staff enter information about their daily work and health into a terminal and send it to a server. The server analyzes this data and notifies the company staff if it detects any abnormalities. This anomaly detection uses an algorithm that automatically detects abnormalities that differ from normal work or health conditions.

[1366] The system also includes a means to enable workers with disabilities to access generated job lists and training programs in real time using smart devices, enabling them to work safely and efficiently in factories.

[1367] As a concrete example, consider the case where a company employee inputs, "We would like to hire one worker with basic machine operation skills." This data is sent to the server, and the generative AI model generates a list of suitable tasks, such as "simple machine operation, parts assembly, and shipping preparation." This list is notified to the employee, who then generates a customized training program, such as "basic machine operation training, explanation of assembly procedures, and shipping preparation methods." The employee can also ask, "What visual support tools do you recommend?" and the AI ​​chatbot can respond, "Screen reader software is recommended."

[1368] Here are some examples of prompts to input to the generative AI model:

[1369] 1. Generate a list of tasks:

[1370] Company information: Major manufacturing company, 500 employees, required skill set is basic machine operation, purpose of employing people with disabilities is to promote diversity and contribute to society

[1371] Generate a suitable task list.

[1372] 2. Generating training programs:

[1373] Job List: Simple machine operation, parts assembly, shipping preparation

[1374] Generate a training program based on this.

[1375] 3. Real-time chat support:

[1376] Disability employment question: What visual aids do you recommend?

[1377] Please respond in real time.

[1378] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1379] Step 1:

[1380] A user uses a dedicated terminal to input company information, including a business overview, number of employees, required skill sets, and the purpose of hiring people with disabilities. This data is formatted by the terminal and sent to the server. The input data on the terminal is, "We would like to hire one worker who can operate basic machines."

[1381] Step 2:

[1382] The server stores the received company information in a database. Specifically, it converts the input data into an appropriate format and stores it in the database. For example, information such as "basic machine operation, number of employees: 1" is stored.

[1383] Step 3:

[1384] The server sends the saved company information to the generative AI model, which then analyzes the input data using prompts and generates a list of tasks suitable for people with disabilities. The generated list of tasks is called "simple machine operation, parts assembly, and shipping preparation."

[1385] Step 4:

[1386] The server receives the task list generated by the generative AI model and sends it to the company's personnel. This includes sending notifications containing the task list via email or notification system. The output is "Suitable task list: simple machine operation, parts assembly, and shipping preparation."

[1387] Step 5:

[1388] The server searches the database and lists candidates with disabilities who meet the company's requirements. The search results are a list of suitable candidates such as "Mr. A, Mr. B, Mr. C."

[1389] Step 6:

[1390] The server uses a generative AI model to generate a customized training program based on the company's training requirements. The training program generated by this prompt is "Training basic machine operation, explaining assembly procedures, and how to prepare for shipment."

[1391] Step 7:

[1392] The server sends the generated training program to company personnel and disabled workers. This includes sending notifications containing the training program details via email and notification systems. The output is "specific training program details."

[1393] Step 8:

[1394] A user inputs a question about employment for people with disabilities into the AI ​​chatbot, for example, "What visual assistive tools do you recommend?"

[1395] Step 9:

[1396] The AI ​​chatbot answers questions in real time, using a generative AI model to generate appropriate answers and provide them to the user. The output is an immediate response such as "Screen reader software recommended."

[1397] Step 10:

[1398] The user inputs daily report data into the terminal, and the server receives the data. For example, the daily report may include, "I was not feeling well today and was unable to work."

[1399] Step 11:

[1400] The server analyzes the daily report data and detects anomalies. If an anomaly is detected, the server sends a notification to the company's responsible person. The output is an alert stating "Anomaly detected: Notify responsible person."

[1401] Step 12:

[1402] Users can view the generated work lists and training programs in real time using smart devices such as smartphones, smart glasses, and head-mounted displays.

[1403] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1404] This invention provides a system that provides more effective support by combining an emotion engine with a total support system that enables companies to smoothly recruit, employ, and sustainably support people with disabilities. This system includes a means for automatically creating a list of tasks suitable for people with disabilities using a generative AI model based on data input from the company and sending that list to the company. It also includes a means for selecting candidates with disabilities who meet the company's requirements from a database and a means for generating a customized training program using the generative AI model based on the company's training requirements. Furthermore, it includes a means for using an AI chatbot to answer questions about the employment of people with disabilities in real time and a means for analyzing daily report data, detecting anomalies, and notifying company personnel. In addition, by incorporating an emotion engine, the system can recognize user emotions and use them for analysis and customizing support content.

[1405] Natural language description of the program

[1406] 1. The user (company representative) enters information such as an overview of their company's business, number of employees, required skill sets, and the purpose of employing people with disabilities on a dedicated terminal.

[1407] Example: A company employee types into a terminal, "We would like to hire one person to perform data entry work."

[1408] 2. The terminal formats the data entered by the user and sends the data to the server.

[1409] Example: The terminal sends information such as "Data entry work, 1 position available" to the server.

[1410] 3. The server stores the received data in a database.

[1411] Example: A server stores information such as "Data entry job, 1 position available" in a database.

[1412] 4. The server sends the stored data to the generative AI model.

[1413] Example: The server sends the information "data entry work, number of positions available: 1" to the generative AI model.

[1414] 5. The generative AI model analyzes the received data and automatically creates a list of tasks suitable for people with disabilities.

[1415] Example: The AI ​​model creates a list of candidates with disabilities who are best suited for data entry work: A, B, and C.

[1416] 6. The server sends the generated list of tasks to the company representative.

[1417] Example: The server sends a list of information about "Mr. A, Mr. B, and Mr. C" to a company representative.

[1418] 7. The server searches the database of disabled people and lists candidates with disabilities who meet the company's requirements.

[1419] Example: The server creates a list of suitable candidates based on data such as "Person A needs visual assistance, Person B is fully visually capable, and Person C needs audio assistance."

[1420] 8. The server sends the details of the listed matching candidates to the company representative.

[1421] Example: The server sends detailed information about "Mr. A, Mr. B, and Mr. C" to the person in charge.

[1422] 9. The server generates a customized training program using the generative AI model based on the company's training requirements.

[1423] Example: AI generates customized training programs such as "basics of data entry, how to use visual support tools, and regular skill checks."

[1424] 10. The server sends the generated training program to the company's personnel and the disabled worker.

[1425] Example: A server sends training programs to personnel and workers, such as "Basics of data entry, how to use visual aids, and regular skill checks."

[1426] 11. The user (company representative or disabled worker) enters a question into the AI ​​chatbot.

[1427] Example: A company representative asks the chatbot, "What visual support tools do you recommend?"

[1428] 12. The terminal sends the entered question to the server.

[1429] Example: A device sends a question to a server: "What visual support tools do you recommend?"

[1430] 13. The server analyzes the question and requests the appropriate answer from the generative AI model.

[1431] Example: The server sends the analysis results of a "question about visual support tools" to a generative AI model.

[1432] 14. The generative AI model generates an appropriate answer based on the question and returns it to the server.

[1433] Example: An AI model generates the answer "Screen reader software is recommended."

[1434] 15. The server generates a response and sends it back to the device.

[1435] Example: The server sends a response to the device saying "Screen reader software is recommended."

[1436] 16. The device will display the answer on the screen.

[1437] Example: The device displays the response "Screen reader software recommended" on the screen.

[1438] 17. The emotion engine automatically identifies emotions from user input data and dialogue.

[1439] Example: An emotion engine identifies emotions such as "joy" or "anxiety" from user input and dialogue history.

[1440] 18. The emotion engine sends the identified emotion data to the server, which uses the emotion data for analysis.

