system

Abstract

We provide the system. [Solution] A means for inputting user characteristic information and analyzing said characteristic information, A means of organizing multiple simple tasks collected from within a company and storing the specific details of each task in a database, A means for selecting the simple task based on the user's characteristics and presenting the task in a format suitable for the user, A means for receiving the results of the task performed by the user, automatically verifying those results, and instructing corrections as necessary, 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, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In modern society, expanding employment opportunities for the disabled is an urgent issue. However, companies do not have a sufficient system for taking job considerations according to the characteristics of the disabled, and as a result, employment tends to be limited. In particular, for the mildly intellectually disabled, there is a lack of effective support means to improve the quality and satisfaction of labor while taking their characteristics into consideration. Therefore, there is a demand for a system that can appropriately support the disabled and efficiently perform tasks while maximizing their abilities.

Means for Solving the Problems

[0005] This invention solves the above problems by providing a system that has means for inputting and analyzing characteristic information of persons with disabilities. It also employs means for organizing multiple simple tasks within a company and storing them in a database. Furthermore, it selects appropriate tasks based on the characteristics of persons with disabilities and presents them in an easily understandable format. This allows for the assignment of tasks suited to the individual abilities of persons with disabilities, enabling them to perform their work efficiently. In addition, by incorporating means for automatically verifying the results of tasks performed by persons with disabilities and issuing correction instructions if necessary, the accuracy of the work can be improved. Furthermore, by presenting visually simplified work procedures, it enables easier execution of tasks. This provides a system that can effectively expand employment opportunities for persons with disabilities while contributing to increased productivity in companies.

[0006] "Characteristic information" refers to data that shows the individual characteristics of a person with a disability, such as their comprehension, communication skills, and concentration.

[0007] "Simple tasks" refer to repetitive work activities within a company that do not require complex judgment, such as data entry and file organization.

[0008] A "database" is an information system for efficiently storing, managing, and retrieving entered data.

[0009] A "task" is a unit of work that is individually defined in order to achieve a specific goal.

[0010] "Verification" is the process of checking whether the work was performed correctly and issuing instructions for correction as needed.

[0011] "Visually simplified procedures" refer to instructions that are presented in a visually easy-to-understand format, such as through diagrams or step-by-step instructions. [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, the labeled 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, the labeled 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, the labeled 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, the labeled 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] The system for implementing the present invention consists of three main components: a server, a terminal, and a user. This system is designed to support the employment of persons with disabilities and provides processes to support appropriate work tailored to the characteristics of persons with disabilities.

[0034] The user first enters information about their disability characteristics into a terminal. This information includes comprehension level, work speed, and attention span. The entered information is sent from the terminal to a server, which analyzes it and stores it in a database.

[0035] Next, multiple simple tasks collected from the company via terminals are transferred to a server. The server organizes these tasks and stores characteristic information about each task in a database. Examples of such tasks include data entry that requires repetitive input and file organization that follows a set procedure.

[0036] The server assigns tasks to individuals with disabilities based on their specific characteristics. For example, a person with a disability who excels at handling repetitive patterns might be assigned a data management task in a particular format. Task assignment is performed automatically by the server's algorithm.

[0037] Assigned tasks are presented to the user via the terminal as visually simplified instructions. This allows the user to efficiently understand and perform the work. The simplified instructions aid understanding of the task through visual guidance and step-by-step instructions.

[0038] Once the user completes the task, the results are sent from the terminal to the server. The server uses an AI model to verify the results and confirm their accuracy. If inaccurate data is detected, the user is instructed to correct it.

[0039] These processes enable people with disabilities to receive support tailored to their individual characteristics, and allow companies to effectively employ people with disabilities and improve productivity. Specific application examples include data entry when registering new product information in a database and document filing. In both of these tasks, people with disabilities can understand and perform the work in a way that suits their individual characteristics.

[0040] The following describes the processing flow.

[0041] Step 1:

[0042] Users input information about their disability characteristics into a terminal. This includes comprehension level, work speed, and communication skills. The terminal collects the entered data and sends it to a server.

[0043] Step 2:

[0044] The server analyzes the received characteristic information and generates an appropriate profile. This profile takes into account the abilities and characteristics of the person with a disability and is stored in a searchable database.

[0045] Step 3:

[0046] Companies use terminals to submit simple tasks required by various departments within the company to a server. The terminals transfer detailed information about the tasks, such as priority and deadlines, to the server.

[0047] Step 4:

[0048] The server analyzes the received work list and registers the details of each task in the database. Furthermore, it matches each task with the disability profile and selects the appropriate task.

[0049] Step 5:

[0050] The server converts the assigned tasks into visually simplified procedures. This conversion is tailored to the disability's level of understanding and uses visual information and diagrams to create an easy-to-understand format.

[0051] Step 6:

[0052] The terminal displays visualized instructions to the user. The user then uses this information to complete the task.

[0053] Step 7:

[0054] Once the user completes a task, the terminal reports the results to the server. The report includes data on the task's completion status and execution results.

[0055] Step 8:

[0056] The server uses an AI model to verify the received work results and check the accuracy and completeness of the data. If there are any inaccuracies, it will present the user with the items that need correction.

[0057] Step 9:

[0058] The user receives correction instructions, makes the necessary corrections, and then resubmits the work results to the server for verification. This improves the overall accuracy of the work.

[0059] (Example 1)

[0060] 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."

[0061] To expand employment opportunities for people with disabilities, a system is needed that provides them with appropriate tasks tailored to their characteristics and abilities, enabling them to perform their work efficiently. However, traditional methods make it difficult to accurately understand the characteristics of people with disabilities and automatically select and apply tasks based on those characteristics. Furthermore, manual verification of work results is time-consuming, hindering efficient support.

[0062] 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.

[0063] In this invention, the server includes means for inputting characteristic information of persons with disabilities via a terminal, analyzing the characteristic information and storing it in a database; means for organizing multiple simple tasks collected from the organization and maintaining characteristic information for each task in the database; means for automatically selecting the simple tasks using an AI model based on the characteristics of persons with disabilities and presenting the tasks in a format suitable for the persons with disabilities; and means for receiving the results of task execution by the persons with disabilities, automatically verifying them using the AI ​​model, and instructing corrections as necessary. This enables the assignment of tasks suitable for persons with disabilities and rapid verification of the results.

[0064] "Information on the characteristics of persons with disabilities" refers to information about the individual abilities and characteristics of persons with disabilities, such as their comprehension level, work speed, and attention span.

[0065] "Analysis" is the process of understanding characteristics and trends by classifying, comparing, and evaluating data.

[0066] A "database" is an information system that organizes and stores information, allowing it to be efficiently retrieved as needed.

[0067] An "organization" is a company, association, or group formed to achieve a specific purpose.

[0068] "Simple tasks" are defined as work that does not require complex judgment and is performed according to prescribed procedures.

[0069] A "generative AI model" is an artificial intelligence system that learns from large amounts of data and makes appropriate predictions and judgments about new data.

[0070] "Automatic" means that a device or system performs tasks or makes decisions independently, without human intervention.

[0071] A "task" is a specific job or set of tasks that needs to be performed.

[0072] A "terminal" is an electronic device used by a user to input, output, or process information.

[0073] "Verification" is the process of checking whether results and information are accurate and identifying problems as necessary.

[0074] "Correction" refers to correcting errors or deficiencies and restoring the product to its correct state.

[0075] One embodiment of this invention is a system that provides work adaptation based on the characteristics of persons with disabilities. This system operates through the cooperation of a server, terminals, and users. The roles and specific processes of each component are described below.

[0076] First, the user uses a terminal to input information about the person's disability characteristics. This information includes comprehension level, work speed, and attention span. The terminal securely transmits the entered information to a server. This process typically involves hardware such as a personal computer or tablet, and user interface software for inputting the information.

[0077] The server analyzes the received characteristic information and stores it in a database. The database stores characteristic information for all individuals with disabilities, allowing for quick retrieval when needed. The server also organizes simple tasks submitted by the organization and registers them in the database along with their characteristic information. At this stage, data analysis is performed using Python scripts or similar tools.

[0078] A server equipped with a generative AI model selects suitable simple tasks based on the characteristics of individuals with disabilities. The model assigns tasks using specific prompt statements. For example, the AI ​​model might be given a prompt statement such as, "Assign the most suitable user to task type 001." This prompt statement enables optimal task assignment.

[0079] The selected task is presented to the user via the terminal and displayed as a visually simplified work procedure through the user interface. This allows the user to perform the task under instructions in a format that is easiest for people with disabilities to understand.

[0080] Finally, once the user completes the task, the results are sent from the terminal to the server and automatically verified by the AI ​​model. This verification process provides correction instructions as needed.

[0081] This system allows people with disabilities to utilize their abilities in work suited to their characteristics, and enables organizations to achieve efficient and effective employment management.

[0082] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0083] Step 1:

[0084] Users input information about their disability characteristics via a terminal. Specifically, they use the user interface on the terminal to input information such as comprehension level, work speed, and attention span using a keyboard or touchscreen. The input information is prepared as a dataset and transmitted to the server via a secure communication protocol.

[0085] Step 2:

[0086] The server receives characteristic information sent from the terminal and stores it in a database. Python scripts are often used to analyze the received data and check for anomalies. This analyzed data is structured for future searching and processing and stored in the database.

[0087] Step 3:

[0088] Organizations use terminals to input information about light tasks and send it to a server. Specifically, they input job details, including standard procedures and required skills for tasks, from the terminal, and the server stores each task's information in a database.

[0089] Step 4:

[0090] The server uses a generated AI model based on stored characteristic information to automatically assign harmonized tasks. Using the prompt "Assign the best user for task type 001," the AI ​​model selects and assigns the task to the most suitable person with a disability. As a result, a set of assigned tasks is generated.

[0091] Step 5:

[0092] The device displays the tasks assigned to the person with a disability on its screen. The user interface presents task details in a visually simplified manner to help the person with a disability easily understand and perform the tasks. Specifically, icons and step-by-step guides are displayed.

[0093] Step 6:

[0094] The user performs the task according to the instructions displayed on the terminal. Once the task is completed, the user reports the results to the server via the terminal. The result data, including metrics such as completion time and accuracy, is transferred to the server.

[0095] Step 7:

[0096] The server uses a generating AI model to verify the received work results. The AI ​​model automatically evaluates the results and verifies their accuracy. If inaccurate, detailed feedback on areas requiring correction is provided again, and instructions are given to the user via their terminal. This establishes an appropriate feedback system and improves the quality of work.

[0097] (Application Example 1)

[0098] 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."

[0099] There is a need for systems that efficiently support the work of people with disabilities in a way that is tailored to their individual characteristics. It is also important to create an environment where people with disabilities can work in collaboration with consumer-grade equipment and utilize their own strengths. However, current systems lack sufficient mechanisms for automatically assigning appropriate tasks and providing work support based on characteristic information, making it difficult to contribute to improving corporate productivity.

[0100] 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.

[0101] In this invention, the server includes means for inputting and analyzing characteristic information of persons with disabilities; means for organizing multiple simple tasks collected from the work area and storing the specific details of each task in a database; and means for selecting the simple tasks based on the characteristics of persons with disabilities and presenting the tasks in a format suitable for persons with disabilities. As a result, persons with disabilities can more easily perform tasks optimized based on their own characteristics and can efficiently carry out their work in cooperation with consumer electronics.

[0102] "Information on the characteristics of persons with disabilities" refers to information that indicates the individual characteristics of persons with disabilities, such as their comprehension ability, work speed, and level of attention.

[0103] "Multiple simple tasks collected from the work area" refers to repetitive and standardized tasks performed in businesses and homes.

[0104] "Means of presenting tasks" refers to a system that presents tasks selected based on the characteristics of people with disabilities in an appropriate format.

[0105] "Means for automatically verifying execution results" refers to a process that uses AI models or similar tools to determine the accuracy of the results of tasks performed by people with disabilities.

[0106] "Means of collaborative work assistance using consumer-grade equipment" refers to work support systems in which general-purpose equipment such as robots used at home or in the workplace compensates for aspects that are difficult for people with disabilities.

[0107] The system for implementing this invention mainly consists of three main components: a server, a terminal, and a user. A specific example using this system is shown below.

[0108] The server first receives and analyzes information about the characteristics of individuals with disabilities. This information is based on comprehension, work speed, and attention span, and is entered by the user via a terminal. The server stores the received information in a database, then organizes multiple simple tasks collected from the work area and saves the specific details of each task in the database. This process uses the Flask platform developed in Python, and PostgreSQL is used as the database.

[0109] The user terminal not only transmits the entered characteristic information to the server, but also plays a role in visually displaying the tasks sent from the server. This is achieved through a UI using JavaScript (registered trademark), and the visually simplified information is presented in a format suitable for people with disabilities.

[0110] Once the user completes the task, the results are sent back to the server via the terminal. The server automatically verifies these results using an AI model and instructs corrections as needed. In this process, the AI ​​model used is TENSORFLOW®, which evaluates the accuracy of the execution results.

[0111] Furthermore, the system works in conjunction with consumer electronics (such as robots) to enable people with disabilities to receive support tailored to their specific needs. Robots can assist with specific tasks in homes and workplaces, allowing people with disabilities to perform their duties in a way that maximizes their strengths.

[0112] As a concrete example, when inputting information about the characteristics of a person with a disability, a prompt such as "Explain how the AI ​​system installed in the household support robot can automatically assign appropriate tasks (e.g., sorting kitchen items) based on the characteristics of a specific user and work collaboratively" is used. Based on this prompt, the generated AI model performs optimal task assignment and enables collaborative work.

[0113] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0114] Step 1:

[0115] The user inputs their characteristic information via a terminal. This input includes comprehension, work speed, and attention span. The terminal sends this information as input to the server. The server stores the received information in a database and retains it as data necessary for subsequent processing based on the user's characteristics.

