system

Abstract

We provide the system. [Solution] Data collection methods for obtaining employment information, A data analysis tool that analyzes acquired employment information to identify a suitable work environment for the user, An information provision means for distributing identified work environment information to user terminals, A means of communication that connects users and employees within a company, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In the employment of disabled persons, a high turnover rate is a problem. The main reasons include the gap between pre-employment expectations and actual job content and workplace environment, anxiety about human relationships, and dissatisfaction with wages. These factors make it difficult for disabled persons to adapt and thrive in the workplace over the long term. There is a need to improve such a situation and provide an environment in which disabled persons can work with confidence.

Means for Solving the Problems

[0005] To solve the above problems, the present invention includes a data collection means for acquiring employment information for persons with disabilities. This system includes a data analysis means for analyzing the acquired employment information and identifying a suitable work environment for persons with disabilities. Furthermore, it includes an information provision means for transmitting the identified work environment information to a user terminal and a communication means for connecting the user with employees with disabilities within the company. As a result, persons with disabilities can understand detailed job content and the actual work environment before employment, and it is possible to reduce the gap after joining the company.

[0006] "Employment information for people with disabilities" refers to information about job descriptions, work environments, and facilities and systems that accommodate people with disabilities when they seek employment.

[0007] "Data collection means" refers to functional elements for acquiring job information and internal environment information from companies, and includes devices and processes that automatically collect information from various data sources.

[0008] "Data analysis means" refers to an algorithm and its execution environment that has the function of analyzing collected employment-related data to identify the most suitable job content and environment for persons with disabilities.

[0009] "Information provision means" refers to a means of delivering analyzed work environment information to a user terminal in an appropriate format and displaying it in a way that the user can understand.

[0010] "Communication methods" refer to functions, including chat and messaging protocols, that enable system users to exchange information with employees with disabilities within a company.

[0011] A "user terminal" is a computer device used by users of the system, and it is a device that enables the display of employment information and communication through the transmission and reception of information. [Brief explanation of the drawing]

[0012] [Figure 1]This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2, which combines an emotion engine. [Modes for carrying out the invention]

[0013] Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings.

[0014] First, the terms used in the following description will be explained.

[0015] In the following embodiments, a tagged processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0016] In the following embodiments, a tagged RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0017] In the following embodiments, a tagged storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0018] In the following embodiments, a tagged communication I / F (Interface) is an interface including a communication processor and 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), or Bluetooth (registered trademark), etc.

[0019] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0020] [First Embodiment]

[0021] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0022] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0023] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0024] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0025] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0026] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0027] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0028] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0029] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0030] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0031] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0032] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0033] This invention is a system for supporting the adaptation of people with disabilities to the work environment, and its main components consist of a server, terminals, and users.

[0034] Server Role

[0035] The server has the function of regularly collecting job information and internal environment information from companies. This ensures that the database is always up-to-date. The server also implements an AI algorithm to analyze the collected data and identify the most suitable work environment for people with disabilities. This identified information is converted into a user-friendly format and sent to the terminal.

[0036] Terminal role

[0037] The terminal has the function of displaying matching information provided by the server based on the type of disability and desired job conditions entered by the user. The terminal is equipped with a user interface that visualizes detailed company information, which serves as a reference for users when selecting a company. In addition, the terminal provides a chat function, allowing users to communicate directly with disabled employees of companies. This communication helps users to learn about the actual work content and workplace atmosphere in advance.

[0038] User actions

[0039] Users register their profile information via their device and provide the system with job search parameters. Users can view company information displayed on their device and research companies that interest them in more detail. Users can use the chat function to interact with current and former employees of companies and ask specific questions to deepen their understanding of the work environment. Through this process, people with disabilities can select companies that meet their criteria and proceed with applications with confidence.

[0040] Specific example

[0041] For example, suppose a visually impaired user is seeking an IT-related job. The user enters details of their disability and desired job type into a terminal and sends the information to a server. Based on this information, the server lists IT companies with workplace environments that accommodate visually impaired individuals and sends detailed information to the terminal. This allows the user to gain a deeper understanding of the work content and communication methods at each company and proceed with applications based on the matching results. The purpose of this process is to reduce anxiety after joining a company by allowing the user to know in advance about any gaps in the workplace environment.

[0042] The following describes the processing flow.

[0043] Step 1:

[0044] The server retrieves job information and internal environment information from companies via APIs and stores it in a database. This ensures that the latest employment information is always maintained.

[0045] Step 2:

[0046] The server analyzes information collected from the database and applies an AI algorithm to identify suitable work environments for people with disabilities. This generates a matching score based on the type of disability and desired job.

[0047] Step 3:

[0048] The terminal launches the user interface, allowing the user to enter their profile information and desired job conditions. It also sends the user's input data to the server.

[0049] Step 4:

[0050] Based on the information received from the user, the server organizes company information, including a suitable work environment and matching score, and sends it to the terminal.

[0051] Step 5:

[0052] The terminal visually displays company information and matching results sent from the server to the user. This allows the user to view detailed information about potential companies.

[0053] Step 6:

[0054] Based on the displayed information, users can select companies they are interested in and, if they want to learn more, they can use the chat function to communicate with company representatives or alumni.

[0055] Step 7:

[0056] When a user applies to a company they have selected, they can upload the necessary documents and schedule an interview via their device. This completes the application process.

[0057] (Example 1)

[0058] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0059] To appropriately match individuals with disabilities to a company's work environment, it is necessary to efficiently collect and analyze the latest job information and internal environment information, and to provide a work environment that meets the individual needs of each person with a disability. However, conventional systems have not adequately collected and analyzed such information, resulting in the challenge that it is difficult for people with disabilities to find a suitable work environment.

[0060] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0061] In this invention, the server includes data collection means for acquiring employment information and internal environment information from companies and storing it in a database; preprocessing means for imputing missing values ​​and scaling the acquired information; and data analysis means for analyzing the preprocessed information and using an AI algorithm to identify a work environment suitable for persons with disabilities. This makes it possible for persons with disabilities to easily find a work environment that suits their own conditions.

[0062] "Data collection means" refers to a function for acquiring employment information and internal environment information from companies and storing it in a database.

[0063] "Preprocessing means" refers to functions that perform actions such as imputing missing values ​​and scaling in order to convert the acquired information into a format suitable for analysis by AI algorithms.

[0064] "Data analysis tools" refer to functions that use machine learning and artificial intelligence algorithms, based on pre-processed information, to identify suitable work environments for people with disabilities.

[0065] "Information provision means" refers to a function that converts identified work environment information into a format that is easy for users to understand and delivers it to the user's terminal.

[0066] "Display means" refers to a function that visualizes detailed job information of a company on the user interface, making it easy for users to understand the information.

[0067] "Communication methods" refer to functions that provide conversational features, such as chat, to enable users and company employees to exchange information in real time.

[0068] This invention is a system for supporting the adaptation of persons with disabilities to the work environment, and includes a server, terminals, and users as its main components.

[0069] The server communicates with external databases via APIs to collect employment information and internal workplace environment information from companies. The collected data is stored in database systems such as MySQL® or PostgreSQL on the server. The server uses the Python Pandas library to perform data preprocessing for analysis by AI algorithms, including imputing missing values ​​and scaling. The AI ​​algorithms used for analysis are built using machine learning frameworks such as TENSORFLOW® or PyTorch. These algorithms identify the most suitable work environment for people with disabilities.

[0070] The terminal displays matching information provided by the server based on the disability information and desired job conditions entered by the user. The user interface on the terminal is built with React and Vue.js frameworks and visually presents company information. It also asynchronously receives and displays information from the server using JavaScript's Axios and Fetch APIs. In addition, the terminal uses WebSocket and WebRTC to enable real-time communication between the user and the company's disabled employees.

[0071] Users enter their profile information using a terminal and provide the system with their job search criteria. The server then provides the user with suitable company information, allowing the user to proceed with selecting a work environment based on that information. For example, if a visually impaired user desires an IT-related job, they enter details of their disability and desired job type into the terminal. The server then uses this information to list IT companies with workplace environments suitable for visually impaired individuals and sends detailed information to the terminal.

[0072] Possible inputs to the generating AI model include prompts such as, "Please suggest companies with suitable IT-related work environments for a visually impaired user. This user prefers a remote work environment." In this way, the system aims to help people with disabilities quickly and appropriately find work environments that meet their specific needs.

[0073] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0074] Step 1:

[0075] The server collects employment and internal environment information from companies. It uses data obtained from the company's HR system or job posting platform via an API as input. The output is stored in a database in raw data form, specifically including company name, job description, required skills, and workplace accessibility information.

[0076] Step 2:

[0077] The server preprocesses the collected data. The input is raw data stored in a database. Data processing includes imputing missing values, encoding categorical data, and scaling numerical data. Specifically, these preprocessing steps are performed using the Python Pandas library. The output is data converted into a parseable format.

[0078] Step 3:

[0079] The server analyzes pre-processed data based on AI algorithms to identify the optimal work environment. The input is pre-processed data. As a data computation, machine learning models and generative AI models are used to calculate a work environment evaluation score based on the user's profile information. Specific operations include executing models using TensorFlow or PyTorch. The output is a list of the optimal work environments for the user.

[0080] Step 4:

[0081] The server sends the work environment information identified through analysis to the terminal. The input is a list of work environments. For informational purposes, the data is formatted into an easy-to-understand list or graphical form. Specifically, the data is sent to the terminal in JSON format using the HTTP protocol. The output is visualized information displayed on the user's terminal.

[0082] Step 5:

[0083] The terminal displays job information to the user. Input is job environment data sent from the server. Specifically, it displays information in card or list format using a GUI built with React or Vue.js. Output is job and company information that the user can visually understand.

[0084] Step 6:

[0085] The user views and selects detailed information about companies they are interested in through their device. The input is the job information of the company displayed on the device. Specifically, the user selects a company of interest and is redirected to its details page. The output is a list of companies of interest based on the user's selection.

[0086] Step 7:

[0087] Users interact with disabled employees of a company using the chat function on their device. Input consists of the company information selected by the user and a request to start a chat. The system utilizes WebSocket or WebRTC to achieve real-time chat. Output consists of information about the workplace atmosphere and job duties obtained by the user.

[0088] (Application Example 1)

[0089] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0090] Finding suitable jobs for workers with diverse disabilities in diverse work environments such as logistics centers is difficult due to differences in environment and tasks. Furthermore, understanding the actual work environment beforehand is necessary to determine if it is appropriate before employment. This presents a challenge in avoiding employment in unsuitable environments and reducing worker anxiety.

[0091] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0092] In this invention, the server includes a data collection means for acquiring work information for persons with disabilities, a data analysis means for analyzing the acquired work information to identify a work environment suitable for persons with disabilities, and an information provision means for distributing the identified work environment information to a user terminal. This enables persons with disabilities to understand a work environment optimized for their individual disability characteristics based on work information collected from various workplaces, and to confidently choose an appropriate workplace.

[0093] "Job information for people with disabilities" refers to data on work content and work environment that is necessary for people with disabilities when choosing a job.

[0094] "Data collection methods" refer to systems that collect information about employment and work from companies and workplaces.

[0095] "Data analysis methods" refer to algorithms and tools used to identify the most suitable work environment for individuals with disabilities based on collected information.

[0096] "Information provision means" refers to a mechanism for transmitting analysis results to the user's terminal in an appropriate format.

[0097] "Means of communication" refers to methods for users to communicate with disabled employees or staff within the workplace.

[0098] An "optimization method" is a process that presents the optimal option from multiple task candidates based on the user's disability characteristics.

[0099] A "user terminal" is a device used by a user to receive and display information.

[0100] The system for implementing the present invention consists of the aforementioned components and primarily operates around a server, terminals, and users. The server collects work information for people with disabilities from multiple workplaces, including logistics centers, through data collection means. The collected information is analyzed by data analysis means to identify work environments adapted to specific disability characteristics. AI analysis algorithms such as TensorFlow are used for the analysis.

[0101] The analysis results are delivered to the user's terminal via an information delivery system. The terminal is equipped with a display interface using visualization technology, allowing the user to view the presented work environment information. This information includes job duties and a workplace overview in a visually easy-to-understand format. The terminal also features a chat function, enabling users to communicate directly with logistics center staff. This allows for a deeper understanding of the specific on-site environment and job duties.

[0102] As a concrete example, if a visually impaired user wishes to perform light work at a logistics center, the server will list suitable centers and send that information to the user's terminal. The user can then obtain more detailed information based on the displayed data and ask further questions via chat. This helps reduce mismatches and anxieties after joining the company.

[0103] An example of a prompt message might be: "A visually impaired individual is seeking light work at a logistics center. Please list and provide details of the inclusive work environment and its specific requirements."

[0104] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0105] Step 1:

[0106] The server retrieves work information for people with disabilities from the logistics center. Inputs include the logistics center's API and database, while output is unanalyzed work data. This data includes work content and workplace conditions, and is stored on the server using data collection methods.