[1441] Example: An emotion engine identifies the emotion "anxiety" and sends that information to a server.

[1442] 19. The server will also take emotional data into account to customize more appropriate training programs and support content.

[1443] Example: A server customizes a training program for users who feel "anxious," including relaxation techniques and encouragement.

[1444] 20. The user (disabled worker or person in charge) enters the daily report data into the terminal.

[1445] Example: A disabled worker writes in his daily report, "I was unable to work today due to poor health."

[1446] 21. The terminal sends the entered daily report data to the server.

[1447] Example: A terminal sends daily report data to a server stating, "I was unable to work today due to poor health."

[1448] 22. The server analyzes the received daily report data using an anomaly detection algorithm.

[1449] Example: The server runs the "illness" information through an anomaly detection algorithm.

[1450] 23. If the server detects an abnormality, it will send an alert to the company representative.

[1451] Example: A server sends an "urgent action required" alert to a company representative.

[1452] 24. The emotion engine analyzes daily report data as well as user emotions and customizes alert content based on that.

[1453] Example: The emotion engine analyzes the information "I am feeling unwell and anxious today" and notifies the person in charge that "special consideration is required."

[1454] This will enable companies to streamline the entire process of recruiting, training, and supporting people with disabilities, and also provide ongoing support that takes users' emotions into consideration.

[1455] The processing flow will be explained below.

[1456] Step 1:

[1457] The user (company representative) enters information such as the company's business overview, number of employees, required skill sets, and purpose of employing people with disabilities on the terminal.

[1458] Example: A company employee types into a terminal, "We would like to hire one person to perform data entry work."

[1459] Step 2:

[1460] The terminal formats the data entered by the user and sends the data to the server.

[1461] Example: The terminal sends information such as "Data entry work, 1 position available" to the server.

[1462] Step 3:

[1463] The server stores the received data in a database.

[1464] Example: A server stores information such as "Data entry job, 1 position available" in a database.

[1465] Step 4:

[1466] The server sends the stored data to the generative AI model.

[1467] Example: The server sends the information "data entry work, number of positions available: 1" to the generative AI model.

[1468] Step 5:

[1469] The generative AI model analyzes the received data and automatically creates a list of tasks suitable for people with disabilities.

[1470] Example: The AI ​​model creates a list of candidates with disabilities who are best suited for data entry work: A, B, and C.

[1471] Step 6:

[1472] The server sends the generated list of tasks to the company representative.

[1473] Example: The server sends a list of information about "Mr. A, Mr. B, and Mr. C" to a company representative.

[1474] Step 7:

[1475] The server searches a database of people with disabilities and lists candidates with disabilities who meet the company's requirements.

[1476] Example: The server creates a list of suitable candidates based on data such as "Person A needs visual assistance, Person B is fully visually capable, and Person C needs audio assistance."

[1477] Step 8:

[1478] The server sends detailed information of the listed suitable candidates to the company representative.

[1479] Example: The server sends detailed information about "Mr. A, Mr. B, and Mr. C" to the person in charge.

[1480] Step 9:

[1481] The server generates a customized training program using a generative AI model based on the company's training requirements.

[1482] Example: AI generates customized training programs such as "basics of data entry, how to use visual support tools, and regular skill checks."

[1483] Step 10:

[1484] The server transmits the generated training program to the company personnel and the disabled workers.

[1485] Example: A server sends training programs to personnel and workers, such as "Basics of data entry, how to use visual aids, and regular skill checks."

[1486] Step 11:

[1487] The user (company representative or disabled worker) enters a question into the AI ​​chatbot.

[1488] Example: A company representative asks the chatbot, "What visual support tools do you recommend?"

[1489] Step 12:

[1490] The terminal transmits the entered question to the server.

[1491] Example: A device sends a question to a server: "What visual support tools do you recommend?"

[1492] Step 13:

[1493] The server analyzes the question and requests the appropriate answer from the generative AI model.

[1494] Example: The server sends the analysis results of a "question about visual support tools" to a generative AI model.

[1495] Step 14:

[1496] The generative AI model generates an appropriate answer based on the question and returns it to the server.

[1497] Example: An AI model generates the answer "Screen reader software is recommended."

[1498] Step 15:

[1499] The server generates a response and sends it back to the terminal.

[1500] Example: The server sends a response to the device saying "Screen reader software is recommended."

[1501] Step 16:

[1502] The device displays the answer on the screen.

[1503] Example: The device displays the response "Screen reader software recommended" on the screen.

[1504] Step 17:

[1505] The emotion engine automatically identifies emotions from user input data and dialogue content.

[1506] Example: An emotion engine identifies emotions such as "joy" or "anxiety" from user input and dialogue history.

[1507] Step 18:

[1508] The emotion engine sends the identified emotion data to the server, which uses the emotion data for analysis.

[1509] Example: An emotion engine identifies the emotion "anxiety" and sends that information to a server.

[1510] Step 19:

[1511] The server also takes emotional data into account to customize more appropriate training programs and support content.

[1512] Example: A server customizes a training program for users who feel "anxious," including relaxation techniques and encouragement.

[1513] Step 20:

[1514] The user (disabled worker or person in charge) enters the daily report data into the terminal.

[1515] Example: A disabled worker writes in his daily report, "I was unable to work today due to poor health."

[1516] Step 21:

[1517] The terminal transmits the input daily report data to the server.

[1518] Example: A terminal sends daily report data to a server stating, "I was unable to work today due to poor health."

[1519] Step 22:

[1520] The server analyzes the received daily report data using an anomaly detection algorithm.

[1521] Example: The server runs the "illness" information through an anomaly detection algorithm.

[1522] Step 23:

[1523] If the server detects an abnormality, it will send an alert to company personnel.

[1524] Example: A server sends an "urgent action required" alert to a company representative.

[1525] Step 24:

[1526] The emotion engine analyzes daily report data as well as user emotions and customizes alert content based on that.

[1527] Example: The emotion engine analyzes the information "I am feeling unwell and anxious today" and notifies the person in charge that "special consideration is required."

[1528] Example 2

[1529] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1530] The current recruitment and hiring process for people with disabilities in companies is difficult to accommodate special needs and individual requirements, making it difficult to operate efficiently. Furthermore, there is insufficient support that takes into account the feelings and individual needs of people with disabilities, and there is no sustainable support system in place. This has led to a need for effective tools to facilitate the recruitment and hiring process for people with disabilities and provide continuous support.

[1531] The identification processing 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 automatically listing jobs suitable for persons with disabilities based on data input from a company, means for transmitting the list of jobs suitable for persons with disabilities to the company, means for listing disabled candidates who meet the company's preferences from a database, means for generating a customized training program based on the company's training requirements, emotion engine means for identifying and analyzing the user's emotions, means for providing customized support content using the emotion data, and means for customizing the content of alerts based on daily report data and emotion data. This enables companies to streamline the recruitment and employment process for persons with disabilities and provide continuous support that takes emotions into consideration.

[1532] A "company" refers to an organization that provides goods and services through business activities and aims to pursue profits.

[1533] "Input data" refers to information entered into the system by users, such as business overview, number of employees, required skill sets, and purpose of employing people with disabilities.

[1534] "Disabled person" refers to an employee or job applicant who has a physical or mental impairment and requires special assistance.

[1535] "Task list" refers to a list of specific tasks suitable for people with disabilities that is created through analysis by the generative AI model.

[1536] "Database" refers to structured data storage that allows a system to efficiently store, manage, and retrieve data.

[1537] A "generative AI model" refers to an artificial intelligence model that uses machine learning algorithms to analyze data and generate task lists and training programs.