[0116] Step 2:

[0117] The server organizes information from simple tasks collected from businesses and households. This information consists of repetitive tasks such as data entry and document organization, and the server registers the specific details of these tasks in a database. This database serves as the foundational data for later task assignments.

[0118] Step 3:

[0119] The server uses a generated AI model to select the optimal task based on user characteristic information and work information in the database. This task selection process uses prompts, allowing the AI ​​model to automatically determine tasks suitable for users with disabilities. The selected tasks are presented with user characteristics in mind, and therefore, ease of execution is paramount.

[0120] Step 4:

[0121] The terminal visually presents tasks sent from the server to the user. The presented information consists of simplified procedures tailored to the user's characteristics, including visual guides and step-by-step instructions to aid understanding. This allows the user to easily grasp the task content and begin working.

[0122] Step 5:

[0123] When a user completes a task, the results are sent from the terminal to the server. The server automatically verifies the received results based on the generating AI model and evaluates the accuracy of the results. In this evaluation step, the input data is compared with accurate baseline data, and if there is any inaccuracy, the server sends correction instructions to the terminal.

[0124] Step 6:

[0125] The server will work in conjunction with consumer electronics to provide further support to people with disabilities. Specifically, it envisions scenarios where devices such as robots assist users, providing support for difficult parts of task completion. Through this collaborative work, users can leverage their own strengths while receiving assistance to successfully complete tasks.

[0126] 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.

[0127] This invention aims to improve work efficiency and user comfort in an employment support system for people with disabilities by incorporating an emotion engine. This system consists of a server, terminals, and users, and the addition of the emotion engine enhances the functionality of each component.

[0128] The user first inputs information about the characteristics of the person with a disability through a terminal. This information includes characteristics such as comprehension, work speed, and emotional response. The terminal sends this information to a server, which analyzes it and stores it in a database.

[0129] Companies use terminals to submit lists of simple internal tasks to a server. These lists include task details, importance, and deadlines, which the server then organizes and stores in a database.

[0130] The server matches the characteristics of the person with a disability with the work content, selects an appropriate task, and presents it to the user via the terminal. A key feature here is that the emotion engine analyzes the user's real-time emotional state and adaptively adjusts the task presentation method. For example, if the user is feeling stressed, the complexity of the task is reduced and converted into simple visual instructions.

[0131] Users perform tasks and report the results to the server via their terminal. The server uses an AI model to verify the results and instructs corrections if any inaccuracies are found. Furthermore, an emotion engine monitors the user's emotional changes and generates alerts if anomalies are detected, prompting improvements to the work environment.

[0132] As a concrete example, the emotion engine analyzes the user's camera footage and audio data to identify emotions such as joy, anger, and anxiety in real time. Based on this information, it dynamically adapts by presenting tasks when the user is relaxed and recommending rest when they are stressed.

[0133] In this way, this system provides an optimal work environment for people with disabilities, maximizing their work performance capabilities while improving productivity within companies. This is expected to improve both the quality and quantity of employment, leading to sustainable employment support.

[0134] The following describes the processing flow.

[0135] Step 1:

[0136] The user inputs information about the individual's disability characteristics into the terminal. This information includes profiles of comprehension, work speed, and emotional response. The terminal then transmits the entered information to the server.

[0137] Step 2:

[0138] The server analyzes the characteristic information received from the terminal and generates a profile based on the characteristics of the person with a disability. These profiles are stored in a database and used for subsequent task assignment.

[0139] Step 3:

[0140] Companies send a list of simple tasks they want to perform via their terminals to a server. This list includes the specific tasks, their importance, and deadlines. The server registers this information in a database.

[0141] Step 4:

[0142] The server matches the profile of the person with a disability with the received list of simple tasks and performs a process to select appropriate tasks. The selected tasks are presented in a way that suits the user's characteristics.

[0143] Step 5:

[0144] The emotion engine uses the device to recognize the user's real-time emotional state. For this purpose, the user's camera video and audio data are analyzed. Based on these emotions, the way tasks are presented is adjusted.

[0145] Step 6:

[0146] The device presents the user with visually simplified instructions adjusted by an emotion engine. For example, if the user is feeling stressed, it uses simplified displays and softer colors.

[0147] Step 7:

[0148] The user performs the task by following instructions provided via the terminal. The results are reported from the terminal to the server.

[0149] Step 8:

[0150] The server verifies the reported task results using an AI model to confirm their accuracy. If necessary, it returns specific correction instructions to the user via the terminal.

[0151] Step 9:

[0152] The emotion engine continuously monitors the user's emotional state during work and generates alerts if significant emotional anomalies are detected. This information is communicated to the user and company administrators to encourage improvements to the work environment.

[0153] (Example 2)

[0154] 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".

[0155] In employing people with disabilities, it is essential to optimize the process of assigning and executing tasks, taking into full consideration their characteristics and emotional states. Without this optimization, the abilities of the individuals with disabilities may not be fully utilized, and employers may experience decreased productivity. Furthermore, considering that emotional states directly impact work efficiency and effectiveness, there is a need for real-time sentiment analysis and adaptive task presentation.

[0156] 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.

[0157] In this invention, the server includes a device for inputting and analyzing information based on the characteristics of persons with disabilities, a device for organizing multiple tasks collected from the organization and storing the specific details of each task in a data storage device, and a device for analyzing emotional states in real time and dynamically adapting the method of presenting tasks. This makes it possible to assign optimal tasks according to the characteristics of persons with disabilities and to adaptively present tasks according to their emotional states.

[0158] A "person with a disability" is an individual who has physical, intellectual, or mental limitations and requires special consideration or support.

[0159] "Characteristic information" refers to data about the individual abilities and characteristics of people with disabilities, such as comprehension, work speed, and emotional response.

[0160] An "organization" is a group of people, such as a company or a group of businesses, that carry out business operations, and is the entity that manages the business processes within that group.

[0161] "Business operations" refers to the collective term for specific activities and tasks performed by members within an organization.

[0162] A "data storage device" refers to a system or equipment for safely and efficiently storing information and data.

[0163] "Emotional state" refers to the emotional reactions or psychological conditions that an individual exhibits in specific situations, such as joy, anger, or stress.

[0164] "Analysis" is the process of breaking down complex information or data and examining its constituent elements in detail.

[0165] "Job assignment" refers to the act of providing an individual or group with specific job duties and instructions on how to carry them out.

[0166] This invention is a system that supports the employment of people with disabilities, and the program operates based on information input and analysis from a server, terminals, and users. The server has a data analysis engine that processes characteristic information of people with disabilities input from users via terminals and stores that data in a data storage device using a database management system (DBMS). This uses general database software and an AI analysis module.

[0167] Users input characteristic information about individuals with disabilities, such as their comprehension level, work speed, and emotional responses, through a terminal. The terminal sends this information to a server, which then uses that information to select the most suitable tasks for the individuals with disabilities.

[0168] The server uses a generative AI model to match a list of tasks collected from within the organization with the characteristics of individuals with disabilities, thereby matching them with the most suitable tasks. The task list is entered from a terminal and analyzed and organized by the server. In particular, the emotion engine analyzes the user's real-time emotional state and dynamically adjusts how tasks are presented. For example, the emotion engine analyzes the user's facial expressions and voice data obtained through the camera and microphone to determine whether the user is relaxed or stressed.

[0169] For example, if the user is relaxed, the server will present normal tasks, but if it detects that the user is stressed, the server will simplify the tasks and provide visually simplified instructions. Another example of a prompt message would be: "Based on the characteristics of the person with a disability and the company's operations, please suggest the most suitable tasks. The current emotional state is stressed."

[0170] This system not only optimizes task assignments for users but also enables task presentations that take into account their real-time emotional state, thereby supporting the efficient and comfortable work performance of people with disabilities.

[0171] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0172] Step 1:

[0173] Users input characteristic information about individuals with disabilities, such as their comprehension level, work speed, and emotional responses, through a terminal. The terminal converts this information into the correct format and sends it to the server. This characteristic information is important because it is used later for job matching and sentiment analysis, and the server supplies the received information to the data analysis engine.

[0174] Step 2:

[0175] The server analyzes the characteristic information submitted by the user based on its data analysis engine. During this process, the data is organized and classified based on the characteristics of each individual with a disability. The analysis results are stored in a data storage device via a database management system (DBMS) and serve as reference data for subsequent task selection.

[0176] Step 3:

[0177] Companies use terminals to input a list of tasks within their organization and send it to a server. The list includes details of the tasks, their importance, and deadlines. The terminals format the task lists appropriately and transfer them to the server. The server stores the received task lists in a database and uses them in the task matching process.

[0178] Step 4:

[0179] The server uses a generated AI model to compare disability characteristics information stored in the database with a list of tasks. In this process, the AI ​​model compares characteristics with task requirements and selects the most suitable task. The selected task is sent from the server to the terminal and presented to the user.

[0180] Step 5:

[0181] The server activates the emotion engine to analyze real-time emotional state data obtained from the terminal. It analyzes video and audio data acquired by the user via the terminal's camera and microphone to identify emotions such as joy, anger, and stress. This emotional state data is used to adjust the way tasks are presented.

[0182] Step 6:

[0183] Based on the analysis results of the emotion engine, the server determines how to present tasks according to the user's emotional state. For example, if the user is feeling stressed, the server simplifies the task content and displays it on the terminal in a visually easy-to-understand format. By tailoring the display method to the user's emotions, the efficiency of task execution is improved.

[0184] Step 7:

[0185] The user uses a terminal to perform the assigned tasks and reports the results to the server upon completion. The terminal formats the user's input and sends it to the server. The server reviews the report using a generative AI model and issues correction instructions if the report is inaccurate.

[0186] Step 8:

[0187] The server continuously monitors changes in the user's emotions using an emotion engine. If an abnormal emotional state is detected, it generates an alert and provides instructions for improving the work environment. This continuous monitoring aims to enhance user comfort and work efficiency.

[0188] (Application Example 2)

[0189] 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".

[0190] A major challenge in modern work environments is the lack of systems that enable people with disabilities to efficiently perform tasks suited to their individual characteristics. Furthermore, there are insufficient methods to reduce mental stress during work and provide a comfortable working environment. Additionally, there is a need for a system that can monitor users' emotional changes in real time during work and adapt accordingly.

[0191] 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.

[0192] In this invention, the server includes means for acquiring and analyzing attribute information of persons with disabilities; means for collecting work sets from within the organization and storing the specific details of each work in an information storage location; means for selecting the work based on the attributes of persons with disabilities and presenting the tasks in a format suitable for those persons with disabilities; and means for analyzing the user's emotional state in real time using an emotion analysis device and dynamically optimizing the task presentation method. This makes it possible not only for persons with disabilities to select the most suitable work, but also to provide a consistently comfortable working environment.

[0193] "Attribute information of persons with disabilities" refers to data that includes characteristics such as the comprehension level, work speed, and emotional response of individuals with disabilities.

[0194] A "work set" refers to a collection of multiple simple tasks or routines required within a company or organization.

[0195] An "information repository" is a database or recording medium used to store specific details of each task, attribute information of people with disabilities, and so on.

[0196] "Task presentation methods" refer to techniques for communicating tasks and work content to people with disabilities in the most appropriate format.

[0197] An "emotion analysis device" is a device or software that analyzes a user's emotional state in real time and makes appropriate changes to the work environment or proposed tasks.

[0198] This invention is a system that allows people with disabilities to select the most suitable tasks based on their individual characteristics and improve their comfort while working.

[0199] The server first receives attribute information of individuals with disabilities and analyzes it. This includes data such as the individual's comprehension level, work speed, and emotional responses, which are entered via a terminal. Next, the server organizes the sets of tasks collected from within the company and stores the specific details of each task in an information repository. This allows for the selection of tasks suitable for each individual with a disability.

[0200] An emotion analysis device is used to analyze the user's emotional state in real time. This analysis utilizes the user's camera video and audio data, and an emotion analysis AI determines the user's emotions. If the system determines that the user is experiencing stress, it dynamically optimizes the task presentation method, adjusting the complexity of the task or providing visually simpler instructions.

[0201] Furthermore, an emotion analysis device monitors changes in the user's emotions during work and generates alerts to prompt appropriate responses if an anomaly is detected. As part of this process, a generative AI model is used to perform real-time emotion assessment and adaptation.

[0202] As a concrete example, the server sends a prompt to the emotion analysis AI saying, "Evaluate my stress level based on what I'm saying now and suggest advice that will help me relax," which then generates appropriate feedback. This reduces the user's mental burden and improves task efficiency.

[0203] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0204] Step 1:

[0205] The terminal inputs attribute information of the user, who is a person with a disability. This input information includes comprehension level, work speed, and emotional response. This data is sent to the server, which stores this information in a database. Based on the input attribute information, the server builds the basic data for selecting the most suitable task for the user.

[0206] Step 2:

[0207] The server organizes task sets collected from within the company. It stores information such as the specific content, importance, and deadline for each task in a database. This allows for matching user attribute information with the task set data, preparing the system for selecting appropriate tasks.

[0208] Step 3:

[0209] The server uses a generative AI model to match user attribute information with task sets. The input consists of attribute and task information from the database, and the output is a list of tasks suitable for the user. These tasks are then presented to the user's terminal in a format tailored to them, prompting them to complete the tasks.

[0210] Step 4:

[0211] Using an emotion analysis device, the server analyzes the user's emotional state in real time. Receiving camera video and audio data as input, the emotion analysis AI identifies emotions such as joy, anger, and anxiety. If the user is experiencing stress, dynamic adjustments are made. Specifically, this might involve lowering the difficulty of the task or providing visually clearer instructions.

[0212] Step 5:

[0213] Users complete the assigned tasks and report their results via their devices. The server receives these results and automatically evaluates them using a generative AI model. If there are any inaccuracies, the server generates correction instructions to help improve future task assignments.

