system

Abstract

We provide the system. [Solution] A system that utilizes an information network to enable collaborative work in which multiple users participate via terminals accessible from different locations, A means for receiving user authentication data and identifying attributes, A means of adjusting work assignments and generating instructions based on the attributes of each user using machine learning, A means of constructing an augmented reality environment and displaying synchronized information among users, A means to continuously monitor the user's progress and propose countermeasures when problems occur, A means of providing an optimized work schedule through machine learning and providing operational guidance via augmented reality display, 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 persona chatbot control method 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 maintenance and manufacturing processes in enterprises, it is difficult for multiple technicians to work efficiently in cooperation from geographically separated locations. In particular, it is difficult to perform appropriate work sharing according to the skills of each technician and real-time progress management. As a result, there are problems such as a decrease in work efficiency and a delay in the response speed in an emergency.

Means for Solving the Problems

[0005] The present invention provides a system that enables multiple users to share tasks based on their respective roles and synchronize information in real time through an augmented reality environment, using artificial intelligence technology via a device accessible from different geographical locations. This system includes means for receiving user authentication information, means for generating work instructions using artificial intelligence, means for constructing an augmented reality environment, and means for monitoring user progress and immediately proposing countermeasures when problems occur.

[0006] A "user" is a technician who participates in the system and collaborates with others through a device.

[0007] A "device" is an electronic device that a user uses to access a system and utilize an augmented reality environment.

[0008] "Artificial intelligence" is a computer programming technology used to coordinate the division of labor among users and generate work instructions.

[0009] An "augmented reality environment" is an interface that overlays real-world information with virtual information and presents it to the user.

[0010] A "role" refers to the tasks and responsibilities that a user should perform within the system.

[0011] "Work allocation" is a plan aimed at efficiently distributing tasks among multiple users.

[0012] "Information synchronization" is the process of updating and matching data and progress shared by different users within a system in real time.

[0013] "Progress status" refers to an indicator that shows the status and progress of the work that the user is responsible for.

[0014] "Countermeasures" refer to solutions or actions proposed by artificial intelligence in response to problems that arise during the process. [Brief explanation of the drawing]

[0015] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

Embodiments for Carrying Out the Invention

[0016] Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0017] First, the terms used in the following description will be explained.

[0018] In the following embodiments, the numbered 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.

[0019] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0020] In the following embodiments, the numbered 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, and the like.

[0021] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0022] 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."

[0023] [First Embodiment]

[0024] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0025] 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.

[0026] 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).

[0027] 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.

[0028] 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.

[0029] 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.

[0030] 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.

[0031] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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".

[0036] To implement this invention, a central server must first be connected to multiple terminals via the internet. Users can connect to the server and participate in the system using a terminal equipped with a dedicated application. When a user logs in, the server authenticates the user and generates appropriate work instructions based on their skills and role.

[0037] The server is equipped with an artificial intelligence module that analyzes users' skills, roles, and past performance to determine the optimal task allocation. The AI ​​monitors each user's progress in real time and updates work instructions as needed. This allows the system to maintain an efficient workflow.

[0038] The device provides users with digital information related to the physical environment being accessed through an augmented reality display. For example, virtual guidelines or 3D models are overlaid on real-world equipment, allowing users to intuitively understand and perform the necessary tasks.

[0039] Users utilize this augmented reality environment to share the same virtual workspace with other engineers. This allows users to easily communicate and coordinate with other members while performing their own tasks. Furthermore, if problems arise, the server provides users with rapid solutions based on artificial intelligence analysis.

[0040] As a concrete example, consider the maintenance of a manufacturing line. User A is responsible for the physical inspection of equipment and checks its status via a terminal. User B performs software inspections remotely and analyzes anomalies using real-time data provided by a server. Both users exchange information in an augmented reality environment and work together to solve problems based on work procedures recommended by artificial intelligence.

[0041] In this way, the system in the invention enables efficient and effective collaborative work that transcends geographical constraints, and allows for the optimization of corporate processes.

[0042] The following describes the processing flow.

[0043] Step 1:

[0044] The server receives an access request from the user and verifies the user's authentication information. If authentication is successful, the server assigns the user a unique session ID and initializes the connection.

[0045] Step 2:

[0046] Users log in via their terminals and retrieve role information sent from the server. Based on this information, the terminals prepare a work environment that matches the skills and responsibilities of each technician.

[0047] Step 3:

[0048] An artificial intelligence module on the server analyzes each user's role and skills to determine efficient task allocation. The determined tasks are then sent from the server to the terminals as work instructions.

[0049] Step 4:

[0050] The terminal displays work instructions received from the server on an augmented reality display, overlaying virtual information onto the real world and providing it to the user. This allows the user to intuitively understand the instructions.

[0051] Step 5:

[0052] The user follows instructions and performs tasks in an augmented reality environment. As the user works, the device sends progress data to the server in real time.

[0053] Step 6:

[0054] The server aggregates the received progress data, and artificial intelligence evaluates the progress and any problems. If necessary, it creates appropriate countermeasures and sends them back to the terminal to update the instructions.

[0055] Step 7:

[0056] When a user completes a task, the terminal reports its completion status to the server and sends logs and feedback information. The server saves this data and uses it for the next project.

[0057] (Example 1)

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

[0059] In modern workplaces, multiple engineers and workers located in geographically separated areas need to collaborate to complete tasks. However, traditional systems often suffer from insufficient information sharing and communication, leading to decreased work efficiency. Furthermore, determining the optimal division of labor based on each worker's skills and roles is difficult, hindering process optimization. In addition, a lack of real-time monitoring of progress and prompt response measures can lead to delays in appropriate responses when problems arise.

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

[0061] In this invention, the server includes means for adjusting work assignments and generating instructions based on each user's role using intelligent functions, means for constructing a virtual reality environment and displaying synchronized information among users, and means for analyzing users' past performance using a generated AI model and determining the optimal task assignment. This enables efficient collaborative work among geographically dispersed workers, as well as real-time progress monitoring and rapid problem solving.

[0062] "User" refers to an individual or organization that operates specialized equipment to perform tasks using the system.

[0063] "Information processing equipment" refers to computer-related devices used for inputting, processing, and outputting digital data.

[0064] A "computer network" refers to a digital communication system in which multiple computers are connected to enable them to communicate with one another.

[0065] "Authentication information" refers to data used by users to identify themselves when accessing a system.

[0066] "Intelligent function" refers to artificial intelligence technology that analyzes user data and circumstances to make decisions and generate instructions.

[0067] A "virtual reality environment" refers to a system that allows users to visualize the real world overlaid with digital information.

[0068] "Progress data" refers to information that shows the progress of a task and is analyzed for the next processing step.

[0069] A "generative AI model" refers to a machine learning algorithm used to support predictions and decision-making based on historical data.

[0070] To implement this invention, a server must first be connected to multiple information processing devices via a computer network. The server is equipped with intelligent functions and receives user authentication information to identify roles. This allows the server to use a generative AI model to determine the optimal work assignment and generate instructions based on each user's skills and past performance. To build such a system, it is recommended to use general-purpose server hardware and a software framework for implementing machine learning algorithms (e.g., TENSORFLOW®, PyTorch).

[0071] The terminal acts as an information processing device, receiving work instructions from the server and displaying them to the user. Furthermore, the terminal overlays virtual information onto the physical world through a virtual reality environment. This operation requires display technology to realize augmented reality (e.g., AR glasses) and software libraries to display the necessary information (e.g., ARKit, ARCore).

[0072] Users can log into the system and work within a virtual reality environment. This allows users to efficiently complete their tasks and collaborate with other users to solve problems while sharing information. As a result, the system enables highly efficient collaborative work, independent of specific geographical locations.

[0073] As a concrete example, consider maintenance work in the manufacturing industry. When a user inspects equipment, the server sends instructions with virtual guidelines superimposed on the terminal, allowing the user to perform the work accordingly. If an anomaly is detected, the server can use its intelligent functions to conduct a detailed analysis and immediately suggest appropriate countermeasures.

[0074] An example of a prompt would be an instruction such as, "Please suggest the optimal task allocation required for manufacturing line maintenance." This prompt would prompt the generating AI model to suggest appropriate task allocations based on the user's role and situation. In this way, it becomes possible to construct concrete means for implementing the invention.

[0075] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0076] Step 1:

[0077] The server receives user authentication information as input and performs authentication by comparing it with the database. If authentication is successful, the server outputs user role and skill information. This process involves data processing, such as comparing authentication information like user ID and password with an internal database.

[0078] Step 2:

[0079] The server uses the acquired role and skill information as input to determine appropriate work assignments using a generating AI model. This process involves analyzing past performance data, assigning the most suitable tasks to each user, and generating work instructions. This output appears as specific work instructions sent to the terminals.

[0080] Step 3:

[0081] The terminal processes work instructions received from the server as input and outputs them to the user as visual information via an augmented reality display. Here, data processing is performed to overlay it onto the physical world, displaying specific work areas and procedures. Virtual information is provided so that the user can intuitively understand the real environment.

[0082] Step 4:

[0083] Users proceed with their work based on virtual information provided through their terminal. They provide information about their work progress and any problems that occur as input to the terminal, which then sends this information to the server. This output functions as real-time progress reporting and problem logging.

[0084] Step 5:

[0085] The server analyzes progress and problem reports from users as input and uses intelligent functions to suggest solutions. It updates work instructions as needed and sends the new instructions to the terminal. The final output provides the user with specific operations and procedures to perform in the next stage.

[0086] (Application Example 1)

[0087] 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."

[0088] In modern manufacturing environments, processes involving multiple workers and machines are becoming increasingly complex. Therefore, traditional methods struggle to efficiently adjust task allocation based on each worker's skills and roles, leading to delays, errors, and even decreased efficiency. Furthermore, real-time monitoring of work status and rapid response to problems are crucial. Consequently, a system is needed to address these challenges and improve overall factory efficiency through partially automated processes.

[0089] 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.

[0090] In this invention, the server includes means for receiving user authentication data and identifying attributes, means for adjusting work assignments and generating instructions based on each user's attributes using machine learning, and means for constructing an augmented reality environment and displaying synchronized information among users. This enables each worker to perform tasks efficiently and solve problems in real time, regardless of their location.

[0091] "Users" refers to individuals or groups who participate in this system and perform tasks based on their roles.

[0092] A "terminal" refers to a device used by a user to access a system and obtain or input information.

[0093] "Authentication data" refers to information necessary to identify a user and is used for security and role setting purposes.

[0094] "Machine learning" is a method for systems to adaptively learn through data analysis and generate optimal work instructions for individual users.

[0095] "Attributes" refer to characteristics such as a user's skills, experience, and role, and are used for appropriate task assignment.

[0096] "Task assignment" is the process of assigning tasks that are suitable for the user's attributes.

[0097] "Instructions" are pieces of information that indicate the specific actions necessary to carry out a task.

[0098] An "augmented reality environment" is a technology that overlays digital information onto the real-world visual environment, providing intuitive and easy-to-understand work support for users.

[0099] "Synchronized information" refers to information that is unified in real time so that multiple users can see the same data and progress.

[0100] "Progress status" refers to the degree of completion and status of tasks performed by users, and is monitored by the system in real time.

[0101] "Problem resolution measures" refer to the solutions or instructions that the system provides when a problem arises in the work process.

[0102] To realize this invention, the server first receives user authentication data and identifies the attributes of each user. Multi-factor authentication is employed to ensure security. Based on this information, the server uses a machine learning model to adjust the most suitable work assignment for each user and then generates work instructions. This maintains an optimal process flow.

[0103] The device provides services within the user's physical environment. Specifically, it uses an augmented reality (AR) display. This AR functionality is implemented using a software platform like Unity, overlaying user-operable virtual data onto the real world. Users can, for example, view necessary instructions and guidelines in real time using a smartphone or augmented reality headset.

[0104] Users receive work instructions sent from the server via their terminals and perform tasks based on them. Progress is monitored in real time, and the server detects problems as needed. If a problem occurs, the server uses machine learning to analyze it and proposes quick and optimal solutions to the user.

[0105] As a concrete example, consider a parts assembly process in a factory. When a user puts on an AR headset, a list of necessary parts and assembly instructions are displayed in their field of view. The server then automatically optimizes the next step based on the user's progress and sends new instructions immediately.

[0106] Examples of prompt messages are as follows:

[0107] "Please tell me how to use AI to optimize factory robot work schedules and provide work guidance using AR technology."

[0108] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0109] Step 1:

[0110] The server receives authentication data sent from the terminal as input and authenticates the user. This input data includes user ID and password, or biometric authentication information. Once authentication is successful, the server retrieves the user's attribute information from the database and generates a user profile as output. This profile includes roles, skill sets, and past work history.