[1538] "Customized training program" refers to training content that is tailored to meet the needs of specific individuals with disabilities based on the training requirements of the company.

[1539] "Real-time answers" refers to the ability to provide immediate responses to questions regarding employment of people with disabilities.

[1540] "Daily report data" refers to the data reported by disabled workers recording their daily work, physical condition, emotions, etc.

[1541] An "anomaly detection algorithm" refers to a calculation method for analyzing daily report data and detecting patterns that are out of the ordinary.

[1542] An "emotion engine" refers to technology or software for automatically identifying and analyzing emotions from user input data and dialogue content.

[1543] An "alert" refers to a warning message sent to notify users (company personnel) of abnormalities or important information detected by the system.

[1544] "Support content" refers to the specific advice, training and assistance provided to businesses and disabled workers.

[1545] This invention is a total support system that enables companies to smoothly recruit and employ people with disabilities and provide continuous support. This system uses a generative AI model to automatically create a list of jobs suitable for people with disabilities based on data input from the company and sends that list to the company. It also includes a means for selecting candidates with disabilities who meet the company's requirements from a database and a means for the generative AI model to generate a customized training program based on the company's training requirements. Furthermore, it provides a means for answering questions about the employment of people with disabilities in real time using an AI chatbot, and a means for analyzing daily report data, detecting anomalies, and notifying company personnel. In addition, by combining it with an emotion engine, the system can recognize user emotions and use them for analysis and customizing support content.

[1546] To implement this system, a server, a dedicated terminal, a generative AI model, a database, an anomaly detection algorithm, and an emotion engine are required. Below, we will explain in detail how the system works using these components.

[1547] The user, a company representative, first enters information on a dedicated terminal, such as an overview of the company's business, the number of employees, the required skill set, and the purpose of hiring people with disabilities. For example, a company representative might enter, "We would like to hire one person to perform data entry work."

[1548] The terminal formats the data entered by the user and sends it to the server. This data specifically indicates the content of "Data entry work, number of positions available: 1."

[1549] The server stores the received data in a database and sends it to the generative AI model. The generative AI model analyzes the received data and automatically creates a list of suitable tasks. For example, it might list "Person A, Person B, and Person C are the most suitable candidates for disabled people for data entry work."

[1550] The server sends the generated job list to the company's personnel, who then selects from a database a list of candidates with disabilities who meet the company's requirements. The company's personnel then receive detailed information about the list of "Mr. A, Mr. B, and Mr. C." For example, this information may include data such as "Mr. A requires visual assistance, Mr. B is fully visually-enabled, and Mr. C requires voice assistance."

[1551] Next, the server uses the generative AI model to generate a customized training program based on the company's training requirements. For example, the training program could include "basics of data entry, how to use visual aids, and regular skill checks." The server then sends the generated training program to company personnel and disabled workers.

[1552] Furthermore, users (business representatives or workers with disabilities) can use the AI ​​chatbot to ask questions. For example, if a business representative asks, "What visual aid tools do you recommend?", the server sends this question to the generative AI model to get an answer. The generative AI model generates the answer, "Screen reader software is recommended," which the server then sends to the device and displays to the user.

[1553] The emotion engine automatically identifies emotions from user input data and dialogue content and sends the results to the server, which then uses the emotional data for analysis to customize more appropriate training programs and support content.

[1554] The user (disabled worker or person in charge) enters daily report data into the terminal, which then sends the data to the server. The server analyzes the daily report data using an anomaly detection algorithm and sends an alert to the company's person in charge if an anomaly is detected. The emotion engine analyzes emotions along with the daily report data, and the content of the alert can be customized as needed.

[1555] In this way, the present invention can streamline the hiring and employment process for people with disabilities and provide continuous support that takes emotions into consideration. Specific examples of prompts provided include "We are looking to hire one person for data entry work" and "What visual support tools do you recommend?"

[1556] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1557] Step 1:

[1558] Users (company representatives) use dedicated terminals to input information such as their company's business overview, number of employees, required skill sets, and purpose of employing people with disabilities.

[1559] Input: Company information such as business overview and number of employees.

[1560] Output: Formatted company information data.

[1561] Operation: A company employee types into the terminal, "We would like to hire one person for data entry work," and presses the "Send" button.

[1562] Step 2:

[1563] The terminal formats the input data and sends it to the server.

[1564] Input: Company information data entered by the user.

[1565] Output: The data sent to the server in JSON format.

[1566] How it works: The device formats information such as "Data entry job, 1 position available" and sends it to the server via an HTTP request.

[1567] Step 3:

[1568] The server stores the received data in a database.

[1569] Input: Company information data in formatted JSON.

[1570] Output: Company information stored in a database.

[1571] How it works: The server uses a parser to break down the data and executes SQL queries to insert it into the database.

[1572] Step 4:

[1573] The server sends the data to the generative AI model.

[1574] Input: Company information stored in a database.

[1575] Output: The business data sent to the generative AI model.

[1576] How it works: The server sends company information to the generative AI model via an HTTP request.

[1577] Step 5:

[1578] A generative AI model analyzes the data and generates a list of tasks suitable for people with disabilities.

[1579] Input: Business data sent from the server.

[1580] Output: The generated job list.

[1581] How it works: The generative AI model analyzes the data and creates a list of "the most suitable candidates for data entry work who are disabled: A, B, and C."

[1582] Step 6:

[1583] The server sends the generated list of tasks to the company representative.

[1584] Input: The list of jobs returned by the generative AI model.

[1585] Output: A list of tasks sent to the company contact.

[1586] How it works: The server sends the list of tasks to the company representative's email address or a dedicated dashboard.

[1587] Step 7:

[1588] The server searches a database of people with disabilities and lists candidates with disabilities who meet the company's requirements.

[1589] Input: Job listing and company requirements.

[1590] Output: List of potential disabled people.

[1591] How it works: The server queries the database and generates a list of matching candidates.

[1592] Step 8:

[1593] The server sends the candidate's details to the company representative.

[1594] Input: A list of potential disabled people.

[1595] Output: Detailed information sent to company contact.

[1596] How it works: The server sends the details to the company representative via email or dashboard.

[1597] Step 9:

[1598] The server generates a training program using a generative AI model.

[1599] Input: Company training requirements.

[1600] Output: The generated customized training program.

[1601] How it works: A server sends a company's requirements to a generative AI model, which generates a customized training program.

[1602] Step 10:

[1603] The server transmits the training program to business personnel and disabled workers.

[1604] Input: The generated training program.

[1605] Output: The training program is sent via email and a dedicated dashboard.

[1606] How it works: The server sends training programs to company personnel and workers.

[1607] Step 11:

[1608] The user (company representative or disabled worker) enters a question into the AI ​​chatbot.

[1609] Input: The question.

[1610] Output: The question sent to the AI ​​chatbot.

[1611] How it works: A company representative asks the chatbot, "What visual aids do you recommend?"

[1612] Step 12:

[1613] The terminal transmits the entered question to the server.

[1614] Input: The question entered.

[1615] Output: The question sent to the server.

[1616] How it works: The device analyzes the question and sends it to the server.

[1617] Step 13:

[1618] The server sends the question to the generative AI model.

[1619] Input: The question sent from the terminal.

[1620] Output: The question sent to the generative AI model.

[1621] How it works: The server sends the question to the generative AI model and requests an answer.

[1622] Step 14:

[1623] The generative AI model generates an appropriate answer based on the question and returns it to the server.

[1624] Input: The question.

[1625] Output: The generated answer.

[1626] How it works: The generative AI model generates an answer such as "Screen reader software is recommended."

[1627] Step 15:

[1628] The server sends the generated response to the terminal.