[0214] Step 6:

[0215] The server continuously uses an emotion analysis device to monitor the user's emotional changes. Based on the analysis results, it generates an alert when an anomaly is detected and provides appropriate feedback to the user. Specific actions include playing relaxing music or suggesting a break.

[0216] 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.

[0217] 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.

[0218] 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.

[0219] [Second Embodiment]

[0220] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0221] 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.

[0222] 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).

[0223] 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.

[0224] 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.

[0225] 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).

[0226] 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.

[0227] 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.

[0228] 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.

[0229] 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.

[0230] 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.

[0231] 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".

[0232] The system for implementing the present invention consists of three main components: a server, a terminal, and a user. This system is designed to support the employment of persons with disabilities and provides processes to support appropriate work tailored to the characteristics of persons with disabilities.

[0233] The user first enters information about their disability characteristics into a terminal. This information includes comprehension level, work speed, and attention span. The entered information is sent from the terminal to a server, which analyzes it and stores it in a database.

[0234] Next, multiple simple tasks collected from the company via terminals are transferred to a server. The server organizes these tasks and stores characteristic information about each task in a database. Examples of such tasks include data entry that requires repetitive input and file organization that follows a set procedure.

[0235] The server assigns tasks to individuals with disabilities based on their specific characteristics. For example, a person with a disability who excels at handling repetitive patterns might be assigned a data management task in a particular format. Task assignment is performed automatically by the server's algorithm.

[0236] Assigned tasks are presented to the user via the terminal as visually simplified instructions. This allows the user to efficiently understand and perform the work. The simplified instructions aid understanding of the task through visual guidance and step-by-step instructions.

[0237] Once the user completes the task, the results are sent from the terminal to the server. The server uses an AI model to verify the results and confirm their accuracy. If inaccurate data is detected, the user is instructed to correct it.

[0238] These processes enable people with disabilities to receive support tailored to their individual characteristics, and allow companies to effectively employ people with disabilities and improve productivity. Specific application examples include data entry when registering new product information in a database and document filing. In both of these tasks, people with disabilities can understand and perform the work in a way that suits their individual characteristics.

[0239] The following describes the processing flow.

[0240] Step 1:

[0241] Users input information about their disability characteristics into a terminal. This includes comprehension level, work speed, and communication skills. The terminal collects the entered data and sends it to a server.

[0242] Step 2:

[0243] The server analyzes the received characteristic information and generates an appropriate profile. This profile takes into account the abilities and characteristics of the person with a disability and is stored in a searchable database.

[0244] Step 3:

[0245] Companies use terminals to submit simple tasks required by various departments within the company to a server. The terminals transfer detailed information about the tasks, such as priority and deadlines, to the server.

[0246] Step 4:

[0247] The server analyzes the received work list and registers the details of each task in the database. Furthermore, it matches each task with the disability profile and selects the appropriate task.

[0248] Step 5:

[0249] The server converts the assigned tasks into visually simplified procedures. This conversion is tailored to the disability's level of understanding and uses visual information and diagrams to create an easy-to-understand format.

[0250] Step 6:

[0251] The terminal displays visualized instructions to the user. The user then uses this information to complete the task.

[0252] Step 7:

[0253] Once the user completes a task, the terminal reports the results to the server. The report includes data on the task's completion status and execution results.

[0254] Step 8:

[0255] The server uses an AI model to verify the received work results and check the accuracy and completeness of the data. If there are any inaccuracies, it will present the user with the items that need correction.

[0256] Step 9:

[0257] The user receives correction instructions, makes the necessary corrections, and then resubmits the work results to the server for verification. This improves the overall accuracy of the work.

[0258] (Example 1)

[0259] 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."

[0260] To expand employment opportunities for people with disabilities, a system is needed that provides them with appropriate tasks tailored to their characteristics and abilities, enabling them to perform their work efficiently. However, traditional methods make it difficult to accurately understand the characteristics of people with disabilities and automatically select and apply tasks based on those characteristics. Furthermore, manual verification of work results is time-consuming, hindering efficient support.

[0261] 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.

[0262] In this invention, the server includes means for inputting characteristic information of persons with disabilities via a terminal, analyzing the characteristic information and storing it in a database; means for organizing multiple simple tasks collected from the organization and maintaining characteristic information for each task in the database; means for automatically selecting the simple tasks using an AI model based on the characteristics of persons with disabilities and presenting the tasks in a format suitable for the persons with disabilities; and means for receiving the results of task execution by the persons with disabilities, automatically verifying them using the AI ​​model, and instructing corrections as necessary. This enables the assignment of tasks suitable for persons with disabilities and rapid verification of the results.

[0263] "Information on the characteristics of persons with disabilities" refers to information about the individual abilities and characteristics of persons with disabilities, such as their comprehension level, work speed, and attention span.

[0264] "Analysis" is the process of understanding characteristics and trends by classifying, comparing, and evaluating data.

[0265] A "database" is an information system that organizes and stores information, allowing it to be efficiently retrieved as needed.

[0266] An "organization" is a company, association, or group formed to achieve a specific purpose.

[0267] "Simple tasks" are defined as work that does not require complex judgment and is performed according to prescribed procedures.

[0268] A "generative AI model" is an artificial intelligence system that learns from large amounts of data and makes appropriate predictions and judgments about new data.

[0269] "Automatic" means that a device or system performs tasks or makes decisions independently, without human intervention.

[0270] A "task" is a specific job or set of tasks that needs to be performed.

[0271] A "terminal" is an electronic device used by a user to input, output, or process information.

[0272] "Verification" is the process of checking whether results and information are accurate and identifying problems as necessary.

[0273] "Correction" refers to correcting errors or deficiencies and restoring the product to its correct state.

[0274] One embodiment of this invention is a system that provides work adaptation based on the characteristics of persons with disabilities. This system operates through the cooperation of a server, terminals, and users. The roles and specific processes of each component are described below.

[0275] First, the user uses a terminal to input information about the person's disability characteristics. This information includes comprehension level, work speed, and attention span. The terminal securely transmits the entered information to a server. This process typically involves hardware such as a personal computer or tablet, and user interface software for inputting the information.

[0276] The server analyzes the received characteristic information and stores it in a database. The database stores characteristic information for all individuals with disabilities, allowing for quick retrieval when needed. The server also organizes simple tasks submitted by the organization and registers them in the database along with their characteristic information. At this stage, data analysis is performed using Python scripts or similar tools.

[0277] A server equipped with a generative AI model selects suitable simple tasks based on the characteristics of individuals with disabilities. The model assigns tasks using specific prompt statements. For example, the AI ​​model might be given a prompt statement such as, "Assign the most suitable user to task type 001." This prompt statement enables optimal task assignment.

[0278] The selected task is presented to the user via the terminal and displayed as a visually simplified work procedure through the user interface. As a result, the user can perform the work under instructions in a form that is most understandable to the disabled.

[0279] Finally, when the user completes the work, the result is sent from the terminal to the server and automatically verified by the AI model. Based on this result verification, correction instructions are given as necessary.

[0280] With this system, the disabled can demonstrate their abilities in tasks that suit their characteristics, and the organization can achieve efficient and effective employment management.

[0281] The flow of the specific process in Example 1 will be described using FIG. 11.

[0282] Step 1:

[0283] The user inputs the characteristic information of the disabled person using the terminal. Specifically, using the user interface on the terminal, information such as comprehension ability, work speed, and attention concentration is input via the keyboard or touch screen. The input information is prepared as a dataset and transmitted through a secure communication protocol to the server.

[0284] Step 2:

[0285] The server receives the characteristic information transmitted from the terminal and stores it in the database. To analyze the received data and check for outliers, Python scripts are often used. This analyzed data is structured for future search and processing and stored in the database.

[0286] Step 3:

[0287] Organizations use terminals to input information about light tasks and send it to a server. Specifically, they input job details, including standard procedures and required skills for tasks, from the terminal, and the server stores each task's information in a database.

[0288] Step 4:

[0289] The server uses a generated AI model based on stored characteristic information to automatically assign harmonized tasks. Using the prompt "Assign the best user for task type 001," the AI ​​model selects and assigns the task to the most suitable person with a disability. As a result, a set of assigned tasks is generated.

[0290] Step 5:

[0291] The device displays the tasks assigned to the person with a disability on its screen. The user interface presents task details in a visually simplified manner to help the person with a disability easily understand and perform the tasks. Specifically, icons and step-by-step guides are displayed.

[0292] Step 6:

[0293] The user performs the task according to the instructions displayed on the terminal. Once the task is completed, the user reports the results to the server via the terminal. The result data, including metrics such as completion time and accuracy, is transferred to the server.

[0294] Step 7:

[0295] The server uses a generating AI model to verify the received work results. The AI ​​model automatically evaluates the results and verifies their accuracy. If inaccurate, detailed feedback on areas requiring correction is provided again, and instructions are given to the user via their terminal. This establishes an appropriate feedback system and improves the quality of work.

[0296] (Application Example 1)

[0297] 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."

[0298] There is a need for systems that efficiently support the work of people with disabilities in a way that is tailored to their individual characteristics. It is also important to create an environment where people with disabilities can work in collaboration with consumer-grade equipment and utilize their own strengths. However, current systems lack sufficient mechanisms for automatically assigning appropriate tasks and providing work support based on characteristic information, making it difficult to contribute to improving corporate productivity.

[0299] 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.

[0300] In this invention, the server includes means for inputting and analyzing characteristic information of persons with disabilities; means for organizing multiple simple tasks collected from the work area and storing the specific details of each task in a database; and means for selecting the simple tasks based on the characteristics of persons with disabilities and presenting the tasks in a format suitable for persons with disabilities. As a result, persons with disabilities can more easily perform tasks optimized based on their own characteristics and can efficiently carry out their work in cooperation with consumer electronics.

[0301] "Information on the characteristics of persons with disabilities" refers to information that indicates the individual characteristics of persons with disabilities, such as their comprehension ability, work speed, and level of attention.

[0302] "Multiple simple tasks collected from the work area" refers to repetitive and standardized tasks performed in businesses and homes.

[0303] "Means of presenting tasks" refers to a system that presents tasks selected based on the characteristics of people with disabilities in an appropriate format.

[0304] The "means for automatically verifying the execution result" is a process of determining the accuracy of the result of a task performed by a person with a disability using an AI model or the like.

[0305] The "means for assisting work by collaborating with consumer devices" refers to a work support system in which general devices such as robots used in homes and workplaces supplement difficult parts for people with disabilities.

[0306] The system for implementing this invention is mainly composed of three main components: a server, a terminal, and a user. A specific example using this system is shown below.

[0307] The server first receives the characteristic information of the person with a disability and analyzes it. The information is based on factors such as comprehension ability, work speed, and concentration of attention, and is input from the user via the terminal. The server stores the received information in a database, and then organizes a plurality of simple tasks collected from the work area and stores the specific content of each task in the database. In this process, the Flask platform developed in Python is used, and PostgreSQL is adopted for the database.

[0308] The user terminal not only sends the input characteristic information to the server but also plays the role of visually displaying the tasks sent from the server. This is realized by a UI using JavaScript, and visually simplified information is presented in a form suitable for people with disabilities.

[0309] When the user completes the work, the result is sent back to the server through the terminal again. The server automatically verifies this execution result using an AI model and instructs corrections if necessary. At this time, TensorFlow is used for the AI model to evaluate the accuracy of the execution result.

[0310] Furthermore, the system works in conjunction with consumer electronics (such as robots) to enable people with disabilities to receive support tailored to their specific needs. Robots can assist with specific tasks in homes and workplaces, allowing people with disabilities to perform their duties in a way that maximizes their strengths.

[0311] As a concrete example, when inputting information about the characteristics of a person with a disability, a prompt such as "Explain how the AI ​​system installed in the household support robot can automatically assign appropriate tasks (e.g., sorting kitchen items) based on the characteristics of a specific user and work collaboratively" is used. Based on this prompt, the generated AI model performs optimal task assignment and enables collaborative work.

[0312] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0313] Step 1:

[0314] The user inputs their characteristic information via a terminal. This input includes comprehension, work speed, and attention span. The terminal sends this information as input to the server. The server stores the received information in a database and retains it as data necessary for subsequent processing based on the user's characteristics.

[0315] Step 2:

[0316] The server organizes information from businesses and households regarding simple tasks. This information consists of repetitive tasks such as data entry and document organization, and the server registers the specific details of these tasks in a database. This database serves as the foundational data for later task assignments.

[0317] Step 3:

[0318] The server uses a generated AI model to select the optimal task based on user characteristic information and work information in the database. This task selection process uses prompts, allowing the AI ​​model to automatically determine tasks suitable for users with disabilities. The selected tasks are presented with user characteristics in mind, and therefore, ease of execution is paramount.

[0319] Step 4:

[0320] The terminal visually presents tasks sent from the server to the user. The presented information consists of simplified procedures tailored to the user's characteristics, including visual guides and step-by-step instructions to aid understanding. This allows the user to easily grasp the task content and begin working.

[0321] Step 5:

[0322] When a user completes a task, the results are sent from the terminal to the server. The server automatically verifies the received results based on the generating AI model and evaluates the accuracy of the results. In this evaluation step, the input data is compared with accurate baseline data, and if there is any inaccuracy, the server sends correction instructions to the terminal.

[0323] Step 6:

[0324] The server will work in conjunction with consumer electronics to provide further support to people with disabilities. Specifically, it envisions scenarios where devices such as robots assist users, providing support for difficult parts of task completion. Through this collaborative work, users can leverage their own strengths while receiving assistance to successfully complete tasks.

[0325] 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.

[0326] This invention aims to improve work efficiency and user comfort in an employment support system for people with disabilities by incorporating an emotion engine. This system consists of a server, terminals, and users, and the addition of the emotion engine enhances the functionality of each component.

[0327] The user first inputs information about the characteristics of the person with a disability through a terminal. This information includes characteristics such as comprehension, work speed, and emotional response. The terminal sends this information to a server, which analyzes it and stores it in a database.