[0111] Step 2:

[0112] The server uses machine learning algorithms to calculate the optimal task assignment based on each user's profile as input data. As part of the data processing, it first analyzes the profile data to generate a user skill matrix. Based on this, it generates appropriate work instructions and designs the next work step as output. It also utilizes a generative AI model to create situation-sensitive prompts.

[0113] Step 3:

[0114] The server sends work instructions to the terminal. The terminal then converts the received work instruction data into an augmented reality (AR) display. Specifically, it overlays virtual guidelines onto the user's physical environment based on the instruction data. This allows the user to intuitively and visually understand the next work step.

[0115] Step 4:

[0116] The user performs the assigned task while referring to the AR display. They periodically report their work progress to the server via their device as input data. The server monitors the progress data in real time and records the updated work status in a database as output.

[0117] Step 5:

[0118] The server uses machine learning models to analyze progress data collected in real time, and when problems arise, it proposes the optimal solution to the user. By utilizing generative AI models to output immediate prompts, users can quickly move on to the next task.

[0119] Step 6:

[0120] The user continues working based on the proposed solution. The server receives the final work output as input and stores it in the output database. This data is later analyzed to improve future work plans.

[0121] 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.

[0122] This invention combines an emotion engine with a system in which multiple users collaborate via a computer network to recognize the emotional state of users in real time and dynamically adjust work instructions and the environment. The system consists of a central server, user terminals, and an emotion engine as its main components.

[0123] The server connects to multiple terminals via the network and, after receiving authentication information from each user, generates work instructions based on the user's skills and role. The artificial intelligence assigns tasks optimally according to each user's role and sends those instructions from the server.

[0124] The terminal presents the user with an augmented reality environment based on instructions received from the server. Through the augmented reality display, the physical work environment and virtual work instructions are overlaid, allowing the user to intuitively proceed with their tasks. The terminal also incorporates an emotion engine that recognizes the user's emotional state through the camera and voice input, and transmits this data to the server. The emotion engine determines the user's stress level and concentration level from their facial expressions and tone of voice, dynamically changing the presence and content of work instructions accordingly.

[0125] Users work while utilizing the augmented reality environment provided by their device. Work instructions are adjusted based on recognized emotions, allowing users to perform tasks efficiently while reducing their burden. For example, in a machine assembly task, if the user is feeling stressed, the system can simplify the task or provide messages to encourage relaxation.

[0126] The server continuously monitors user progress and emotional data, performing data analysis to improve overall work efficiency. The analysis results are fed back into the next work plan and used to optimize the work environment for each user. In this way, the system takes into account the user's emotional state, enabling flexible instruction adjustments and creating a more effective collaborative work environment.

[0127] The following describes the processing flow.

[0128] Step 1:

[0129] The server receives a login request from a user and initiates the authentication process. It verifies the authentication information entered by the user and identifies the role and skills information corresponding to that user.

[0130] Step 2:

[0131] The terminal sets up the augmented reality environment based on the user's role information received from the server. The terminal loads the necessary virtual content and prepares to overlay the virtual information onto the physical environment that the user is accessing.

[0132] Step 3:

[0133] The server's artificial intelligence analyzes each user's role, skills, and progress data to determine appropriate work instructions and task assignments. The determined work instructions are then sent from the server to the relevant terminals.

[0134] Step 4:

[0135] The terminal displays work instructions received from the server on an augmented reality display, providing the user with an intuitive work guide. Furthermore, an emotion engine built into the terminal analyzes the user's facial expressions and voice in real time to evaluate their emotional state.

[0136] Step 5:

[0137] The user receives adjustments to the work instructions provided by the device based on their emotional state, which is assessed by the emotion engine. For example, if the user indicates a high stress level, the device may simplify the work procedure or display a message prompting them to take a break.

[0138] Step 6:

[0139] The server monitors progress and sentiment data transmitted from terminals in real time and analyzes each user's work status. If a problem is detected, the server immediately derives a solution and sends that information to the relevant terminal.

[0140] Step 7:

[0141] Once a user completes a task, the terminal reports the results to the server. The server collects data on completed tasks and sentiment feedback, and analyzes it to help improve future projects.

[0142] (Example 2)

[0143] 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".

[0144] Current collaborative work systems suffer from insufficient adjustment of dynamic work instructions based on user emotions, and are unable to provide appropriate support according to user stress levels and concentration levels. Furthermore, while it is necessary to consider emotional states in real time to improve work progress and efficiency, systems with such functionality are limited.

[0145] 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.

[0146] In this invention, the server includes means for receiving user authentication information and identifying roles, means for using artificial intelligence to adjust work assignments based on each user's role and generate instructions, and means for recognizing the user's emotional state in real time using an emotion analysis device and generating and dynamically adjusting work instructions accordingly. This makes it possible to immediately reflect the user's emotional state and provide an optimal work environment and support.

[0147] "User authentication information" refers to data used to identify a user when accessing a system, and typically includes a username and password.

[0148] Artificial intelligence is a technology that enables computers to mimic human intellectual activity, automating data analysis and complex decision-making processes.

[0149] An "augmented reality environment" is a technology that overlays computer-generated information onto the real world, allowing users to experience both the physical environment and digital information simultaneously.

[0150] An "emotion analysis device" is a device or system that analyzes a user's facial expressions and tone of voice to determine their emotional state and output it as data.

[0151] "Dynamic adjustment" refers to a mechanism where the system automatically changes its functions and behavior in response to the user's state and circumstances, which change in real time.

[0152] This invention provides a system for collaborative work among multiple users using a computer network, aiming to recognize the emotional state of users in real time and provide dynamic work instructions accordingly. The system mainly consists of a server, terminals, and an emotion analysis device.

[0153] The server connects to each user terminal via the network and receives user authentication information. After successful authentication, the server uses artificial intelligence to generate optimal work instructions based on the user's skills and role. A generative AI model is used for this process.

[0154] The terminal provides the user with an augmented reality environment based on work instructions received from the server. For example, by using an augmented reality display as the terminal, the user can view the physical work environment overlaid with virtual information. The terminal also incorporates an emotion analysis device that recognizes the user's emotional state in real time through a camera and voice input device. The recognized data is sent to the server to analyze the user's stress level and concentration level.

[0155] Users perform tasks using their devices, but they can receive different work instructions based on their emotional data. For example, if the system detects that a user is experiencing high levels of stress, it may simplify tasks or offer encouraging messages. In this way, users can work more efficiently.

[0156] As a concrete example, consider the assembly of parts in manufacturing. If a user encounters difficulties in a part of the process, the system can provide a message such as "Proceed with confidence" and display other guidance to reduce the workload.

[0157] An example of a prompt might be, "The user is tackling a difficult task and is highly focused. Please suggest the most appropriate support message for this situation." By using this prompt, the generative AI model can provide appropriate responses based on the situation.

[0158] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0159] Step 1:

[0160] The server receives authentication information from each user's terminal via the network. This authentication information includes user ID and password. Based on the entered authentication information, the server performs authentication by comparing it with user information in the database. If authentication is successful, the server extracts and outputs profile information such as the user's role and skill set.

[0161] Step 2:

[0162] The server generates work instructions using an AI model based on the acquired user role and skill information. The AI ​​model takes prompt text as input and calculates the optimal task distribution for each user. As a result of the calculation, the specific tasks and procedures required for each user are output and sent as instructions to the user's terminal.

[0163] Step 3:

[0164] The terminal displays work instructions received from the server. Using an augmented reality display, virtual information is overlaid onto the physical work environment. This information includes task procedures, warnings, and visual guides to assist the user. By viewing the terminal display, the user can intuitively proceed with their work.

[0165] Step 4:

[0166] The user performs tasks while operating the device. During the task, the device's camera captures the user's facial expressions and the microphone records their voice. Based on this data, the device's emotion analysis device recognizes the user's emotional state in real time. The analysis results in the user's stress level and concentration level being output as numerical data, which is then sent to the server.

[0167] Step 5:

[0168] The server analyzes emotional data transmitted from the terminal. Based on the input data, it identifies the problems and difficulties the user is currently facing. Based on the identified information, the server dynamically adjusts the instructions and outputs and transmits newly generated work instructions to the terminal. This reduces the burden on the user and improves efficiency.

[0169] (Application Example 2)

[0170] 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".

[0171] In conventional collaborative work systems, uniform work instructions are given without considering the emotional state of the users, which can increase the workload on users and decrease productivity. Furthermore, efficient use of machinery and equipment in cooperation with users is difficult, making it challenging to optimize the overall work process. Therefore, there is a need for a means to dynamically adjust work instructions based on users' emotions and to strengthen coordination with machinery and equipment.

[0172] 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.

[0173] In this invention, the server includes means for adjusting work assignments and generating instructions based on the roles of users; means for constructing a virtual reality environment and presenting synchronized information among users; means for detecting the emotional state of users using an emotion recognition engine and dynamically adjusting work instructions based on the detection results; and means for reducing the burden on users in cooperation with mechanical devices that support the work. This enables flexible and efficient work management according to the user's situation, thereby improving productivity.

[0174] An "information processing network" is a system that connects multiple terminals accessible from different geographical locations to send, receive, and process information.

[0175] A "user" is a person who participates in collaborative work via an information processing network and operates a terminal.

[0176] A "terminal" is a device used by users to access an information processing network, and includes computers and smart glasses.

[0177] An "intelligent engine" is a control device that includes algorithms and programs that adjust the division of tasks and generate instructions based on the user's role and situation.

[0178] A "virtual reality environment" is a technology that overlays virtual information onto the physical environment of the real world, providing users with an immersive experience.

[0179] An "emotion recognition engine" is a system that detects a user's emotional state from their facial expressions, voice, etc., and processes it as data.

[0180] "Mechanical equipment" is a general term for robots and automated machines that work in cooperation with users in factories and workplaces.

[0181] "Work management" refers to the process of assigning tasks and giving instructions in the most appropriate way, taking into account the work status and emotional state of the users.

[0182] The system that realizes this invention comprises an information processing network, terminal devices, and an intelligent engine, a virtual reality environment, and an emotion recognition engine as integrated components.

[0183] The server has the ability to receive user authentication information from multiple terminals located in different geographical locations via an information processing network. For authenticated users, the intelligent engine efficiently assigns tasks based on their respective roles and generates work instructions. This allows users to immediately understand the specific tasks assigned to their roles.

[0184] The terminal receives instructions generated by an intelligent engine and provides a virtual reality environment. By overlaying virtual elements onto the physical workspace, users can intuitively understand the instructions and perform the tasks. The terminal is also equipped with a camera and microphone, and an emotion recognition engine records the user's real-time emotional state through these input devices.

[0185] The emotion recognition engine uses machine learning frameworks such as TensorFlow to analyze the user's emotions, including stress levels and concentration, from their facial expressions and voice. The server receives the emotion data and dynamically adjusts the instructions based on the analysis results. This reduces the burden on the user and improves work efficiency.

[0186] As a concrete example, consider a factory production line. If fatigue is detected while a user is wearing smart glasses and assembling a product, the system displays a message prompting them to take a break and, if necessary, redistributes instructions to automated machinery to take over the work. An example of a prompt message in this case would be, "User fatigue has been detected. Assign additional assembly tasks to the robot and prompt the user to take a break."

[0187] In this way, the system can flexibly adapt to the user's condition and continuously provide the optimal working environment.

[0188] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0189] Step 1:

[0190] The server receives user authentication information from the terminal via the information processing network. It receives user IDs and authentication tokens as input, and identifies users by comparing them with the database. As a result of the comparison, role information is output for users who have successfully been authenticated.

[0191] Step 2:

[0192] The server uses an intelligent engine to coordinate work assignments based on the roles of authenticated users. Using role information and current work status data as input, the intelligent engine calculates the optimal tasks and their order. As output, it generates customized work instructions for each user.

[0193] Step 3:

[0194] The terminal receives work instructions sent from the server and presents them to the user in a virtual reality environment. Using the received work instruction data as input, it visualizes the work procedure on the AR display by overlaying it with the physical environment. As output, it provides an interactive work guide that the user can visually recognize.

[0195] Step 4:

[0196] The device collects user emotional data in real time via its camera and microphone. It acquires video and audio data as input and feeds it into an emotion recognition engine. Through data processing, it analyzes the user's emotional state and outputs metrics such as stress levels and concentration levels.

[0197] Step 5:

[0198] The server analyzes emotional data received from the terminal and dynamically adjusts work instructions as needed. Using the user's emotional metrics and current work status as input, a generative AI model formulates optimal work modification proposals. As output, it provides the user with new instructions and relaxation suggestions.

[0199] Step 6:

[0200] Users perform tasks based on instructions from their terminals, and in some cases, collaborate with machinery to reduce their workload. They refer to on-screen guides as input and achieve efficient work execution and smooth collaborative work as output. This entire process forms a continuous feedback loop, continuously optimizing the work environment.