[0107] Step 2:

[0108] The server analyzes the collected work information using AI. In this step, an AI analysis algorithm (such as TensorFlow) identifies work environments that are appropriate for the characteristics of people with disabilities. The input is the work data from step 1, and the output is a list of work environments with a high degree of fit. The server processes the work data using data analysis tools and selects the candidate that best matches the user's needs.

[0109] Step 3:

[0110] The identified work environment information is delivered to the user's terminal via the server's information delivery system. The input is the work environment data identified in step 2, and the output is detailed information displayed on the user's terminal. The server selects and sends the most relevant information in response to user prompts.

[0111] Step 4:

[0112] The user reviews the information provided through the terminal. The terminal uses visualization technology to display the information visually. The input is the data acquired in step 3, and the output is information formatted in a way that is easy for the user to understand. The user views the displayed work environment and tasks, and checks for details as needed.

[0113] Step 5:

[0114] Users communicate with logistics center staff using the chat function built into their devices. Input consists of questions and opinions the user wants to express, while output includes responses from staff. Through the device's communication, users resolve questions about specific tasks and the work environment.

[0115] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0116] This invention combines an emotion engine with a system that supports the promotion and retention of employment for people with disabilities. This system functions through complex interactions between a server, terminals, and users.

[0117] Server Role

[0118] The server has the function of periodically collecting job information and internal environment data provided by companies and storing it in a database. Furthermore, it is equipped with a data analysis function using an emotion engine, which identifies the optimal work environment based on the user's profile information and emotional responses during actual use. The server integrates the identified work environment and the user's emotional data and transmits it to the terminal.

[0119] Terminal role

[0120] The terminal allows users to access job information through a user interface and provides forms for entering disability type and job preferences. It also has sensors for an emotion engine that analyzes the user's emotions in real time. This allows the way information is presented and the interaction to be dynamically adjusted according to the user's emotional state. For example, if the user indicates a sense of security, more detailed information than usual may be presented.

[0121] User actions

[0122] Users input their profile information and job-seeking conditions through the terminal's user interface and set them in the system. When viewing information, an emotion engine monitors the user's reactions, and the server uses this emotion data to provide more appropriate information. At the same time, users can interact with employees with disabilities within the company using the chat function and hear about their actual work experiences.

[0123] Specific example

[0124] For example, suppose a wheelchair user is looking for a job in manufacturing. This user enters their requirements into a terminal and views detailed information about the work environment and equipment. The system recognizes the user's emotions, and if the user expresses anxiety, it provides additional information such as photos of the equipment and testimonials from actual users. In this way, the user can gain a deeper understanding of the workplace atmosphere and the possibility of adaptation.

[0125] This entire process is designed to provide essential support to help people with disabilities reduce anxiety about their work environment and adapt smoothly to the workplace.

[0126] The following describes the processing flow.

[0127] Step 1:

[0128] The server periodically collects job information and internal environment information from companies and stores it in a database. This ensures that the latest employment information is always maintained.

[0129] Step 2:

[0130] The terminal launches a user interface, prompting the user to input their disability type and job preferences. The entered data is then sent to the server.

[0131] Step 3:

[0132] The server uses an emotion engine to analyze the received user information and identify a suitable work environment. The analysis involves matching the user's profile information with their job information.

[0133] Step 4:

[0134] The device activates an emotion engine and monitors the user's emotional state in real time while they are viewing information. Sensors detect the user's facial expressions and voice, and transmit this data to a server.

[0135] Step 5:

[0136] The server dynamically adjusts how information is delivered based on the user's emotional data. For example, it might provide positive feedback to users who are feeling anxious to help them feel more at ease.

[0137] Step 6:

[0138] The device visualizes and displays information tailored to the user's emotional state based on information sent from the server. This allows users to receive in-depth information and support when needed.

[0139] Step 7:

[0140] Users can use their device's chat function to communicate with employees with disabilities within the company and ask questions about their actual work environment. The feedback received through chat is also recorded on the server and used for future use.

[0141] (Example 2)

[0142] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0143] In today's workplace environment, providing appropriate support for people with disabilities requires not only job information but also support that takes into account their individual emotions and adaptation levels. Existing systems lack the ability to grasp the emotional state of people with disabilities in real time and identify the optimal work environment based on that information. Therefore, there is a need for a system that reduces anxiety about the workplace environment and supports smooth integration.

[0144] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0145] In this invention, the server includes an information gathering means for acquiring job information for persons with disabilities, an information analysis means for analyzing the acquired job information and identifying the optimal work environment for persons with disabilities based on sentiment analysis, and an information supply means for distributing the identified work environment information to the user terminal. This makes it possible to grasp the user's emotional state in real time and display information accordingly. This provides a system that supports persons with disabilities in deepening their understanding of the workplace environment, reducing anxiety, and adapting to their work.

[0146] "Information gathering means" refers to a system for collecting job information for people with disabilities and obtaining data necessary for system analysis.

[0147] "Information analysis means" refers to a system that analyzes collected job information based on sentiment analysis and executes a process to identify the optimal work environment for people with disabilities.

[0148] An "information supply means" is a system that delivers business environment information identified through analysis to user terminals and provides users with appropriate information.

[0149] "Emotion recognition means" refers to technology that grasps the user's emotional state in real time and dynamically adjusts the information displayed accordingly.

[0150] "Communication means" refers to network infrastructure or protocols that connect users with disabled employees within a company and enable two-way communication.

[0151] A "computational means" refers to an algorithm or processor that compares the profile data of people with disabilities with the business data of companies to perform optimal matching.

[0152] "Display means" refers to a device or software for visually presenting a company's internal environment data and job-related data through a user interface.

[0153] This invention is a system to support the promotion of employment and job retention for people with disabilities. Specific embodiments are described below.

[0154] The server collects job information and internal environment data from companies and stores this data in a database. MySQL is used as an example of a database management system in this process, and data from companies is obtained via API or FTP. The collected data is analyzed through an emotion engine. Here, an emotion analysis API such as IBM Watson® is used to identify the optimal work environment based on the user's profile information and emotion data.

[0155] The terminal provides an interface to the user. Through this interface, the user can input their profile data and job search criteria. A web browser is used for this interface. The terminal has built-in sensors for an emotion engine, which capture emotions in real time through the camera and microphone. Based on the emotion data analyzed by the emotion engine, the terminal dynamically presents information and enables interaction that responds to the user's emotional state.

[0156] Users can access job information through their devices. Based on optimal work environment information transmitted from the server, users can obtain detailed workplace information. Job information is adjusted according to the user's emotions, and additional information is provided as needed. For example, if a user expresses anxiety, supplementary information such as photos of facilities and testimonials from actual users may be displayed.

[0157] Furthermore, users can interact with employees with disabilities within the company using the system's chat function. This allows them to hear about specific work experiences and deepen their understanding of the work environment.

[0158] The prompts used in the generating AI model include phrases like, "Please provide details about the workplace environment in the manufacturing industry. In particular, please include information about the experiences of wheelchair users and photos of the equipment." These prompts are a crucial element in providing information tailored to the user's needs.

[0159] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0160] Step 1:

[0161] The server retrieves job information and internal environment data from companies. Input data comes from company databases and cloud services. This information is received via API or FTP. The server preprocesses the received data to standardize the data format before storing it in the database. The output data is saved in the database and used for subsequent analysis.

[0162] Step 2:

[0163] The terminal receives input from the user and sends the user's profile data and job-seeking conditions to the server. This information includes desired job type, work location, and type of disability. The server stores this information in a database before analyzing it. The user's profile is stored in the database as output.

[0164] Step 3:

[0165] Sensors built into the device capture the user's emotional data in real time. Inputs include video and audio data acquired through the camera and microphone. The emotion engine analyzes this data to identify the user's emotional state. Specifically, it uses a generative AI model to determine emotions from facial expressions and tone of voice, and quantifies them. The output is data of the identified emotional state.

[0166] Step 4:

[0167] The server identifies the optimal work environment based on collected job information, user profiles, and sentiment data. This process takes job information, user data, and sentiment data obtained from a database as input. The server uses information analysis tools to calculate the relationships between the data and perform appropriate matching. The output is information about the work environment optimized for the user.

[0168] Step 5:

[0169] The server transmits identified work environment information to the terminal. The terminal displays the information on its user interface based on the received information. The input is the work environment information transmitted from the server. The terminal dynamically adjusts the content and order of the displayed information according to the user's emotional state. The output is the visually presented work environment information.

[0170] Step 6:

[0171] Users review job information provided via their devices and communicate with employees with disabilities within the company as needed. This involves using communication methods such as chat and video calls. Input consists of the displayed information and user reactions, while output consists of new insights and feedback gained by the user.

[0172] Step 7:

[0173] User feedback is sent from the terminal to the server and stored in a database. The server uses this feedback to analyze and improve the system. The input is user feedback data, and the output is new insights for improving system performance.

[0174] (Application Example 2)

[0175] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0176] There is insufficient information available to support the adaptation of people with disabilities to the work environment, and in particular, there is a need for adaptive adjustments to the work environment that are tailored to each individual's emotional state. Furthermore, a system is needed to measure anxiety and stress in the workplace and dynamically provide feedback for appropriate environmental improvements.

[0177] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0178] In this invention, the server includes data collection means for acquiring employment information for persons with disabilities, data analysis means for analyzing the acquired employment information to identify a work environment suitable for persons with disabilities, information provision means for distributing the identified work environment information to a user terminal, communication means for connecting the user with employees with disabilities within the company, emotion recognition means for analyzing the user's emotional state in real time, and environment adjustment means for dynamically adjusting the environment settings based on the emotional state. This makes it possible for persons with disabilities to adaptively improve their work environment based on their individual emotional state.

[0179] "Employment information for people with disabilities" refers to information about job details, working conditions, and work environments provided for people with disabilities to use in the labor market.

[0180] "Data collection means" refers to a device or technology that automatically collects necessary information and prepares it for storage or analysis.

[0181] "Data analysis tools" are technologies used to process collected information and to make understandings and judgments according to specific purposes.

[0182] "Information provision means" refers to technology or equipment for presenting necessary information to users in an appropriate format.

[0183] "Means of communication" are means of exchanging information between multiple entities located in different places.

[0184] "Emotion recognition means" refers to technology that detects a user's emotional state and applies that information.

[0185] "Environmental adjustment means" refers to technologies that dynamically change the physical or digital environment based on the user's state or needs.

[0186] This invention provides a system to help people with disabilities adapt to their work environment. The system primarily utilizes the following hardware and software. The server, as a data collection means, acquires employment information for people with disabilities from multiple information sources. This information includes the company's internal environment and job descriptions. As a data analysis means, the server analyzes this information to identify a suitable work environment for people with disabilities. The analysis uses an emotion engine to apply algorithms based on the collected data.

[0187] The terminal allows users to access job information through a user interface. Furthermore, it is equipped with emotion recognition capabilities to analyze the user's emotional state in real time. The emotional data obtained from this analysis is sent to a server and used to dynamically adjust job information and environment settings.

[0188] Users can input their profile information and job-seeking conditions using the device to receive suggestions for the most suitable work environment. They can also interact with employees with disabilities within companies using communication tools, gaining information about their actual work experiences. If a user expresses anxiety, the device will adjust the work environment by playing music or visualizing information.

[0189] As a concrete example, consider a case where a wheelchair user is engaged in manufacturing work at a factory. This invention uses sensors to play relaxing music and adjust lighting when the user feels anxious, thereby making the work easier. In this way, the aim is to support the user in adapting well to their work on-site.

[0190] Using a generative AI model, it is possible to generate suggestions in real time that are tailored to the user's state. An example of such a prompt would be, "Please describe the specific working methods for a factory robot that adjusts the environment based on the emotional data of disabled workers so that they can work safely on the production line." Using this prompt, the AI ​​can provide real-time suggestions for adjusting the work environment to suit the user's situation.

[0191] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0192] Step 1:

[0193] The server periodically acquires job information and internal environment data for people with disabilities provided by companies using data collection methods. The inputs here are internal environment and job information, and the output is a database that stores this information in preparation for subsequent analysis.

[0194] Step 2:

[0195] The server uses data analysis tools to identify appropriate work environments based on collected information and the profile information of individuals with disabilities. This process utilizes an emotion engine to analyze collected data and a matching algorithm to estimate the optimal work environment. The inputs are profile information and job information, and the output is the optimal job suggestion.

[0196] Step 3:

[0197] The user enters their job search criteria and profile information using the terminal's user interface. At this stage, the input is the user's job search criteria and profile information, and the output is the user data sent to the server.

[0198] Step 4:

[0199] The device uses emotion recognition to analyze the user's emotional state in real time. It acquires emotional data from an emotion sensor and sends it to the server based on the analysis results. The input is the user's real-time emotional data, and the output is a report of the emotional state to the server.

[0200] Step 5:

[0201] Based on the received emotional state, the server uses a generative AI model to generate appropriate job information and environment settings suggestions for the user. The input in this process is emotional data and analytical data, and the output is environment adjustment and job information suggestions.