[1629] Input: The answer from the generative AI model.

[1630] Output: The answer sent to the terminal.

[1631] Action: The server sends a response to the device.

[1632] Step 16:

[1633] The terminal displays the answer to the user.

[1634] Input: The response from the server.

[1635] Output: The answer displayed on the terminal.

[1636] Behavior: The device displays "Screen reader software recommended."

[1637] Step 17:

[1638] The emotion engine identifies emotions from user input data and dialogue content.

[1639] Input: Input data and dialogue.

[1640] Output: Identified emotion data.

[1641] How it works: The emotion engine automatically identifies emotions such as "joy" and "anxiety."

[1642] Step 18:

[1643] The emotion engine sends the emotion data to the server, which uses the data for analysis.

[1644] Input: Identified emotion data.

[1645] Output: Emotion data sent to the server.

[1646] How it works: The emotion engine sends emotions, such as "anxiety," to the server, which then analyzes the data.

[1647] Step 19:

[1648] The server takes emotional data into account to customize training programs and support content.

[1649] Input: Emotion data and existing training program information.

[1650] Output: Customized training programs and support.

[1651] What it does: The server tailors a training program for users who feel "anxious," including relaxation techniques and encouragement.

[1652] Step 20:

[1653] The user inputs the daily report data into the terminal.

[1654] Input: Daily report data.

[1655] Output: Daily report data entered into the terminal.

[1656] Action: A disabled worker writes in his daily report, "I was unable to work today due to poor health."

[1657] Step 21:

[1658] The terminal transmits the daily report data to the server.

[1659] Input: Daily report data entered.

[1660] Output: Daily report data sent to the server.

[1661] Operation: The device formats the daily report data and sends it to the server.

[1662] Step 22:

[1663] The server analyzes the daily report data using an anomaly detection algorithm.

[1664] Input: Daily report data sent to the server.

[1665] Output: Anomaly detection results.

[1666] Operation: The server analyzes the daily report data and detects any abnormalities.

[1667] Step 23:

[1668] If the server detects an abnormality, it will notify the company representative.

[1669] Input: Anomaly detection results.

[1670] Output: Anomaly alert.

[1671] How it works: The server detects an anomaly and sends an alert to company personnel that "urgent action is required."

[1672] Step 24:

[1673] The emotion engine analyzes daily report data as well as user emotions and customizes alert content based on that.

[1674] Input: Daily report data and emotion data.

[1675] Output: The customized alert content.

[1676] How it works: The emotion engine analyzes the information "I'm feeling unwell and anxious today" and sends a notification to the company representative, including an alert that special consideration is needed.

[1677] (Application example 2)

[1678] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1679] Traditionally, companies that employ people with disabilities have often lacked the precision to assign appropriate tasks or the ability to customize training programs for people with disabilities. Furthermore, the lack of a way to analyze workers' emotions in real time and provide support based on those emotions makes it difficult to create an environment where workers can work sustainably and safely. This has hindered efforts to increase the employment rate of people with disabilities and improve their workplace adaptation after employment.

[1680] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for automatically listing tasks suitable for persons with disabilities based on data input from companies, means for formatting the data input from companies and sending it to the server, and means for analyzing the emotions of workers in real time and sending the emotion data to the server. This enables automatic listing of tasks based on the aptitudes of persons with disabilities and customized support based on real-time emotion analysis.

[1681] "Data input from companies" is a general term for information such as the type of work provided by companies, the required skill sets, number of employees, and the purpose of employing people with disabilities.

[1682] The "means for automatically listing jobs suitable for people with disabilities" is a function in which a generative AI model automatically identifies and lists jobs suitable for people with disabilities based on data provided by companies.

[1683] The "means of listing disabled candidates from a database who meet the company's requirements" is a process for extracting disabled candidates from a database based on the skills and requirements required by the company.

[1684] The "means for generating customized training programs" refers to the process by which a generative AI model creates training programs tailored to individual individuals with disabilities based on the training requirements set by the company.

[1685] The "means of answering questions about the employment of people with disabilities in real time" is a system in which an AI chatbot instantly responds to questions from company representatives and workers with disabilities.

[1686] The "means of analyzing daily report data and detecting abnormalities" refers to an algorithm that analyzes workers' daily report data and detects abnormalities, as well as a notification system for doing so.

[1687] "Means for analyzing workers' emotions in real time and sending emotional data to a server" refers to a function that uses an emotion engine to analyze the emotions of workers while they are working and sends the results to a server.

[1688] "Means for customizing training programs and support content based on emotional data" refers to the process of adjusting and optimizing the training programs and support content provided based on the emotional state of workers.

[1689] This invention is a total support system that enables companies to smoothly recruit, employ, and continuously support people with disabilities. The system is composed of the following:

[1690] System configuration

[1691] Hardware and Software

[1692] Hardware: Factory robots, general-purpose industrial tablets, servers

[1693] Software: Python, EmotionAnalyzer (emotion analysis engine), AIChatbot, generative AI model

[1694] Program Overview

[1695] 1. Data collection from companies:

[1696] Users (company personnel) use dedicated terminals to input information such as their company's business operations, number of employees, required skill sets, and purpose of employing people with disabilities. This input data is sent to the server.

[1697] 2. Formatting and listing the data:

[1698] The server then formats the data it receives and uses a generative AI model to automatically create a list of jobs suitable for people with disabilities. The list is then sent to the company's personnel.

[1699] 3. Database search and candidate list generation:

[1700] The server extracts from the database candidates with disabilities who meet the company's requirements, creates a list, and provides detailed information to the company's personnel.

[1701] 4. Customized training programs:

[1702] The server uses a generative AI model based on the company's training requirements to generate a training program tailored to each individual with a disability and sends it to company personnel and workers.

[1703] 5. Real-time response:

[1704] When a user (a company representative or a disabled worker) inputs a question into the AI ​​chatbot, the server analyzes the question and generates an appropriate answer using a generative AI model. The generated answer is then displayed on the device.

[1705] 6. Sentiment Analysis and Customization:

[1706] The emotion engine analyzes the worker's input data and dialogue in real time, and the resulting emotional data is sent to the server, which then analyzes the data and customizes training programs and support accordingly.

[1707] 7. Anomaly detection in daily report data:

[1708] When a user (a disabled worker or a person in charge) enters daily report data, the data is sent to the server and analyzed using an anomaly detection algorithm. If an anomaly is detected, the server sends an alert to the company's person in charge.

[1709] Examples and prompts

[1710] Company personnel enter data such as:

[1711] "I would like to hire one person to perform data entry work."

[1712] The server uses a generative AI model to generate a list of tasks, such as:

[1713] "The best candidates for disabled people for data entry work are A, B, and C."

[1714] Additionally, we create customized training programs for your company, such as:

[1715] "Data entry basics, how to use visual aids, and regular skill checks."

[1716] An example of how a chatbot can be used is to ask the following questions:

[1717] "What visual aids do you recommend?"

[1718] The server uses an AI chatbot and emotion engine to generate answers based on the following prompts:

[1719] Type of disability: Visual

[1720] Question: What are the best tools for an assembly line?

[1721] Context: Workers are anxious about new tasks

[1722] Tone of response: Encouraging

[1723] By generating specific answers using the above prompts, companies can provide support that takes into consideration the feelings of workers. This allows companies to streamline the entire process of hiring, training, and supporting people with disabilities, and also provides continuous support that takes into consideration the feelings of users.

[1724] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1725] Step 1:

[1726] The user (company representative) uses a dedicated terminal to input information such as the company's business overview, number of employees, required skill sets, and purpose of hiring people with disabilities. This input data is formatted and sent to the server. An example of input is "We would like to hire one person to perform data entry work." This information is formatted in JSON format.