[0201] 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.

[0202] 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.

[0203] 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.

[0204] [Second Embodiment]

[0205] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0206] 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.

[0207] 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).

[0208] 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.

[0209] 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.

[0210] 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).

[0211] 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.

[0212] 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.

[0213] 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.

[0214] 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.

[0215] 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.

[0216] 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".

[0217] To implement this invention, a central server must first be connected to multiple terminals via the internet. Users can connect to the server and participate in the system using a terminal equipped with a dedicated application. When a user logs in, the server authenticates the user and generates appropriate work instructions based on their skills and role.

[0218] The server is equipped with an artificial intelligence module that analyzes users' skills, roles, and past performance to determine the optimal task allocation. The AI ​​monitors each user's progress in real time and updates work instructions as needed. This allows the system to maintain an efficient workflow.

[0219] The device provides users with digital information related to the physical environment being accessed through an augmented reality display. For example, virtual guidelines or 3D models are overlaid on real-world equipment, allowing users to intuitively understand and perform the necessary tasks.

[0220] Users utilize this augmented reality environment to share the same virtual workspace with other engineers. This allows users to easily communicate and coordinate with other members while performing their own tasks. Furthermore, if problems arise, the server provides users with rapid solutions based on artificial intelligence analysis.

[0221] As a concrete example, consider the maintenance of a manufacturing line. User A is responsible for the physical inspection of equipment and checks its status via a terminal. User B performs software inspections remotely and analyzes anomalies using real-time data provided by a server. Both users exchange information in an augmented reality environment and work together to solve problems based on work procedures recommended by artificial intelligence.

[0222] In this way, the system in the invention enables efficient and effective collaborative work that transcends geographical constraints, and allows for the optimization of corporate processes.

[0223] The following describes the processing flow.

[0224] Step 1:

[0225] The server receives an access request from the user and verifies the user's authentication information. If authentication is successful, the server assigns the user a unique session ID and initializes the connection.

[0226] Step 2:

[0227] Users log in via their terminals and retrieve role information sent from the server. Based on this information, the terminals prepare a work environment that matches the skills and responsibilities of each technician.

[0228] Step 3:

[0229] An artificial intelligence module on the server analyzes each user's role and skills to determine efficient task allocation. The determined tasks are then sent from the server to the terminals as work instructions.

[0230] Step 4:

[0231] The terminal displays work instructions received from the server on an augmented reality display, overlaying virtual information onto the real world and providing it to the user. This allows the user to intuitively understand the instructions.

[0232] Step 5:

[0233] The user follows instructions and performs tasks in an augmented reality environment. As the user works, the device sends progress data to the server in real time.

[0234] Step 6:

[0235] The server aggregates the received progress data, and artificial intelligence evaluates the progress and any problems. If necessary, it creates appropriate countermeasures and sends them back to the terminal to update the instructions.

[0236] Step 7:

[0237] When a user completes a task, the terminal reports its completion status to the server and sends logs and feedback information. The server saves this data and uses it for the next project.

[0238] (Example 1)

[0239] 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".

[0240] In modern workplaces, multiple engineers and workers located in geographically separated areas need to collaborate to complete tasks. However, traditional systems often suffer from insufficient information sharing and communication, leading to decreased work efficiency. Furthermore, determining the optimal division of labor based on each worker's skills and roles is difficult, hindering process optimization. In addition, a lack of real-time monitoring of progress and prompt response measures can lead to delays in appropriate responses when problems arise.

[0241] 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.

[0242] In this invention, the server includes means for adjusting work assignments and generating instructions based on each user's role using intelligent functions, means for constructing a virtual reality environment and displaying synchronized information among users, and means for analyzing users' past performance using a generated AI model and determining the optimal task assignment. This enables efficient collaborative work among geographically dispersed workers, as well as real-time progress monitoring and rapid problem solving.

[0243] "User" refers to an individual or organization that operates specialized equipment to perform tasks using the system.

[0244] "Information processing equipment" refers to computer-related devices used for inputting, processing, and outputting digital data.

[0245] A "computer network" refers to a digital communication system in which multiple computers are connected to enable them to communicate with one another.

[0246] "Authentication information" refers to data used by users to identify themselves when accessing a system.

[0247] "Intelligent function" refers to artificial intelligence technology that analyzes user data and circumstances to make decisions and generate instructions.

[0248] A "virtual reality environment" refers to a system that allows users to visualize the real world overlaid with digital information.

[0249] "Progress data" refers to information that shows the progress of a task and is analyzed for the next processing step.

[0250] A "generative AI model" refers to a machine learning algorithm used to support predictions and decision-making based on historical data.

[0251] To implement this invention, a server must first be connected to multiple information processing devices via a computer network. The server is equipped with intelligent functions and receives user authentication information to identify roles. This allows the server to use a generative AI model to determine the optimal work assignment and generate instructions based on each user's skills and past performance. To build such a system, it is recommended to use general-purpose server hardware and a software framework for implementing machine learning algorithms (e.g., TensorFlow, PyTorch).

[0252] The terminal acts as an information processing device, receiving work instructions from the server and displaying them to the user. Furthermore, the terminal overlays virtual information onto the physical world through a virtual reality environment. This operation requires display technology to realize augmented reality (e.g., AR glasses) and software libraries to display the necessary information (e.g., ARKit, ARCore).

[0253] Users can log into the system and work within a virtual reality environment. This allows users to efficiently complete their tasks and collaborate with other users to solve problems while sharing information. As a result, the system enables highly efficient collaborative work, independent of specific geographical locations.

[0254] As a concrete example, consider maintenance work in the manufacturing industry. When a user inspects equipment, the server sends instructions with virtual guidelines superimposed on the terminal, allowing the user to perform the work accordingly. If an anomaly is detected, the server can use its intelligent functions to conduct a detailed analysis and immediately suggest appropriate countermeasures.

[0255] An example of a prompt would be an instruction such as, "Please suggest the optimal task allocation required for manufacturing line maintenance." This prompt would prompt the generating AI model to suggest appropriate task allocations based on the user's role and situation. In this way, it becomes possible to construct concrete means for implementing the invention.

[0256] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0257] Step 1:

[0258] The server receives user authentication information as input and performs authentication by comparing it with the database. If authentication is successful, the server outputs user role and skill information. This process involves data processing, such as comparing authentication information like user ID and password with an internal database.

[0259] Step 2:

[0260] The server uses the acquired role and skill information as input to determine appropriate work assignments using a generating AI model. This process involves analyzing past performance data, assigning the most suitable tasks to each user, and generating work instructions. This output appears as specific work instructions sent to the terminals.

[0261] Step 3:

[0262] The terminal processes work instructions received from the server as input and outputs them to the user as visual information via an augmented reality display. Here, data processing is performed to overlay it onto the physical world, displaying specific work areas and procedures. Virtual information is provided so that the user can intuitively understand the real environment.

[0263] Step 4:

[0264] Users proceed with their work based on virtual information provided through their terminal. They provide information about their work progress and any problems that occur as input to the terminal, which then sends this information to the server. This output functions as real-time progress reporting and problem logging.

[0265] Step 5:

[0266] The server analyzes progress and problem reports from users as input and uses intelligent functions to suggest solutions. It updates work instructions as needed and sends the new instructions to the terminal. The final output provides the user with specific operations and procedures to perform in the next stage.

[0267] (Application Example 1)

[0268] 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."

[0269] In modern manufacturing environments, processes involving multiple workers and machines are becoming increasingly complex. Therefore, traditional methods struggle to efficiently adjust task allocation based on each worker's skills and roles, leading to delays, errors, and even decreased efficiency. Furthermore, real-time monitoring of work status and rapid response to problems are crucial. Consequently, a system is needed to address these challenges and improve overall factory efficiency through partially automated processes.

[0270] 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.

[0271] In this invention, the server includes means for receiving user authentication data and identifying attributes, means for adjusting work assignments and generating instructions based on each user's attributes using machine learning, and means for constructing an augmented reality environment and displaying synchronized information among users. This enables each worker to perform tasks efficiently and solve problems in real time, regardless of their location.

[0272] "Users" refers to individuals or groups who participate in this system and perform tasks based on their roles.

[0273] A "terminal" refers to a device used by a user to access a system and obtain or input information.

[0274] "Authentication data" refers to information necessary to identify a user and is used for security and role setting purposes.

[0275] "Machine learning" is a method for systems to adaptively learn through data analysis and generate optimal work instructions for individual users.

[0276] "Attributes" refer to characteristics such as a user's skills, experience, and role, and are used for appropriate task assignment.

[0277] "Task Assignment" is a process of allocating tasks that match the attributes of users.

[0278] "Instruction" is information indicating specific actions necessary for task execution.

[0279] "Augmented Reality Environment" is a technology that overlays digital information on the real visual environment and provides work support that can be intuitively understood by users.

[0280] "Synchronized Information" is information unified in real time so that multiple users can recognize the same data and progress status.

[0281] "Progress Status" indicates the degree of achievement or status of tasks performed by users and is the object monitored by the system in real time.

[0282] "Countermeasures at the Time of Problem Occurrence" are solutions or instructions presented by the system when problems occur in the work process.

[0283] To implement this invention, the server first receives the authentication data of users and identifies the attributes of each user. Multi-factor authentication is adopted for authentication to ensure security. Based on this information, the server uses a machine learning model to adjust the most suitable task assignment for users and further generate work instructions. Thereby, an optimal process flow is maintained.

[0284] The terminal provides services in the physical environment of users. Specifically, an Augmented Reality (AR) display is used. This AR function is implemented using a software platform such as Unity to overlay virtual data operable by users on the real world. Users can check the necessary instructions and guidelines in real time using, for example, a smartphone or an augmented reality headset.

[0285] The user receives a work instruction sent from the server via the terminal and performs tasks based on it. The progress is monitored in real time, and the server detects the occurrence of problems as necessary. When a problem occurs, the server analyzes it through machine learning and proposes a quick and optimal solution to the user.

[0286] As a specific example, consider the component assembly process in a factory. When the user wears an AR headset, a list of required components and assembly procedures are displayed in the field of view. Then, the server automatically optimizes the next step based on the user's progress and immediately sends a new instruction.

[0287] Examples of prompt texts are as follows.

[0288] "Please teach me about the method of optimizing the work schedule of factory robots using AI and providing work guidance with AR technology."

[0289] The flow of the specific process in Application Example 1 will be described using FIG. 12.

[0290] Step 1:

[0291] The server receives the authentication data sent from the terminal as input and authenticates the user. The input data includes the user ID and password, or biometric authentication information. Once the authentication is successful, the server retrieves the user's attribute information from the database and generates a user profile as output. This profile includes the role, skill set, past work history, etc.

[0292] Step 2:

[0293] The server uses machine learning algorithms to calculate the optimal task assignment based on each user's profile as input data. As part of the data processing, it first analyzes the profile data to generate a user skill matrix. Based on this, it generates appropriate work instructions and designs the next work step as output. It also utilizes a generative AI model to create situation-sensitive prompts.

[0294] Step 3:

[0295] The server sends work instructions to the terminal. The terminal then converts the received work instruction data into an augmented reality (AR) display. Specifically, it overlays virtual guidelines onto the user's physical environment based on the instruction data. This allows the user to intuitively and visually understand the next work step.

[0296] Step 4:

[0297] The user performs the assigned task while referring to the AR display. They periodically report their work progress to the server via their device as input data. The server monitors the progress data in real time and records the updated work status in a database as output.

[0298] Step 5:

[0299] The server uses machine learning models to analyze progress data collected in real time, and when problems arise, it proposes the optimal solution to the user. By utilizing generative AI models to output immediate prompts, users can quickly move on to the next task.

[0300] Step 6:

[0301] The user continues working based on the proposed solution. The server receives the final work output as input and stores it in the output database. This data is later analyzed to improve future work plans.

[0302] 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.

[0303] This invention combines an emotion engine with a system in which multiple users collaborate via a computer network to recognize the emotional state of users in real time and dynamically adjust work instructions and the environment. The system consists of a central server, user terminals, and an emotion engine as its main components.

[0304] The server connects to multiple terminals via the network and, after receiving authentication information from each user, generates work instructions based on the user's skills and role. The artificial intelligence assigns tasks optimally according to each user's role and sends those instructions from the server.

[0305] The terminal presents the user with an augmented reality environment based on instructions received from the server. Through the augmented reality display, the physical work environment and virtual work instructions are overlaid, allowing the user to intuitively proceed with their tasks. The terminal also incorporates an emotion engine that recognizes the user's emotional state through the camera and voice input, and transmits this data to the server. The emotion engine determines the user's stress level and concentration level from their facial expressions and tone of voice, dynamically changing the presence and content of work instructions accordingly.