[0202] Step 6:

[0203] Users access suggested information using a terminal, select job information as needed, and interact with disabled employees within the company via communication methods. The input is the suggested job information, and the output is the selected job information and the results of the interaction.

[0204] Step 7:

[0205] The device dynamically adjusts the environment based on the user's emotional state. For example, if it detects anxiety, it might play relaxing music or adjust the lighting. The input is the user's current emotional state, and the output is the adjusted physical or digital environment.

[0206] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0207] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0208] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0209] [Second Embodiment]

[0210] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0211] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0212] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0213] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0214] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0215] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0216] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0217] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0218] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0219] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0220] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0221] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0222] This invention is a system for supporting the adaptation of people with disabilities to the work environment, and its main components consist of a server, terminals, and users.

[0223] Server Role

[0224] The server has the function of regularly collecting job information and internal environment information from companies. This ensures that the database is always up-to-date. The server also implements an AI algorithm to analyze the collected data and identify the most suitable work environment for people with disabilities. This identified information is converted into a user-friendly format and sent to the terminal.

[0225] Terminal role

[0226] The terminal has the function of displaying matching information provided by the server based on the type of disability and desired job conditions entered by the user. The terminal is equipped with a user interface that visualizes detailed company information, which serves as a reference for users when selecting a company. In addition, the terminal provides a chat function, allowing users to communicate directly with disabled employees of companies. This communication helps users to learn about the actual work content and workplace atmosphere in advance.

[0227] User actions

[0228] Users register their profile information via their device and provide the system with job search parameters. Users can view company information displayed on their device and research companies that interest them in more detail. Users can use the chat function to interact with current and former employees of companies and ask specific questions to deepen their understanding of the work environment. Through this process, people with disabilities can select companies that meet their criteria and proceed with applications with confidence.

[0229] Specific example

[0230] For example, suppose a visually impaired user is seeking an IT-related job. The user enters details of their disability and desired job type into a terminal and sends the information to a server. Based on this information, the server lists IT companies with workplace environments that accommodate visually impaired individuals and sends detailed information to the terminal. This allows the user to gain a deeper understanding of the work content and communication methods at each company and proceed with applications based on the matching results. The purpose of this process is to reduce anxiety after joining a company by allowing the user to know in advance about any gaps in the workplace environment.

[0231] The following describes the processing flow.

[0232] Step 1:

[0233] The server retrieves job information and internal environment information from companies via APIs and stores it in a database. This ensures that the latest employment information is always maintained.

[0234] Step 2:

[0235] The server analyzes information collected from the database and applies an AI algorithm to identify suitable work environments for people with disabilities. This generates a matching score based on the type of disability and desired job.

[0236] Step 3:

[0237] The terminal launches the user interface, allowing the user to enter their profile information and desired job conditions. It also sends the user's input data to the server.

[0238] Step 4:

[0239] Based on the information received from the user, the server organizes company information, including a suitable work environment and matching score, and sends it to the terminal.

[0240] Step 5:

[0241] The terminal visually displays company information and matching results sent from the server to the user. This allows the user to view detailed information about potential companies.

[0242] Step 6:

[0243] Based on the displayed information, users can select companies they are interested in and, if they want to learn more, they can use the chat function to communicate with company representatives or alumni.

[0244] Step 7:

[0245] When a user applies to a company they have selected, they can upload the necessary documents and schedule an interview via their device. This completes the application process.

[0246] (Example 1)

[0247] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0248] To appropriately match individuals with disabilities to a company's work environment, it is necessary to efficiently collect and analyze the latest job information and internal environment information, and to provide a work environment that meets the individual needs of each person with a disability. However, conventional systems have not adequately collected and analyzed such information, resulting in the challenge that it is difficult for people with disabilities to find a suitable work environment.

[0249] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0250] In this invention, the server includes data collection means for acquiring employment information and internal environment information from companies and storing it in a database; preprocessing means for imputing missing values ​​and scaling the acquired information; and data analysis means for analyzing the preprocessed information and using an AI algorithm to identify a work environment suitable for persons with disabilities. This makes it possible for persons with disabilities to easily find a work environment that suits their own conditions.

[0251] "Data collection means" refers to a function for acquiring employment information and internal environment information from companies and storing it in a database.

[0252] "Preprocessing means" refers to functions that perform actions such as imputing missing values ​​and scaling in order to convert the acquired information into a format suitable for analysis by AI algorithms.

[0253] "Data analysis tools" refer to functions that use machine learning and artificial intelligence algorithms, based on pre-processed information, to identify suitable work environments for people with disabilities.

[0254] "Information provision means" refers to a function that converts identified work environment information into a format that is easy for users to understand and delivers it to the user's terminal.

[0255] "Display means" refers to a function that visualizes detailed job information of a company on the user interface, making it easy for users to understand the information.

[0256] "Communication methods" refer to functions that provide conversational features, such as chat, to enable users and company employees to exchange information in real time.

[0257] This invention is a system for supporting the adaptation of persons with disabilities to the work environment, and includes a server, terminals, and users as its main components.

[0258] The server communicates with external databases via APIs to collect employment information and internal workplace environment information from companies. The collected data is stored in database systems such as MySQL or PostgreSQL on the server. The server uses the Python Pandas library to perform preprocessing for analysis by AI algorithms, including imputing missing values ​​and scaling the data. The AI ​​algorithms used for analysis are built using machine learning frameworks such as TensorFlow and PyTorch. These algorithms identify the most suitable work environment for people with disabilities.

[0259] The terminal displays matching information provided by the server based on the disability information and desired job conditions entered by the user. The user interface on the terminal is built with React and Vue.js frameworks and visually presents company information. It also asynchronously receives and displays information from the server using JavaScript's Axios and Fetch APIs. In addition, the terminal uses WebSocket and WebRTC to enable real-time communication between the user and the company's disabled employees.

[0260] Users enter their profile information using a terminal and provide the system with their job search criteria. The server then provides the user with suitable company information, allowing the user to proceed with selecting a work environment based on that information. For example, if a visually impaired user desires an IT-related job, they enter details of their disability and desired job type into the terminal. The server then uses this information to list IT companies with workplace environments suitable for visually impaired individuals and sends detailed information to the terminal.

[0261] Possible inputs to the generating AI model include prompts such as, "Please suggest companies with suitable IT-related work environments for a visually impaired user. This user prefers a remote work environment." In this way, the system aims to help people with disabilities quickly and appropriately find work environments that meet their specific needs.

[0262] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0263] Step 1:

[0264] The server collects employment and internal environment information from companies. It uses data obtained from the company's HR system or job posting platform via an API as input. The output is stored in a database in raw data form, specifically including company name, job description, required skills, and workplace accessibility information.

[0265] Step 2:

[0266] The server preprocesses the collected data. The input is raw data stored in a database. Data processing includes imputing missing values, encoding categorical data, and scaling numerical data. Specifically, these preprocessing steps are performed using the Python Pandas library. The output is data converted into a parseable format.

[0267] Step 3:

[0268] The server analyzes pre-processed data based on AI algorithms to identify the optimal work environment. The input is pre-processed data. As a data computation, machine learning models and generative AI models are used to calculate a work environment evaluation score based on the user's profile information. Specific operations include executing models using TensorFlow or PyTorch. The output is a list of the optimal work environments for the user.

[0269] Step 4:

[0270] The server sends the work environment information identified through analysis to the terminal. The input is a list of work environments. For informational purposes, the data is formatted into an easy-to-understand list or graphical form. Specifically, the data is sent to the terminal in JSON format using the HTTP protocol. The output is visualized information displayed on the user's terminal.

[0271] Step 5:

[0272] The terminal displays job information to the user. Input is job environment data sent from the server. Specifically, it displays information in card or list format using a GUI built with React or Vue.js. Output is job and company information that the user can visually understand.

[0273] Step 6:

[0274] The user views and selects detailed information about companies they are interested in through their device. The input is the job information of the company displayed on the device. Specifically, the user selects a company of interest and is redirected to its details page. The output is a list of companies of interest based on the user's selection.

[0275] Step 7:

[0276] Users interact with disabled employees of a company using the chat function on their device. Input consists of the company information selected by the user and a request to start a chat. The system utilizes WebSocket or WebRTC to achieve real-time chat. Output consists of information about the workplace atmosphere and job duties obtained by the user.

[0277] (Application Example 1)

[0278] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0279] Finding suitable jobs for workers with diverse disabilities in diverse work environments such as logistics centers is difficult due to differences in environment and tasks. Furthermore, understanding the actual work environment beforehand is necessary to determine if it is appropriate before employment. This presents a challenge in avoiding employment in unsuitable environments and reducing worker anxiety.

[0280] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0281] In this invention, the server includes data collection means for acquiring business information for disabled persons, data analysis means for analyzing the acquired business information to identify a working environment suitable for disabled persons, and information providing means for distributing the identified working environment information to user terminals. Thereby, based on the business information collected from various workplaces by disabled persons, it becomes possible to understand a job environment optimized for individual disability characteristics and to safely select an appropriate workplace.

[0282] "Business information for disabled persons" refers to data on work content and job environment required when a person with a disability selects a job.

[0283] "Data collection means" refers to a mechanism for collecting information related to employment and business from companies and workplaces.

[0284] "Data analysis means" refers to algorithms and tools for identifying the most suitable working environment for a person with a disability based on the collected information.

[0285] "Information providing means" refers to a mechanism for transmitting the analysis results to user terminals in an appropriate format.

[0286] "Communication means" refers to a method for a user to communicate with disabled employees or staff within a workplace.

[0287] "Optimization means" refers to a process of presenting an optimal option from multiple work candidates based on the disability characteristics of the user.

[0288] "User terminal" refers to a device for a user to receive and display information.

[0289] The system for implementing the present invention consists of the aforementioned components and primarily operates around a server, terminals, and users. The server collects work information for people with disabilities from multiple workplaces, including logistics centers, through data collection means. The collected information is analyzed by data analysis means to identify work environments adapted to specific disability characteristics. AI analysis algorithms such as TensorFlow are used for the analysis.

[0290] The analysis results are delivered to the user's terminal via an information delivery system. The terminal is equipped with a display interface using visualization technology, allowing the user to view the presented work environment information. This information includes job duties and a workplace overview in a visually easy-to-understand format. The terminal also features a chat function, enabling users to communicate directly with logistics center staff. This allows for a deeper understanding of the specific on-site environment and job duties.

[0291] As a concrete example, if a visually impaired user wishes to perform light work at a logistics center, the server will list suitable centers and send that information to the user's terminal. The user can then obtain more detailed information based on the displayed data and ask further questions via chat. This helps reduce mismatches and anxieties after joining the company.

[0292] An example of a prompt message might be: "A visually impaired individual is seeking light work at a logistics center. Please list and provide details of the inclusive work environment and its specific requirements."

[0293] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0294] Step 1:

[0295] The server retrieves work information for people with disabilities from the logistics center. Inputs include the logistics center's API and database, while output is unanalyzed work data. This data includes work content and workplace conditions, and is stored on the server using data collection methods.

[0296] Step 2:

[0297] The server analyzes the collected work information using AI. In this step, an AI analysis algorithm (such as TensorFlow) identifies work environments that are appropriate for the characteristics of people with disabilities. The input is the work data from step 1, and the output is a list of work environments with a high degree of fit. The server processes the work data using data analysis tools and selects the candidate that best matches the user's needs.

[0298] Step 3:

[0299] The identified work environment information is delivered to the user's terminal via the server's information delivery system. The input is the work environment data identified in step 2, and the output is detailed information displayed on the user's terminal. The server selects and sends the most relevant information in response to user prompts.

[0300] Step 4:

[0301] The user reviews the information provided through the terminal. The terminal uses visualization technology to display the information visually. The input is the data acquired in step 3, and the output is information formatted in a way that is easy for the user to understand. The user views the displayed work environment and tasks, and checks for details as needed.

[0302] Step 5:

[0303] The user communicates with the staff of the logistics center by using the chat function installed on the terminal. The input includes the questions and opinions that the user wants to know, and the output includes the responses from the staff. Through the communication means of the terminal, the user performs operations to resolve doubts about specific business contents and workplace environments.

[0304] Furthermore, an emotion engine for estimating the user's emotion may be combined. That is, the specific processing unit 290 may estimate the user's emotion using the emotion specific model 59 and perform specific processing using the user's emotion.

[0305] The present invention combines an emotion engine with a system for supporting the employment promotion and settlement of disabled persons. This system functions through the complex interaction of a server, a terminal, and a user.

[0306] Role of the server

[0307] The server has a function of regularly collecting job information and in-company environment data provided by the company and storing them in a database. Furthermore, it has a data analysis function using an emotion engine, and identifies the optimal job environment based on the user's profile information and emotional reactions during actual use. The server integrates the identified job environment and the user's emotion data and transmits them to the terminal.