[0328] Companies use terminals to submit lists of simple internal tasks to a server. These lists include task details, importance, and deadlines, which the server then organizes and stores in a database.

[0329] The server matches the characteristics of the person with a disability with the work content, selects an appropriate task, and presents it to the user via the terminal. A key feature here is that the emotion engine analyzes the user's real-time emotional state and adaptively adjusts the task presentation method. For example, if the user is feeling stressed, the complexity of the task is reduced and converted into simple visual instructions.

[0330] Users perform tasks and report the results to the server via their terminal. The server uses an AI model to verify the results and instructs corrections if any inaccuracies are found. Furthermore, an emotion engine monitors the user's emotional changes and generates alerts if anomalies are detected, prompting improvements to the work environment.

[0331] As a concrete example, the emotion engine analyzes the user's camera footage and audio data to identify emotions such as joy, anger, and anxiety in real time. Based on this information, it dynamically adapts by presenting tasks when the user is relaxed and recommending rest when they are stressed.

[0332] In this way, this system provides an optimal work environment for people with disabilities, maximizing their work performance capabilities while improving productivity within companies. This is expected to improve both the quality and quantity of employment, leading to sustainable employment support.

[0333] The following describes the processing flow.

[0334] Step 1:

[0335] The user inputs information about the individual's disability characteristics into the terminal. This information includes profiles of comprehension, work speed, and emotional response. The terminal then transmits the entered information to the server.

[0336] Step 2:

[0337] The server analyzes the characteristic information received from the terminal and generates a profile based on the characteristics of the person with a disability. These profiles are stored in a database and used for subsequent task assignment.

[0338] Step 3:

[0339] Companies send a list of simple tasks they want to perform via their terminals to a server. This list includes the specific tasks, their importance, and deadlines. The server registers this information in a database.

[0340] Step 4:

[0341] The server matches the profile of the person with a disability with the received list of simple tasks and performs a process to select appropriate tasks. The selected tasks are presented in a way that suits the user's characteristics.

[0342] Step 5:

[0343] The emotion engine uses the device to recognize the user's real-time emotional state. For this purpose, the user's camera video and audio data are analyzed. Based on these emotions, the way tasks are presented is adjusted.

[0344] Step 6:

[0345] The device presents the user with visually simplified instructions adjusted by an emotion engine. For example, if the user is feeling stressed, it uses simplified displays and softer colors.

[0346] Step 7:

[0347] The user performs the task by following instructions provided via the terminal. The results are reported from the terminal to the server.

[0348] Step 8:

[0349] The server verifies the reported task results using an AI model to confirm their accuracy. If necessary, it returns specific correction instructions to the user via the terminal.

[0350] Step 9:

[0351] The emotion engine continuously monitors the user's emotional state during work and generates alerts if significant emotional anomalies are detected. This information is communicated to the user and company administrators to encourage improvements to the work environment.

[0352] (Example 2)

[0353] 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".

[0354] In employing people with disabilities, it is essential to optimize the process of assigning and executing tasks, taking into full consideration their characteristics and emotional states. Without this optimization, the abilities of the individuals with disabilities may not be fully utilized, and employers may experience decreased productivity. Furthermore, considering that emotional states directly impact work efficiency and effectiveness, there is a need for real-time sentiment analysis and adaptive task presentation.

[0355] 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.

[0356] In this invention, the server includes a device for inputting and analyzing information based on the characteristics of persons with disabilities, a device for organizing multiple tasks collected from the organization and storing the specific details of each task in a data storage device, and a device for analyzing emotional states in real time and dynamically adapting the method of presenting tasks. This makes it possible to assign optimal tasks according to the characteristics of persons with disabilities and to adaptively present tasks according to their emotional states.

[0357] A "person with a disability" is an individual who has physical, intellectual, or mental limitations and requires special consideration or support.

[0358] "Characteristic information" refers to data about the individual abilities and characteristics of people with disabilities, such as comprehension, work speed, and emotional response.

[0359] An "organization" is a group of people, such as a company or a group of businesses, that carry out business operations, and is the entity that manages the business processes within that group.

[0360] "Business operations" refers to the collective term for specific activities and tasks performed by members within an organization.

[0361] A "data storage device" refers to a system or equipment for safely and efficiently storing information and data.

[0362] "Emotional state" refers to the emotional reactions or psychological conditions that an individual exhibits in specific situations, such as joy, anger, or stress.

[0363] "Analysis" is the process of breaking down complex information or data and examining its constituent elements in detail.

[0364] "Job assignment" refers to the act of providing an individual or group with specific job duties and instructions on how to carry them out.

[0365] This invention is a system that supports the employment of people with disabilities, and the program operates based on information input and analysis from a server, terminals, and users. The server has a data analysis engine that processes characteristic information of people with disabilities input from users via terminals and stores that data in a data storage device using a database management system (DBMS). This uses general database software and an AI analysis module.

[0366] Users input characteristic information about individuals with disabilities, such as their comprehension level, work speed, and emotional responses, through a terminal. The terminal sends this information to a server, which then uses that information to select the most suitable tasks for the individuals with disabilities.

[0367] The server uses a generative AI model to match a list of tasks collected from within the organization with the characteristics of individuals with disabilities, thereby matching them with the most suitable tasks. The task list is entered from a terminal and analyzed and organized by the server. In particular, the emotion engine analyzes the user's real-time emotional state and dynamically adjusts how tasks are presented. For example, the emotion engine analyzes the user's facial expressions and voice data obtained through the camera and microphone to determine whether the user is relaxed or stressed.

[0368] For example, if the user is relaxed, the server will present normal tasks, but if it detects that the user is stressed, the server will simplify the tasks and provide visually simplified instructions. Another example of a prompt message would be: "Based on the characteristics of the person with a disability and the company's operations, please suggest the most suitable tasks. The current emotional state is stressed."

[0369] This system not only optimizes task assignments for users but also enables task presentations that take into account their real-time emotional state, thereby supporting the efficient and comfortable work performance of people with disabilities.

[0370] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0371] Step 1:

[0372] Users input characteristic information about individuals with disabilities, such as their comprehension level, work speed, and emotional responses, through a terminal. The terminal converts this information into the correct format and sends it to the server. This characteristic information is important because it is used later for job matching and sentiment analysis, and the server supplies the received information to the data analysis engine.

[0373] Step 2:

[0374] The server analyzes the characteristic information submitted by the user based on its data analysis engine. During this process, the data is organized and classified based on the characteristics of each individual with a disability. The analysis results are stored in a data storage device via a database management system (DBMS) and serve as reference data for subsequent task selection.

[0375] Step 3:

[0376] Companies use terminals to input a list of tasks within their organization and send it to a server. The list includes details of the tasks, their importance, and deadlines. The terminals format the task lists appropriately and transfer them to the server. The server stores the received task lists in a database and uses them in the task matching process.

[0377] Step 4:

[0378] The server uses a generated AI model to compare disability characteristics information stored in the database with a list of tasks. In this process, the AI ​​model compares characteristics with task requirements and selects the most suitable task. The selected task is sent from the server to the terminal and presented to the user.

[0379] Step 5:

[0380] The server activates the emotion engine to analyze real-time emotional state data obtained from the terminal. It analyzes video and audio data acquired by the user via the terminal's camera and microphone to identify emotions such as joy, anger, and stress. This emotional state data is used to adjust the way tasks are presented.

[0381] Step 6:

[0382] Based on the analysis results of the emotion engine, the server determines how to present tasks according to the user's emotional state. For example, if the user is feeling stressed, the server simplifies the task content and displays it on the terminal in a visually easy-to-understand format. By tailoring the display method to the user's emotions, the efficiency of task execution is improved.

[0383] Step 7:

[0384] The user uses a terminal to perform the assigned tasks and reports the results to the server upon completion. The terminal formats the user's input and sends it to the server. The server reviews the report using a generative AI model and issues correction instructions if the report is inaccurate.

[0385] Step 8:

[0386] The server continuously monitors changes in the user's emotions using an emotion engine. If an abnormal emotional state is detected, it generates an alert and provides instructions for improving the work environment. This continuous monitoring aims to enhance user comfort and work efficiency.

[0387] (Application Example 2)

[0388] 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."

[0389] A major challenge in modern work environments is the lack of systems that enable people with disabilities to efficiently perform tasks suited to their individual characteristics. Furthermore, there are insufficient methods to reduce mental stress during work and provide a comfortable working environment. Additionally, there is a need for a system that can monitor users' emotional changes in real time during work and adapt accordingly.

[0390] 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.

[0391] In this invention, the server includes means for acquiring and analyzing attribute information of persons with disabilities; means for collecting work sets from within the organization and storing the specific details of each work in an information storage location; means for selecting the work based on the attributes of persons with disabilities and presenting the tasks in a format suitable for those persons with disabilities; and means for analyzing the user's emotional state in real time using an emotion analysis device and dynamically optimizing the task presentation method. This makes it possible not only for persons with disabilities to select the most suitable work, but also to provide a consistently comfortable working environment.

[0392] "Attribute information of persons with disabilities" refers to data that includes characteristics such as the comprehension level, work speed, and emotional response of individuals with disabilities.

[0393] A "work set" refers to a collection of multiple simple tasks or routines required within a company or organization.

[0394] An "information repository" is a database or recording medium used to store specific details of each task, attribute information of people with disabilities, and so on.

[0395] "Task presentation methods" refer to techniques for communicating tasks and work content to people with disabilities in the most appropriate format.

[0396] An "emotion analysis device" is a device or software that analyzes a user's emotional state in real time and makes appropriate changes to the work environment or proposed tasks.

[0397] This invention is a system that allows people with disabilities to select the most suitable tasks based on their individual characteristics and improve their comfort while working.

[0398] The server first receives attribute information of individuals with disabilities and analyzes it. This includes data such as the individual's comprehension level, work speed, and emotional responses, which are entered via a terminal. Next, the server organizes the sets of tasks collected from within the company and stores the specific details of each task in an information repository. This allows for the selection of tasks suitable for each individual with a disability.

[0399] An emotion analysis device is used to analyze the user's emotional state in real time. This analysis utilizes the user's camera video and audio data, and an emotion analysis AI determines the user's emotions. If the system determines that the user is experiencing stress, it dynamically optimizes the task presentation method, adjusting the complexity of the task or providing visually simpler instructions.

[0400] Furthermore, an emotion analysis device monitors changes in the user's emotions during work and generates alerts to prompt appropriate responses if an anomaly is detected. As part of this process, a generative AI model is used to perform real-time emotion assessment and adaptation.

[0401] As a concrete example, the server sends a prompt to the emotion analysis AI saying, "Evaluate my stress level based on what I'm saying now and suggest advice that will help me relax," which then generates appropriate feedback. This reduces the user's mental burden and improves task efficiency.

[0402] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0403] Step 1:

[0404] The terminal inputs attribute information of the user, who is a person with a disability. This input information includes comprehension level, work speed, and emotional response. This data is sent to the server, which stores this information in a database. Based on the input attribute information, the server builds the basic data for selecting the most suitable task for the user.

[0405] Step 2:

[0406] The server organizes task sets collected from within the company. It stores information such as the specific content, importance, and deadline for each task in a database. This allows for matching user attribute information with the task set data, preparing the system for selecting appropriate tasks.

[0407] Step 3:

[0408] The server uses a generative AI model to match user attribute information with task sets. The input consists of attribute and task information from the database, and the output is a list of tasks suitable for the user. These tasks are then presented to the user's terminal in a format tailored to them, prompting them to complete the tasks.

[0409] Step 4:

[0410] Using an emotion analysis device, the server analyzes the user's emotional state in real time. Receiving camera video and audio data as input, the emotion analysis AI identifies emotions such as joy, anger, and anxiety. If the user is experiencing stress, dynamic adjustments are made. Specifically, this might involve lowering the difficulty of the task or providing visually clearer instructions.

[0411] Step 5:

[0412] Users complete the assigned tasks and report their results via their devices. The server receives these results and automatically evaluates them using a generative AI model. If there are any inaccuracies, the server generates correction instructions to help improve future task assignments.

[0413] Step 6:

[0414] The server continuously uses an emotion analysis device to monitor the user's emotional changes. Based on the analysis results, it generates an alert when an anomaly is detected and provides appropriate feedback to the user. Specific actions include playing relaxing music or suggesting a break.

[0415] 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.

[0416] 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.

[0417] 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.

[0418] [Third Embodiment]

[0419] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0420] 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.

[0421] 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).

[0422] 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.

[0423] 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.

[0424] 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).

[0425] 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.

[0426] 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.

[0427] 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.

[0428] 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.

[0429] 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.

[0430] 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".

[0431] The system for implementing the present invention consists of three main components: a server, a terminal, and a user. This system is designed to support the employment of persons with disabilities and provides processes to support appropriate work tailored to the characteristics of persons with disabilities.

[0432] The user first enters information about their disability characteristics into a terminal. This information includes comprehension level, work speed, and attention span. The entered information is sent from the terminal to a server, which analyzes it and stores it in a database.

[0433] Next, multiple simple tasks collected from the company via terminals are transferred to a server. The server organizes these tasks and stores characteristic information about each task in a database. Examples of such tasks include data entry that requires repetitive input and file organization that follows a set procedure.

[0434] The server assigns tasks to individuals with disabilities based on their specific characteristics. For example, a person with a disability who excels at handling repetitive patterns might be assigned a data management task in a particular format. Task assignment is performed automatically by the server's algorithm.

[0435] Assigned tasks are presented to the user via the terminal as visually simplified instructions. This allows the user to efficiently understand and perform the work. The simplified instructions aid understanding of the task through visual guidance and step-by-step instructions.

[0436] Once the user completes the task, the results are sent from the terminal to the server. The server uses an AI model to verify the results and confirm their accuracy. If inaccurate data is detected, the user is instructed to correct it.