[0306] Users work while utilizing the augmented reality environment provided by their device. Work instructions are adjusted based on recognized emotions, allowing users to perform tasks efficiently while reducing their burden. For example, in a machine assembly task, if the user is feeling stressed, the system can simplify the task or provide messages to encourage relaxation.

[0307] The server continuously monitors the user's progress data and sentiment data, and performs data analysis to improve the overall work efficiency. The analysis results are fed back to the next work plan and used to optimize the working environment for each user. In this way, the system enables flexible instruction adjustment while considering the user's emotional state, and realizes a more effective collaborative working environment.

[0308] The following describes the processing flow.

[0309] Step 1:

[0310] The server receives a login request from the user and starts the authentication process. It verifies the authentication information entered by the user and identifies the role and skill information corresponding to that user.

[0311] Step 2:

[0312] Based on the role information of the user received from the server, the terminal sets up an augmented reality environment. The terminal loads the necessary virtual content and prepares to overlay virtual information on the physical environment accessed by the user.

[0313] Step 3:

[0314] The artificial intelligence of the server analyzes the role, skill, and progress data of each user, and determines appropriate work instructions and task assignments. The determined work instructions are sent from the server to the relevant terminals.

[0315] Step 4:

[0316] The terminal displays the work instructions received from the server on the augmented reality display, providing an intuitive work guide for the user. Also, the emotion engine installed on the terminal analyzes the user's expressions and voices in real time and evaluates the emotional state.

[0317] Step 5:

[0318] The user receives adjustments to the work instructions provided by the device based on their emotional state, which is assessed by the emotion engine. For example, if the user indicates a high stress level, the device may simplify the work procedure or display a message prompting them to take a break.

[0319] Step 6:

[0320] The server monitors progress and sentiment data transmitted from terminals in real time and analyzes each user's work status. If a problem is detected, the server immediately derives a solution and sends that information to the relevant terminal.

[0321] Step 7:

[0322] Once a user completes a task, the terminal reports the results to the server. The server collects data on completed tasks and sentiment feedback, and analyzes it to help improve future projects.

[0323] (Example 2)

[0324] 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".

[0325] Current collaborative work systems suffer from insufficient adjustment of dynamic work instructions based on user emotions, and are unable to provide appropriate support according to user stress levels and concentration levels. Furthermore, while it is necessary to consider emotional states in real time to improve work progress and efficiency, systems with such functionality are limited.

[0326] 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.

[0327] In this invention, the server includes means for receiving user authentication information and identifying roles, means for using artificial intelligence to adjust work assignments based on each user's role and generate instructions, and means for recognizing the user's emotional state in real time using an emotion analysis device and generating and dynamically adjusting work instructions accordingly. This makes it possible to immediately reflect the user's emotional state and provide an optimal work environment and support.

[0328] "User authentication information" refers to data used to identify a user when accessing a system, and typically includes a username and password.

[0329] Artificial intelligence is a technology that enables computers to mimic human intellectual activity, automating data analysis and complex decision-making processes.

[0330] An "augmented reality environment" is a technology that overlays computer-generated information onto the real world, allowing users to experience both the physical environment and digital information simultaneously.

[0331] An "emotion analysis device" is a device or system that analyzes a user's facial expressions and tone of voice to determine their emotional state and output it as data.

[0332] "Dynamic adjustment" refers to a mechanism where the system automatically changes its functions and behavior in response to the user's state and circumstances, which change in real time.

[0333] This invention provides a system for collaborative work among multiple users using a computer network, aiming to recognize the emotional state of users in real time and provide dynamic work instructions accordingly. The system mainly consists of a server, terminals, and an emotion analysis device.

[0334] The server connects to each user terminal via the network and receives user authentication information. After successful authentication, the server uses artificial intelligence to generate optimal work instructions based on the user's skills and role. A generative AI model is used for this process.

[0335] The terminal provides the user with an augmented reality environment based on work instructions received from the server. For example, by using an augmented reality display as the terminal, the user can view the physical work environment overlaid with virtual information. The terminal also incorporates an emotion analysis device that recognizes the user's emotional state in real time through a camera and voice input device. The recognized data is sent to the server to analyze the user's stress level and concentration level.

[0336] Users perform tasks using their devices, but they can receive different work instructions based on their emotional data. For example, if the system detects that a user is experiencing high levels of stress, it may simplify tasks or offer encouraging messages. In this way, users can work more efficiently.

[0337] As a concrete example, consider the assembly of parts in manufacturing. If a user encounters difficulties in a part of the process, the system can provide a message such as "Proceed with confidence" and display other guidance to reduce the workload.

[0338] An example of a prompt might be, "The user is tackling a difficult task and is highly focused. Please suggest the most appropriate support message for this situation." By using this prompt, the generative AI model can provide appropriate responses based on the situation.

[0339] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0340] Step 1:

[0341] The server receives authentication information from each user's terminal via the network. This authentication information includes user ID and password. Based on the entered authentication information, the server performs authentication by comparing it with user information in the database. If authentication is successful, the server extracts and outputs profile information such as the user's role and skill set.

[0342] Step 2:

[0343] The server generates work instructions using an AI model based on the acquired user role and skill information. The AI ​​model takes prompt text as input and calculates the optimal task distribution for each user. As a result of the calculation, the specific tasks and procedures required for each user are output and sent as instructions to the user's terminal.

[0344] Step 3:

[0345] The terminal displays work instructions received from the server. Using an augmented reality display, virtual information is overlaid onto the physical work environment. This information includes task procedures, warnings, and visual guides to assist the user. By viewing the terminal display, the user can intuitively proceed with their work.

[0346] Step 4:

[0347] The user performs tasks while operating the device. During the task, the device's camera captures the user's facial expressions and the microphone records their voice. Based on this data, the device's emotion analysis device recognizes the user's emotional state in real time. The analysis results in the user's stress level and concentration level being output as numerical data, which is then sent to the server.

[0348] Step 5:

[0349] The server analyzes emotional data transmitted from the terminal. Based on the input data, it identifies the problems and difficulties the user is currently facing. Based on the identified information, the server dynamically adjusts the instructions and outputs and transmits newly generated work instructions to the terminal. This reduces the burden on the user and improves efficiency.

[0350] (Application Example 2)

[0351] 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."

[0352] In conventional collaborative work systems, uniform work instructions are given without considering the emotional state of the users, which can increase the workload on users and decrease productivity. Furthermore, efficient use of machinery and equipment in cooperation with users is difficult, making it challenging to optimize the overall work process. Therefore, there is a need for a means to dynamically adjust work instructions based on users' emotions and to strengthen coordination with machinery and equipment.

[0353] 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.

[0354] In this invention, the server includes means for adjusting work assignments and generating instructions based on the roles of users; means for constructing a virtual reality environment and presenting synchronized information among users; means for detecting the emotional state of users using an emotion recognition engine and dynamically adjusting work instructions based on the detection results; and means for reducing the burden on users in cooperation with mechanical devices that support the work. This enables flexible and efficient work management according to the user's situation, thereby improving productivity.

[0355] An "information processing network" is a system that connects multiple terminals accessible from different geographical locations to send, receive, and process information.

[0356] A "user" is a person who participates in collaborative work via an information processing network and operates a terminal.

[0357] A "terminal" is a device used by users to access an information processing network, and includes computers and smart glasses.

[0358] An "intelligent engine" is a control device that includes algorithms and programs that adjust the division of tasks and generate instructions based on the user's role and situation.

[0359] A "virtual reality environment" is a technology that overlays virtual information onto the physical environment of the real world, providing users with an immersive experience.

[0360] An "emotion recognition engine" is a system that detects a user's emotional state from their facial expressions, voice, etc., and processes it as data.

[0361] "Mechanical equipment" is a general term for robots and automated machines that work in cooperation with users in factories and workplaces.

[0362] "Work management" refers to the process of assigning tasks and giving instructions in the most appropriate way, taking into account the work status and emotional state of the users.

[0363] The system that realizes this invention comprises an information processing network, terminal devices, and an intelligent engine, a virtual reality environment, and an emotion recognition engine as integrated components.

[0364] The server has the ability to receive user authentication information from multiple terminals located in different geographical locations via an information processing network. For authenticated users, the intelligent engine efficiently assigns tasks based on their respective roles and generates work instructions. This allows users to immediately understand the specific tasks assigned to their roles.

[0365] The terminal receives instructions generated by an intelligent engine and provides a virtual reality environment. By overlaying virtual elements onto the physical workspace, users can intuitively understand the instructions and perform the tasks. The terminal is also equipped with a camera and microphone, and an emotion recognition engine records the user's real-time emotional state through these input devices.

[0366] The emotion recognition engine uses machine learning frameworks such as TensorFlow to analyze the user's emotions, including stress levels and concentration, from their facial expressions and voice. The server receives the emotion data and dynamically adjusts the instructions based on the analysis results. This reduces the burden on the user and improves work efficiency.

[0367] As a concrete example, consider a factory production line. If fatigue is detected while a user is wearing smart glasses and assembling a product, the system displays a message prompting them to take a break and, if necessary, redistributes instructions to automated machinery to take over the work. An example of a prompt message in this case would be, "User fatigue has been detected. Assign additional assembly tasks to the robot and prompt the user to take a break."

[0368] In this way, the system can flexibly adapt to the user's condition and continuously provide the optimal working environment.

[0369] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0370] Step 1:

[0371] The server receives user authentication information from the terminal via the information processing network. It receives user IDs and authentication tokens as input, and identifies users by comparing them with the database. As a result of the comparison, role information is output for users who have successfully been authenticated.

[0372] Step 2:

[0373] The server uses an intelligent engine to coordinate work assignments based on the roles of authenticated users. Using role information and current work status data as input, the intelligent engine calculates the optimal tasks and their order. As output, it generates customized work instructions for each user.

[0374] Step 3:

[0375] The terminal receives work instructions sent from the server and presents them to the user in a virtual reality environment. Using the received work instruction data as input, it visualizes the work procedure on the AR display by overlaying it with the physical environment. As output, it provides an interactive work guide that the user can visually recognize.

[0376] Step 4:

[0377] The device collects user emotional data in real time via its camera and microphone. It acquires video and audio data as input and feeds it into an emotion recognition engine. Through data processing, it analyzes the user's emotional state and outputs metrics such as stress levels and concentration levels.

[0378] Step 5:

[0379] The server analyzes emotional data received from the terminal and dynamically adjusts work instructions as needed. Using the user's emotional metrics and current work status as input, a generative AI model formulates optimal work modification proposals. As output, it provides the user with new instructions and relaxation suggestions.

[0380] Step 6:

[0381] Users perform tasks based on instructions from their terminals, and in some cases, collaborate with machinery to reduce their workload. They refer to on-screen guides as input and achieve efficient work execution and smooth collaborative work as output. This entire process forms a continuous feedback loop, continuously optimizing the work environment.

[0382] 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.

[0383] 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.

[0384] 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.

[0385] [Third Embodiment]

[0386] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0387] 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.

[0388] 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).

[0389] 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.

[0390] 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.

[0391] 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).

[0392] 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.

[0393] 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.

[0394] 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.

[0395] 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.

[0396] 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.

[0397] 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".

[0398] To implement this invention, a central server must first be connected to multiple terminals via the internet. Users can connect to the server and participate in the system using a terminal equipped with a dedicated application. When a user logs in, the server authenticates the user and generates appropriate work instructions based on their skills and role.

[0399] The server is equipped with an artificial intelligence module that analyzes users' skills, roles, and past performance to determine the optimal task allocation. The AI ​​monitors each user's progress in real time and updates work instructions as needed. This allows the system to maintain an efficient workflow.

[0400] The device provides users with digital information related to the physical environment being accessed through an augmented reality display. For example, virtual guidelines or 3D models are overlaid on real-world equipment, allowing users to intuitively understand and perform the necessary tasks.

[0401] Users utilize this augmented reality environment to share the same virtual workspace with other engineers. This allows users to easily communicate and coordinate with other members while performing their own tasks. Furthermore, if problems arise, the server provides users with rapid solutions based on artificial intelligence analysis.

[0402] As a concrete example, consider the maintenance of a manufacturing line. User A is responsible for the physical inspection of equipment and checks its status via a terminal. User B performs software inspections remotely and analyzes anomalies using real-time data provided by a server. Both users exchange information in an augmented reality environment and work together to solve problems based on work procedures recommended by artificial intelligence.

[0403] In this way, the system in the invention enables efficient and effective collaborative work that transcends geographical constraints, and allows for the optimization of corporate processes.

[0404] The following describes the processing flow.

[0405] Step 1:

[0406] The server receives an access request from the user and verifies the user's authentication information. If authentication is successful, the server assigns the user a unique session ID and initializes the connection.