[0308] Role of the terminal

[0309] The terminal enables the user to access job information through the user interface and provides a form for inputting the type of disability and job aspirations. It also has a sensor for the emotion engine and analyzes the user's emotion in real time. As a result, the information presentation method and interaction are dynamically adjusted according to the user's emotional state. For example, when the user shows a sense of security, operations such as presenting more detailed information than usual are performed.

[0310] User operations

[0311] Users input their profile information and job-seeking conditions through the terminal's user interface and set them in the system. When viewing information, an emotion engine monitors the user's reactions, and the server uses this emotion data to provide more appropriate information. At the same time, users can interact with employees with disabilities within the company using the chat function and hear about their actual work experiences.

[0312] Specific example

[0313] For example, suppose a wheelchair user is looking for a job in manufacturing. This user enters their requirements into a terminal and views detailed information about the work environment and equipment. The system recognizes the user's emotions, and if the user expresses anxiety, it provides additional information such as photos of the equipment and testimonials from actual users. In this way, the user can gain a deeper understanding of the workplace atmosphere and the possibility of adaptation.

[0314] This entire process is designed to provide essential support to help people with disabilities reduce anxiety about their work environment and adapt smoothly to the workplace.

[0315] The following describes the processing flow.

[0316] Step 1:

[0317] The server periodically collects job information and internal environment information from companies and stores it in a database. This ensures that the latest employment information is always maintained.

[0318] Step 2:

[0319] The terminal launches a user interface, prompting the user to input their disability type and job preferences. The entered data is then sent to the server.

[0320] Step 3:

[0321] The server uses an emotion engine to analyze the received user information and identify a suitable work environment. The analysis involves matching the user's profile information with their job information.

[0322] Step 4:

[0323] The device activates an emotion engine and monitors the user's emotional state in real time while they are viewing information. Sensors detect the user's facial expressions and voice, and transmit this data to a server.

[0324] Step 5:

[0325] The server dynamically adjusts how information is delivered based on the user's emotional data. For example, it might provide positive feedback to users who are feeling anxious to help them feel more at ease.

[0326] Step 6:

[0327] The device visualizes and displays information tailored to the user's emotional state based on information sent from the server. This allows users to receive in-depth information and support when needed.

[0328] Step 7:

[0329] Users can use their device's chat function to communicate with employees with disabilities within the company and ask questions about their actual work environment. The feedback received through chat is also recorded on the server and used for future use.

[0330] (Example 2)

[0331] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0332] In today's workplace environment, providing appropriate support for people with disabilities requires not only job information but also support that takes into account their individual emotions and adaptation levels. Existing systems lack the ability to grasp the emotional state of people with disabilities in real time and identify the optimal work environment based on that information. Therefore, there is a need for a system that reduces anxiety about the workplace environment and supports smooth integration.

[0333] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0334] In this invention, the server includes an information gathering means for acquiring job information for persons with disabilities, an information analysis means for analyzing the acquired job information and identifying the optimal work environment for persons with disabilities based on sentiment analysis, and an information supply means for distributing the identified work environment information to the user terminal. This makes it possible to grasp the user's emotional state in real time and display information accordingly. This provides a system that supports persons with disabilities in deepening their understanding of the workplace environment, reducing anxiety, and adapting to their work.

[0335] "Information gathering means" refers to a system for collecting job information for people with disabilities and obtaining data necessary for system analysis.

[0336] "Information analysis means" refers to a system that analyzes collected job information based on sentiment analysis and executes a process to identify the optimal work environment for people with disabilities.

[0337] An "information supply means" is a system that delivers business environment information identified through analysis to user terminals and provides users with appropriate information.

[0338] "Emotion recognition means" refers to technology that grasps the user's emotional state in real time and dynamically adjusts the information displayed accordingly.

[0339] "Communication means" refers to network infrastructure or protocols that connect users with disabled employees within a company and enable two-way communication.

[0340] A "computational means" refers to an algorithm or processor that compares the profile data of people with disabilities with the business data of companies to perform optimal matching.

[0341] "Display means" refers to a device or software for visually presenting a company's internal environment data and job-related data through a user interface.

[0342] This invention is a system to support the promotion of employment and job retention for people with disabilities. Specific embodiments are described below.

[0343] The server collects job information and internal environment data from companies and stores this data in a database. MySQL is used as an example of a database management system in this process, and data from companies is retrieved via API or FTP. The collected data is analyzed through an emotion engine. Here, an emotion analysis API such as IBM Watson is used to identify the optimal work environment based on the user's profile information and emotion data.

[0344] The terminal provides an interface to the user. Through this interface, the user can input their profile data and job search criteria. A web browser is used for this interface. The terminal has built-in sensors for an emotion engine, which capture emotions in real time through the camera and microphone. Based on the emotion data analyzed by the emotion engine, the terminal dynamically presents information and enables interaction that responds to the user's emotional state.

[0345] Users can access job information through their devices. Based on optimal work environment information transmitted from the server, users can obtain detailed workplace information. Job information is adjusted according to the user's emotions, and additional information is provided as needed. For example, if a user expresses anxiety, supplementary information such as photos of facilities and testimonials from actual users may be displayed.

[0346] Furthermore, users can interact with employees with disabilities within the company using the system's chat function. This allows them to hear about specific work experiences and deepen their understanding of the work environment.

[0347] The prompts used in the generating AI model include phrases like, "Please provide details about the workplace environment in the manufacturing industry. In particular, please include information about the experiences of wheelchair users and photos of the equipment." These prompts are a crucial element in providing information tailored to the user's needs.

[0348] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0349] Step 1:

[0350] The server retrieves job information and internal environment data from companies. Input data comes from company databases and cloud services. This information is received via API or FTP. The server preprocesses the received data to standardize the data format before storing it in the database. The output data is saved in the database and used for subsequent analysis.

[0351] Step 2:

[0352] The terminal receives input from the user and sends the user's profile data and job-seeking conditions to the server. This information includes desired job type, work location, and type of disability. The server stores this information in a database before analyzing it. The user's profile is stored in the database as output.

[0353] Step 3:

[0354] Sensors built into the device capture the user's emotional data in real time. Inputs include video and audio data acquired through the camera and microphone. The emotion engine analyzes this data to identify the user's emotional state. Specifically, it uses a generative AI model to determine emotions from facial expressions and tone of voice, and quantifies them. The output is data of the identified emotional state.

[0355] Step 4:

[0356] The server identifies the optimal work environment based on collected job information, user profiles, and sentiment data. This process takes job information, user data, and sentiment data obtained from a database as input. The server uses information analysis tools to calculate the relationships between the data and perform appropriate matching. The output is information about the work environment optimized for the user.

[0357] Step 5:

[0358] The server transmits identified work environment information to the terminal. The terminal displays the information on its user interface based on the received information. The input is the work environment information transmitted from the server. The terminal dynamically adjusts the content and order of the displayed information according to the user's emotional state. The output is the visually presented work environment information.

[0359] Step 6:

[0360] Users review job information provided via their devices and communicate with employees with disabilities within the company as needed. This involves using communication methods such as chat and video calls. Input consists of the displayed information and user reactions, while output consists of new insights and feedback gained by the user.

[0361] Step 7:

[0362] User feedback is sent from the terminal to the server and stored in a database. The server uses this feedback to analyze and improve the system. The input is user feedback data, and the output is new insights for improving system performance.

[0363] (Application Example 2)

[0364] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0365] There is insufficient information available to support the adaptation of people with disabilities to the work environment, and in particular, there is a need for adaptive adjustments to the work environment that are tailored to each individual's emotional state. Furthermore, a system is needed to measure anxiety and stress in the workplace and dynamically provide feedback for appropriate environmental improvements.

[0366] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0367] In this invention, the server includes data collection means for acquiring employment information for persons with disabilities, data analysis means for analyzing the acquired employment information to identify a work environment suitable for persons with disabilities, information provision means for distributing the identified work environment information to a user terminal, communication means for connecting the user with employees with disabilities within the company, emotion recognition means for analyzing the user's emotional state in real time, and environment adjustment means for dynamically adjusting the environment settings based on the emotional state. This makes it possible for persons with disabilities to adaptively improve their work environment based on their individual emotional state.

[0368] "Employment information for people with disabilities" refers to information about job details, working conditions, and work environments provided for people with disabilities to use in the labor market.

[0369] "Data collection means" refers to a device or technology that automatically collects necessary information and prepares it for storage or analysis.

[0370] "Data analysis tools" are technologies used to process collected information and to make understandings and judgments according to specific purposes.

[0371] "Information provision means" refers to technology or equipment for presenting necessary information to users in an appropriate format.

[0372] "Means of communication" are means of exchanging information between multiple entities located in different places.

[0373] "Emotion recognition means" refers to technology that detects a user's emotional state and applies that information.

[0374] "Environmental adjustment means" refers to technologies that dynamically change the physical or digital environment based on the user's state or needs.

[0375] This invention provides a system to help people with disabilities adapt to their work environment. The system primarily utilizes the following hardware and software. The server, as a data collection means, acquires employment information for people with disabilities from multiple information sources. This information includes the company's internal environment and job descriptions. As a data analysis means, the server analyzes this information to identify a suitable work environment for people with disabilities. The analysis uses an emotion engine to apply algorithms based on the collected data.

[0376] The terminal allows users to access job information through a user interface. Furthermore, it is equipped with emotion recognition capabilities to analyze the user's emotional state in real time. The emotional data obtained from this analysis is sent to a server and used to dynamically adjust job information and environment settings.

[0377] Users can input their profile information and job-seeking conditions using the device to receive suggestions for the most suitable work environment. They can also interact with employees with disabilities within companies using communication tools, gaining information about their actual work experiences. If a user expresses anxiety, the device will adjust the work environment by playing music or visualizing information.

[0378] As a concrete example, consider a case where a wheelchair user is engaged in manufacturing work at a factory. This invention uses sensors to play relaxing music and adjust lighting when the user feels anxious, thereby making the work easier. In this way, the aim is to support the user in adapting well to their work on-site.

[0379] Using a generative AI model, it is possible to generate suggestions in real time that are tailored to the user's state. An example of such a prompt would be, "Please describe the specific working methods for a factory robot that adjusts the environment based on the emotional data of disabled workers so that they can work safely on the production line." Using this prompt, the AI ​​can provide real-time suggestions for adjusting the work environment to suit the user's situation.

[0380] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0381] Step 1:

[0382] The server periodically acquires job information and internal environment data for people with disabilities provided by companies using data collection methods. The inputs here are internal environment and job information, and the output is a database that stores this information in preparation for subsequent analysis.

[0383] Step 2:

[0384] The server uses data analysis tools to identify appropriate work environments based on collected information and the profile information of individuals with disabilities. This process utilizes an emotion engine to analyze collected data and a matching algorithm to estimate the optimal work environment. The inputs are profile information and job information, and the output is the optimal job suggestion.

[0385] Step 3:

[0386] The user enters their job search criteria and profile information using the terminal's user interface. At this stage, the input is the user's job search criteria and profile information, and the output is the user data sent to the server.

[0387] Step 4:

[0388] The device uses emotion recognition to analyze the user's emotional state in real time. It acquires emotional data from an emotion sensor and sends it to the server based on the analysis results. The input is the user's real-time emotional data, and the output is a report of the emotional state to the server.

[0389] Step 5:

[0390] Based on the received emotional state, the server uses a generative AI model to generate appropriate job information and environment settings suggestions for the user. The input in this process is emotional data and analytical data, and the output is environment adjustment and job information suggestions.

[0391] Step 6:

[0392] Users access suggested information using a terminal, select job information as needed, and interact with disabled employees within the company via communication methods. The input is the suggested job information, and the output is the selected job information and the results of the interaction.

[0393] Step 7:

[0394] The device dynamically adjusts the environment based on the user's emotional state. For example, if it detects anxiety, it might play relaxing music or adjust the lighting. The input is the user's current emotional state, and the output is the adjusted physical or digital environment.

[0395] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0396] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0397] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0398] [Third Embodiment]

[0399] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0400] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0401] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0402] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0403] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0404] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0405] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0406] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0407] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0408] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0409] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0410] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0411] This invention is a system for supporting the adaptation of people with disabilities to the work environment, and its main components consist of a server, terminals, and users.

[0412] Server Role

[0413] The server has the function of regularly collecting job information and internal environment information from companies. This ensures that the database is always up-to-date. The server also implements an AI algorithm to analyze the collected data and identify the most suitable work environment for people with disabilities. This identified information is converted into a user-friendly format and sent to the terminal.

[0414] Terminal role

[0415] The terminal has the function of displaying matching information provided by the server based on the type of disability and desired job conditions entered by the user. The terminal is equipped with a user interface that visualizes detailed company information, which serves as a reference for users when selecting a company. In addition, the terminal provides a chat function, allowing users to communicate directly with disabled employees of companies. This communication helps users to learn about the actual work content and workplace atmosphere in advance.