[0437] These processes enable people with disabilities to receive support tailored to their individual characteristics, and allow companies to effectively employ people with disabilities and improve productivity. Specific application examples include data entry when registering new product information in a database and document filing. In both of these tasks, people with disabilities can understand and perform the work in a way that suits their individual characteristics.

[0438] The following describes the processing flow.

[0439] Step 1:

[0440] Users input information about their disability characteristics into a terminal. This includes comprehension level, work speed, and communication skills. The terminal collects the entered data and sends it to a server.

[0441] Step 2:

[0442] The server analyzes the received characteristic information and generates an appropriate profile. This profile takes into account the abilities and characteristics of the person with a disability and is stored in a searchable database.

[0443] Step 3:

[0444] Companies use terminals to submit simple tasks required by various departments within the company to a server. The terminals transfer detailed information about the tasks, such as priority and deadlines, to the server.

[0445] Step 4:

[0446] The server analyzes the received work list and registers the details of each task in the database. Furthermore, it matches each task with the disability profile and selects the appropriate task.

[0447] Step 5:

[0448] The server converts the assigned tasks into visually simplified procedures. This conversion is tailored to the disability's level of understanding and uses visual information and diagrams to create an easy-to-understand format.

[0449] Step 6:

[0450] The terminal displays visualized instructions to the user. The user then uses this information to complete the task.

[0451] Step 7:

[0452] Once the user completes a task, the terminal reports the results to the server. The report includes data on the task's completion status and execution results.

[0453] Step 8:

[0454] The server uses an AI model to verify the received work results and check the accuracy and completeness of the data. If there are any inaccuracies, it will present the user with the items that need correction.

[0455] Step 9:

[0456] The user receives correction instructions, makes the necessary corrections, and then resubmits the work results to the server for verification. This improves the overall accuracy of the work.

[0457] (Example 1)

[0458] 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."

[0459] To expand employment opportunities for people with disabilities, a system is needed that provides them with appropriate tasks tailored to their characteristics and abilities, enabling them to perform their work efficiently. However, traditional methods make it difficult to accurately understand the characteristics of people with disabilities and automatically select and apply tasks based on those characteristics. Furthermore, manual verification of work results is time-consuming, hindering efficient support.

[0460] 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.

[0461] In this invention, the server includes means for inputting characteristic information of persons with disabilities via a terminal, analyzing the characteristic information and storing it in a database; means for organizing multiple simple tasks collected from the organization and maintaining characteristic information for each task in the database; means for automatically selecting the simple tasks using an AI model based on the characteristics of persons with disabilities and presenting the tasks in a format suitable for the persons with disabilities; and means for receiving the results of task execution by the persons with disabilities, automatically verifying them using the AI ​​model, and instructing corrections as necessary. This enables the assignment of tasks suitable for persons with disabilities and rapid verification of the results.

[0462] "Information on the characteristics of persons with disabilities" refers to information about the individual abilities and characteristics of persons with disabilities, such as their comprehension level, work speed, and attention span.

[0463] "Analysis" is the process of understanding characteristics and trends by classifying, comparing, and evaluating data.

[0464] A "database" is an information system that organizes and stores information, allowing it to be efficiently retrieved as needed.

[0465] An "organization" is a company, association, or group formed to achieve a specific purpose.

[0466] "Simple tasks" are defined as work that does not require complex judgment and is performed according to prescribed procedures.

[0467] A "generative AI model" is an artificial intelligence system that learns from large amounts of data and makes appropriate predictions and judgments about new data.

[0468] "Automatic" means that a device or system performs tasks or makes decisions independently, without human intervention.

[0469] A "task" is a specific job or set of tasks that needs to be performed.

[0470] A "terminal" is an electronic device used by a user to input, output, or process information.

[0471] "Verification" is the process of checking whether results and information are accurate and identifying problems as necessary.

[0472] "Correction" refers to correcting errors or deficiencies and restoring the product to its correct state.

[0473] One embodiment of this invention is a system that provides work adaptation based on the characteristics of persons with disabilities. This system operates through the cooperation of a server, terminals, and users. The roles and specific processes of each component are described below.

[0474] First, the user uses a terminal to input information about the person's disability characteristics. This information includes comprehension level, work speed, and attention span. The terminal securely transmits the entered information to a server. This process typically involves hardware such as a personal computer or tablet, and user interface software for inputting the information.

[0475] The server analyzes the received characteristic information and stores it in a database. The database stores characteristic information for all individuals with disabilities, allowing for quick retrieval when needed. The server also organizes simple tasks submitted by the organization and registers them in the database along with their characteristic information. At this stage, data analysis is performed using Python scripts or similar tools.

[0476] A server equipped with a generative AI model selects suitable simple tasks based on the characteristics of individuals with disabilities. The model assigns tasks using specific prompt statements. For example, the AI ​​model might be given a prompt statement such as, "Assign the most suitable user to task type 001." This prompt statement enables optimal task assignment.

[0477] The selected task is presented to the user via the terminal and displayed as a visually simplified work procedure through the user interface. This allows the user to perform the task under instructions in a format that is easiest for people with disabilities to understand.

[0478] Finally, once the user completes the task, the results are sent from the terminal to the server and automatically verified by the AI ​​model. This verification process provides correction instructions as needed.

[0479] This system allows people with disabilities to utilize their abilities in work suited to their characteristics, and enables organizations to achieve efficient and effective employment management.

[0480] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0481] Step 1:

[0482] Users input information about their disability characteristics via a terminal. Specifically, they use the user interface on the terminal to input information such as comprehension level, work speed, and attention span using a keyboard or touchscreen. The input information is prepared as a dataset and transmitted to the server via a secure communication protocol.

[0483] Step 2:

[0484] The server receives characteristic information sent from the terminal and stores it in a database. Python scripts are often used to analyze the received data and check for anomalies. This analyzed data is structured for future searching and processing and stored in the database.

[0485] Step 3:

[0486] Organizations use terminals to input information about light tasks and send it to a server. Specifically, they input job details, including standard procedures and required skills for tasks, from the terminal, and the server stores each task's information in a database.

[0487] Step 4:

[0488] The server uses a generated AI model based on stored characteristic information to automatically assign harmonized tasks. Using the prompt "Assign the best user for task type 001," the AI ​​model selects and assigns the task to the most suitable person with a disability. As a result, a set of assigned tasks is generated.

[0489] Step 5:

[0490] The device displays the tasks assigned to the person with a disability on its screen. The user interface presents task details in a visually simplified manner to help the person with a disability easily understand and perform the tasks. Specifically, icons and step-by-step guides are displayed.

[0491] Step 6:

[0492] The user performs the task according to the instructions displayed on the terminal. Once the task is completed, the user reports the results to the server via the terminal. The result data, including metrics such as completion time and accuracy, is transferred to the server.

[0493] Step 7:

[0494] The server uses a generating AI model to verify the received work results. The AI ​​model automatically evaluates the results and verifies their accuracy. If inaccurate, detailed feedback on areas requiring correction is provided again, and instructions are given to the user via their terminal. This establishes an appropriate feedback system and improves the quality of work.

[0495] (Application Example 1)

[0496] 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."

[0497] There is a need for systems that efficiently support the work of people with disabilities in a way that is tailored to their individual characteristics. It is also important to create an environment where people with disabilities can work in collaboration with consumer-grade equipment and utilize their own strengths. However, current systems lack sufficient mechanisms for automatically assigning appropriate tasks and providing work support based on characteristic information, making it difficult to contribute to improving corporate productivity.

[0498] 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.

[0499] In this invention, the server includes means for inputting and analyzing characteristic information of persons with disabilities; means for organizing multiple simple tasks collected from the work area and storing the specific details of each task in a database; and means for selecting the simple tasks based on the characteristics of persons with disabilities and presenting the tasks in a format suitable for persons with disabilities. As a result, persons with disabilities can more easily perform tasks optimized based on their own characteristics and can efficiently carry out their work in cooperation with consumer electronics.

[0500] "Information on the characteristics of persons with disabilities" refers to information that indicates the individual characteristics of persons with disabilities, such as their comprehension ability, work speed, and level of attention.

[0501] "Multiple simple tasks collected from the work area" refers to repetitive and standardized tasks performed in businesses and homes.

[0502] "Means of presenting tasks" refers to a system that presents tasks selected based on the characteristics of people with disabilities in an appropriate format.

[0503] "Means for automatically verifying execution results" refers to a process that uses AI models or similar tools to determine the accuracy of the results of tasks performed by people with disabilities.

[0504] "Means of collaborative work assistance using consumer-grade equipment" refers to work support systems in which general-purpose equipment such as robots used at home or in the workplace compensates for aspects that are difficult for people with disabilities.

[0505] The system for implementing this invention mainly consists of three main components: a server, a terminal, and a user. A specific example using this system is shown below.

[0506] The server first receives and analyzes information about the characteristics of individuals with disabilities. This information is based on comprehension, work speed, and attention span, and is entered by the user via a terminal. The server stores the received information in a database, then organizes multiple simple tasks collected from the work area and saves the specific details of each task in the database. This process uses the Flask platform developed in Python, and PostgreSQL is used as the database.

[0507] The user terminal not only transmits the entered characteristic information to the server, but also plays a role in visually displaying the tasks sent from the server. This is achieved through a JavaScript-based UI, where visually simplified information is presented in a format suitable for people with disabilities.

[0508] Once the user completes the task, the results are sent back to the server via the terminal. The server automatically verifies these results using an AI model and instructs corrections as needed. TensorFlow is used as the AI ​​model to evaluate the accuracy of the execution results.

[0509] Furthermore, the system works in conjunction with consumer electronics (such as robots) to enable people with disabilities to receive support tailored to their specific needs. Robots can assist with specific tasks in homes and workplaces, allowing people with disabilities to perform their duties in a way that maximizes their strengths.

[0510] As a concrete example, when inputting information about the characteristics of a person with a disability, a prompt such as "Explain how the AI ​​system installed in the household support robot can automatically assign appropriate tasks (e.g., sorting kitchen items) based on the characteristics of a specific user and work collaboratively" is used. Based on this prompt, the generated AI model performs optimal task assignment and enables collaborative work.

[0511] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0512] Step 1:

[0513] The user inputs their characteristic information via a terminal. This input includes comprehension, work speed, and attention span. The terminal sends this information as input to the server. The server stores the received information in a database and retains it as data necessary for subsequent processing based on the user's characteristics.

[0514] Step 2:

[0515] The server organizes information from businesses and households regarding simple tasks. This information consists of repetitive tasks such as data entry and document organization, and the server registers the specific details of these tasks in a database. This database serves as the foundational data for later task assignments.

[0516] Step 3:

[0517] The server uses a generated AI model to select the optimal task based on user characteristic information and work information in the database. This task selection process uses prompts, allowing the AI ​​model to automatically determine tasks suitable for users with disabilities. The selected tasks are presented with user characteristics in mind, and therefore, ease of execution is paramount.

[0518] Step 4:

[0519] The terminal visually presents tasks sent from the server to the user. The presented information consists of simplified procedures tailored to the user's characteristics, including visual guides and step-by-step instructions to aid understanding. This allows the user to easily grasp the task content and begin working.

[0520] Step 5:

[0521] When a user completes a task, the results are sent from the terminal to the server. The server automatically verifies the received results based on the generating AI model and evaluates the accuracy of the results. In this evaluation step, the input data is compared with accurate baseline data, and if there is any inaccuracy, the server sends correction instructions to the terminal.

[0522] Step 6:

[0523] The server will work in conjunction with consumer electronics to provide further support to people with disabilities. Specifically, it envisions scenarios where devices such as robots assist users, providing support for difficult parts of task completion. Through this collaborative work, users can leverage their own strengths while receiving assistance to successfully complete tasks.

[0524] 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.

[0525] This invention aims to improve work efficiency and user comfort in an employment support system for people with disabilities by incorporating an emotion engine. This system consists of a server, terminals, and users, and the addition of the emotion engine enhances the functionality of each component.

[0526] The user first inputs information about the characteristics of the person with a disability through a terminal. This information includes characteristics such as comprehension, work speed, and emotional response. The terminal sends this information to a server, which analyzes it and stores it in a database.

[0527] Companies use terminals to submit lists of simple internal tasks to a server. These lists include task details, importance, and deadlines, which the server then organizes and stores in a database.

[0528] The server matches the characteristics of the person with a disability with the work content, selects an appropriate task, and presents it to the user via the terminal. A key feature here is that the emotion engine analyzes the user's real-time emotional state and adaptively adjusts the task presentation method. For example, if the user is feeling stressed, the complexity of the task is reduced and converted into simple visual instructions.

[0529] Users perform tasks and report the results to the server via their terminal. The server uses an AI model to verify the results and instructs corrections if any inaccuracies are found. Furthermore, an emotion engine monitors the user's emotional changes and generates alerts if anomalies are detected, prompting improvements to the work environment.

[0530] As a concrete example, the emotion engine analyzes the user's camera footage and audio data to identify emotions such as joy, anger, and anxiety in real time. Based on this information, it dynamically adapts by presenting tasks when the user is relaxed and recommending rest when they are stressed.

[0531] In this way, this system provides an optimal work environment for people with disabilities, maximizing their work performance capabilities while improving productivity within companies. This is expected to improve both the quality and quantity of employment, leading to sustainable employment support.

[0532] The following describes the processing flow.

[0533] Step 1:

[0534] The user inputs information about the individual's disability characteristics into the terminal. This information includes profiles of comprehension, work speed, and emotional response. The terminal then transmits the entered information to the server.

[0535] Step 2:

[0536] The server analyzes the characteristic information received from the terminal and generates a profile based on the characteristics of the person with a disability. These profiles are stored in a database and used for subsequent task assignment.

[0537] Step 3:

[0538] Companies send a list of simple tasks they want to perform via their terminals to a server. This list includes the specific tasks, their importance, and deadlines. The server registers this information in a database.

[0539] Step 4:

[0540] The server matches the profile of the person with a disability with the received list of simple tasks and performs a process to select appropriate tasks. The selected tasks are presented in a way that suits the user's characteristics.