[0407] Step 2:

[0408] Users log in via their terminals and retrieve role information sent from the server. Based on this information, the terminals prepare a work environment that matches the skills and responsibilities of each technician.

[0409] Step 3:

[0410] An artificial intelligence module on the server analyzes each user's role and skills to determine efficient task allocation. The determined tasks are then sent from the server to the terminals as work instructions.

[0411] Step 4:

[0412] The terminal displays work instructions received from the server on an augmented reality display, overlaying virtual information onto the real world and providing it to the user. This allows the user to intuitively understand the instructions.

[0413] Step 5:

[0414] The user follows instructions and performs tasks in an augmented reality environment. As the user works, the device sends progress data to the server in real time.

[0415] Step 6:

[0416] The server aggregates the received progress data, and artificial intelligence evaluates the progress and any problems. If necessary, it creates appropriate countermeasures and sends them back to the terminal to update the instructions.

[0417] Step 7:

[0418] When a user completes a task, the terminal reports its completion status to the server and sends logs and feedback information. The server saves this data and uses it for the next project.

[0419] (Example 1)

[0420] 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."

[0421] In modern workplaces, multiple engineers and workers located in geographically separated areas need to collaborate to complete tasks. However, traditional systems often suffer from insufficient information sharing and communication, leading to decreased work efficiency. Furthermore, determining the optimal division of labor based on each worker's skills and roles is difficult, hindering process optimization. In addition, a lack of real-time monitoring of progress and prompt response measures can lead to delays in appropriate responses when problems arise.

[0422] 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.

[0423] In this invention, the server includes means for adjusting work assignments and generating instructions based on each user's role using intelligent functions, means for constructing a virtual reality environment and displaying synchronized information among users, and means for analyzing users' past performance using a generated AI model and determining the optimal task assignment. This enables efficient collaborative work among geographically dispersed workers, as well as real-time progress monitoring and rapid problem solving.

[0424] "User" refers to an individual or organization that operates specialized equipment to perform tasks using the system.

[0425] "Information processing equipment" refers to computer-related devices used for inputting, processing, and outputting digital data.

[0426] A "computer network" refers to a digital communication system in which multiple computers are connected to enable them to communicate with one another.

[0427] "Authentication information" refers to data used by users to identify themselves when accessing a system.

[0428] "Intelligent function" refers to artificial intelligence technology that analyzes user data and circumstances to make decisions and generate instructions.

[0429] A "virtual reality environment" refers to a system that allows users to visualize the real world overlaid with digital information.

[0430] "Progress data" refers to information that shows the progress of a task and is analyzed for the next processing step.

[0431] A "generative AI model" refers to a machine learning algorithm used to support predictions and decision-making based on historical data.

[0432] To implement this invention, a server must first be connected to multiple information processing devices via a computer network. The server is equipped with intelligent functions and receives user authentication information to identify roles. This allows the server to use a generative AI model to determine the optimal work assignment and generate instructions based on each user's skills and past performance. To build such a system, it is recommended to use general-purpose server hardware and a software framework for implementing machine learning algorithms (e.g., TensorFlow, PyTorch).

[0433] The terminal acts as an information processing device, receiving work instructions from the server and displaying them to the user. Furthermore, the terminal overlays virtual information onto the physical world through a virtual reality environment. This operation requires display technology to realize augmented reality (e.g., AR glasses) and software libraries to display the necessary information (e.g., ARKit, ARCore).

[0434] Users can log into the system and work within a virtual reality environment. This allows users to efficiently complete their tasks and collaborate with other users to solve problems while sharing information. As a result, the system enables highly efficient collaborative work, independent of specific geographical locations.

[0435] As a concrete example, consider maintenance work in the manufacturing industry. When a user inspects equipment, the server sends instructions with virtual guidelines superimposed on the terminal, allowing the user to perform the work accordingly. If an anomaly is detected, the server can use its intelligent functions to conduct a detailed analysis and immediately suggest appropriate countermeasures.

[0436] An example of a prompt would be an instruction such as, "Please suggest the optimal task allocation required for manufacturing line maintenance." This prompt would prompt the generating AI model to suggest appropriate task allocations based on the user's role and situation. In this way, it becomes possible to construct concrete means for implementing the invention.

[0437] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0438] Step 1:

[0439] The server receives user authentication information as input and performs authentication by comparing it with the database. If authentication is successful, the server outputs user role and skill information. This process involves data processing, such as comparing authentication information like user ID and password with an internal database.

[0440] Step 2:

[0441] The server uses the acquired role and skill information as input to determine appropriate work assignments using a generating AI model. This process involves analyzing past performance data, assigning the most suitable tasks to each user, and generating work instructions. This output appears as specific work instructions sent to the terminals.

[0442] Step 3:

[0443] The terminal processes work instructions received from the server as input and outputs them to the user as visual information via an augmented reality display. Here, data processing is performed to overlay it onto the physical world, displaying specific work areas and procedures. Virtual information is provided so that the user can intuitively understand the real environment.

[0444] Step 4:

[0445] Users proceed with their work based on virtual information provided through their terminal. They provide information about their work progress and any problems that occur as input to the terminal, which then sends this information to the server. This output functions as real-time progress reporting and problem logging.

[0446] Step 5:

[0447] The server analyzes progress and problem reports from users as input and uses intelligent functions to suggest solutions. It updates work instructions as needed and sends the new instructions to the terminal. The final output provides the user with specific operations and procedures to perform in the next stage.

[0448] (Application Example 1)

[0449] 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."

[0450] In modern manufacturing environments, processes involving multiple workers and machines are becoming increasingly complex. Therefore, traditional methods struggle to efficiently adjust task allocation based on each worker's skills and roles, leading to delays, errors, and even decreased efficiency. Furthermore, real-time monitoring of work status and rapid response to problems are crucial. Consequently, a system is needed to address these challenges and improve overall factory efficiency through partially automated processes.

[0451] 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.

[0452] In this invention, the server includes means for receiving user authentication data and identifying attributes, means for adjusting work assignments and generating instructions based on each user's attributes using machine learning, and means for constructing an augmented reality environment and displaying synchronized information among users. This enables each worker to perform tasks efficiently and solve problems in real time, regardless of their location.

[0453] "Users" refers to individuals or groups who participate in this system and perform tasks based on their roles.

[0454] A "terminal" refers to a device used by a user to access a system and obtain or input information.

[0455] "Authentication data" refers to information necessary to identify a user and is used for security and role setting purposes.

[0456] "Machine learning" is a method for systems to adaptively learn through data analysis and generate optimal work instructions for individual users.

[0457] "Attributes" refer to characteristics such as a user's skills, experience, and role, and are used for appropriate task assignment.

[0458] "Task assignment" is the process of assigning tasks that are suitable for the user's attributes.

[0459] "Instructions" are pieces of information that indicate the specific actions necessary to carry out a task.

[0460] An "augmented reality environment" is a technology that overlays digital information onto the real-world visual environment, providing intuitive and easy-to-understand work support for users.

[0461] "Synchronized information" refers to information that is unified in real time so that multiple users can see the same data and progress.

[0462] "Progress status" refers to the degree of completion and status of tasks performed by users, and is monitored by the system in real time.

[0463] "Problem resolution measures" refer to the solutions or instructions that the system provides when a problem arises in the work process.

[0464] To realize this invention, the server first receives user authentication data and identifies the attributes of each user. Multi-factor authentication is employed to ensure security. Based on this information, the server uses a machine learning model to adjust the most suitable work assignment for each user and then generates work instructions. This maintains an optimal process flow.

[0465] The device provides services within the user's physical environment. Specifically, it uses an augmented reality (AR) display. This AR functionality is implemented using a software platform like Unity, overlaying user-operable virtual data onto the real world. Users can, for example, view necessary instructions and guidelines in real time using a smartphone or augmented reality headset.

[0466] Users receive work instructions sent from the server via their terminals and perform tasks based on them. Progress is monitored in real time, and the server detects problems as needed. If a problem occurs, the server uses machine learning to analyze it and proposes quick and optimal solutions to the user.

[0467] As a concrete example, consider a parts assembly process in a factory. When a user puts on an AR headset, a list of necessary parts and assembly instructions are displayed in their field of view. The server then automatically optimizes the next step based on the user's progress and sends new instructions immediately.

[0468] Examples of prompt messages are as follows:

[0469] "Please tell me how to use AI to optimize factory robot work schedules and provide work guidance using AR technology."

[0470] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0471] Step 1:

[0472] The server receives authentication data sent from the terminal as input and authenticates the user. This input data includes user ID and password, or biometric authentication information. Once authentication is successful, the server retrieves the user's attribute information from the database and generates a user profile as output. This profile includes roles, skill sets, and past work history.

[0473] Step 2:

[0474] The server uses machine learning algorithms to calculate the optimal task assignment based on each user's profile as input data. As part of the data processing, it first analyzes the profile data to generate a user skill matrix. Based on this, it generates appropriate work instructions and designs the next work step as output. It also utilizes a generative AI model to create situation-sensitive prompts.

[0475] Step 3:

[0476] The server sends work instructions to the terminal. The terminal then converts the received work instruction data into an augmented reality (AR) display. Specifically, it overlays virtual guidelines onto the user's physical environment based on the instruction data. This allows the user to intuitively and visually understand the next work step.

[0477] Step 4:

[0478] The user performs the assigned task while referring to the AR display. They periodically report their work progress to the server via their device as input data. The server monitors the progress data in real time and records the updated work status in a database as output.

[0479] Step 5:

[0480] The server uses machine learning models to analyze progress data collected in real time, and when problems arise, it proposes the optimal solution to the user. By utilizing generative AI models to output immediate prompts, users can quickly move on to the next task.

[0481] Step 6:

[0482] The user continues working based on the proposed solution. The server receives the final work output as input and stores it in the output database. This data is later analyzed to improve future work plans.

[0483] 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.

[0484] This invention combines an emotion engine with a system in which multiple users collaborate via a computer network to recognize the emotional state of users in real time and dynamically adjust work instructions and the environment. The system consists of a central server, user terminals, and an emotion engine as its main components.

[0485] The server connects to multiple terminals via the network and, after receiving authentication information from each user, generates work instructions based on the user's skills and role. The artificial intelligence assigns tasks optimally according to each user's role and sends those instructions from the server.

[0486] The terminal presents the user with an augmented reality environment based on instructions received from the server. Through the augmented reality display, the physical work environment and virtual work instructions are overlaid, allowing the user to intuitively proceed with their tasks. The terminal also incorporates an emotion engine that recognizes the user's emotional state through the camera and voice input, and transmits this data to the server. The emotion engine determines the user's stress level and concentration level from their facial expressions and tone of voice, dynamically changing the presence and content of work instructions accordingly.

[0487] Users work while utilizing the augmented reality environment provided by their device. Work instructions are adjusted based on recognized emotions, allowing users to perform tasks efficiently while reducing their burden. For example, in a machine assembly task, if the user is feeling stressed, the system can simplify the task or provide messages to encourage relaxation.

[0488] The server continuously monitors user progress and emotional data, performing data analysis to improve overall work efficiency. The analysis results are fed back into the next work plan and used to optimize the work environment for each user. In this way, the system takes into account the user's emotional state, enabling flexible instruction adjustments and creating a more effective collaborative work environment.

[0489] The following describes the processing flow.

[0490] Step 1:

[0491] The server receives a login request from a user and initiates the authentication process. It verifies the authentication information entered by the user and identifies the role and skills information corresponding to that user.

[0492] Step 2:

[0493] The terminal sets up the augmented reality environment based on the user's role information received from the server. The terminal loads the necessary virtual content and prepares to overlay the virtual information onto the physical environment that the user is accessing.

[0494] Step 3:

[0495] The server's artificial intelligence analyzes each user's role, skills, and progress data to determine appropriate work instructions and task assignments. The determined work instructions are then sent from the server to the relevant terminals.

[0496] Step 4:

[0497] The terminal displays work instructions received from the server on an augmented reality display, providing the user with an intuitive work guide. Furthermore, an emotion engine built into the terminal analyzes the user's facial expressions and voice in real time to evaluate their emotional state.

[0498] Step 5:

[0499] The user receives adjustments to the work instructions provided by the device based on their emotional state, which is assessed by the emotion engine. For example, if the user indicates a high stress level, the device may simplify the work procedure or display a message prompting them to take a break.

[0500] Step 6:

[0501] The server monitors progress and sentiment data transmitted from terminals in real time and analyzes each user's work status. If a problem is detected, the server immediately derives a solution and sends that information to the relevant terminal.

[0502] Step 7:

[0503] Once a user completes a task, the terminal reports the results to the server. The server collects data on completed tasks and sentiment feedback, and analyzes it to help improve future projects.

[0504] (Example 2)

[0505] 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."