[0416] User actions

[0417] Users register their profile information via their device and provide the system with job search parameters. Users can view company information displayed on their device and research companies that interest them in more detail. Users can use the chat function to interact with current and former employees of companies and ask specific questions to deepen their understanding of the work environment. Through this process, people with disabilities can select companies that meet their criteria and proceed with applications with confidence.

[0418] Specific example

[0419] For example, suppose a visually impaired user is seeking an IT-related job. The user enters details of their disability and desired job type into a terminal and sends the information to a server. Based on this information, the server lists IT companies with workplace environments that accommodate visually impaired individuals and sends detailed information to the terminal. This allows the user to gain a deeper understanding of the work content and communication methods at each company and proceed with applications based on the matching results. The purpose of this process is to reduce anxiety after joining a company by allowing the user to know in advance about any gaps in the workplace environment.

[0420] The following describes the processing flow.

[0421] Step 1:

[0422] The server retrieves job information and internal environment information from companies via APIs and stores it in a database. This ensures that the latest employment information is always maintained.

[0423] Step 2:

[0424] The server analyzes information collected from the database and applies an AI algorithm to identify suitable work environments for people with disabilities. This generates a matching score based on the type of disability and desired job.

[0425] Step 3:

[0426] The terminal launches the user interface, allowing the user to enter their profile information and desired job conditions. It also sends the user's input data to the server.

[0427] Step 4:

[0428] Based on the information received from the user, the server organizes company information, including a suitable work environment and matching score, and sends it to the terminal.

[0429] Step 5:

[0430] The terminal visually displays company information and matching results sent from the server to the user. This allows the user to view detailed information about potential companies.

[0431] Step 6:

[0432] Based on the displayed information, users can select companies they are interested in and, if they want to learn more, they can use the chat function to communicate with company representatives or alumni.

[0433] Step 7:

[0434] When a user applies to a company they have selected, they can upload the necessary documents and schedule an interview via their device. This completes the application process.

[0435] (Example 1)

[0436] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0437] To appropriately match individuals with disabilities to a company's work environment, it is necessary to efficiently collect and analyze the latest job information and internal environment information, and to provide a work environment that meets the individual needs of each person with a disability. However, conventional systems have not adequately collected and analyzed such information, resulting in the challenge that it is difficult for people with disabilities to find a suitable work environment.

[0438] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0439] In this invention, the server includes data collection means for acquiring employment information and internal environment information from companies and storing it in a database; preprocessing means for imputing missing values ​​and scaling the acquired information; and data analysis means for analyzing the preprocessed information and using an AI algorithm to identify a work environment suitable for persons with disabilities. This makes it possible for persons with disabilities to easily find a work environment that suits their own conditions.

[0440] "Data collection means" refers to a function for acquiring employment information and internal environment information from companies and storing it in a database.

[0441] "Preprocessing means" refers to functions that perform actions such as imputing missing values ​​and scaling in order to convert the acquired information into a format suitable for analysis by AI algorithms.

[0442] "Data analysis tools" refer to functions that use machine learning and artificial intelligence algorithms, based on pre-processed information, to identify suitable work environments for people with disabilities.

[0443] "Information provision means" refers to a function that converts identified work environment information into a format that is easy for users to understand and delivers it to the user's terminal.

[0444] "Display means" refers to a function that visualizes detailed job information of a company on the user interface, making it easy for users to understand the information.

[0445] "Communication methods" refer to functions that provide conversational features, such as chat, to enable users and company employees to exchange information in real time.

[0446] This invention is a system for supporting the adaptation of persons with disabilities to the work environment, and includes a server, terminals, and users as its main components.

[0447] The server communicates with external databases via APIs to collect employment information and internal workplace environment information from companies. The collected data is stored in database systems such as MySQL or PostgreSQL on the server. The server uses the Python Pandas library to perform preprocessing for analysis by AI algorithms, including imputing missing values ​​and scaling the data. The AI ​​algorithms used for analysis are built using machine learning frameworks such as TensorFlow and PyTorch. These algorithms identify the most suitable work environment for people with disabilities.

[0448] The terminal displays matching information provided by the server based on the disability information and desired job conditions entered by the user. The user interface on the terminal is built with React and Vue.js frameworks and visually presents company information. It also asynchronously receives and displays information from the server using JavaScript's Axios and Fetch APIs. In addition, the terminal uses WebSocket and WebRTC to enable real-time communication between the user and the company's disabled employees.

[0449] Users enter their profile information using a terminal and provide the system with their job search criteria. The server then provides the user with suitable company information, allowing the user to proceed with selecting a work environment based on that information. For example, if a visually impaired user desires an IT-related job, they enter details of their disability and desired job type into the terminal. The server then uses this information to list IT companies with workplace environments suitable for visually impaired individuals and sends detailed information to the terminal.

[0450] Possible inputs to the generating AI model include prompts such as, "Please suggest companies with suitable IT-related work environments for a visually impaired user. This user prefers a remote work environment." In this way, the system aims to help people with disabilities quickly and appropriately find work environments that meet their specific needs.

[0451] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0452] Step 1:

[0453] The server collects employment and internal environment information from companies. It uses data obtained from the company's HR system or job posting platform via an API as input. The output is stored in a database in raw data form, specifically including company name, job description, required skills, and workplace accessibility information.

[0454] Step 2:

[0455] The server preprocesses the collected data. The input is raw data stored in a database. Data processing includes imputing missing values, encoding categorical data, and scaling numerical data. Specifically, these preprocessing steps are performed using the Python Pandas library. The output is data converted into a parseable format.

[0456] Step 3:

[0457] The server analyzes pre-processed data based on AI algorithms to identify the optimal work environment. The input is pre-processed data. As a data computation, machine learning models and generative AI models are used to calculate a work environment evaluation score based on the user's profile information. Specific operations include executing models using TensorFlow or PyTorch. The output is a list of the optimal work environments for the user.

[0458] Step 4:

[0459] The server sends the work environment information identified through analysis to the terminal. The input is a list of work environments. For informational purposes, the data is formatted into an easy-to-understand list or graphical form. Specifically, the data is sent to the terminal in JSON format using the HTTP protocol. The output is visualized information displayed on the user's terminal.

[0460] Step 5:

[0461] The terminal displays job information to the user. Input is job environment data sent from the server. Specifically, it displays information in card or list format using a GUI built with React or Vue.js. Output is job and company information that the user can visually understand.

[0462] Step 6:

[0463] The user views and selects detailed information about companies they are interested in through their device. The input is the job information of the company displayed on the device. Specifically, the user selects a company of interest and is redirected to its details page. The output is a list of companies of interest based on the user's selection.

[0464] Step 7:

[0465] Users interact with disabled employees of a company using the chat function on their device. Input consists of the company information selected by the user and a request to start a chat. The system utilizes WebSocket or WebRTC to achieve real-time chat. Output consists of information about the workplace atmosphere and job duties obtained by the user.

[0466] (Application Example 1)

[0467] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0468] Finding suitable jobs for workers with diverse disabilities in diverse work environments such as logistics centers is difficult due to differences in environment and tasks. Furthermore, understanding the actual work environment beforehand is necessary to determine if it is appropriate before employment. This presents a challenge in avoiding employment in unsuitable environments and reducing worker anxiety.

[0469] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0470] In this invention, the server includes a data collection means for acquiring work information for persons with disabilities, a data analysis means for analyzing the acquired work information to identify a work environment suitable for persons with disabilities, and an information provision means for distributing the identified work environment information to a user terminal. This enables persons with disabilities to understand a work environment optimized for their individual disability characteristics based on work information collected from various workplaces, and to confidently choose an appropriate workplace.

[0471] "Job information for people with disabilities" refers to data on work content and work environment that is necessary for people with disabilities when choosing a job.

[0472] "Data collection methods" refer to systems that collect information about employment and work from companies and workplaces.

[0473] "Data analysis methods" refer to algorithms and tools used to identify the most suitable work environment for individuals with disabilities based on collected information.

[0474] "Information provision means" refers to a mechanism for transmitting analysis results to the user's terminal in an appropriate format.

[0475] "Means of communication" refers to methods for users to communicate with disabled employees or staff within the workplace.

[0476] An "optimization method" is a process that presents the optimal option from multiple task candidates based on the user's disability characteristics.

[0477] A "user terminal" is a device used by a user to receive and display information.

[0478] The system for implementing the present invention consists of the aforementioned components and primarily operates around a server, terminals, and users. The server collects work information for people with disabilities from multiple workplaces, including logistics centers, through data collection means. The collected information is analyzed by data analysis means to identify work environments adapted to specific disability characteristics. AI analysis algorithms such as TensorFlow are used for the analysis.

[0479] The analysis results are delivered to the user's terminal via an information delivery system. The terminal is equipped with a display interface using visualization technology, allowing the user to view the presented work environment information. This information includes job duties and a workplace overview in a visually easy-to-understand format. The terminal also features a chat function, enabling users to communicate directly with logistics center staff. This allows for a deeper understanding of the specific on-site environment and job duties.

[0480] As a concrete example, if a visually impaired user wishes to perform light work at a logistics center, the server will list suitable centers and send that information to the user's terminal. The user can then obtain more detailed information based on the displayed data and ask further questions via chat. This helps reduce mismatches and anxieties after joining the company.

[0481] An example of a prompt message might be: "A visually impaired individual is seeking light work at a logistics center. Please list and provide details of the inclusive work environment and its specific requirements."

[0482] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0483] Step 1:

[0484] The server retrieves work information for people with disabilities from the logistics center. Inputs include the logistics center's API and database, while output is unanalyzed work data. This data includes work content and workplace conditions, and is stored on the server using data collection methods.

[0485] Step 2:

[0486] The server analyzes the collected work information using AI. In this step, an AI analysis algorithm (such as TensorFlow) identifies work environments that are appropriate for the characteristics of people with disabilities. The input is the work data from step 1, and the output is a list of work environments with a high degree of fit. The server processes the work data using data analysis tools and selects the candidate that best matches the user's needs.

[0487] Step 3:

[0488] The identified work environment information is delivered to the user's terminal via the server's information delivery system. The input is the work environment data identified in step 2, and the output is detailed information displayed on the user's terminal. The server selects and sends the most relevant information in response to user prompts.

[0489] Step 4:

[0490] The user reviews the information provided through the terminal. The terminal uses visualization technology to display the information visually. The input is the data acquired in step 3, and the output is information formatted in a way that is easy for the user to understand. The user views the displayed work environment and tasks, and checks for details as needed.

[0491] Step 5:

[0492] Users communicate with logistics center staff using the chat function built into their devices. Input consists of questions and opinions the user wants to express, while output includes responses from staff. Through the device's communication, users resolve questions about specific tasks and the work environment.

[0493] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0494] This invention combines an emotion engine with a system that supports the promotion and retention of employment for people with disabilities. This system functions through complex interactions between a server, terminals, and users.

[0495] Server Role

[0496] The server has the function of periodically collecting job information and internal environment data provided by companies and storing it in a database. Furthermore, it is equipped with a data analysis function using an emotion engine, which identifies the optimal work environment based on the user's profile information and emotional responses during actual use. The server integrates the identified work environment and the user's emotional data and transmits it to the terminal.

[0497] Terminal role

[0498] The terminal allows users to access job information through a user interface and provides forms for entering disability type and job preferences. It also has sensors for an emotion engine that analyzes the user's emotions in real time. This allows the way information is presented and the interaction to be dynamically adjusted according to the user's emotional state. For example, if the user indicates a sense of security, more detailed information than usual may be presented.

[0499] User actions

[0500] Users input their profile information and job-seeking conditions through the terminal's user interface and set them in the system. When viewing information, an emotion engine monitors the user's reactions, and the server uses this emotion data to provide more appropriate information. At the same time, users can interact with employees with disabilities within the company using the chat function and hear about their actual work experiences.

[0501] Specific example

[0502] For example, suppose a wheelchair user is looking for a job in manufacturing. This user enters their requirements into a terminal and views detailed information about the work environment and equipment. The system recognizes the user's emotions, and if the user expresses anxiety, it provides additional information such as photos of the equipment and testimonials from actual users. In this way, the user can gain a deeper understanding of the workplace atmosphere and the possibility of adaptation.

[0503] This entire process is designed to provide essential support to help people with disabilities reduce anxiety about their work environment and adapt smoothly to the workplace.

[0504] The following describes the processing flow.

[0505] Step 1:

[0506] The server periodically collects job information and internal environment information from companies and stores it in a database. This ensures that the latest employment information is always maintained.

[0507] Step 2:

[0508] The terminal launches a user interface, prompting the user to input their disability type and job preferences. The entered data is then sent to the server.

[0509] Step 3:

[0510] The server uses an emotion engine to analyze the received user information and identify a suitable work environment. The analysis involves matching the user's profile information with their job information.

[0511] Step 4:

[0512] The device activates an emotion engine and monitors the user's emotional state in real time while they are viewing information. Sensors detect the user's facial expressions and voice, and transmit this data to a server.