[1727] Step 2:

[1728] The server analyzes the data it receives and stores it in a database, including job descriptions, number of employees, etc. The server then sends this data to a generative AI model.

[1729] Step 3:

[1730] The generative AI model analyzes the received data and automatically creates a list of suitable jobs. For example, it might list "The most suitable candidates for disabled people for data entry work are A, B, and C." The generated list is then sent back to the server.

[1731] Step 4:

[1732] The server sends the list of job information to the company's personnel. The output format is a list such as "Mr. A, Mr. B, Mr. C." The personnel will use this information to identify suitable candidates.

[1733] Step 5:

[1734] The server searches the database based on the company representative's requests and creates a list of candidates with disabilities. For example, it narrows down the candidates based on data such as "Person A needs visual assistance, Person B is fully visual, and Person C needs voice assistance." The resulting list is then sent to the company representative.

[1735] Step 6:

[1736] The server uses a generative AI model to generate a customized training program based on the company's training requirements. For example, a program might be generated that covers the basics of data entry, how to use visual support tools, and regular skill checks. The generated training program is then sent to company personnel and workers.

[1737] Step 7:

[1738] The user (a company representative or a worker with a disability) inputs a question into the AI ​​chatbot. For example, a question might be asked, "What visual support tools do you recommend?" The device then sends this question to the server.

[1739] Step 8:

[1740] The server receives and analyzes the question and generates an appropriate answer based on the generative AI model. For example, it might generate an answer such as "Screen reader software is recommended." The generated answer is sent to the device and displayed on the screen.

[1741] Step 9:

[1742] The emotion engine automatically identifies emotions from the user's input data and dialogue content. For example, it identifies emotions such as "joy" or "anxiety" from the user's input content and dialogue history. The identified emotion data is sent to the server.

[1743] Step 10:

[1744] The server analyzes the emotional data and customizes the training program and support content based on that data. For example, for a user who is feeling anxious, the server customizes the training program to include relaxation techniques and encouraging content, thereby providing more appropriate support.

[1745] Step 11:

[1746] The user (disabled worker or person in charge) inputs daily report data into the terminal. For example, the user may write in the daily report, "I was unable to work today due to poor health." The input daily report data is formatted and sent to the server.

[1747] Step 12:

[1748] The server analyzes the received daily report data using an anomaly detection algorithm. For example, information about "feeling unwell" is run through the algorithm, and if an abnormality is detected, an alert is sent to the company's responsible person.

[1749] Step 13:

[1750] The emotion engine analyzes the user's emotions along with the daily report data and customizes the alert content based on the results. For example, if the information is "I'm feeling unwell and anxious today," it will notify the person in charge that "special attention is required."

[1751] By taking these steps, companies can streamline the entire process of recruiting, training, and supporting people with disabilities, and provide ongoing support that takes users' emotions into consideration.

[1752] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1753] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1754] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1755] [Fourth embodiment]

[1756] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1757] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1758] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1759] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1760] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1761] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1762] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1763] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1764] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1765] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1766] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1767] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1768] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1769] This invention provides a total support system that enables companies to smoothly recruit and employ people with disabilities and provide continuous support. This system uses a generative AI model to automatically create a list of jobs suitable for people with disabilities based on data input from the company and sends the list to the company. It also includes a means for selecting candidates with disabilities who meet the company's requirements from a database and a means for the generative AI model to generate a customized training program based on the company's training requirements. Furthermore, the system has a means for using an AI chatbot to answer questions about the employment of people with disabilities in real time and a means for analyzing daily report data, detecting anomalies, and notifying company personnel.

[1770] Natural language description of the program

[1771] 1. The user (company representative) enters information such as an overview of their company's business, number of employees, required skill sets, and the purpose of employing people with disabilities on a dedicated terminal.

[1772] Example: A company employee types into a terminal, "We would like to hire one person to perform data entry work."

[1773] 2. The terminal formats the input data and sends it to the server, which stores it in a database.

[1774] Example: The terminal sends information such as "Data entry work, 1 position" to the server, which then stores it in a database.

[1775] 3. The server sends the received data to a generative AI model, which automatically generates a list of jobs suitable for people with disabilities. This list is then immediately sent to the company's representative.

[1776] Example: The AI ​​model creates a list of "the best candidates for data entry work are A, B, and C" and notifies the person in charge.

[1777] 4. The server searches a database of people with disabilities and lists candidates with disabilities who meet the company's requirements.

[1778] Example: The server creates a list of suitable candidates based on data such as "Person A needs visual assistance, Person B is fully visually capable, and Person C needs audio assistance."

[1779] 5. The server uses the generative AI model to generate a customized training program based on the company's training requirements, and sends the program to the company's personnel and disabled workers.

[1780] Example: AI generates training programs such as "basics of data entry, how to use visual support tools, and regular skill checks" and sends them to staff and people with disabilities.

[1781] 6. An AI chatbot will be available 24 hours a day to answer questions about employment for people with disabilities in real time.

[1782] Example: A company representative asks a chatbot, "What visual aid tools do you recommend?" and the chatbot immediately replies, "We recommend screen reader software."

[1783] 7. The server receives the daily report data entered by the disabled worker or the person in charge and analyzes the data using an anomaly detection algorithm. If an anomaly is detected, an alert is sent to the company's person in charge.

[1784] Example: A disabled worker writes in his daily report that "I was unable to work today due to poor health," and the server detects this information and alerts the person in charge that "urgent action is required."

[1785] This will enable companies to streamline the entire process of recruiting, training, and supporting people with disabilities, and provide ongoing support.

[1786] The processing flow will be explained below.

[1787] Step 1:

[1788] The user (company representative) operates the terminal to input information such as an overview of the company's business, number of employees, required skill sets, and the purpose of employing people with disabilities.

[1789] Example: A company employee types into a terminal, "We would like to hire one person to perform data entry work."

[1790] Step 2:

[1791] The terminal formats the data entered by the user and sends the data to the server.

[1792] Example: The terminal sends information such as "Data entry work, 1 position available" to the server.

[1793] Step 3:

[1794] The server stores the received data in a database.

[1795] Example: A server stores information such as "Data entry job, 1 position available" in a database.

[1796] Step 4:

[1797] The server sends the stored data to the generative AI model.

[1798] Example: The server sends the information "data entry work, number of positions available: 1" to the generative AI model.

[1799] Step 5:

[1800] The generative AI model analyzes the received data and automatically creates a list of tasks suitable for people with disabilities.

[1801] Example: The AI ​​model creates a list of candidates with disabilities who are best suited for data entry work: A, B, and C.

[1802] Step 6:

[1803] The server sends the generated list of tasks to the company representative.

[1804] Example: The server sends a list of information about "Mr. A, Mr. B, and Mr. C" to a company representative.

[1805] Step 7:

[1806] The server searches a database of people with disabilities and lists candidates with disabilities who meet the company's requirements.

[1807] Example: The server creates a list of suitable candidates based on data such as "Person A needs visual assistance, Person B is fully visually capable, and Person C needs audio assistance."

[1808] Step 8:

[1809] The server sends detailed information of the listed suitable candidates to the company representative.

[1810] Example: The server sends detailed information about "Mr. A, Mr. B, and Mr. C" to the person in charge.

[1811] Step 9:

[1812] The server generates a customized training program using a generative AI model based on the company's training requirements.

[1813] Example: AI generates customized training programs such as "basics of data entry, how to use visual support tools, and regular skill checks."

[1814] Step 10:

[1815] The server transmits the generated training program to the company personnel and the disabled workers.