[0506] Current collaborative work systems suffer from insufficient adjustment of dynamic work instructions based on user emotions, and are unable to provide appropriate support according to user stress levels and concentration levels. Furthermore, while it is necessary to consider emotional states in real time to improve work progress and efficiency, systems with such functionality are limited.

[0507] 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.

[0508] In this invention, the server includes means for receiving user authentication information and identifying roles, means for using artificial intelligence to adjust work assignments based on each user's role and generate instructions, and means for recognizing the user's emotional state in real time using an emotion analysis device and generating and dynamically adjusting work instructions accordingly. This makes it possible to immediately reflect the user's emotional state and provide an optimal work environment and support.

[0509] "User authentication information" refers to data used to identify a user when accessing a system, and typically includes a username and password.

[0510] Artificial intelligence is a technology that enables computers to mimic human intellectual activity, automating data analysis and complex decision-making processes.

[0511] An "augmented reality environment" is a technology that overlays computer-generated information onto the real world, allowing users to experience both the physical environment and digital information simultaneously.

[0512] An "emotion analysis device" is a device or system that analyzes a user's facial expressions and tone of voice to determine their emotional state and output it as data.

[0513] "Dynamic adjustment" refers to a mechanism where the system automatically changes its functions and behavior in response to the user's state and circumstances, which change in real time.

[0514] This invention provides a system for collaborative work among multiple users using a computer network, aiming to recognize the emotional state of users in real time and provide dynamic work instructions accordingly. The system mainly consists of a server, terminals, and an emotion analysis device.

[0515] The server connects to each user terminal via the network and receives user authentication information. After successful authentication, the server uses artificial intelligence to generate optimal work instructions based on the user's skills and role. A generative AI model is used for this process.

[0516] The terminal provides the user with an augmented reality environment based on work instructions received from the server. For example, by using an augmented reality display as the terminal, the user can view the physical work environment overlaid with virtual information. The terminal also incorporates an emotion analysis device that recognizes the user's emotional state in real time through a camera and voice input device. The recognized data is sent to the server to analyze the user's stress level and concentration level.

[0517] Users perform tasks using their devices, but they can receive different work instructions based on their emotional data. For example, if the system detects that a user is experiencing high levels of stress, it may simplify tasks or offer encouraging messages. In this way, users can work more efficiently.

[0518] As a concrete example, consider the assembly of parts in manufacturing. If a user encounters difficulties in a part of the process, the system can provide a message such as "Proceed with confidence" and display other guidance to reduce the workload.

[0519] An example of a prompt might be, "The user is tackling a difficult task and is highly focused. Please suggest the most appropriate support message for this situation." By using this prompt, the generative AI model can provide appropriate responses based on the situation.

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

[0521] Step 1:

[0522] The server receives authentication information from each user's terminal via the network. This authentication information includes user ID and password. Based on the entered authentication information, the server performs authentication by comparing it with user information in the database. If authentication is successful, the server extracts and outputs profile information such as the user's role and skill set.

[0523] Step 2:

[0524] The server generates work instructions using an AI model based on the acquired user role and skill information. The AI ​​model takes prompt text as input and calculates the optimal task distribution for each user. As a result of the calculation, the specific tasks and procedures required for each user are output and sent as instructions to the user's terminal.

[0525] Step 3:

[0526] The terminal displays work instructions received from the server. Using an augmented reality display, virtual information is overlaid onto the physical work environment. This information includes task procedures, warnings, and visual guides to assist the user. By viewing the terminal display, the user can intuitively proceed with their work.

[0527] Step 4:

[0528] The user performs tasks while operating the device. During the task, the device's camera captures the user's facial expressions and the microphone records their voice. Based on this data, the device's emotion analysis device recognizes the user's emotional state in real time. The analysis results in the user's stress level and concentration level being output as numerical data, which is then sent to the server.

[0529] Step 5:

[0530] The server analyzes emotional data transmitted from the terminal. Based on the input data, it identifies the problems and difficulties the user is currently facing. Based on the identified information, the server dynamically adjusts the instructions and outputs and transmits newly generated work instructions to the terminal. This reduces the burden on the user and improves efficiency.

[0531] (Application Example 2)

[0532] 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."

[0533] In conventional collaborative work systems, uniform work instructions are given without considering the emotional state of the users, which can increase the workload on users and decrease productivity. Furthermore, efficient use of machinery and equipment in cooperation with users is difficult, making it challenging to optimize the overall work process. Therefore, there is a need for a means to dynamically adjust work instructions based on users' emotions and to strengthen coordination with machinery and equipment.

[0534] 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.

[0535] In this invention, the server includes means for adjusting work assignments and generating instructions based on the roles of users; means for constructing a virtual reality environment and presenting synchronized information among users; means for detecting the emotional state of users using an emotion recognition engine and dynamically adjusting work instructions based on the detection results; and means for reducing the burden on users in cooperation with mechanical devices that support the work. This enables flexible and efficient work management according to the user's situation, thereby improving productivity.

[0536] An "information processing network" is a system that connects multiple terminals accessible from different geographical locations to send, receive, and process information.

[0537] A "user" is a person who participates in collaborative work via an information processing network and operates a terminal.

[0538] A "terminal" is a device used by users to access an information processing network, and includes computers and smart glasses.

[0539] An "intelligent engine" is a control device that includes algorithms and programs that adjust the division of tasks and generate instructions based on the user's role and situation.

[0540] A "virtual reality environment" is a technology that overlays virtual information onto the physical environment of the real world, providing users with an immersive experience.

[0541] An "emotion recognition engine" is a system that detects a user's emotional state from their facial expressions, voice, etc., and processes it as data.

[0542] "Mechanical equipment" is a general term for robots and automated machines that work in cooperation with users in factories and workplaces.

[0543] "Work management" refers to the process of assigning tasks and giving instructions in the most appropriate way, taking into account the work status and emotional state of the users.

[0544] The system that realizes this invention comprises an information processing network, terminal devices, and an intelligent engine, a virtual reality environment, and an emotion recognition engine as integrated components.

[0545] The server has the ability to receive user authentication information from multiple terminals located in different geographical locations via an information processing network. For authenticated users, the intelligent engine efficiently assigns tasks based on their respective roles and generates work instructions. This allows users to immediately understand the specific tasks assigned to their roles.

[0546] The terminal receives instructions generated by an intelligent engine and provides a virtual reality environment. By overlaying virtual elements onto the physical workspace, users can intuitively understand the instructions and perform the tasks. The terminal is also equipped with a camera and microphone, and an emotion recognition engine records the user's real-time emotional state through these input devices.

[0547] The emotion recognition engine uses machine learning frameworks such as TensorFlow to analyze the user's emotions, including stress levels and concentration, from their facial expressions and voice. The server receives the emotion data and dynamically adjusts the instructions based on the analysis results. This reduces the burden on the user and improves work efficiency.

[0548] As a concrete example, consider a factory production line. If fatigue is detected while a user is wearing smart glasses and assembling a product, the system displays a message prompting them to take a break and, if necessary, redistributes instructions to automated machinery to take over the work. An example of a prompt message in this case would be, "User fatigue has been detected. Assign additional assembly tasks to the robot and prompt the user to take a break."

[0549] In this way, the system can flexibly adapt to the user's condition and continuously provide the optimal working environment.

[0550] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0551] Step 1:

[0552] The server receives user authentication information from the terminal via the information processing network. It receives user IDs and authentication tokens as input, and identifies users by comparing them with the database. As a result of the comparison, role information is output for users who have successfully been authenticated.

[0553] Step 2:

[0554] The server uses an intelligent engine to coordinate work assignments based on the roles of authenticated users. Using role information and current work status data as input, the intelligent engine calculates the optimal tasks and their order. As output, it generates customized work instructions for each user.

[0555] Step 3:

[0556] The terminal receives work instructions sent from the server and presents them to the user in a virtual reality environment. Using the received work instruction data as input, it visualizes the work procedure on the AR display by overlaying it with the physical environment. As output, it provides an interactive work guide that the user can visually recognize.

[0557] Step 4:

[0558] The device collects user emotional data in real time via its camera and microphone. It acquires video and audio data as input and feeds it into an emotion recognition engine. Through data processing, it analyzes the user's emotional state and outputs metrics such as stress levels and concentration levels.

[0559] Step 5:

[0560] The server analyzes emotional data received from the terminal and dynamically adjusts work instructions as needed. Using the user's emotional metrics and current work status as input, a generative AI model formulates optimal work modification proposals. As output, it provides the user with new instructions and relaxation suggestions.

[0561] Step 6:

[0562] Users perform tasks based on instructions from their terminals, and in some cases, collaborate with machinery to reduce their workload. They refer to on-screen guides as input and achieve efficient work execution and smooth collaborative work as output. This entire process forms a continuous feedback loop, continuously optimizing the work environment.

[0563] 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.

[0564] 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.

[0565] 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.

[0566] [Fourth Embodiment]

[0567] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0568] 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.

[0569] 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).

[0570] 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.

[0571] 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.

[0572] 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).

[0573] 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.

[0574] 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.

[0575] 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.

[0576] 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.

[0577] 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.

[0578] 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.

[0579] 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".

[0580] To implement this invention, a central server must first be connected to multiple terminals via the internet. Users can connect to the server and participate in the system using a terminal equipped with a dedicated application. When a user logs in, the server authenticates the user and generates appropriate work instructions based on their skills and role.

[0581] The server is equipped with an artificial intelligence module that analyzes users' skills, roles, and past performance to determine the optimal task allocation. The AI ​​monitors each user's progress in real time and updates work instructions as needed. This allows the system to maintain an efficient workflow.

[0582] The device provides users with digital information related to the physical environment being accessed through an augmented reality display. For example, virtual guidelines or 3D models are overlaid on real-world equipment, allowing users to intuitively understand and perform the necessary tasks.

[0583] Users utilize this augmented reality environment to share the same virtual workspace with other engineers. This allows users to easily communicate and coordinate with other members while performing their own tasks. Furthermore, if problems arise, the server provides users with rapid solutions based on artificial intelligence analysis.

[0584] As a concrete example, consider the maintenance of a manufacturing line. User A is responsible for the physical inspection of equipment and checks its status via a terminal. User B performs software inspections remotely and analyzes anomalies using real-time data provided by a server. Both users exchange information in an augmented reality environment and work together to solve problems based on work procedures recommended by artificial intelligence.

[0585] In this way, the system in the invention enables efficient and effective collaborative work that transcends geographical constraints, and allows for the optimization of corporate processes.

[0586] The following describes the processing flow.

[0587] Step 1:

[0588] The server receives an access request from the user and verifies the user's authentication information. If authentication is successful, the server assigns the user a unique session ID and initializes the connection.

[0589] Step 2:

[0590] Users log in via their terminals and retrieve role information sent from the server. Based on this information, the terminals prepare a work environment that matches the skills and responsibilities of each technician.

[0591] Step 3:

[0592] An artificial intelligence module on the server analyzes each user's role and skills to determine efficient task allocation. The determined tasks are then sent from the server to the terminals as work instructions.

[0593] Step 4:

[0594] The terminal displays work instructions received from the server on an augmented reality display, overlaying virtual information onto the real world and providing it to the user. This allows the user to intuitively understand the instructions.

[0595] Step 5:

[0596] The user follows instructions and performs tasks in an augmented reality environment. As the user works, the device sends progress data to the server in real time.

[0597] Step 6:

[0598] The server aggregates the received progress data, and artificial intelligence evaluates the progress and any problems. If necessary, it creates appropriate countermeasures and sends them back to the terminal to update the instructions.

[0599] Step 7:

[0600] When a user completes a task, the terminal reports its completion status to the server and sends logs and feedback information. The server saves this data and uses it for the next project.

[0601] (Example 1)

[0602] 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".

[0603] In modern workplaces, multiple engineers and workers located in geographically separated areas need to collaborate to complete tasks. However, traditional systems often suffer from insufficient information sharing and communication, leading to decreased work efficiency. Furthermore, determining the optimal division of labor based on each worker's skills and roles is difficult, hindering process optimization. In addition, a lack of real-time monitoring of progress and prompt response measures can lead to delays in appropriate responses when problems arise.

[0604] 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.

[0605] In this invention, the server includes means for adjusting work assignments and generating instructions based on each user's role using intelligent functions, means for constructing a virtual reality environment and displaying synchronized information among users, and means for analyzing users' past performance using a generated AI model and determining the optimal task assignment. This enables efficient collaborative work among geographically dispersed workers, as well as real-time progress monitoring and rapid problem solving.

[0606] "User" refers to an individual or organization that operates specialized equipment to perform tasks using the system.

[0607] "Information processing equipment" refers to computer-related devices used for inputting, processing, and outputting digital data.