[0513] Step 5:

[0514] The server dynamically adjusts how information is delivered based on the user's emotional data. For example, it might provide positive feedback to users who are feeling anxious to help them feel more at ease.

[0515] Step 6:

[0516] The device visualizes and displays information tailored to the user's emotional state based on information sent from the server. This allows users to receive in-depth information and support when needed.

[0517] Step 7:

[0518] Users can use their device's chat function to communicate with employees with disabilities within the company and ask questions about their actual work environment. The feedback received through chat is also recorded on the server and used for future use.

[0519] (Example 2)

[0520] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0521] In today's workplace environment, providing appropriate support for people with disabilities requires not only job information but also support that takes into account their individual emotions and adaptation levels. Existing systems lack the ability to grasp the emotional state of people with disabilities in real time and identify the optimal work environment based on that information. Therefore, there is a need for a system that reduces anxiety about the workplace environment and supports smooth integration.

[0522] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0523] In this invention, the server includes an information gathering means for acquiring job information for persons with disabilities, an information analysis means for analyzing the acquired job information and identifying the optimal work environment for persons with disabilities based on sentiment analysis, and an information supply means for distributing the identified work environment information to the user terminal. This makes it possible to grasp the user's emotional state in real time and display information accordingly. This provides a system that supports persons with disabilities in deepening their understanding of the workplace environment, reducing anxiety, and adapting to their work.

[0524] "Information gathering means" refers to a system for collecting job information for people with disabilities and obtaining data necessary for system analysis.

[0525] "Information analysis means" refers to a system that analyzes collected job information based on sentiment analysis and executes a process to identify the optimal work environment for people with disabilities.

[0526] An "information supply means" is a system that delivers business environment information identified through analysis to user terminals and provides users with appropriate information.

[0527] "Emotion recognition means" refers to technology that grasps the user's emotional state in real time and dynamically adjusts the information displayed accordingly.

[0528] "Communication means" refers to network infrastructure or protocols that connect users with disabled employees within a company and enable two-way communication.

[0529] A "computational means" refers to an algorithm or processor that compares the profile data of people with disabilities with the business data of companies to perform optimal matching.

[0530] "Display means" refers to a device or software for visually presenting a company's internal environment data and job-related data through a user interface.

[0531] This invention is a system to support the promotion of employment and job retention for people with disabilities. Specific embodiments are described below.

[0532] The server collects job information and internal environment data from companies and stores this data in a database. MySQL is used as an example of a database management system in this process, and data from companies is retrieved via API or FTP. The collected data is analyzed through an emotion engine. Here, an emotion analysis API such as IBM Watson is used to identify the optimal work environment based on the user's profile information and emotion data.

[0533] The terminal provides an interface to the user. Through this interface, the user can input their profile data and job search criteria. A web browser is used for this interface. The terminal has built-in sensors for an emotion engine, which capture emotions in real time through the camera and microphone. Based on the emotion data analyzed by the emotion engine, the terminal dynamically presents information and enables interaction that responds to the user's emotional state.

[0534] Users can access job information through their devices. Based on optimal work environment information transmitted from the server, users can obtain detailed workplace information. Job information is adjusted according to the user's emotions, and additional information is provided as needed. For example, if a user expresses anxiety, supplementary information such as photos of facilities and testimonials from actual users may be displayed.

[0535] Furthermore, users can interact with employees with disabilities within the company using the system's chat function. This allows them to hear about specific work experiences and deepen their understanding of the work environment.

[0536] The prompts used in the generating AI model include phrases like, "Please provide details about the workplace environment in the manufacturing industry. In particular, please include information about the experiences of wheelchair users and photos of the equipment." These prompts are a crucial element in providing information tailored to the user's needs.

[0537] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0538] Step 1:

[0539] The server retrieves job information and internal environment data from companies. Input data comes from company databases and cloud services. This information is received via API or FTP. The server preprocesses the received data to standardize the data format before storing it in the database. The output data is saved in the database and used for subsequent analysis.

[0540] Step 2:

[0541] The terminal receives input from the user and sends the user's profile data and job-seeking conditions to the server. This information includes desired job type, work location, and type of disability. The server stores this information in a database before analyzing it. The user's profile is stored in the database as output.

[0542] Step 3:

[0543] Sensors built into the device capture the user's emotional data in real time. Inputs include video and audio data acquired through the camera and microphone. The emotion engine analyzes this data to identify the user's emotional state. Specifically, it uses a generative AI model to determine emotions from facial expressions and tone of voice, and quantifies them. The output is data of the identified emotional state.

[0544] Step 4:

[0545] The server identifies the optimal work environment based on collected job information, user profiles, and sentiment data. This process takes job information, user data, and sentiment data obtained from a database as input. The server uses information analysis tools to calculate the relationships between the data and perform appropriate matching. The output is information about the work environment optimized for the user.

[0546] Step 5:

[0547] The server transmits identified work environment information to the terminal. The terminal displays the information on its user interface based on the received information. The input is the work environment information transmitted from the server. The terminal dynamically adjusts the content and order of the displayed information according to the user's emotional state. The output is the visually presented work environment information.

[0548] Step 6:

[0549] Users review job information provided via their devices and communicate with employees with disabilities within the company as needed. This involves using communication methods such as chat and video calls. Input consists of the displayed information and user reactions, while output consists of new insights and feedback gained by the user.

[0550] Step 7:

[0551] User feedback is sent from the terminal to the server and stored in a database. The server uses this feedback to analyze and improve the system. The input is user feedback data, and the output is new insights for improving system performance.

[0552] (Application Example 2)

[0553] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0554] There is insufficient information available to support the adaptation of people with disabilities to the work environment, and in particular, there is a need for adaptive adjustments to the work environment that are tailored to each individual's emotional state. Furthermore, a system is needed to measure anxiety and stress in the workplace and dynamically provide feedback for appropriate environmental improvements.

[0555] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0556] In this invention, the server includes data collection means for acquiring employment information for persons with disabilities, data analysis means for analyzing the acquired employment information to identify a work environment suitable for persons with disabilities, information provision means for distributing the identified work environment information to a user terminal, communication means for connecting the user with employees with disabilities within the company, emotion recognition means for analyzing the user's emotional state in real time, and environment adjustment means for dynamically adjusting the environment settings based on the emotional state. This makes it possible for persons with disabilities to adaptively improve their work environment based on their individual emotional state.

[0557] "Employment information for people with disabilities" refers to information about job details, working conditions, and work environments provided for people with disabilities to use in the labor market.

[0558] "Data collection means" refers to a device or technology that automatically collects necessary information and prepares it for storage or analysis.

[0559] "Data analysis tools" are technologies used to process collected information and to make understandings and judgments according to specific purposes.

[0560] "Information provision means" refers to technology or equipment for presenting necessary information to users in an appropriate format.

[0561] "Means of communication" are means of exchanging information between multiple entities located in different places.

[0562] "Emotion recognition means" refers to technology that detects a user's emotional state and applies that information.

[0563] "Environmental adjustment means" refers to technologies that dynamically change the physical or digital environment based on the user's state or needs.

[0564] This invention provides a system to help people with disabilities adapt to their work environment. The system primarily utilizes the following hardware and software. The server, as a data collection means, acquires employment information for people with disabilities from multiple information sources. This information includes the company's internal environment and job descriptions. As a data analysis means, the server analyzes this information to identify a suitable work environment for people with disabilities. The analysis uses an emotion engine to apply algorithms based on the collected data.

[0565] The terminal allows users to access job information through a user interface. Furthermore, it is equipped with emotion recognition capabilities to analyze the user's emotional state in real time. The emotional data obtained from this analysis is sent to a server and used to dynamically adjust job information and environment settings.

[0566] Users can input their profile information and job-seeking conditions using the device to receive suggestions for the most suitable work environment. They can also interact with employees with disabilities within companies using communication tools, gaining information about their actual work experiences. If a user expresses anxiety, the device will adjust the work environment by playing music or visualizing information.

[0567] As a concrete example, consider a case where a wheelchair user is engaged in manufacturing work at a factory. This invention uses sensors to play relaxing music and adjust lighting when the user feels anxious, thereby making the work easier. In this way, the aim is to support the user in adapting well to their work on-site.

[0568] Using a generative AI model, it is possible to generate suggestions in real time that are tailored to the user's state. An example of such a prompt would be, "Please describe the specific working methods for a factory robot that adjusts the environment based on the emotional data of disabled workers so that they can work safely on the production line." Using this prompt, the AI ​​can provide real-time suggestions for adjusting the work environment to suit the user's situation.

[0569] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0570] Step 1:

[0571] The server periodically acquires job information and internal environment data for people with disabilities provided by companies using data collection methods. The inputs here are internal environment and job information, and the output is a database that stores this information in preparation for subsequent analysis.

[0572] Step 2:

[0573] The server uses data analysis tools to identify appropriate work environments based on collected information and the profile information of individuals with disabilities. This process utilizes an emotion engine to analyze collected data and a matching algorithm to estimate the optimal work environment. The inputs are profile information and job information, and the output is the optimal job suggestion.

[0574] Step 3:

[0575] The user enters their job search criteria and profile information using the terminal's user interface. At this stage, the input is the user's job search criteria and profile information, and the output is the user data sent to the server.

[0576] Step 4:

[0577] The device uses emotion recognition to analyze the user's emotional state in real time. It acquires emotional data from an emotion sensor and sends it to the server based on the analysis results. The input is the user's real-time emotional data, and the output is a report of the emotional state to the server.

[0578] Step 5:

[0579] Based on the received emotional state, the server uses a generative AI model to generate appropriate job information and environment settings suggestions for the user. The input in this process is emotional data and analytical data, and the output is environment adjustment and job information suggestions.

[0580] Step 6:

[0581] Users access suggested information using a terminal, select job information as needed, and interact with disabled employees within the company via communication methods. The input is the suggested job information, and the output is the selected job information and the results of the interaction.

[0582] Step 7:

[0583] The device dynamically adjusts the environment based on the user's emotional state. For example, if it detects anxiety, it might play relaxing music or adjust the lighting. The input is the user's current emotional state, and the output is the adjusted physical or digital environment.

[0584] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0585] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0586] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0587] [Fourth Embodiment]

[0588] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0589] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0590] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0591] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0592] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0593] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0594] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0595] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0596] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0597] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0598] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0599] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0600] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0601] This invention is a system for supporting the adaptation of people with disabilities to the work environment, and its main components consist of a server, terminals, and users.

[0602] Server Role

[0603] The server has the function of regularly collecting job information and internal environment information from companies. This ensures that the database is always up-to-date. The server also implements an AI algorithm to analyze the collected data and identify the most suitable work environment for people with disabilities. This identified information is converted into a user-friendly format and sent to the terminal.

[0604] Terminal role

[0605] The terminal has the function of displaying matching information provided by the server based on the type of disability and desired job conditions entered by the user. The terminal is equipped with a user interface that visualizes detailed company information, which serves as a reference for users when selecting a company. In addition, the terminal provides a chat function, allowing users to communicate directly with disabled employees of companies. This communication helps users to learn about the actual work content and workplace atmosphere in advance.

[0606] User actions

[0607] Users register their profile information via their device and provide the system with job search parameters. Users can view company information displayed on their device and research companies that interest them in more detail. Users can use the chat function to interact with current and former employees of companies and ask specific questions to deepen their understanding of the work environment. Through this process, people with disabilities can select companies that meet their criteria and proceed with applications with confidence.

[0608] Specific example

[0609] For example, suppose a visually impaired user is seeking an IT-related job. The user enters details of their disability and desired job type into a terminal and sends the information to a server. Based on this information, the server lists IT companies with workplace environments that accommodate visually impaired individuals and sends detailed information to the terminal. This allows the user to gain a deeper understanding of the work content and communication methods at each company and proceed with applications based on the matching results. The purpose of this process is to reduce anxiety after joining a company by allowing the user to know in advance about any gaps in the workplace environment.

[0610] The following describes the processing flow.

[0611] Step 1:

[0612] The server retrieves job information and internal environment information from companies via APIs and stores it in a database. This ensures that the latest employment information is always maintained.

[0613] Step 2:

[0614] The server analyzes information collected from the database and applies an AI algorithm to identify suitable work environments for people with disabilities. This generates a matching score based on the type of disability and desired job.

[0615] Step 3:

[0616] The terminal launches the user interface, allowing the user to enter their profile information and desired job conditions. It also sends the user's input data to the server.

[0617] Step 4:

[0618] Based on the information received from the user, the server organizes company information, including a suitable work environment and matching score, and sends it to the terminal.

[0619] Step 5:

[0620] The terminal visually displays company information and matching results sent from the server to the user. This allows the user to view detailed information about potential companies.

[0621] Step 6:

[0622] Based on the displayed information, users can select companies they are interested in and, if they want to learn more, they can use the chat function to communicate with company representatives or alumni.

[0623] Step 7:

[0624] When a user applies to a company they have selected, they can upload the necessary documents and schedule an interview via their device. This completes the application process.