[0541] Step 5:

[0542] The emotion engine uses the device to recognize the user's real-time emotional state. For this purpose, the user's camera video and audio data are analyzed. Based on these emotions, the way tasks are presented is adjusted.

[0543] Step 6:

[0544] The device presents the user with visually simplified instructions adjusted by an emotion engine. For example, if the user is feeling stressed, it uses simplified displays and softer colors.

[0545] Step 7:

[0546] The user performs the task by following instructions provided via the terminal. The results are reported from the terminal to the server.

[0547] Step 8:

[0548] The server verifies the reported task results using an AI model to confirm their accuracy. If necessary, it returns specific correction instructions to the user via the terminal.

[0549] Step 9:

[0550] The emotion engine continuously monitors the user's emotional state during work and generates alerts if significant emotional anomalies are detected. This information is communicated to the user and company administrators to encourage improvements to the work environment.

[0551] (Example 2)

[0552] 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."

[0553] In employing people with disabilities, it is essential to optimize the process of assigning and executing tasks, taking into full consideration their characteristics and emotional states. Without this optimization, the abilities of the individuals with disabilities may not be fully utilized, and employers may experience decreased productivity. Furthermore, considering that emotional states directly impact work efficiency and effectiveness, there is a need for real-time sentiment analysis and adaptive task presentation.

[0554] 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.

[0555] In this invention, the server includes a device for inputting and analyzing information based on the characteristics of persons with disabilities, a device for organizing multiple tasks collected from the organization and storing the specific details of each task in a data storage device, and a device for analyzing emotional states in real time and dynamically adapting the method of presenting tasks. This makes it possible to assign optimal tasks according to the characteristics of persons with disabilities and to adaptively present tasks according to their emotional states.

[0556] A "person with a disability" is an individual who has physical, intellectual, or mental limitations and requires special consideration or support.

[0557] "Characteristic information" refers to data about the individual abilities and characteristics of people with disabilities, such as comprehension, work speed, and emotional response.

[0558] An "organization" is a group of people, such as a company or a group of businesses, that carry out business operations, and is the entity that manages the business processes within that group.

[0559] "Business operations" refers to the collective term for specific activities and tasks performed by members within an organization.

[0560] A "data storage device" refers to a system or equipment for safely and efficiently storing information and data.

[0561] "Emotional state" refers to the emotional reactions or psychological conditions that an individual exhibits in specific situations, such as joy, anger, or stress.

[0562] "Analysis" is the process of breaking down complex information or data and examining its constituent elements in detail.

[0563] "Job assignment" refers to the act of providing an individual or group with specific job duties and instructions on how to carry them out.

[0564] This invention is a system that supports the employment of people with disabilities, and the program operates based on information input and analysis from a server, terminals, and users. The server has a data analysis engine that processes characteristic information of people with disabilities input from users via terminals and stores that data in a data storage device using a database management system (DBMS). This uses general database software and an AI analysis module.

[0565] Users input characteristic information about individuals with disabilities, such as their comprehension level, work speed, and emotional responses, through a terminal. The terminal sends this information to a server, which then uses that information to select the most suitable tasks for the individuals with disabilities.

[0566] The server uses a generative AI model to match a list of tasks collected from within the organization with the characteristics of individuals with disabilities, thereby matching them with the most suitable tasks. The task list is entered from a terminal and analyzed and organized by the server. In particular, the emotion engine analyzes the user's real-time emotional state and dynamically adjusts how tasks are presented. For example, the emotion engine analyzes the user's facial expressions and voice data obtained through the camera and microphone to determine whether the user is relaxed or stressed.

[0567] For example, if the user is relaxed, the server will present normal tasks, but if it detects that the user is stressed, the server will simplify the tasks and provide visually simplified instructions. Another example of a prompt message would be: "Based on the characteristics of the person with a disability and the company's operations, please suggest the most suitable tasks. The current emotional state is stressed."

[0568] This system not only optimizes task assignments for users but also enables task presentations that take into account their real-time emotional state, thereby supporting the efficient and comfortable work performance of people with disabilities.

[0569] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0570] Step 1:

[0571] Users input characteristic information about individuals with disabilities, such as their comprehension level, work speed, and emotional responses, through a terminal. The terminal converts this information into the correct format and sends it to the server. This characteristic information is important because it is used later for job matching and sentiment analysis, and the server supplies the received information to the data analysis engine.

[0572] Step 2:

[0573] The server analyzes the characteristic information submitted by the user based on its data analysis engine. During this process, the data is organized and classified based on the characteristics of each individual with a disability. The analysis results are stored in a data storage device via a database management system (DBMS) and serve as reference data for subsequent task selection.

[0574] Step 3:

[0575] Companies use terminals to input a list of tasks within their organization and send it to a server. The list includes details of the tasks, their importance, and deadlines. The terminals format the task lists appropriately and transfer them to the server. The server stores the received task lists in a database and uses them in the task matching process.

[0576] Step 4:

[0577] The server uses a generated AI model to compare disability characteristics information stored in the database with a list of tasks. In this process, the AI ​​model compares characteristics with task requirements and selects the most suitable task. The selected task is sent from the server to the terminal and presented to the user.

[0578] Step 5:

[0579] The server activates the emotion engine to analyze real-time emotional state data obtained from the terminal. It analyzes video and audio data acquired by the user via the terminal's camera and microphone to identify emotions such as joy, anger, and stress. This emotional state data is used to adjust the way tasks are presented.

[0580] Step 6:

[0581] Based on the analysis results of the emotion engine, the server determines how to present tasks according to the user's emotional state. For example, if the user is feeling stressed, the server simplifies the task content and displays it on the terminal in a visually easy-to-understand format. By tailoring the display method to the user's emotions, the efficiency of task execution is improved.

[0582] Step 7:

[0583] The user uses a terminal to perform the assigned tasks and reports the results to the server upon completion. The terminal formats the user's input and sends it to the server. The server reviews the report using a generative AI model and issues correction instructions if the report is inaccurate.

[0584] Step 8:

[0585] The server continuously monitors changes in the user's emotions using an emotion engine. If an abnormal emotional state is detected, it generates an alert and provides instructions for improving the work environment. This continuous monitoring aims to enhance user comfort and work efficiency.

[0586] (Application Example 2)

[0587] 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."

[0588] A major challenge in modern work environments is the lack of systems that enable people with disabilities to efficiently perform tasks suited to their individual characteristics. Furthermore, there are insufficient methods to reduce mental stress during work and provide a comfortable working environment. Additionally, there is a need for a system that can monitor users' emotional changes in real time during work and adapt accordingly.

[0589] 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.

[0590] In this invention, the server includes means for acquiring and analyzing attribute information of persons with disabilities; means for collecting work sets from within the organization and storing the specific details of each work in an information storage location; means for selecting the work based on the attributes of persons with disabilities and presenting the tasks in a format suitable for those persons with disabilities; and means for analyzing the user's emotional state in real time using an emotion analysis device and dynamically optimizing the task presentation method. This makes it possible not only for persons with disabilities to select the most suitable work, but also to provide a consistently comfortable working environment.

[0591] "Attribute information of persons with disabilities" refers to data that includes characteristics such as the comprehension level, work speed, and emotional response of individuals with disabilities.

[0592] A "work set" refers to a collection of multiple simple tasks or routines required within a company or organization.

[0593] An "information repository" is a database or recording medium used to store specific details of each task, attribute information of people with disabilities, and so on.

[0594] "Task presentation methods" refer to techniques for communicating tasks and work content to people with disabilities in the most appropriate format.

[0595] An "emotion analysis device" is a device or software that analyzes a user's emotional state in real time and makes appropriate changes to the work environment or proposed tasks.

[0596] This invention is a system that allows people with disabilities to select the most suitable tasks based on their individual characteristics and improve their comfort while working.

[0597] The server first receives attribute information of individuals with disabilities and analyzes it. This includes data such as the individual's comprehension level, work speed, and emotional responses, which are entered via a terminal. Next, the server organizes the sets of tasks collected from within the company and stores the specific details of each task in an information repository. This allows for the selection of tasks suitable for each individual with a disability.

[0598] An emotion analysis device is used to analyze the user's emotional state in real time. This analysis utilizes the user's camera video and audio data, and an emotion analysis AI determines the user's emotions. If the system determines that the user is experiencing stress, it dynamically optimizes the task presentation method, adjusting the complexity of the task or providing visually simpler instructions.

[0599] Furthermore, an emotion analysis device monitors changes in the user's emotions during work and generates alerts to prompt appropriate responses if an anomaly is detected. As part of this process, a generative AI model is used to perform real-time emotion assessment and adaptation.

[0600] As a concrete example, the server sends a prompt to the emotion analysis AI saying, "Evaluate my stress level based on what I'm saying now and suggest advice that will help me relax," which then generates appropriate feedback. This reduces the user's mental burden and improves task efficiency.

[0601] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0602] Step 1:

[0603] The terminal inputs attribute information of the user, who is a person with a disability. This input information includes comprehension level, work speed, and emotional response. This data is sent to the server, which stores this information in a database. Based on the input attribute information, the server builds the basic data for selecting the most suitable task for the user.

[0604] Step 2:

[0605] The server organizes task sets collected from within the company. It stores information such as the specific content, importance, and deadline for each task in a database. This allows for matching user attribute information with the task set data, preparing the system for selecting appropriate tasks.

[0606] Step 3:

[0607] The server uses a generative AI model to match user attribute information with task sets. The input consists of attribute and task information from the database, and the output is a list of tasks suitable for the user. These tasks are then presented to the user's terminal in a format tailored to them, prompting them to complete the tasks.

[0608] Step 4:

[0609] Using an emotion analysis device, the server analyzes the user's emotional state in real time. Receiving camera video and audio data as input, the emotion analysis AI identifies emotions such as joy, anger, and anxiety. If the user is experiencing stress, dynamic adjustments are made. Specifically, this might involve lowering the difficulty of the task or providing visually clearer instructions.

[0610] Step 5:

[0611] Users complete the assigned tasks and report their results via their devices. The server receives these results and automatically evaluates them using a generative AI model. If there are any inaccuracies, the server generates correction instructions to help improve future task assignments.

[0612] Step 6:

[0613] The server continuously uses an emotion analysis device to monitor the user's emotional changes. Based on the analysis results, it generates an alert when an anomaly is detected and provides appropriate feedback to the user. Specific actions include playing relaxing music or suggesting a break.

[0614] 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.

[0615] 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.

[0616] 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.

[0617] [Fourth Embodiment]

[0618] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0619] 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.

[0620] 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).

[0621] 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.

[0622] 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.

[0623] 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).

[0624] 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.

[0625] 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.

[0626] 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.

[0627] 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.

[0628] 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.

[0629] 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.

[0630] 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".

[0631] The system for implementing the present invention consists of three main components: a server, a terminal, and a user. This system is designed to support the employment of persons with disabilities and provides processes to support appropriate work tailored to the characteristics of persons with disabilities.

[0632] The user first enters information about their disability characteristics into a terminal. This information includes comprehension level, work speed, and attention span. The entered information is sent from the terminal to a server, which analyzes it and stores it in a database.

[0633] Next, multiple simple tasks collected from the company via terminals are transferred to a server. The server organizes these tasks and stores characteristic information about each task in a database. Examples of such tasks include data entry that requires repetitive input and file organization that follows a set procedure.

[0634] The server assigns tasks to individuals with disabilities based on their specific characteristics. For example, a person with a disability who excels at handling repetitive patterns might be assigned a data management task in a particular format. Task assignment is performed automatically by the server's algorithm.

[0635] Assigned tasks are presented to the user via the terminal as visually simplified instructions. This allows the user to efficiently understand and perform the work. The simplified instructions aid understanding of the task through visual guidance and step-by-step instructions.

[0636] Once the user completes the task, the results are sent from the terminal to the server. The server uses an AI model to verify the results and confirm their accuracy. If inaccurate data is detected, the user is instructed to correct it.

[0637] These processes enable people with disabilities to receive support tailored to their individual characteristics, and allow companies to effectively employ people with disabilities and improve productivity. Specific application examples include data entry when registering new product information in a database and document filing. In both of these tasks, people with disabilities can understand and perform the work in a way that suits their individual characteristics.

[0638] The following describes the processing flow.

[0639] Step 1:

[0640] Users input information about their disability characteristics into a terminal. This includes comprehension level, work speed, and communication skills. The terminal collects the entered data and sends it to a server.

[0641] Step 2:

[0642] The server analyzes the received characteristic information and generates an appropriate profile. This profile takes into account the abilities and characteristics of the person with a disability and is stored in a searchable database.

[0643] Step 3:

[0644] Companies use terminals to submit simple tasks required by various departments within the company to a server. The terminals transfer detailed information about the tasks, such as priority and deadlines, to the server.

[0645] Step 4:

[0646] The server analyzes the received work list and registers the details of each task in the database. Furthermore, it matches each task with the disability profile and selects the appropriate task.

[0647] Step 5:

[0648] The server converts the assigned tasks into visually simplified procedures. This conversion is tailored to the disability's level of understanding and uses visual information and diagrams to create an easy-to-understand format.

[0649] Step 6:

[0650] The terminal displays visualized instructions to the user. The user then uses this information to complete the task.

[0651] Step 7:

[0652] Once the user completes a task, the terminal reports the results to the server. The report includes data on the task's completion status and execution results.

[0653] Step 8:

[0654] The server uses an AI model to verify the received work results and check the accuracy and completeness of the data. If there are any inaccuracies, it will present the user with the items that need correction.

[0655] Step 9:

[0656] The user receives correction instructions, makes the necessary corrections, and then resubmits the work results to the server for verification. This improves the overall accuracy of the work.

[0657] (Example 1)

[0658] 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".