[1816] Example: A server sends training programs to personnel and workers, such as "Basics of data entry, how to use visual aids, and regular skill checks."

[1817] Step 11:

[1818] The user (company representative or disabled worker) enters a question into the AI ​​chatbot.

[1819] Example: A company representative asks the chatbot, "What visual support tools do you recommend?"

[1820] Step 12:

[1821] The terminal transmits the entered question to the server.

[1822] Example: A device sends a question to a server: "What visual support tools do you recommend?"

[1823] Step 13:

[1824] The server analyzes the question and requests the appropriate answer from the generative AI model.

[1825] Example: The server sends the analysis results of a "question about visual support tools" to a generative AI model.

[1826] Step 14:

[1827] The generative AI model generates an appropriate answer based on the question and returns it to the server.

[1828] Example: An AI model generates the answer "Screen reader software is recommended."

[1829] Step 15:

[1830] The server generates a response and sends it back to the terminal.

[1831] Example: The server sends a response to the device saying "Screen reader software is recommended."

[1832] Step 16:

[1833] The device displays the answer on the screen.

[1834] Example: The device displays the response "Screen reader software recommended" on the screen.

[1835] Step 17:

[1836] The user (disabled worker or person in charge) enters the daily report data into the terminal.

[1837] Example: A disabled worker writes in his daily report, "I was unable to work today due to poor health."

[1838] Step 18:

[1839] The terminal transmits the input daily report data to the server.

[1840] Example: A terminal sends daily report data to a server stating, "I was unable to work today due to poor health."

[1841] Step 19:

[1842] The server analyzes the received daily report data using an anomaly detection algorithm.

[1843] Example: The server runs the "illness" information through an anomaly detection algorithm.

[1844] Step 20:

[1845] If the server detects an abnormality, it will send an alert to company personnel.

[1846] Example: A server sends an "urgent action required" alert to a company representative.

[1847] Example 1

[1848] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1849] The goal is to solve the many challenges that arise when companies hire and employ people with disabilities. Conventional methods require time and effort to create a list of jobs suitable for people with disabilities, identify suitable candidates, create training programs, and detect anomalies in daily report data, making these tasks inefficient. Furthermore, there are no adequate means to respond to questions about hiring people with disabilities in real time.

[1850] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1851] In this invention, the server includes means for automatically creating a list of jobs suitable for persons with disabilities based on data input from a terminal, means for sending the list of jobs suitable for persons with disabilities to a company, means for compiling a list of disabled candidates from a database that meets the company's preferences, means for using a generative AI model to create a customized training program based on the company's training requirements, means for using an AI chatbot to answer questions about the employment of persons with disabilities in real time, means for analyzing daily report data, detecting anomalies, and notifying company personnel, and means for formatting input data from the terminal and sending it to the server. This makes it possible to select jobs and candidates suitable for persons with disabilities based on data input from the terminal, provide customized training programs, respond to questions about the employment of persons with disabilities in real time, and detect and notify anomalies in daily report data.

[1852] A "terminal" is a hardware device for inputting and displaying data.

[1853] A "server" is a hardware and software configuration for storing, processing, sending and receiving data over a network.

[1854] A "generative AI model" is an algorithm that uses artificial intelligence technology to automate and optimize specific tasks.

[1855] A "list" is a collection of data that is organized and categorized based on specific criteria.

[1856] A "database" is a software system for efficiently storing, searching, and managing large amounts of data.

[1857] "Training Program" means an educational or training plan designed to acquire specific skills or knowledge.

[1858] An "AI chatbot" is a program that uses artificial intelligence technology to automatically hold conversations and provide answers to users' questions in real time.

[1859] "Daily report data" refers to information that records the progress of work and working conditions.

[1860] An "anomaly detection algorithm" is a computational method for analyzing data and detecting unusual patterns or anomalies.

[1861] An "alert" is a notification that notifies you of an abnormality or important information.

[1862] A "customized training program" is an education and training plan that is tailored to the requirements of a specific company or individual.

[1863] "Input data" refers to information entered into the system via a terminal.

[1864] "Real-time" refers to a state in which data processing and information provision are carried out immediately.

[1865] This is a total support system that enables companies to smoothly recruit, employ, and continuously support people with disabilities. The system is implemented using a server, terminals, a generative AI model, a database, and an AI chatbot.

[1866] First, the user (company representative) enters information such as the job summary, number of employees, required skill set, and purpose of hiring people with disabilities into a dedicated terminal. This information is necessary to clarify the skills and conditions that the company is looking for in people with disabilities. As a concrete example, the user might enter the following into the terminal: "We would like to hire one person to do data entry work. Visual assistance is required."

[1867] Next, the terminal formats the input data and sends it to the server. The formatted data is converted into a format that the server can easily accept, such as JSON. For example, the terminal converts information such as "Task: Data entry, Number of people: 1, Visual support: Required" into JSON format and sends it to the server.

[1868] The server stores the received data in a database. At the same time, it sends the data to the generative AI model and instructs it to analyze it. The generative AI model automatically creates a list of tasks suitable for people with disabilities based on the data entered from the device. This list includes specific tasks suitable for people with disabilities and candidates based on the company's requirements. As a concrete example, the generative AI model creates a list such as "The best candidates for data entry work are Person A, Person B, and Person C," and the server sends this list to the company employee's device.

[1869] The server then searches a database of people with disabilities and creates a list of candidates who meet the company's requirements. The list includes the skillsets and support required by each person with a disability. For example, the server creates a list based on data such as "Person A needs visual support, Person B needs voice support, and Person C needs physical support," and sends it to the company's representative.

[1870] The server also uses a generative AI model to generate a customized training program based on the company's training requirements. This program is tailored to each company's specific needs. The generated program is then sent to the company's personnel and disabled workers. For example, the AI ​​generates a training program titled "Basics of data entry, how to use visual aids, and regular skill checks," and sends it to the company's personnel and disabled workers via email.

[1871] An AI chatbot is available 24 hours a day to answer questions about the employment of people with disabilities in real time. This AI chatbot uses natural language processing technology to answer questions from users. For example, if a company representative asks the chatbot, "What visual assistance tools do you recommend?", the chatbot will immediately reply, "We recommend screen reader software."

[1872] Finally, the server analyzes the daily report data and notifies company personnel if an abnormality is detected. When disabled workers or personnel enter daily report data into their terminals, the server analyzes the data using an anomaly detection algorithm, and if an abnormality is detected, it notifies company personnel as an alert. For example, if a disabled worker enters in their daily report that "I was unable to work today due to poor health," the server analyzes the information and sends an alert to company personnel that "urgent action is required."

[1873] Prompt Sentence Examples

[1874] Job Listing: "Job Description: Data Entry. Position: 1. Please list suitable candidates."

[1875] Candidate Listing: "Company Request: Please list candidates who can handle data entry work."

[1876] Training Program Generation: "Training Requirements: Please generate a training program that includes training content on basic data entry skills and how to use visual aids."

[1877] Chatbot response example: "Question about employment for people with disabilities: What visual aids do you recommend?"

[1878] Anomaly detection: "Daily report data analysis: It is stated that the employee was unable to work today due to poor health. Please detect any anomalies and notify us."

[1879] These components enable companies to streamline the entire process of hiring, training, and supporting people with disabilities, and provide continuous support. By utilizing generative AI models and AI chatbots, the system achieves automation and real-time responses, contributing to companies' promotion of hiring people with disabilities.

[1880] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1881] Step 1:

[1882] The user (company representative) enters information such as the business overview, number of employees, required skill sets, and purpose of employing people with disabilities on a dedicated terminal.