[0625] (Example 1)

[0626] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0627] To appropriately match individuals with disabilities to a company's work environment, it is necessary to efficiently collect and analyze the latest job information and internal environment information, and to provide a work environment that meets the individual needs of each person with a disability. However, conventional systems have not adequately collected and analyzed such information, resulting in the challenge that it is difficult for people with disabilities to find a suitable work environment.

[0628] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0629] In this invention, the server includes data collection means for acquiring employment information and internal environment information from companies and storing it in a database; preprocessing means for imputing missing values ​​and scaling the acquired information; and data analysis means for analyzing the preprocessed information and using an AI algorithm to identify a work environment suitable for persons with disabilities. This makes it possible for persons with disabilities to easily find a work environment that suits their own conditions.

[0630] "Data collection means" refers to a function for acquiring employment information and internal environment information from companies and storing it in a database.

[0631] "Preprocessing means" refers to functions that perform actions such as imputing missing values ​​and scaling in order to convert the acquired information into a format suitable for analysis by AI algorithms.

[0632] "Data analysis tools" refer to functions that use machine learning and artificial intelligence algorithms, based on pre-processed information, to identify suitable work environments for people with disabilities.

[0633] "Information provision means" refers to a function that converts identified work environment information into a format that is easy for users to understand and delivers it to the user's terminal.

[0634] "Display means" refers to a function that visualizes detailed job information of a company on the user interface, making it easy for users to understand the information.

[0635] "Communication methods" refer to functions that provide conversational features, such as chat, to enable users and company employees to exchange information in real time.

[0636] This invention is a system for supporting the adaptation of persons with disabilities to the work environment, and includes a server, terminals, and users as its main components.

[0637] The server communicates with external databases via APIs to collect employment information and internal workplace environment information from companies. The collected data is stored in database systems such as MySQL or PostgreSQL on the server. The server uses the Python Pandas library to perform preprocessing for analysis by AI algorithms, including imputing missing values ​​and scaling the data. The AI ​​algorithms used for analysis are built using machine learning frameworks such as TensorFlow and PyTorch. These algorithms identify the most suitable work environment for people with disabilities.

[0638] The terminal displays matching information provided by the server based on the disability information and desired job conditions entered by the user. The user interface on the terminal is built with React and Vue.js frameworks and visually presents company information. It also asynchronously receives and displays information from the server using JavaScript's Axios and Fetch APIs. In addition, the terminal uses WebSocket and WebRTC to enable real-time communication between the user and the company's disabled employees.

[0639] Users enter their profile information using a terminal and provide the system with their job search criteria. The server then provides the user with suitable company information, allowing the user to proceed with selecting a work environment based on that information. For example, if a visually impaired user desires an IT-related job, they enter details of their disability and desired job type into the terminal. The server then uses this information to list IT companies with workplace environments suitable for visually impaired individuals and sends detailed information to the terminal.

[0640] Possible inputs to the generating AI model include prompts such as, "Please suggest companies with suitable IT-related work environments for a visually impaired user. This user prefers a remote work environment." In this way, the system aims to help people with disabilities quickly and appropriately find work environments that meet their specific needs.

[0641] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0642] Step 1:

[0643] The server collects employment and internal environment information from companies. It uses data obtained from the company's HR system or job posting platform via an API as input. The output is stored in a database in raw data form, specifically including company name, job description, required skills, and workplace accessibility information.

[0644] Step 2:

[0645] The server preprocesses the collected data. The input is raw data stored in a database. Data processing includes imputing missing values, encoding categorical data, and scaling numerical data. Specifically, these preprocessing steps are performed using the Python Pandas library. The output is data converted into a parseable format.

[0646] Step 3:

[0647] The server analyzes pre-processed data based on AI algorithms to identify the optimal work environment. The input is pre-processed data. As a data computation, machine learning models and generative AI models are used to calculate a work environment evaluation score based on the user's profile information. Specific operations include executing models using TensorFlow or PyTorch. The output is a list of the optimal work environments for the user.

[0648] Step 4:

[0649] The server sends the work environment information identified through analysis to the terminal. The input is a list of work environments. For informational purposes, the data is formatted into an easy-to-understand list or graphical form. Specifically, the data is sent to the terminal in JSON format using the HTTP protocol. The output is visualized information displayed on the user's terminal.

[0650] Step 5:

[0651] The terminal displays job information to the user. Input is job environment data sent from the server. Specifically, it displays information in card or list format using a GUI built with React or Vue.js. Output is job and company information that the user can visually understand.

[0652] Step 6:

[0653] The user views and selects detailed information about companies they are interested in through their device. The input is the job information of the company displayed on the device. Specifically, the user selects a company of interest and is redirected to its details page. The output is a list of companies of interest based on the user's selection.

[0654] Step 7:

[0655] Users interact with disabled employees of a company using the chat function on their device. Input consists of the company information selected by the user and a request to start a chat. The system utilizes WebSocket or WebRTC to achieve real-time chat. Output consists of information about the workplace atmosphere and job duties obtained by the user.

[0656] (Application Example 1)

[0657] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0658] Finding suitable jobs for workers with diverse disabilities in diverse work environments such as logistics centers is difficult due to differences in environment and tasks. Furthermore, understanding the actual work environment beforehand is necessary to determine if it is appropriate before employment. This presents a challenge in avoiding employment in unsuitable environments and reducing worker anxiety.

[0659] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0660] In this invention, the server includes a data collection means for acquiring work information for persons with disabilities, a data analysis means for analyzing the acquired work information to identify a work environment suitable for persons with disabilities, and an information provision means for distributing the identified work environment information to a user terminal. This enables persons with disabilities to understand a work environment optimized for their individual disability characteristics based on work information collected from various workplaces, and to confidently choose an appropriate workplace.

[0661] "Job information for people with disabilities" refers to data on work content and work environment that is necessary for people with disabilities when choosing a job.

[0662] "Data collection methods" refer to systems that collect information about employment and work from companies and workplaces.

[0663] "Data analysis methods" refer to algorithms and tools used to identify the most suitable work environment for individuals with disabilities based on collected information.

[0664] "Information provision means" refers to a mechanism for transmitting analysis results to the user's terminal in an appropriate format.

[0665] "Means of communication" refers to methods for users to communicate with disabled employees or staff within the workplace.

[0666] An "optimization method" is a process that presents the optimal option from multiple task candidates based on the user's disability characteristics.

[0667] A "user terminal" is a device used by a user to receive and display information.

[0668] The system for implementing the present invention consists of the aforementioned components and primarily operates around a server, terminals, and users. The server collects work information for people with disabilities from multiple workplaces, including logistics centers, through data collection means. The collected information is analyzed by data analysis means to identify work environments adapted to specific disability characteristics. AI analysis algorithms such as TensorFlow are used for the analysis.

[0669] The analysis results are delivered to the user's terminal via an information delivery system. The terminal is equipped with a display interface using visualization technology, allowing the user to view the presented work environment information. This information includes job duties and a workplace overview in a visually easy-to-understand format. The terminal also features a chat function, enabling users to communicate directly with logistics center staff. This allows for a deeper understanding of the specific on-site environment and job duties.

[0670] As a concrete example, if a visually impaired user wishes to perform light work at a logistics center, the server will list suitable centers and send that information to the user's terminal. The user can then obtain more detailed information based on the displayed data and ask further questions via chat. This helps reduce mismatches and anxieties after joining the company.

[0671] An example of a prompt message might be: "A visually impaired individual is seeking light work at a logistics center. Please list and provide details of the inclusive work environment and its specific requirements."

[0672] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0673] Step 1:

[0674] The server retrieves work information for people with disabilities from the logistics center. Inputs include the logistics center's API and database, while output is unanalyzed work data. This data includes work content and workplace conditions, and is stored on the server using data collection methods.

[0675] Step 2:

[0676] The server analyzes the collected work information using AI. In this step, an AI analysis algorithm (such as TensorFlow) identifies work environments that are appropriate for the characteristics of people with disabilities. The input is the work data from step 1, and the output is a list of work environments with a high degree of fit. The server processes the work data using data analysis tools and selects the candidate that best matches the user's needs.

[0677] Step 3:

[0678] The identified work environment information is delivered to the user's terminal via the server's information delivery system. The input is the work environment data identified in step 2, and the output is detailed information displayed on the user's terminal. The server selects and sends the most relevant information in response to user prompts.

[0679] Step 4:

[0680] The user reviews the information provided through the terminal. The terminal uses visualization technology to display the information visually. The input is the data acquired in step 3, and the output is information formatted in a way that is easy for the user to understand. The user views the displayed work environment and tasks, and checks for details as needed.

[0681] Step 5:

[0682] Users communicate with logistics center staff using the chat function built into their devices. Input consists of questions and opinions the user wants to express, while output includes responses from staff. Through the device's communication, users resolve questions about specific tasks and the work environment.

[0683] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0684] This invention combines an emotion engine with a system that supports the promotion and retention of employment for people with disabilities. This system functions through complex interactions between a server, terminals, and users.

[0685] Server Role

[0686] The server has the function of periodically collecting job information and internal environment data provided by companies and storing it in a database. Furthermore, it is equipped with a data analysis function using an emotion engine, which identifies the optimal work environment based on the user's profile information and emotional responses during actual use. The server integrates the identified work environment and the user's emotional data and transmits it to the terminal.

[0687] Terminal role

[0688] The terminal allows users to access job information through a user interface and provides forms for entering disability type and job preferences. It also has sensors for an emotion engine that analyzes the user's emotions in real time. This allows the way information is presented and the interaction to be dynamically adjusted according to the user's emotional state. For example, if the user indicates a sense of security, more detailed information than usual may be presented.

[0689] User actions

[0690] Users input their profile information and job-seeking conditions through the terminal's user interface and set them in the system. When viewing information, an emotion engine monitors the user's reactions, and the server uses this emotion data to provide more appropriate information. At the same time, users can interact with employees with disabilities within the company using the chat function and hear about their actual work experiences.

[0691] Specific example

[0692] For example, suppose a wheelchair user is looking for a job in manufacturing. This user enters their requirements into a terminal and views detailed information about the work environment and equipment. The system recognizes the user's emotions, and if the user expresses anxiety, it provides additional information such as photos of the equipment and testimonials from actual users. In this way, the user can gain a deeper understanding of the workplace atmosphere and the possibility of adaptation.

[0693] This entire process is designed to provide essential support to help people with disabilities reduce anxiety about their work environment and adapt smoothly to the workplace.

[0694] The following describes the processing flow.

[0695] Step 1:

[0696] The server periodically collects job information and internal environment information from companies and stores it in a database. This ensures that the latest employment information is always maintained.

[0697] Step 2:

[0698] The terminal launches a user interface, prompting the user to input their disability type and job preferences. The entered data is then sent to the server.

[0699] Step 3:

[0700] The server uses an emotion engine to analyze the received user information and identify a suitable work environment. The analysis involves matching the user's profile information with their job information.

[0701] Step 4:

[0702] The device activates an emotion engine and monitors the user's emotional state in real time while they are viewing information. Sensors detect the user's facial expressions and voice, and transmit this data to a server.

[0703] Step 5:

[0704] The server dynamically adjusts how information is delivered based on the user's emotional data. For example, it might provide positive feedback to users who are feeling anxious to help them feel more at ease.

[0705] Step 6:

[0706] The device visualizes and displays information tailored to the user's emotional state based on information sent from the server. This allows users to receive in-depth information and support when needed.

[0707] Step 7:

[0708] Users can use their device's chat function to communicate with employees with disabilities within the company and ask questions about their actual work environment. The feedback received through chat is also recorded on the server and used for future use.

[0709] (Example 2)

[0710] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0711] In today's workplace environment, providing appropriate support for people with disabilities requires not only job information but also support that takes into account their individual emotions and adaptation levels. Existing systems lack the ability to grasp the emotional state of people with disabilities in real time and identify the optimal work environment based on that information. Therefore, there is a need for a system that reduces anxiety about the workplace environment and supports smooth integration.

[0712] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0713] In this invention, the server includes an information gathering means for acquiring job information for persons with disabilities, an information analysis means for analyzing the acquired job information and identifying the optimal work environment for persons with disabilities based on sentiment analysis, and an information supply means for distributing the identified work environment information to the user terminal. This makes it possible to grasp the user's emotional state in real time and display information accordingly. This provides a system that supports persons with disabilities in deepening their understanding of the workplace environment, reducing anxiety, and adapting to their work.

[0714] "Information gathering means" refers to a system for collecting job information for people with disabilities and obtaining data necessary for system analysis.

[0715] "Information analysis means" refers to a system that analyzes collected job information based on sentiment analysis and executes a process to identify the optimal work environment for people with disabilities.

[0716] An "information supply means" is a system that delivers business environment information identified through analysis to user terminals and provides users with appropriate information.

[0717] "Emotion recognition means" refers to technology that grasps the user's emotional state in real time and dynamically adjusts the information displayed accordingly.