[0608] A "computer network" refers to a digital communication system in which multiple computers are connected to enable them to communicate with one another.

[0609] "Authentication information" refers to data used by users to identify themselves when accessing a system.

[0610] "Intelligent function" refers to artificial intelligence technology that analyzes user data and circumstances to make decisions and generate instructions.

[0611] A "virtual reality environment" refers to a system that allows users to visualize the real world overlaid with digital information.

[0612] "Progress data" refers to information that shows the progress of a task and is analyzed for the next processing step.

[0613] A "generative AI model" refers to a machine learning algorithm used to support predictions and decision-making based on historical data.

[0614] To implement this invention, a server must first be connected to multiple information processing devices via a computer network. The server is equipped with intelligent functions and receives user authentication information to identify roles. This allows the server to use a generative AI model to determine the optimal work assignment and generate instructions based on each user's skills and past performance. To build such a system, it is recommended to use general-purpose server hardware and a software framework for implementing machine learning algorithms (e.g., TensorFlow, PyTorch).

[0615] The terminal acts as an information processing device, receiving work instructions from the server and displaying them to the user. Furthermore, the terminal overlays virtual information onto the physical world through a virtual reality environment. This operation requires display technology to realize augmented reality (e.g., AR glasses) and software libraries to display the necessary information (e.g., ARKit, ARCore).

[0616] Users can log into the system and work within a virtual reality environment. This allows users to efficiently complete their tasks and collaborate with other users to solve problems while sharing information. As a result, the system enables highly efficient collaborative work, independent of specific geographical locations.

[0617] As a concrete example, consider maintenance work in the manufacturing industry. When a user inspects equipment, the server sends instructions with virtual guidelines superimposed on the terminal, allowing the user to perform the work accordingly. If an anomaly is detected, the server can use its intelligent functions to conduct a detailed analysis and immediately suggest appropriate countermeasures.

[0618] An example of a prompt would be an instruction such as, "Please suggest the optimal task allocation required for manufacturing line maintenance." This prompt would prompt the generating AI model to suggest appropriate task allocations based on the user's role and situation. In this way, it becomes possible to construct concrete means for implementing the invention.

[0619] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0620] Step 1:

[0621] The server receives user authentication information as input and performs authentication by comparing it with the database. If authentication is successful, the server outputs user role and skill information. This process involves data processing, such as comparing authentication information like user ID and password with an internal database.

[0622] Step 2:

[0623] The server uses the acquired role and skill information as input to determine appropriate work assignments using a generating AI model. This process involves analyzing past performance data, assigning the most suitable tasks to each user, and generating work instructions. This output appears as specific work instructions sent to the terminals.

[0624] Step 3:

[0625] The terminal processes work instructions received from the server as input and outputs them to the user as visual information via an augmented reality display. Here, data processing is performed to overlay it onto the physical world, displaying specific work areas and procedures. Virtual information is provided so that the user can intuitively understand the real environment.

[0626] Step 4:

[0627] Users proceed with their work based on virtual information provided through their terminal. They provide information about their work progress and any problems that occur as input to the terminal, which then sends this information to the server. This output functions as real-time progress reporting and problem logging.

[0628] Step 5:

[0629] The server analyzes progress and problem reports from users as input and uses intelligent functions to suggest solutions. It updates work instructions as needed and sends the new instructions to the terminal. The final output provides the user with specific operations and procedures to perform in the next stage.

[0630] (Application Example 1)

[0631] 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".

[0632] In modern manufacturing environments, processes involving multiple workers and machines are becoming increasingly complex. Therefore, traditional methods struggle to efficiently adjust task allocation based on each worker's skills and roles, leading to delays, errors, and even decreased efficiency. Furthermore, real-time monitoring of work status and rapid response to problems are crucial. Consequently, a system is needed to address these challenges and improve overall factory efficiency through partially automated processes.

[0633] 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.

[0634] In this invention, the server includes means for receiving user authentication data and identifying attributes, means for adjusting work assignments and generating instructions based on each user's attributes using machine learning, and means for constructing an augmented reality environment and displaying synchronized information among users. This enables each worker to perform tasks efficiently and solve problems in real time, regardless of their location.

[0635] "Users" refers to individuals or groups who participate in this system and perform tasks based on their roles.

[0636] A "terminal" refers to a device used by a user to access a system and obtain or input information.

[0637] "Authentication data" refers to information necessary to identify a user and is used for security and role setting purposes.

[0638] "Machine learning" is a method for systems to adaptively learn through data analysis and generate optimal work instructions for individual users.

[0639] "Attributes" refer to characteristics such as a user's skills, experience, and role, and are used for appropriate task assignment.

[0640] "Task assignment" is the process of assigning tasks that are suitable for the user's attributes.

[0641] "Instructions" are pieces of information that indicate the specific actions necessary to carry out a task.

[0642] An "augmented reality environment" is a technology that overlays digital information onto the real-world visual environment, providing intuitive and easy-to-understand work support for users.

[0643] "Synchronized information" refers to information that is unified in real time so that multiple users can see the same data and progress.

[0644] "Progress status" refers to the degree of completion and status of tasks performed by users, and is monitored by the system in real time.

[0645] "Problem resolution measures" refer to the solutions or instructions that the system provides when a problem arises in the work process.

[0646] To realize this invention, the server first receives user authentication data and identifies the attributes of each user. Multi-factor authentication is employed to ensure security. Based on this information, the server uses a machine learning model to adjust the most suitable work assignment for each user and then generates work instructions. This maintains an optimal process flow.

[0647] The device provides services within the user's physical environment. Specifically, it uses an augmented reality (AR) display. This AR functionality is implemented using a software platform like Unity, overlaying user-operable virtual data onto the real world. Users can, for example, view necessary instructions and guidelines in real time using a smartphone or augmented reality headset.

[0648] Users receive work instructions sent from the server via their terminals and perform tasks based on them. Progress is monitored in real time, and the server detects problems as needed. If a problem occurs, the server uses machine learning to analyze it and proposes quick and optimal solutions to the user.

[0649] As a concrete example, consider a parts assembly process in a factory. When a user puts on an AR headset, a list of necessary parts and assembly instructions are displayed in their field of view. The server then automatically optimizes the next step based on the user's progress and sends new instructions immediately.

[0650] Examples of prompt messages are as follows:

[0651] "Please tell me how to use AI to optimize factory robot work schedules and provide work guidance using AR technology."

[0652] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0653] Step 1:

[0654] The server receives authentication data sent from the terminal as input and authenticates the user. This input data includes user ID and password, or biometric authentication information. Once authentication is successful, the server retrieves the user's attribute information from the database and generates a user profile as output. This profile includes roles, skill sets, and past work history.

[0655] Step 2:

[0656] The server uses machine learning algorithms to calculate the optimal task assignment based on each user's profile as input data. As part of the data processing, it first analyzes the profile data to generate a user skill matrix. Based on this, it generates appropriate work instructions and designs the next work step as output. It also utilizes a generative AI model to create situation-sensitive prompts.

[0657] Step 3:

[0658] The server sends work instructions to the terminal. The terminal then converts the received work instruction data into an augmented reality (AR) display. Specifically, it overlays virtual guidelines onto the user's physical environment based on the instruction data. This allows the user to intuitively and visually understand the next work step.

[0659] Step 4:

[0660] The user performs the assigned task while referring to the AR display. They periodically report their work progress to the server via their device as input data. The server monitors the progress data in real time and records the updated work status in a database as output.

[0661] Step 5:

[0662] The server uses machine learning models to analyze progress data collected in real time, and when problems arise, it proposes the optimal solution to the user. By utilizing generative AI models to output immediate prompts, users can quickly move on to the next task.

[0663] Step 6:

[0664] The user continues working based on the proposed solution. The server receives the final work output as input and stores it in the output database. This data is later analyzed to improve future work plans.

[0665] 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.

[0666] This invention combines an emotion engine with a system in which multiple users collaborate via a computer network to recognize the emotional state of users in real time and dynamically adjust work instructions and the environment. The system consists of a central server, user terminals, and an emotion engine as its main components.

[0667] The server connects to multiple terminals via the network and, after receiving authentication information from each user, generates work instructions based on the user's skills and role. The artificial intelligence assigns tasks optimally according to each user's role and sends those instructions from the server.

[0668] The terminal presents the user with an augmented reality environment based on instructions received from the server. Through the augmented reality display, the physical work environment and virtual work instructions are overlaid, allowing the user to intuitively proceed with their tasks. The terminal also incorporates an emotion engine that recognizes the user's emotional state through the camera and voice input, and transmits this data to the server. The emotion engine determines the user's stress level and concentration level from their facial expressions and tone of voice, dynamically changing the presence and content of work instructions accordingly.

[0669] Users work while utilizing the augmented reality environment provided by their device. Work instructions are adjusted based on recognized emotions, allowing users to perform tasks efficiently while reducing their burden. For example, in a machine assembly task, if the user is feeling stressed, the system can simplify the task or provide messages to encourage relaxation.

[0670] The server continuously monitors user progress and emotional data, performing data analysis to improve overall work efficiency. The analysis results are fed back into the next work plan and used to optimize the work environment for each user. In this way, the system takes into account the user's emotional state, enabling flexible instruction adjustments and creating a more effective collaborative work environment.

[0671] The following describes the processing flow.

[0672] Step 1:

[0673] The server receives a login request from a user and initiates the authentication process. It verifies the authentication information entered by the user and identifies the role and skills information corresponding to that user.

[0674] Step 2:

[0675] The terminal sets up the augmented reality environment based on the user's role information received from the server. The terminal loads the necessary virtual content and prepares to overlay the virtual information onto the physical environment that the user is accessing.

[0676] Step 3:

[0677] The server's artificial intelligence analyzes each user's role, skills, and progress data to determine appropriate work instructions and task assignments. The determined work instructions are then sent from the server to the relevant terminals.

[0678] Step 4:

[0679] The terminal displays work instructions received from the server on an augmented reality display, providing the user with an intuitive work guide. Furthermore, an emotion engine built into the terminal analyzes the user's facial expressions and voice in real time to evaluate their emotional state.

[0680] Step 5:

[0681] The user receives adjustments to the work instructions provided by the device based on their emotional state, which is assessed by the emotion engine. For example, if the user indicates a high stress level, the device may simplify the work procedure or display a message prompting them to take a break.

[0682] Step 6:

[0683] The server monitors progress and sentiment data transmitted from terminals in real time and analyzes each user's work status. If a problem is detected, the server immediately derives a solution and sends that information to the relevant terminal.

[0684] Step 7:

[0685] Once a user completes a task, the terminal reports the results to the server. The server collects data on completed tasks and sentiment feedback, and analyzes it to help improve future projects.

[0686] (Example 2)

[0687] 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".

[0688] Current collaborative work systems suffer from insufficient adjustment of dynamic work instructions based on user emotions, and are unable to provide appropriate support according to user stress levels and concentration levels. Furthermore, while it is necessary to consider emotional states in real time to improve work progress and efficiency, systems with such functionality are limited.

[0689] 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.

[0690] In this invention, the server includes means for receiving user authentication information and identifying roles, means for using artificial intelligence to adjust work assignments based on each user's role and generate instructions, and means for recognizing the user's emotional state in real time using an emotion analysis device and generating and dynamically adjusting work instructions accordingly. This makes it possible to immediately reflect the user's emotional state and provide an optimal work environment and support.

[0691] "User authentication information" refers to data used to identify a user when accessing a system, and typically includes a username and password.

[0692] Artificial intelligence is a technology that enables computers to mimic human intellectual activity, automating data analysis and complex decision-making processes.

[0693] An "augmented reality environment" is a technology that overlays computer-generated information onto the real world, allowing users to experience both the physical environment and digital information simultaneously.

[0694] An "emotion analysis device" is a device or system that analyzes a user's facial expressions and tone of voice to determine their emotional state and output it as data.

[0695] "Dynamic adjustment" refers to a mechanism where the system automatically changes its functions and behavior in response to the user's state and circumstances, which change in real time.

[0696] This invention provides a system for collaborative work among multiple users using a computer network, aiming to recognize the emotional state of users in real time and provide dynamic work instructions accordingly. The system mainly consists of a server, terminals, and an emotion analysis device.

[0697] The server connects to each user terminal via the network and receives user authentication information. After successful authentication, the server uses artificial intelligence to generate optimal work instructions based on the user's skills and role. A generative AI model is used for this process.

[0698] The terminal provides the user with an augmented reality environment based on work instructions received from the server. For example, by using an augmented reality display as the terminal, the user can view the physical work environment overlaid with virtual information. The terminal also incorporates an emotion analysis device that recognizes the user's emotional state in real time through a camera and voice input device. The recognized data is sent to the server to analyze the user's stress level and concentration level.