[0659] To expand employment opportunities for people with disabilities, a system is needed that provides them with appropriate tasks tailored to their characteristics and abilities, enabling them to perform their work efficiently. However, traditional methods make it difficult to accurately understand the characteristics of people with disabilities and automatically select and apply tasks based on those characteristics. Furthermore, manual verification of work results is time-consuming, hindering efficient support.

[0660] 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.

[0661] In this invention, the server includes means for inputting characteristic information of persons with disabilities via a terminal, analyzing the characteristic information and storing it in a database; means for organizing multiple simple tasks collected from the organization and maintaining characteristic information for each task in the database; means for automatically selecting the simple tasks using an AI model based on the characteristics of persons with disabilities and presenting the tasks in a format suitable for the persons with disabilities; and means for receiving the results of task execution by the persons with disabilities, automatically verifying them using the AI ​​model, and instructing corrections as necessary. This enables the assignment of tasks suitable for persons with disabilities and rapid verification of the results.

[0662] "Information on the characteristics of persons with disabilities" refers to information about the individual abilities and characteristics of persons with disabilities, such as their comprehension level, work speed, and attention span.

[0663] "Analysis" is the process of understanding characteristics and trends by classifying, comparing, and evaluating data.

[0664] A "database" is an information system that organizes and stores information, allowing it to be efficiently retrieved as needed.

[0665] An "organization" is a company, association, or group formed to achieve a specific purpose.

[0666] "Simple tasks" are defined as work that does not require complex judgment and is performed according to prescribed procedures.

[0667] A "generative AI model" is an artificial intelligence system that learns from large amounts of data and makes appropriate predictions and judgments about new data.

[0668] "Automatic" means that a device or system performs tasks or makes decisions independently, without human intervention.

[0669] A "task" is a specific job or set of tasks that needs to be performed.

[0670] A "terminal" is an electronic device used by a user to input, output, or process information.

[0671] "Verification" is the process of checking whether results and information are accurate and identifying problems as necessary.

[0672] "Correction" refers to correcting errors or deficiencies and restoring the product to its correct state.

[0673] One embodiment of this invention is a system that provides work adaptation based on the characteristics of persons with disabilities. This system operates through the cooperation of a server, terminals, and users. The roles and specific processes of each component are described below.

[0674] First, the user uses a terminal to input information about the person's disability characteristics. This information includes comprehension level, work speed, and attention span. The terminal securely transmits the entered information to a server. This process typically involves hardware such as a personal computer or tablet, and user interface software for inputting the information.

[0675] The server analyzes the received characteristic information and stores it in a database. The database stores characteristic information for all individuals with disabilities, allowing for quick retrieval when needed. The server also organizes simple tasks submitted by the organization and registers them in the database along with their characteristic information. At this stage, data analysis is performed using Python scripts or similar tools.

[0676] A server equipped with a generative AI model selects suitable simple tasks based on the characteristics of individuals with disabilities. The model assigns tasks using specific prompt statements. For example, the AI ​​model might be given a prompt statement such as, "Assign the most suitable user to task type 001." This prompt statement enables optimal task assignment.

[0677] The selected task is presented to the user via the terminal and displayed as a visually simplified work procedure through the user interface. This allows the user to perform the task under instructions in a format that is easiest for people with disabilities to understand.

[0678] Finally, once the user completes the task, the results are sent from the terminal to the server and automatically verified by the AI ​​model. This verification process provides correction instructions as needed.

[0679] This system allows people with disabilities to utilize their abilities in work suited to their characteristics, and enables organizations to achieve efficient and effective employment management.

[0680] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0681] Step 1:

[0682] Users input information about their disability characteristics via a terminal. Specifically, they use the user interface on the terminal to input information such as comprehension level, work speed, and attention span using a keyboard or touchscreen. The input information is prepared as a dataset and transmitted to the server via a secure communication protocol.

[0683] Step 2:

[0684] The server receives characteristic information sent from the terminal and stores it in a database. Python scripts are often used to analyze the received data and check for anomalies. This analyzed data is structured for future searching and processing and stored in the database.

[0685] Step 3:

[0686] Organizations use terminals to input information about light tasks and send it to a server. Specifically, they input job details, including standard procedures and required skills for tasks, from the terminal, and the server stores each task's information in a database.

[0687] Step 4:

[0688] The server uses a generated AI model based on stored characteristic information to automatically assign harmonized tasks. Using the prompt "Assign the best user for task type 001," the AI ​​model selects and assigns the task to the most suitable person with a disability. As a result, a set of assigned tasks is generated.

[0689] Step 5:

[0690] The device displays the tasks assigned to the person with a disability on its screen. The user interface presents task details in a visually simplified manner to help the person with a disability easily understand and perform the tasks. Specifically, icons and step-by-step guides are displayed.

[0691] Step 6:

[0692] The user performs the task according to the instructions displayed on the terminal. Once the task is completed, the user reports the results to the server via the terminal. The result data, including metrics such as completion time and accuracy, is transferred to the server.

[0693] Step 7:

[0694] The server uses a generating AI model to verify the received work results. The AI ​​model automatically evaluates the results and verifies their accuracy. If inaccurate, detailed feedback on areas requiring correction is provided again, and instructions are given to the user via their terminal. This establishes an appropriate feedback system and improves the quality of work.

[0695] (Application Example 1)

[0696] 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".

[0697] There is a need for systems that efficiently support the work of people with disabilities in a way that is tailored to their individual characteristics. It is also important to create an environment where people with disabilities can work in collaboration with consumer-grade equipment and utilize their own strengths. However, current systems lack sufficient mechanisms for automatically assigning appropriate tasks and providing work support based on characteristic information, making it difficult to contribute to improving corporate productivity.

[0698] 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.

[0699] In this invention, the server includes means for inputting and analyzing characteristic information of persons with disabilities; means for organizing multiple simple tasks collected from the work area and storing the specific details of each task in a database; and means for selecting the simple tasks based on the characteristics of persons with disabilities and presenting the tasks in a format suitable for persons with disabilities. As a result, persons with disabilities can more easily perform tasks optimized based on their own characteristics and can efficiently carry out their work in cooperation with consumer electronics.

[0700] "Information on the characteristics of persons with disabilities" refers to information that indicates the individual characteristics of persons with disabilities, such as their comprehension ability, work speed, and level of attention.

[0701] "Multiple simple tasks collected from the work area" refers to repetitive and standardized tasks performed in businesses and homes.

[0702] "Means of presenting tasks" refers to a system that presents tasks selected based on the characteristics of people with disabilities in an appropriate format.

[0703] "Means for automatically verifying execution results" refers to a process that uses AI models or similar tools to determine the accuracy of the results of tasks performed by people with disabilities.

[0704] "Means of collaborative work assistance using consumer-grade equipment" refers to work support systems in which general-purpose equipment such as robots used at home or in the workplace compensates for aspects that are difficult for people with disabilities.

[0705] The system for implementing this invention mainly consists of three main components: a server, a terminal, and a user. A specific example using this system is shown below.

[0706] The server first receives and analyzes information about the characteristics of individuals with disabilities. This information is based on comprehension, work speed, and attention span, and is entered by the user via a terminal. The server stores the received information in a database, then organizes multiple simple tasks collected from the work area and saves the specific details of each task in the database. This process uses the Flask platform developed in Python, and PostgreSQL is used as the database.

[0707] The user terminal not only transmits the entered characteristic information to the server, but also plays a role in visually displaying the tasks sent from the server. This is achieved through a JavaScript-based UI, where visually simplified information is presented in a format suitable for people with disabilities.

[0708] Once the user completes the task, the results are sent back to the server via the terminal. The server automatically verifies these results using an AI model and instructs corrections as needed. TensorFlow is used as the AI ​​model to evaluate the accuracy of the execution results.

[0709] Furthermore, the system works in conjunction with consumer electronics (such as robots) to ensure that people with disabilities receive support tailored to their specific needs. Robots can assist with specific tasks in homes and workplaces, enabling people with disabilities to perform their duties in a way that maximizes their strengths.

[0710] As a concrete example, when inputting information about the characteristics of a person with a disability, a prompt such as "Explain how the AI ​​system installed in the household support robot can automatically assign appropriate tasks (e.g., sorting kitchen items) based on the characteristics of a specific user and work collaboratively" is used. Based on this prompt, the generated AI model performs optimal task assignment and enables collaborative work.

[0711] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0712] Step 1:

[0713] The user inputs their characteristic information via a terminal. This input includes comprehension, work speed, and attention span. The terminal sends this information as input to the server. The server stores the received information in a database and retains it as data necessary for subsequent processing based on the user's characteristics.

[0714] Step 2:

[0715] The server organizes information from businesses and households regarding simple tasks. This information consists of repetitive tasks such as data entry and document organization, and the server registers the specific details of these tasks in a database. This database serves as the foundational data for later task assignments.

[0716] Step 3:

[0717] The server uses a generated AI model to select the optimal task based on user characteristic information and work information in the database. This task selection process uses prompts, allowing the AI ​​model to automatically determine tasks suitable for users with disabilities. The selected tasks are presented with user characteristics in mind, and therefore, ease of execution is paramount.

[0718] Step 4:

[0719] The terminal visually presents tasks sent from the server to the user. The presented information consists of simplified procedures tailored to the user's characteristics, including visual guides and step-by-step instructions to aid understanding. This allows the user to easily grasp the task content and begin working.

[0720] Step 5:

[0721] When a user completes a task, the results are sent from the terminal to the server. The server automatically verifies the received results based on the generating AI model and evaluates the accuracy of the results. In this evaluation step, the input data is compared with accurate baseline data, and if there is any inaccuracy, the server sends correction instructions to the terminal.

[0722] Step 6:

[0723] The server will work in conjunction with consumer electronics to provide further support to people with disabilities. Specifically, it envisions scenarios where devices such as robots assist users, providing support for difficult parts of task completion. Through this collaborative work, users can leverage their own strengths while receiving assistance to successfully complete tasks.

[0724] 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.

[0725] This invention aims to improve work efficiency and user comfort in an employment support system for people with disabilities by incorporating an emotion engine. This system consists of a server, terminals, and users, and the addition of the emotion engine enhances the functionality of each component.

[0726] The user first inputs information about the characteristics of the person with a disability through a terminal. This information includes characteristics such as comprehension, work speed, and emotional response. The terminal sends this information to a server, which analyzes it and stores it in a database.

[0727] Companies use terminals to submit lists of simple internal tasks to a server. These lists include task details, importance, and deadlines, which the server then organizes and stores in a database.

[0728] The server matches the characteristics of the person with a disability with the work content, selects an appropriate task, and presents it to the user via the terminal. A key feature here is that the emotion engine analyzes the user's real-time emotional state and adaptively adjusts the task presentation method. For example, if the user is feeling stressed, the complexity of the task is reduced and converted into simple visual instructions.

[0729] Users perform tasks and report the results to the server via their terminal. The server uses an AI model to verify the results and instructs corrections if any inaccuracies are found. Furthermore, an emotion engine monitors the user's emotional changes and generates alerts if anomalies are detected, prompting improvements to the work environment.

[0730] As a concrete example, the emotion engine analyzes the user's camera footage and audio data to identify emotions such as joy, anger, and anxiety in real time. Based on this information, it dynamically adapts by presenting tasks when the user is relaxed and recommending rest when they are stressed.

[0731] In this way, this system provides an optimal work environment for people with disabilities, maximizing their work performance capabilities while improving productivity within companies. This is expected to improve both the quality and quantity of employment, leading to sustainable employment support.

[0732] The following describes the processing flow.

[0733] Step 1:

[0734] The user inputs information about the individual's disability characteristics into the terminal. This information includes profiles of comprehension, work speed, and emotional response. The terminal then transmits the entered information to the server.

[0735] Step 2:

[0736] The server analyzes the characteristic information received from the terminal and generates a profile based on the characteristics of the person with a disability. These profiles are stored in a database and used for subsequent task assignment.

[0737] Step 3:

[0738] Companies send a list of simple tasks they want to perform via their terminals to a server. This list includes the specific tasks, their importance, and deadlines. The server registers this information in a database.

[0739] Step 4:

[0740] The server matches the profile of the person with a disability with the received list of simple tasks and performs a process to select appropriate tasks. The selected tasks are presented in a way that suits the user's characteristics.

[0741] Step 5:

[0742] The emotion engine uses the device to recognize the user's real-time emotional state. For this purpose, the user's camera video and audio data are analyzed. Based on these emotions, the way tasks are presented is adjusted.

[0743] Step 6:

[0744] The device presents the user with visually simplified instructions adjusted by an emotion engine. For example, if the user is feeling stressed, it uses simplified displays and softer colors.

[0745] Step 7:

[0746] The user performs the task by following instructions provided via the terminal. The results are reported from the terminal to the server.

[0747] Step 8:

[0748] The server verifies the reported task results using an AI model to confirm their accuracy. If necessary, it returns specific correction instructions to the user via the terminal.

[0749] Step 9:

[0750] The emotion engine continuously monitors the user's emotional state during work and generates alerts if significant emotional anomalies are detected. This information is communicated to the user and company administrators to encourage improvements to the work environment.

[0751] (Example 2)

[0752] 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".

[0753] In employing people with disabilities, it is essential to optimize the process of assigning and executing tasks, taking into full consideration their characteristics and emotional states. Without this optimization, the abilities of the individuals with disabilities may not be fully utilized, and employers may experience decreased productivity. Furthermore, considering that emotional states directly impact work efficiency and effectiveness, there is a need for real-time sentiment analysis and adaptive task presentation.

[0754] 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.

[0755] In this invention, the server includes a device for inputting and analyzing information based on the characteristics of persons with disabilities, a device for organizing multiple tasks collected from the organization and storing the specific details of each task in a data storage device, and a device for analyzing emotional states in real time and dynamically adapting the method of presenting tasks. This makes it possible to assign optimal tasks according to the characteristics of persons with disabilities and to adaptively present tasks according to their emotional states.

[0756] A "person with a disability" is an individual who has physical, intellectual, or mental limitations and requires special consideration or support.