[1883] Input: Details such as job description, number of employees, skill set, and employment objectives

[1884] Output: Formatted input data

[1885] Specific example of operation: A company representative enters detailed information into the input field on the terminal, such as "We would like to hire one person for data entry work. Visual assistance is required.", and presses the send button.

[1886] Step 2:

[1887] The terminal formats the input data and sends it to the server.

[1888] Input: Entered business information, number of employees, skill sets, employment purpose

[1889] Output: Formatted data such as JSON

[1890] Specific example of operation: The terminal converts the information "Task: Data entry, Number of people: 1, Visual support: Required" into JSON format and sends it to the server.

[1891] Step 3:

[1892] The server stores the received data in a database and simultaneously sends the data to the generative AI model, instructing it to analyze it.

[1893] Input: Formatted input data

[1894] Output: Data stored in a database, data sent to a generative AI model

[1895] Specific example of operation: The server records the data "Task: Data entry, Number of people: 1, Visual support: Required" in the database and requests the generative AI model to analyze it.

[1896] Step 4:

[1897] The generative AI model automatically creates a list of jobs suitable for people with disabilities based on the data it receives, and the server sends that list to the company's representative.

[1898] Input: Data sent to the generative AI model

[1899] Output: List of jobs suitable for people with disabilities, notified list

[1900] Specific example of operation: The generative AI model creates a list of "the best candidates for data entry work are A, B, and C," and the server sends this to the company employee's device.

[1901] Step 5:

[1902] The server searches a database of people with disabilities and lists candidates with disabilities who meet the company's requirements.

[1903] Input: Company preferences and disability database

[1904] Output: A list of possible matching disabilities

[1905] Specific example of operation: The server creates a list based on data such as "Person A needs visual assistance, Person B needs audio assistance, and Person C needs physical assistance" and sends it to the company representative.

[1906] Step 6:

[1907] The server uses a generative AI model to generate a customized training program based on the company's training requirements and sends it to company personnel and disabled workers.

[1908] Input: Training requirements, analysis data for the generative AI model

[1909] Output: Customized training program, transmitted program

[1910] Specific example of how it works: The AI ​​generates a training program on "basics of data entry, how to use visual support tools, and regular skill checks" and sends it via email to company representatives and disabled workers.

[1911] Step 7:

[1912] An AI chatbot is available 24 hours a day to answer questions about employment for people with disabilities in real time.

[1913] Input: User question

[1914] Output: Answer by AI chatbot

[1915] A specific example of how it works: A company representative asks the chatbot, "What visual support tools do you recommend?" and the chatbot immediately replies, "We recommend screen reader software."

[1916] Step 8:

[1917] The server analyzes the daily report data and notifies company personnel if an abnormality is detected.

[1918] Input: Daily report data, anomaly detection algorithm

[1919] Output: Alert notification when an abnormality is detected

[1920] A concrete example of how it works: When a disabled worker enters in their daily report that "I was unable to work today due to poor health," the server analyzes the information and alerts company personnel that "urgent action is required."

[1921] (Application example 1)

[1922] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1923] In modern manufacturing, employing people with disabilities is important from the perspective of corporate social responsibility and diversity. However, many companies face the challenge of finding appropriate work and training programs to provide a safe and efficient working environment for people with disabilities. In particular, when employing people with disabilities in factories, support is required to ensure both safety and efficiency, but the reality is that the technological means to achieve this are not fully in place.

[1924] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1925] In this invention, the server includes means for automatically creating a list of jobs suitable for persons with disabilities based on data input from a company, means for sending the list of jobs suitable for persons with disabilities to the company, means for compiling a list of disabled candidates from a database that meets the company's preferences, means for creating a customized training program based on the company's training requirements, means for answering questions about the employment of persons with disabilities in real time, means for analyzing daily report data and detecting abnormalities, means for providing support for persons with disabilities to work safely and efficiently in factories, and means for displaying the created job list and training program on a smart device in real time. This enables companies to provide comprehensive support for persons with disabilities, from hiring to training and daily operations, enabling them to work safely and efficiently.

[1926] An "enterprise" is a corporation or individual that conducts economic activities as an organization and provides goods and services.

[1927] "Input data" refers to the information that companies enter into the system, including details of the business, number of employees, required skill sets, and the purpose of employing people with disabilities.

[1928] "Disabled persons" refers to people with physical, mental or sensory impairments who may require special assistance or accommodations.

[1929] "Means for automatically listing tasks" refers to a function that uses a generative AI model to analyze input data and automatically list tasks suitable for people with disabilities.

[1930] "Means for sending the list to the company" refers to a function for electronically notifying the person in charge at the company of the generated business list.

[1931] A "database" is a collection of information that stores information and manages it in an organized manner, allowing it to be searched and listed efficiently.

[1932] "Means for generating training programs" refers to the ability to automatically generate customized training programs using generative AI models based on a company's training requirements.

[1933] "Real-time response means" refers to the ability to instantly provide answers to questions about employment for people with disabilities using generative AI models.

[1934] "Daily report data" refers to records used by disabled workers or those in charge to report on their daily work status, health condition, etc.

[1935] "Means for detecting abnormalities" refers to the function of analyzing daily report data and automatically detecting abnormalities that differ from normal work or health conditions.

[1936] "Measures to provide support within the factory" refers to the technical and human support systems that provide an environment in which persons with disabilities can work safely and efficiently within the factory.

[1937] A "smart device" is a portable electronic device that is capable of connecting to the Internet and has advanced computing power and is capable of running applications, and includes smartphones, smart glasses, head-mounted displays, etc.

[1938] "A means to view generated work lists and training programs in real time" refers to the function that allows generated work lists and training programs to be instantly checked via a smart device.

[1939] The system of the present invention provides total support for companies to smoothly recruit and employ people with disabilities and provide continuous support. This system uses a generative AI model to automatically create a list of jobs suitable for people with disabilities based on data input from the company and transmits the list to the company. It also includes a database listing candidates with disabilities who meet the company's requirements, and a generative AI model to generate a customized training program based on the company's training requirements. Furthermore, the system provides real-time answers to questions about the employment of people with disabilities using an AI chatbot, and a means for analyzing daily report data, detecting abnormalities, and notifying company personnel. When applied to factories, the system supports people with disabilities in working safely and efficiently, allowing them to access necessary information in real time on smart devices.

[1940] The server receives information entered by companies, such as job descriptions, number of employees, required skill sets, and the purpose of hiring people with disabilities, formats it, and stores it in a database. This data is then sent to a generative AI model, which creates a list of jobs suitable for people with disabilities. The generated list of jobs is immediately notified to company personnel. Similarly, the system also has the function of listing candidates with disabilities from the database. This allows companies to quickly find suitable candidates with disabilities.

[1941] Based on the training requirements of the company, the server uses a generative AI model to generate a customized training program.An AI chatbot is also installed, which can provide instant answers to questions about disability employment from company personnel and disabled workers.

[1942] For daily report data, disabled workers or staff enter information about their daily work and health into a terminal and send it to a server. The server analyzes this data and notifies the company staff if it detects any abnormalities. This anomaly detection uses an algorithm that automatically detects abnormalities that differ from normal work or health conditions.

[1943] The system also includes a means to enable workers with disabilities to access generated job lists and training programs in real time using smart devices, enabling them to work safely and efficiently in factories.

[1944] As a concrete example, consider the case where a company employee inputs, "We would like to hire one worker with basic machine operation skills." This data is sent to the server, and the generative AI model generates a list of suitable tasks, such as "simple machine operation, parts assembly, and shipping preparation." This list is notified to the employee, who then generates a customized training program, such as "basic machine operation training, explanation of assembly procedures, and shipping preparation methods." The employee can also ask, "What visual support tools do you recommend?" and the AI ​​chatbot can respond, "Screen reader software is recommended."