[0699] Users perform tasks using their devices, but they can receive different work instructions based on their emotional data. For example, if the system detects that a user is experiencing high levels of stress, it may simplify tasks or offer encouraging messages. In this way, users can work more efficiently.

[0700] As a concrete example, consider the assembly of parts in manufacturing. If a user encounters difficulties in a part of the process, the system can provide a message such as "Proceed with confidence" and display other guidance to reduce the workload.

[0701] An example of a prompt might be, "The user is tackling a difficult task and is highly focused. Please suggest the most appropriate support message for this situation." By using this prompt, the generative AI model can provide appropriate responses based on the situation.

[0702] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0703] Step 1:

[0704] The server receives authentication information from each user's terminal via the network. This authentication information includes user ID and password. Based on the entered authentication information, the server performs authentication by comparing it with user information in the database. If authentication is successful, the server extracts and outputs profile information such as the user's role and skill set.

[0705] Step 2:

[0706] The server generates work instructions using an AI model based on the acquired user role and skill information. The AI ​​model takes prompt text as input and calculates the optimal task distribution for each user. As a result of the calculation, the specific tasks and procedures required for each user are output and sent as instructions to the user's terminal.

[0707] Step 3:

[0708] The terminal displays work instructions received from the server. Using an augmented reality display, virtual information is overlaid onto the physical work environment. This information includes task procedures, warnings, and visual guides to assist the user. By viewing the terminal display, the user can intuitively proceed with their work.

[0709] Step 4:

[0710] The user performs tasks while operating the device. During the task, the device's camera captures the user's facial expressions and the microphone records their voice. Based on this data, the device's emotion analysis device recognizes the user's emotional state in real time. The analysis results in the user's stress level and concentration level being output as numerical data, which is then sent to the server.

[0711] Step 5:

[0712] The server analyzes emotional data transmitted from the terminal. Based on the input data, it identifies the problems and difficulties the user is currently facing. Based on the identified information, the server dynamically adjusts the instructions and outputs and transmits newly generated work instructions to the terminal. This reduces the burden on the user and improves efficiency.

[0713] (Application Example 2)

[0714] 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".

[0715] In conventional collaborative work systems, uniform work instructions are given without considering the emotional state of the users, which can increase the workload on users and decrease productivity. Furthermore, efficient use of machinery and equipment in cooperation with users is difficult, making it challenging to optimize the overall work process. Therefore, there is a need for a means to dynamically adjust work instructions based on users' emotions and to strengthen coordination with machinery and equipment.

[0716] 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.

[0717] In this invention, the server includes means for adjusting work assignments and generating instructions based on the roles of users; means for constructing a virtual reality environment and presenting synchronized information among users; means for detecting the emotional state of users using an emotion recognition engine and dynamically adjusting work instructions based on the detection results; and means for reducing the burden on users in cooperation with mechanical devices that support the work. This enables flexible and efficient work management according to the user's situation, thereby improving productivity.

[0718] An "information processing network" is a system that connects multiple terminals accessible from different geographical locations to send, receive, and process information.

[0719] A "user" is a person who participates in collaborative work via an information processing network and operates a terminal.

[0720] A "terminal" is a device used by users to access an information processing network, and includes computers and smart glasses.

[0721] An "intelligent engine" is a control device that includes algorithms and programs that adjust the division of tasks and generate instructions based on the user's role and situation.

[0722] A "virtual reality environment" is a technology that overlays virtual information onto the physical environment of the real world, providing users with an immersive experience.

[0723] An "emotion recognition engine" is a system that detects a user's emotional state from their facial expressions, voice, etc., and processes it as data.

[0724] "Mechanical equipment" is a general term for robots and automated machines that work in cooperation with users in factories and workplaces.

[0725] "Work management" refers to the process of assigning tasks and giving instructions in the most appropriate way, taking into account the work status and emotional state of the users.

[0726] The system that realizes this invention comprises an information processing network, terminal devices, and an intelligent engine, a virtual reality environment, and an emotion recognition engine as integrated components.

[0727] The server has the ability to receive user authentication information from multiple terminals located in different geographical locations via an information processing network. For authenticated users, the intelligent engine efficiently assigns tasks based on their respective roles and generates work instructions. This allows users to immediately understand the specific tasks assigned to their roles.

[0728] The terminal receives instructions generated by an intelligent engine and provides a virtual reality environment. By overlaying virtual elements onto the physical workspace, users can intuitively understand the instructions and perform the tasks. The terminal is also equipped with a camera and microphone, and an emotion recognition engine records the user's real-time emotional state through these input devices.

[0729] The emotion recognition engine uses machine learning frameworks such as TensorFlow to analyze the user's emotions, including stress levels and concentration, from their facial expressions and voice. The server receives the emotion data and dynamically adjusts the instructions based on the analysis results. This reduces the burden on the user and improves work efficiency.

[0730] As a concrete example, consider a factory production line. If fatigue is detected while a user is wearing smart glasses and assembling a product, the system displays a message prompting them to take a break and, if necessary, redistributes instructions to automated machinery to take over the work. An example of a prompt message in this case would be, "User fatigue has been detected. Assign additional assembly tasks to the robot and prompt the user to take a break."

[0731] In this way, the system can flexibly adapt to the user's condition and continuously provide the optimal working environment.

[0732] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0733] Step 1:

[0734] The server receives user authentication information from the terminal via the information processing network. It receives user IDs and authentication tokens as input, and identifies users by comparing them with the database. As a result of the comparison, role information is output for users who have successfully been authenticated.

[0735] Step 2:

[0736] The server uses an intelligent engine to coordinate work assignments based on the roles of authenticated users. Using role information and current work status data as input, the intelligent engine calculates the optimal tasks and their order. As output, it generates customized work instructions for each user.

[0737] Step 3:

[0738] The terminal receives work instructions sent from the server and presents them to the user in a virtual reality environment. Using the received work instruction data as input, it visualizes the work procedure on the AR display by overlaying it with the physical environment. As output, it provides an interactive work guide that the user can visually recognize.

[0739] Step 4:

[0740] The device collects user emotional data in real time via its camera and microphone. It acquires video and audio data as input and feeds it into an emotion recognition engine. Through data processing, it analyzes the user's emotional state and outputs metrics such as stress levels and concentration levels.

[0741] Step 5:

[0742] The server analyzes emotional data received from the terminal and dynamically adjusts work instructions as needed. Using the user's emotional metrics and current work status as input, a generative AI model formulates optimal work modification proposals. As output, it provides the user with new instructions and relaxation suggestions.

[0743] Step 6:

[0744] Users perform tasks based on instructions from their terminals, and in some cases, collaborate with machinery to reduce their workload. They refer to on-screen guides as input and achieve efficient work execution and smooth collaborative work as output. This entire process forms a continuous feedback loop, continuously optimizing the work environment.

[0745] 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.

[0746] 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.

[0747] 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.

[0748] 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.

[0749] 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.

[0750] 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.

[0751] 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.

[0752] 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.

[0753] 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."

[0754] 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.

[0755] 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.

[0756] 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.

[0757] 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.

[0758] 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.

[0759] 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.

[0760] 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.

[0761] 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.

[0762] 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.

[0763] 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.

[0764] 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.

[0765] 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.

[0766] The following is further disclosed regarding the embodiments described above.

[0767] (Claim 1)

[0768] A computer network-based system that enables collaborative work involving multiple users from different geographical locations via accessible devices,

[0769] A means for receiving user authentication information and identifying roles,

[0770] A means of using artificial intelligence to adjust the division of tasks based on each user's role and generate instructions,

[0771] A means of constructing an augmented reality environment and displaying synchronized information among users,

[0772] A means to continuously monitor the user's progress and propose countermeasures when problems occur,

[0773] A system that includes this.

[0774] (Claim 2)

[0775] The system according to claim 1, which has means for displaying work instructions received from a server on a user device and providing virtual information overlaid on the physical environment.

[0776] (Claim 3)

[0777] The system according to claim 1, comprising means for collecting and analyzing progress data to identify areas for improvement in the next work.

[0778] "Example 1"

[0779] (Claim 1)

[0780] A computer network-based system that enables collaborative work in which multiple users participate via information processing devices accessible from different geographical locations,

[0781] A means for receiving user authentication information and identifying roles,

[0782] A means of using intelligent functions to adjust the division of labor based on each user's role and generate instructions,

[0783] A means of constructing a virtual reality environment and displaying synchronized information among users,

[0784] A means to continuously monitor the user's progress and propose countermeasures when problems occur,

[0785] In an information processing device, a means for displaying work instructions received from a computer and providing virtual information superimposed on the physical world,

[0786] A means of collecting and analyzing progress data to identify areas for improvement in the next task,

[0787] A method for analyzing users' past performance using a generative AI model to determine the optimal task allocation,

[0788] A means of monitoring progress in real time and updating work instructions as needed,

[0789] A system that includes this.

[0790] (Claim 2)

[0791] The system according to claim 1, comprising means for sharing the same virtual workspace with other engineers using a virtual reality environment.

[0792] (Claim 3)

[0793] The system according to claim 1, comprising means for utilizing intelligent functions to generate rapid countermeasures for identified problems.

[0794] "Application Example 1"

[0795] (Claim 1)

[0796] A system that utilizes an information network to enable collaborative work in which multiple users participate via terminals accessible from different locations,

[0797] A means for receiving user authentication data and identifying attributes,

[0798] A means of adjusting work assignments and generating instructions based on the attributes of each user using machine learning,

[0799] A means of constructing an augmented reality environment and displaying synchronized information among users,

[0800] A means to continuously monitor the user's progress and propose countermeasures when problems occur,

[0801] A means of providing an optimized work schedule through machine learning and providing operational guidance via augmented reality display,

[0802] A system that includes this.

[0803] (Claim 2)

[0804] The system according to claim 1, having means for displaying work instructions received from a server on a terminal and providing virtual data overlaid on a physical environment.

[0805] (Claim 3)

[0806] The system according to claim 1, comprising means for collecting and analyzing progress data to identify areas for improvement in the next work and for providing visual guidelines through augmented reality display.

[0807] "Example 2 of combining an emotion engine"

[0808] (Claim 1)

[0809] A means for receiving user authentication information and identifying roles,

[0810] A means of using artificial intelligence to adjust the division of tasks based on each user's role and generate instructions,

[0811] A means of constructing an augmented reality environment and displaying synchronized information among users,

[0812] A means for recognizing the user's emotional state in real time using an emotion analysis device, and generating and dynamically adjusting work instructions according to the results,

[0813] A means to continuously monitor the user's progress and propose countermeasures when problems occur,

[0814] A system that includes this.

[0815] (Claim 2)

[0816] The system according to claim 1, comprising means for displaying work instructions received from a server and providing virtual information overlaid on a physical environment.

[0817] (Claim 3)

[0818] The system according to claim 1, comprising means for collecting and analyzing progress data and sentiment data to identify areas for improvement in the next work and providing feedback as design input.

[0819] "Application example 2 when combining with an emotional engine"

[0820] (Claim 1)

[0821] A system utilizing an information processing network that enables collaborative work in which multiple users participate via terminals accessible from different geographical locations,

[0822] A device for receiving user authentication information and identifying roles,

[0823] A device that uses an intelligent engine to adjust the division of tasks based on each user's role and generates instructions,

[0824] A device that constructs a virtual reality environment and presents synchronized information among users,

[0825] A device that continuously monitors the user's progress and proposes countermeasures when problems occur,

[0826] A device that uses an emotion recognition engine to detect the user's emotional state and dynamically adjusts work instructions based on the detection results,

[0827] A device that reduces the burden on users by coordinating with machinery and equipment that support the work,

[0828] A system that includes this.

[0829] (Claim 2)

[0830] The system according to claim 1, comprising a device for displaying work instructions received from a server on a user terminal and providing virtual information overlaid on the real environment.

[0831] (Claim 3)

[0832] The system according to claim 1, comprising a device for collecting and analyzing progress data and sentiment data to identify areas for improvement in the next task and for optimizing the work environment for each user. [Explanation of symbols]

[0833] 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 system that utilizes an information network to enable collaborative work in which multiple users participate via terminals accessible from different locations, A means for receiving user authentication data and identifying attributes, A means of adjusting work assignments and generating instructions based on the attributes of each user using machine learning, A means of constructing an augmented reality environment and displaying synchronized information among users, A means to continuously monitor the user's progress and propose countermeasures when problems occur, A means of providing an optimized work schedule through machine learning and providing operational guidance via augmented reality display, A system that includes this.

2. The system according to claim 1, further comprising means for displaying work instructions received from a server on a terminal and providing virtual data overlaid on a physical environment.

3. The system according to claim 1, comprising means for collecting and analyzing progress data to identify areas for improvement in the next work and for providing visual guidelines through augmented reality display.

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