[0757] "Characteristic information" refers to data about the individual abilities and characteristics of people with disabilities, such as comprehension, work speed, and emotional response.

[0758] An "organization" is a group of people, such as a company or a group of businesses, that carry out business operations, and is the entity that manages the business processes within that group.

[0759] "Business operations" refers to the collective term for specific activities and tasks performed by members within an organization.

[0760] A "data storage device" refers to a system or equipment for safely and efficiently storing information and data.

[0761] "Emotional state" refers to the emotional reactions or psychological conditions that an individual exhibits in specific situations, such as joy, anger, or stress.

[0762] "Analysis" is the process of breaking down complex information or data and examining its constituent elements in detail.

[0763] "Job assignment" refers to the act of providing an individual or group with specific job duties and instructions on how to carry them out.

[0764] This invention is a system that supports the employment of people with disabilities, and the program operates based on information input and analysis from a server, terminals, and users. The server has a data analysis engine that processes characteristic information of people with disabilities input from users via terminals and stores that data in a data storage device using a database management system (DBMS). This uses general database software and an AI analysis module.

[0765] Users input characteristic information about individuals with disabilities, such as their comprehension level, work speed, and emotional responses, through a terminal. The terminal sends this information to a server, which then uses that information to select the most suitable tasks for the individuals with disabilities.

[0766] The server uses a generative AI model to match a list of tasks collected from within the organization with the characteristics of individuals with disabilities, thereby matching them with the most suitable tasks. The task list is entered from a terminal and analyzed and organized by the server. In particular, the emotion engine analyzes the user's real-time emotional state and dynamically adjusts how tasks are presented. For example, the emotion engine analyzes the user's facial expressions and voice data obtained through the camera and microphone to determine whether the user is relaxed or stressed.

[0767] For example, if the user is relaxed, the server will present normal tasks, but if it detects that the user is stressed, the server will simplify the tasks and provide visually simplified instructions. Another example of a prompt message would be: "Based on the characteristics of the person with a disability and the company's operations, please suggest the most suitable tasks. The current emotional state is stressed."

[0768] This system not only optimizes task assignments for users but also enables task presentations that take into account their real-time emotional state, thereby supporting the efficient and comfortable work performance of people with disabilities.

[0769] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0770] Step 1:

[0771] Users input characteristic information about individuals with disabilities, such as their comprehension level, work speed, and emotional responses, through a terminal. The terminal converts this information into the correct format and sends it to the server. This characteristic information is important because it is used later for job matching and sentiment analysis, and the server supplies the received information to the data analysis engine.

[0772] Step 2:

[0773] The server analyzes the characteristic information submitted by the user based on its data analysis engine. During this process, the data is organized and classified based on the characteristics of each individual with a disability. The analysis results are stored in a data storage device via a database management system (DBMS) and serve as reference data for subsequent task selection.

[0774] Step 3:

[0775] Companies use terminals to input a list of tasks within their organization and send it to a server. The list includes details of the tasks, their importance, and deadlines. The terminals format the task lists appropriately and transfer them to the server. The server stores the received task lists in a database and uses them in the task matching process.

[0776] Step 4:

[0777] The server uses a generated AI model to compare disability characteristics information stored in the database with a list of tasks. In this process, the AI ​​model compares characteristics with task requirements and selects the most suitable task. The selected task is sent from the server to the terminal and presented to the user.

[0778] Step 5:

[0779] The server activates the emotion engine to analyze real-time emotional state data obtained from the terminal. It analyzes video and audio data acquired by the user via the terminal's camera and microphone to identify emotions such as joy, anger, and stress. This emotional state data is used to adjust the way tasks are presented.

[0780] Step 6:

[0781] Based on the analysis results of the emotion engine, the server determines how to present tasks according to the user's emotional state. For example, if the user is feeling stressed, the server simplifies the task content and displays it on the terminal in a visually easy-to-understand format. By tailoring the display method to the user's emotions, the efficiency of task execution is improved.

[0782] Step 7:

[0783] The user uses a terminal to perform the assigned tasks and reports the results to the server upon completion. The terminal formats the user's input and sends it to the server. The server reviews the report using a generative AI model and issues correction instructions if the report is inaccurate.

[0784] Step 8:

[0785] The server continuously monitors changes in the user's emotions using an emotion engine. If an abnormal emotional state is detected, it generates an alert and provides instructions for improving the work environment. This continuous monitoring aims to enhance user comfort and work efficiency.

[0786] (Application Example 2)

[0787] 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".

[0788] A major challenge in modern work environments is the lack of systems that enable people with disabilities to efficiently perform tasks suited to their individual characteristics. Furthermore, there are insufficient methods to reduce mental stress during work and provide a comfortable working environment. Additionally, there is a need for a system that can monitor users' emotional changes in real time during work and adapt accordingly.

[0789] 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.

[0790] In this invention, the server includes means for acquiring and analyzing attribute information of persons with disabilities; means for collecting work sets from within the organization and storing the specific details of each work in an information storage location; means for selecting the work based on the attributes of persons with disabilities and presenting the tasks in a format suitable for those persons with disabilities; and means for analyzing the user's emotional state in real time using an emotion analysis device and dynamically optimizing the task presentation method. This makes it possible not only for persons with disabilities to select the most suitable work, but also to provide a consistently comfortable working environment.

[0791] "Attribute information of persons with disabilities" refers to data that includes characteristics such as the comprehension level, work speed, and emotional response of individuals with disabilities.

[0792] A "work set" refers to a collection of multiple simple tasks or routines required within a company or organization.

[0793] An "information repository" is a database or recording medium used to store specific details of each task, attribute information of people with disabilities, and so on.

[0794] "Task presentation methods" refer to techniques for communicating tasks and work content to people with disabilities in the most appropriate format.

[0795] An "emotion analysis device" is a device or software that analyzes a user's emotional state in real time and makes appropriate changes to the work environment or proposed tasks.

[0796] This invention is a system that allows people with disabilities to select the most suitable tasks based on their individual characteristics and improve their comfort while working.

[0797] The server first receives attribute information of individuals with disabilities and analyzes it. This includes data such as the individual's comprehension level, work speed, and emotional responses, which are entered via a terminal. Next, the server organizes the sets of tasks collected from within the company and stores the specific details of each task in an information repository. This allows for the selection of tasks suitable for each individual with a disability.

[0798] An emotion analysis device is used to analyze the user's emotional state in real time. This analysis utilizes the user's camera video and audio data, and an emotion analysis AI determines the user's emotions. If the system determines that the user is experiencing stress, it dynamically optimizes the task presentation method, adjusting the complexity of the task or providing visually simpler instructions.

[0799] Furthermore, an emotion analysis device monitors changes in the user's emotions during work and generates alerts to prompt appropriate responses if an anomaly is detected. As part of this process, a generative AI model is used to perform real-time emotion assessment and adaptation.

[0800] As a concrete example, the server sends a prompt to the emotion analysis AI saying, "Evaluate my stress level based on what I'm saying now and suggest advice that will help me relax," which then generates appropriate feedback. This reduces the user's mental burden and improves task efficiency.

[0801] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0802] Step 1:

[0803] The terminal inputs attribute information of the user, who is a person with a disability. This input information includes comprehension level, work speed, and emotional response. This data is sent to the server, which stores this information in a database. Based on the input attribute information, the server builds the basic data for selecting the most suitable task for the user.

[0804] Step 2:

[0805] The server organizes task sets collected from within the company. It stores information such as the specific content, importance, and deadline for each task in a database. This allows for matching user attribute information with the task set data, preparing the system for selecting appropriate tasks.

[0806] Step 3:

[0807] The server uses a generative AI model to match user attribute information with task sets. The input consists of attribute and task information from the database, and the output is a list of tasks suitable for the user. These tasks are then presented to the user's terminal in a format tailored to them, prompting them to complete the tasks.

[0808] Step 4:

[0809] Using an emotion analysis device, the server analyzes the user's emotional state in real time. Receiving camera video and audio data as input, the emotion analysis AI identifies emotions such as joy, anger, and anxiety. If the user is experiencing stress, dynamic adjustments are made. Specifically, this might involve lowering the difficulty of the task or providing visually clearer instructions.

[0810] Step 5:

[0811] Users complete the assigned tasks and report their results via their devices. The server receives these results and automatically evaluates them using a generative AI model. If there are any inaccuracies, the server generates correction instructions to help improve future task assignments.

[0812] Step 6:

[0813] The server continuously uses an emotion analysis device to monitor the user's emotional changes. Based on the analysis results, it generates an alert when an anomaly is detected and provides appropriate feedback to the user. Specific actions include playing relaxing music or suggesting a break.

[0814] 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.

[0815] 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.

[0816] 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.

[0817] 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.

[0818] 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.

[0819] 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.

[0820] 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.

[0821] 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.

[0822] 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."

[0823] 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.

[0824] 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.

[0825] 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.

[0826] 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.

[0827] 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.

[0828] 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.

[0829] 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.

[0830] 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.

[0831] 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.

[0832] 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.

[0833] 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.

[0834] 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.

[0835] The following is further disclosed regarding the embodiments described above.

[0836] (Claim 1)

[0837] A means for inputting characteristic information of persons with disabilities and analyzing said characteristic information,

[0838] A means of organizing multiple simple tasks collected from within a company and storing the specific details of each task in a database,

[0839] A means for selecting the simple task based on the characteristics of the person with a disability and presenting the task in a format suitable for the person with a disability,

[0840] A means for receiving the results of a task performed by the person with a disability, automatically verifying those results, and instructing corrections as necessary,

[0841] A system that includes this.

[0842] (Claim 2)

[0843] The system according to claim 1, further comprising means for visually simplifying and displaying work procedures.

[0844] (Claim 3)

[0845] The system according to claim 1, further comprising means for monitoring the execution status of a task in real time and reporting its progress.

[0846] "Example 1"

[0847] (Claim 1)

[0848] A means for inputting characteristic information of persons with disabilities via a terminal, analyzing said characteristic information, and saving it to a database,

[0849] A means of organizing multiple simple tasks collected from an organization and storing characteristic information of each task in a database,

[0850] A means for automatically selecting the simple task based on the characteristics of the person with a disability using an AI model, and presenting the task in a format suitable for the person with a disability,

[0851] A means for receiving the results of a task performed by the person with a disability, automatically verifying them using the AI ​​model, and instructing corrections as necessary,

[0852] A system that includes this.

[0853] (Claim 2)

[0854] The system according to claim 1, further comprising means for visually simplifying work procedures and displaying them through a terminal.

[0855] (Claim 3)

[0856] The system according to claim 1, further comprising means for monitoring the execution status of a task in real time and reporting its progress.

[0857] "Application Example 1"

[0858] (Claim 1)

[0859] A means for inputting characteristic information of persons with disabilities and analyzing said characteristic information,

[0860] A means of organizing multiple simple tasks collected from the work area and storing the specific details of each task in a database,

[0861] A means for selecting the simple task based on the characteristics of the person with a disability and presenting the task in a format suitable for the person with a disability,

[0862] A means for receiving the results of a task performed by the person with a disability, automatically verifying those results, and instructing corrections as necessary,

[0863] A means of providing collaborative assistance for work using consumer-grade equipment and offering support tailored to the characteristics of people with disabilities,

[0864] A system that includes this.

[0865] (Claim 2)

[0866] The system according to claim 1, further comprising means for visually simplifying and displaying work procedures.

[0867] (Claim 3)

[0868] The system according to claim 1, further comprising means for monitoring the execution status of a task in real time and reporting its progress.

[0869] "Example 2 of combining an emotion engine"

[0870] (Claim 1)

[0871] A device that inputs information based on the characteristics of persons with disabilities and analyzes said information,

[0872] A device that organizes multiple tasks collected from an organization and stores the specific details of each task in a data storage device,

[0873] A device that selects tasks based on the characteristics of persons with disabilities and presents those tasks in a format suitable for those persons with disabilities,

[0874] A device that receives the results of work performed by the disabled person, automatically verifies those results, and instructs corrections as necessary,

[0875] A device that analyzes emotional states in real time and dynamically adapts the method of presenting tasks,

[0876] A system that includes this.

[0877] (Claim 2)

[0878] The system according to claim 1, further comprising a device for visually simplifying and displaying work procedures.

[0879] (Claim 3)

[0880] The system according to claim 1, further comprising a device for monitoring the status of work execution in real time and reporting progress.

[0881] "Application example 2 when combining with an emotional engine"

[0882] (Claim 1)

[0883] A means for acquiring attribute information of persons with disabilities and analyzing said attribute information,

[0884] A means of collecting work sets from within the organization and storing the specific details of each work in an information repository,

[0885] A means of selecting the task based on the attributes of the person with a disability and presenting the task in a format suitable for the person with a disability,

[0886] A means for receiving the results of the task performed by the person with the disability, automatically evaluating those results, and instructing corrections as necessary,

[0887] A means of dynamically optimizing the method of presenting tasks by analyzing the user's emotional state in real time using an emotion analysis device,

[0888] A system that includes this.

[0889] (Claim 2)

[0890] The system according to claim 1, further comprising means for adjusting the work environment based on the user's emotional state to reduce mental burden.

[0891] (Claim 3)

[0892] The system according to claim 1, further comprising means for monitoring emotional changes during task performance and generating an alarm when an anomaly is detected. [Explanation of symbols]

[0893] 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. A means for inputting user characteristic information and analyzing said characteristic information, A means of organizing multiple simple tasks collected from within a company and storing the specific details of each task in a database, A means for selecting the simple task based on the user's characteristics and presenting the task in a format suitable for the user, A means for receiving the results of the task performed by the user, automatically verifying those results, and instructing corrections as necessary, A system that includes this.

2. The system according to claim 1, further comprising means for visually simplifying and displaying work procedures.

3. The system according to claim 1, further comprising means for monitoring the execution status of tasks in real time and reporting progress.

Images