[1945] Here are some examples of prompts to input to the generative AI model:

[1946] 1. Generate a list of tasks:

[1947] Company information: Major manufacturing company, 500 employees, required skill set is basic machine operation, purpose of employing people with disabilities is to promote diversity and contribute to society

[1948] Generate a suitable task list.

[1949] 2. Generating training programs:

[1950] Job List: Simple machine operation, parts assembly, shipping preparation

[1951] Generate a training program based on this.

[1952] 3. Real-time chat support:

[1953] Disability employment question: What visual aids do you recommend?

[1954] Please respond in real time.

[1955] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1956] Step 1:

[1957] A user uses a dedicated terminal to input company information, including a business overview, number of employees, required skill sets, and the purpose of hiring people with disabilities. This data is formatted by the terminal and sent to the server. The input data on the terminal is, "We would like to hire one worker who can operate basic machines."

[1958] Step 2:

[1959] The server stores the received company information in a database. Specifically, it converts the input data into an appropriate format and stores it in the database. For example, information such as "basic machine operation, number of employees: 1" is stored.

[1960] Step 3:

[1961] The server sends the saved company information to the generative AI model, which then analyzes the input data using prompts and generates a list of tasks suitable for people with disabilities. The generated list of tasks is called "simple machine operation, parts assembly, and shipping preparation."

[1962] Step 4:

[1963] The server receives the task list generated by the generative AI model and sends it to the company's personnel. This includes sending notifications containing the task list via email or notification system. The output is "Suitable task list: simple machine operation, parts assembly, and shipping preparation."

[1964] Step 5:

[1965] The server searches the database and lists candidates with disabilities who meet the company's requirements. The search results are a list of suitable candidates such as "Mr. A, Mr. B, Mr. C."

[1966] Step 6:

[1967] The server uses a generative AI model to generate a customized training program based on the company's training requirements. The training program generated by this prompt is "Training basic machine operation, explaining assembly procedures, and how to prepare for shipment."

[1968] Step 7:

[1969] The server sends the generated training program to company personnel and disabled workers. This includes sending notifications containing the training program details via email and notification systems. The output is "specific training program details."

[1970] Step 8:

[1971] A user inputs a question about employment for people with disabilities into the AI ​​chatbot, for example, "What visual assistive tools do you recommend?"

[1972] Step 9:

[1973] The AI ​​chatbot answers questions in real time, using a generative AI model to generate appropriate answers and provide them to the user. The output is an immediate response such as "Screen reader software recommended."

[1974] Step 10:

[1975] The user inputs daily report data into the terminal, and the server receives the data. For example, the daily report may include, "I was not feeling well today and was unable to work."

[1976] Step 11:

[1977] The server analyzes the daily report data and detects anomalies. If an anomaly is detected, the server sends a notification to the company's responsible person. The output is an alert stating "Anomaly detected: Notify responsible person."

[1978] Step 12:

[1979] Users can view the generated work lists and training programs in real time using smart devices such as smartphones, smart glasses, and head-mounted displays.

[1980] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1981] This invention provides a system that provides more effective support by combining an emotion engine with a total support system that enables companies to smoothly recruit, employ, and sustainably support people with disabilities. This system includes a means for automatically creating a list of tasks suitable for people with disabilities using a generative AI model based on data input from the company and sending that list to the company. It also includes a means for selecting candidates with disabilities who meet the company's requirements from a database and a means for generating a customized training program using the generative AI model based on the company's training requirements. Furthermore, it includes a means for using an AI chatbot to answer questions about the employment of people with disabilities in real time and a means for analyzing daily report data, detecting anomalies, and notifying company personnel. In addition, by incorporating an emotion engine, the system can recognize user emotions and use them for analysis and customizing support content.

[1982] Natural language description of the program

[1983] 1. The user (company representative) enters information such as an overview of their company's business, number of employees, required skill sets, and the purpose of employing people with disabilities on a dedicated terminal.

[1984] Example: A company employee types into a terminal, "We would like to hire one person to perform data entry work."

[1985] 2. The terminal formats the data entered by the user and sends the data to the server.

[1986] Example: The terminal sends information such as "Data entry work, 1 position available" to the server.

[1987] 3. The server stores the received data in a database.

[1988] Example: A server stores information such as "Data entry job, 1 position available" in a database.

[1989] 4. The server sends the stored data to the generative AI model.

[1990] Example: The server sends the information "data entry work, number of positions available: 1" to the generative AI model.

[1991] 5. The generative AI model analyzes the received data and automatically creates a list of tasks suitable for people with disabilities.

[1992] Example: The AI ​​model creates a list of candidates with disabilities who are best suited for data entry work: A, B, and C.

[1993] 6. The server sends the generated list of tasks to the company representative.

[1994] Example: The server sends a list of information about "Mr. A, Mr. B, and Mr. C" to a company representative.

[1995] 7. The server searches the database of disabled people and lists candidates with disabilities who meet the company's requirements.

[1996] Example: The server creates a list of suitable candidates based on data such as "Person A needs visual assistance, Person B is fully visually capable, and Person C needs audio assistance."

[1997] 8. The server sends the details of the listed matching candidates to the company representative.

[1998] Example: The server sends detailed information about "Mr. A, Mr. B, and Mr. C" to the person in charge.

[1999] 9. The server generates a customized training program using the generative AI model based on the company's training requirements.

[2000] Example: AI generates customized training programs such as "basics of data entry, how to use visual support tools, and regular skill checks."

[2001] 10. The server sends the generated training program to the company's personnel and the disabled worker.

[2002] Example: A server sends training programs to personnel and workers, such as "Basics of data entry, how to use visual aids, and regular skill checks."

[2003] 11. The user (company representative or disabled worker) enters a question into the AI ​​chatbot.

[2004] Example: A company representative asks the chatbot, "What visual support tools do you recommend?"

[2005] 12. The terminal sends the entered question to the server.

[2006] Example: A device sends a question to a server: "What visual support tools do you recommend?"

[2007] 13. The server analyzes the question and requests the appropriate answer from the generative AI model.

[2008] Example: The server sends the analysis results of a "question about visual support tools" to a generative AI model.

[2009] 14. The generative AI model generates an appropriate answer based on the question and returns it to the server.

[2010] Example: An AI model generates the answer "Screen reader software is recommended."

[2011] 15. The server generates a response and sends it back to the device.

[2012] Example: The server sends a response to the device saying "Screen reader software is recommended."

[2013] 16. The device will display the answer on the screen.

[2014] Example: The device displays the response "Screen reader software recommended" on the screen.

[2015] 17. The emotion engine automatically identifies emotions from user input data and dialogue.

[2016] Example: An emotion engine identifies emotions such as "joy" or "anxiety" from user input and dialogue history.

[2017] 18. The emotion engine sends the identified emotion data to the server, which uses the emotion data for analysis.

[2018] Example: An emotion engine identifies the emotion "anxiety" and sends that information to a server.

[2019] 19. The server will also take emotional data into account to customize more appropriate...

Claims

1. A means to automatically list jobs suitable for people with disabilities based on data input from companies, and a means of transmitting a list of jobs suitable for persons with disabilities to businesses; A means to list candidates with disabilities from a database who meet the company's requirements, a means for generating customized training programs based on the company's training requirements; A means to answer questions about disability employment in real time, and A system that includes a means for analyzing daily report data and detecting abnormalities.

2. 2. The system according to claim 1, wherein data input from a company is formatted and transmitted to a server.

3. The system according to claim 1, wherein an alert is sent to a company representative based on an anomaly detected in the daily report data.

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