[0718] "Communication means" refers to network infrastructure or protocols that connect users with disabled employees within a company and enable two-way communication.

[0719] A "computational means" refers to an algorithm or processor that compares the profile data of people with disabilities with the business data of companies to perform optimal matching.

[0720] "Display means" refers to a device or software for visually presenting a company's internal environment data and job-related data through a user interface.

[0721] This invention is a system to support the promotion of employment and job retention for people with disabilities. Specific embodiments are described below.

[0722] The server collects job information and internal environment data from companies and stores this data in a database. MySQL is used as an example of a database management system in this process, and data from companies is retrieved via API or FTP. The collected data is analyzed through an emotion engine. Here, an emotion analysis API such as IBM Watson is used to identify the optimal work environment based on the user's profile information and emotion data.

[0723] The terminal provides an interface to the user. Through this interface, the user can input their profile data and job search criteria. A web browser is used for this interface. The terminal has built-in sensors for an emotion engine, which capture emotions in real time through the camera and microphone. Based on the emotion data analyzed by the emotion engine, the terminal dynamically presents information and enables interaction that responds to the user's emotional state.

[0724] Users can access job information through their devices. Based on optimal work environment information transmitted from the server, users can obtain detailed workplace information. Job information is adjusted according to the user's emotions, and additional information is provided as needed. For example, if a user expresses anxiety, supplementary information such as photos of facilities and testimonials from actual users may be displayed.

[0725] Furthermore, users can interact with employees with disabilities within the company using the system's chat function. This allows them to hear about specific work experiences and deepen their understanding of the work environment.

[0726] The prompts used in the generating AI model include phrases like, "Please provide details about the workplace environment in the manufacturing industry. In particular, please include information about the experiences of wheelchair users and photos of the equipment." These prompts are a crucial element in providing information tailored to the user's needs.

[0727] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0728] Step 1:

[0729] The server retrieves job information and internal environment data from companies. Input data comes from company databases and cloud services. This information is received via API or FTP. The server preprocesses the received data to standardize the data format before storing it in the database. The output data is saved in the database and used for subsequent analysis.

[0730] Step 2:

[0731] The terminal receives input from the user and sends the user's profile data and job-seeking conditions to the server. This information includes desired job type, work location, and type of disability. The server stores this information in a database before analyzing it. The user's profile is stored in the database as output.

[0732] Step 3:

[0733] Sensors built into the device capture the user's emotional data in real time. Inputs include video and audio data acquired through the camera and microphone. The emotion engine analyzes this data to identify the user's emotional state. Specifically, it uses a generative AI model to determine emotions from facial expressions and tone of voice, and quantifies them. The output is data of the identified emotional state.

[0734] Step 4:

[0735] The server identifies the optimal work environment based on collected job information, user profiles, and sentiment data. This process takes job information, user data, and sentiment data obtained from a database as input. The server uses information analysis tools to calculate the relationships between the data and perform appropriate matching. The output is information about the work environment optimized for the user.

[0736] Step 5:

[0737] The server transmits identified work environment information to the terminal. The terminal displays the information on its user interface based on the received information. The input is the work environment information transmitted from the server. The terminal dynamically adjusts the content and order of the displayed information according to the user's emotional state. The output is the visually presented work environment information.

[0738] Step 6:

[0739] Users review job information provided via their devices and communicate with employees with disabilities within the company as needed. This involves using communication methods such as chat and video calls. Input consists of the displayed information and user reactions, while output consists of new insights and feedback gained by the user.

[0740] Step 7:

[0741] User feedback is sent from the terminal to the server and stored in a database. The server uses this feedback to analyze and improve the system. The input is user feedback data, and the output is new insights for improving system performance.

[0742] (Application Example 2)

[0743] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0744] There is insufficient information available to support the adaptation of people with disabilities to the work environment, and in particular, there is a need for adaptive adjustments to the work environment that are tailored to each individual's emotional state. Furthermore, a system is needed to measure anxiety and stress in the workplace and dynamically provide feedback for appropriate environmental improvements.

[0745] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0746] In this invention, the server includes data collection means for acquiring employment information for persons with disabilities, data analysis means for analyzing the acquired employment information to identify a work environment suitable for persons with disabilities, information provision means for distributing the identified work environment information to a user terminal, communication means for connecting the user with employees with disabilities within the company, emotion recognition means for analyzing the user's emotional state in real time, and environment adjustment means for dynamically adjusting the environment settings based on the emotional state. This makes it possible for persons with disabilities to adaptively improve their work environment based on their individual emotional state.

[0747] "Employment information for people with disabilities" refers to information about job details, working conditions, and work environments provided for people with disabilities to use in the labor market.

[0748] "Data collection means" refers to a device or technology that automatically collects necessary information and prepares it for storage or analysis.

[0749] "Data analysis tools" are technologies used to process collected information and to make understandings and judgments according to specific purposes.

[0750] "Information provision means" refers to technology or equipment for presenting necessary information to users in an appropriate format.

[0751] "Means of communication" are means of exchanging information between multiple entities located in different places.

[0752] "Emotion recognition means" refers to technology that detects a user's emotional state and applies that information.

[0753] "Environmental adjustment means" refers to technologies that dynamically change the physical or digital environment based on the user's state or needs.

[0754] This invention provides a system to help people with disabilities adapt to their work environment. The system primarily utilizes the following hardware and software. The server, as a data collection means, acquires employment information for people with disabilities from multiple information sources. This information includes the company's internal environment and job descriptions. As a data analysis means, the server analyzes this information to identify a suitable work environment for people with disabilities. The analysis uses an emotion engine to apply algorithms based on the collected data.

[0755] The terminal allows users to access job information through a user interface. Furthermore, it is equipped with emotion recognition capabilities to analyze the user's emotional state in real time. The emotional data obtained from this analysis is sent to a server and used to dynamically adjust job information and environment settings.

[0756] Users can input their profile information and job-seeking conditions using the device to receive suggestions for the most suitable work environment. They can also interact with employees with disabilities within companies using communication tools, gaining information about their actual work experiences. If a user expresses anxiety, the device will adjust the work environment by playing music or visualizing information.

[0757] As a concrete example, consider a case where a wheelchair user is engaged in manufacturing work at a factory. This invention uses sensors to play relaxing music and adjust lighting when the user feels anxious, thereby making the work easier. In this way, the aim is to support the user in adapting well to their work on-site.

[0758] Using a generative AI model, it is possible to generate suggestions in real time that are tailored to the user's state. An example of such a prompt would be, "Please describe the specific working methods for a factory robot that adjusts the environment based on the emotional data of disabled workers so that they can work safely on the production line." Using this prompt, the AI ​​can provide real-time suggestions for adjusting the work environment to suit the user's situation.

[0759] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0760] Step 1:

[0761] The server periodically acquires job information and internal environment data for people with disabilities provided by companies using data collection methods. The inputs here are internal environment and job information, and the output is a database that stores this information in preparation for subsequent analysis.

[0762] Step 2:

[0763] The server uses data analysis tools to identify appropriate work environments based on collected information and the profile information of individuals with disabilities. This process utilizes an emotion engine to analyze collected data and a matching algorithm to estimate the optimal work environment. The inputs are profile information and job information, and the output is the optimal job suggestion.

[0764] Step 3:

[0765] The user enters their job search criteria and profile information using the terminal's user interface. At this stage, the input is the user's job search criteria and profile information, and the output is the user data sent to the server.

[0766] Step 4:

[0767] The device uses emotion recognition to analyze the user's emotional state in real time. It acquires emotional data from an emotion sensor and sends it to the server based on the analysis results. The input is the user's real-time emotional data, and the output is a report of the emotional state to the server.

[0768] Step 5:

[0769] Based on the received emotional state, the server uses a generative AI model to generate appropriate job information and environment settings suggestions for the user. The input in this process is emotional data and analytical data, and the output is environment adjustment and job information suggestions.

[0770] Step 6:

[0771] Users access suggested information using a terminal, select job information as needed, and interact with disabled employees within the company via communication methods. The input is the suggested job information, and the output is the selected job information and the results of the interaction.

[0772] Step 7:

[0773] The device dynamically adjusts the environment based on the user's emotional state. For example, if it detects anxiety, it might play relaxing music or adjust the lighting. The input is the user's current emotional state, and the output is the adjusted physical or digital environment.

[0774] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0775] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0776] 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 this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0777] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0778] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0779] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0780] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0781] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0782] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0783] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0784] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0785] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0786] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0787] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0788] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0789] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0790] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0791] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0792] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0793] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0794] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0795] The following is further disclosed regarding the embodiments described above.

[0796] (Claim 1)

[0797] A data collection method for obtaining employment information for people with disabilities,

[0798] A data analysis tool that analyzes acquired employment information to identify a suitable work environment for people with disabilities,

[0799] An information provision means for distributing identified work environment information to user terminals,

[0800] A means of communication that connects users with employees with disabilities within a company,

[0801] A system that includes this.

[0802] (Claim 2)

[0803] The system according to claim 1, comprising an algorithm for matching profile information of persons with disabilities with job information of companies.

[0804] (Claim 3)

[0805] The system according to claim 1, comprising display means for visualizing a company's internal environment information and job information through a user interface.

[0806] "Example 1"

[0807] (Claim 1)

[0808] A data collection method that acquires employment information and internal environment information from companies and stores it in a database,

[0809] The acquired information is preprocessed by means of imputing missing values ​​and scaling,

[0810] A data analysis method that uses an AI algorithm to analyze pre-processed information and identify a suitable work environment for people with disabilities,

[0811] An information provision method that converts identified work environment information into a user-friendly format and delivers it to the user's terminal,

[0812] A display means that displays the details of a company's job through a user interface visualized on a terminal,

[0813] A communication method that allows users to converse with company employees in real time,

[0814] A system that includes this.

[0815] (Claim 2)

[0816] The system according to claim 1, comprising an interface for inputting profile information of persons with disabilities, wherein an algorithm performs matching based on the provided job information.

[0817] (Claim 3)

[0818] The system according to claim 1, further comprising a chat function to allow users to view detailed information about companies and to facilitate communication with selected companies.

[0819] "Application Example 1"

[0820] (Claim 1)

[0821] A data collection method for obtaining job information for people with disabilities,

[0822] A data analysis method that analyzes acquired work information to identify a work environment suitable for people with disabilities,

[0823] An information provision means for distributing identified work environment information to the user terminal,

[0824] A means of communication connecting users and disabled employees within the workplace,

[0825] An optimization method that integrates work information from different workplaces and presents optimized options based on the user's disability characteristics,

[0826] A system that includes this.

[0827] (Claim 2)

[0828] The system according to claim 1, comprising a calculation means for matching personal attribute information of persons with disabilities with work information of the workplace.

[0829] (Claim 3)

[0830] The system according to claim 1, comprising a device that displays internal environmental information and operational information of a workplace using visualization technology.

[0831] "Example 2 of combining an emotion engine"

[0832] (Claim 1)

[0833] Information gathering methods for obtaining job information for people with disabilities,

[0834] An information analysis method that analyzes acquired job information and identifies the optimal work environment for people with disabilities based on sentiment analysis,

[0835] An information supply means that delivers identified work environment information to user terminals,

[0836] An emotion recognition means that grasps the user's emotional state in real time and displays information accordingly,

[0837] A means of communication connecting users and employees with disabilities within a company,

[0838] A system that includes this.

[0839] (Claim 2)

[0840] The system according to claim 1, comprising a calculation means for matching profile data of persons with disabilities with business data of a company.

[0841] (Claim 3)

[0842] The system according to claim 1, comprising display means for visualizing a company's internal environment data and job data through a user operation screen.

[0843] "Application example 2 of combining emotional engines"

[0844] (Claim 1)

[0845] A data collection method for obtaining employment information for people with disabilities,

[0846] A data analysis tool that analyzes acquired employment information to identify a suitable work environment for people with disabilities,

[0847] An information provision means for distributing identified work environment information to user terminals,

[0848] A means of communication that connects users with employees with disabilities within a company,

[0849] A means of recognizing emotions that analyzes the user's emotional state in real time,

[0850] An environmental adjustment means that dynamically adjusts environmental settings based on emotional state,

[0851] A system that includes this.

[0852] (Claim 2)

[0853] The system according to claim 1, comprising an algorithm for matching profile information of persons with disabilities with job information of companies.

[0854] (Claim 3)

[0855] The system according to claim 1, comprising a display means for visualizing internal company environment information and job information through a user interface, and providing adaptive interaction according to emotional state. [Explanation of symbols]

[0856] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. Data collection methods for obtaining employment information, A data analysis tool that analyzes acquired employment information to identify a suitable work environment for the user, An information provision means for distributing identified work environment information to user terminals, A means of communication that connects users and employees within a company, A system that includes this.

2. The system according to claim 1, comprising an algorithm for matching user profile information with company job information.

3. The system according to claim 1, comprising display means for visualizing a company's internal environment information and job information through a user interface.

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