system

Abstract

The system according to this embodiment aims to streamline communication and task management in remote work. [Solution] The system according to the embodiment comprises a provisioning unit, a task management unit, a meeting support unit, a communication promotion unit, and a security measures unit. The provisioning unit provides a virtual office environment that allows users to access a virtual office space and communicate with other team members in real time. The task management unit analyzes the skills and workload of each member and optimally distributes tasks. The meeting support unit automates meeting scheduling and automatically generates meeting minutes. The communication promotion unit analyzes communication patterns within the team and makes improvement suggestions. The security measures unit implements secure data sharing and access management.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In the prior art, communication and task management in remote work are not efficiently performed, and there is room for improvement.

[0005] The system according to the embodiment aims to improve communication and task management in remote work.

Means for Solving the Problems

[0006] The system according to this embodiment comprises a provisioning unit, a task management unit, a meeting support unit, a communication promotion unit, and a security measures unit. The provisioning unit provides a virtual office environment that allows users to access a virtual office space and communicate with other team members in real time. The task management unit analyzes the skills and workload of each member and optimally distributes tasks. The meeting support unit automates meeting scheduling and automatically generates meeting minutes. The communication promotion unit analyzes communication patterns within the team and makes improvement suggestions. The security measures unit implements secure data sharing and access management. [Effects of the Invention]

[0007] The system according to this embodiment can streamline communication and task management in remote work. [Brief explanation of the drawing]

[0008] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Modes for carrying out the invention]

[0009] Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings.

[0010] First, let's explain the terminology used in the following explanation.

[0011] In the following embodiments, the signed processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Furthermore, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include CPU (Central Processing Unit), GPU (Graphics Processing Unit), GPGPU (General-Purpose computing on Graphics Processing Units), APU (Accelerated Processing Unit), or TPU (Tensor Processing Unit).

[0012] In the following embodiments, signed RAM (Random Access Memory) is a memory that temporarily stores information and is used as work memory by the processor.

[0013] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0014] In the following embodiments, the numbered communication I / F (Interface) is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between a plurality of computers. Examples of communication standards applied to the communication I / F include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0015] 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 only A, only B, or a combination of A and B. Also, in this specification, when expressing three or more matters connected by "and / or", the same concept as "A and / or B" is applied.

[0016] [First Embodiment] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0017] As shown in FIG. 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.

[0018] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. Also, the database 24 and the communication I / F 26 are connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0019] 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.

[0020] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, and accepts user input. The touch panel 38A accepts user input via touch by detecting contact with an object (e.g., a pen or finger). The microphone 38B accepts user input via voice 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 unit 12. In the data processing unit 12, the specific processing unit 290 (see Figure 2) acquires the data indicating the user input.

[0021] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user by outputting the data in a form perceptible to the user (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.

[0022] 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.

[0023] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0024] 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.

[0025] 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. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0026] In the smart device 14, specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as a control unit 46A according to the specific processing program 60 executed on the RAM 48. The smart device 14 also has a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0027] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device (e.g., a generation server) may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device having the data generation model 58. The data processing device 12 may also be a server device or a terminal device owned by a user (e.g., a mobile phone, robot, home appliance, etc.). Next, an example of processing by the data processing system 10 according to the first embodiment will be described.

[0028] (Example of form 1) The system according to an embodiment of the present invention is an AI agent that streamlines remote work on the metaverse. This system supports improved productivity in remote work by providing a virtual office space, facilitating communication between teams, and managing tasks. For example, the system provides a virtual office environment in which users can access a virtual office space and communicate with other team members in real time. The system provides a communication environment similar to that of a physical office. The system has a task management function that analyzes the skills and workload of each member and optimally distributes tasks. For example, the system grasps the progress of a project in real time and automatically adjusts task assignments. The system provides a meeting support function that automates meeting scheduling and minute-taking. For example, the system summarizes the content of a meeting using natural language processing technology and shares it as minutes. The system has a communication promotion function that facilitates interaction and information sharing among team members. For example, the system analyzes communication patterns within a team and makes suggestions for improvement. The system provides security measures that ensure the secure sharing and access management of data. For example, the system strictly manages access rights to confidential information and prevents unauthorized access. This allows the system to streamline remote work on the metaverse and improve productivity.

[0029] The system according to this embodiment comprises a provisioning unit, a task management unit, a meeting support unit, a communication promotion unit, and a security measures unit. The provisioning unit allows users to access a virtual office space and communicate with other team members in real time. For example, the provisioning unit allows users to enter a virtual meeting room and conduct video conferences with other members. The provisioning unit provides an interface for users to access the virtual office space. The task management unit analyzes the skills and workload of each member and optimally distributes tasks. For example, the task management unit grasps the progress of a project in real time and automatically adjusts task assignments. The task management unit visualizes the progress of a project in real time and monitors the progress of tasks. The meeting support unit automates scheduling meetings and automatically generates meeting minutes. For example, the meeting support unit summarizes the content of a meeting using natural language processing technology and shares it as meeting minutes. The meeting support unit translates the content of a meeting in real time and generates multilingual meeting minutes. The communication promotion unit analyzes communication patterns within the team and makes improvement suggestions. The Communication Promotion Department, for example, will propose ways to encourage communication at the appropriate time if there is insufficient interaction among team members. The Communication Promotion Department will monitor the frequency of interaction among team members in real time and promote interaction at the appropriate time. The Security Measures Department will implement secure data sharing and access management. For example, the Security Measures Department will strictly manage access rights to confidential information and prevent unauthorized access. The Security Measures Department will analyze data access history in detail and detect signs of unauthorized access in real time. As a result, the system according to the embodiment can streamline remote work on the metaverse and improve productivity.

[0030] The service provider enables users to access a virtual office space and communicate with other team members in real time. Specifically, the service provider provides an interface for users to enter a virtual meeting room and conduct video conferences with other members. This interface is designed for ease of use, allowing users to access the virtual space intuitively. For example, users can control their avatar to move around the virtual office and interact with other members' avatars. During video conferences, camera footage and audio are synchronized in real time, enabling natural communication. The service provider also provides chat and file sharing functions within the virtual space, allowing users to quickly share necessary information. Furthermore, the service provider monitors user access in real time and provides support as needed. For example, if the connection is unstable, the service provider will automatically retry the connection to ensure that users can continue to communicate smoothly. The service provider can also analyze user usage and suggest optimizations for the layout and functions of the virtual space. In this way, the service provider supports users in comfortably using the virtual office space and facilitates smooth communication throughout the team.

[0031] The task management department analyzes each member's skills and workload to optimally distribute tasks. Specifically, it monitors each member's skill set and current workload in real time and automatically adjusts task allocation according to the project's progress. For example, if a member possesses a particular skill, tasks that utilize that skill will be prioritized. It also has a function to evenly distribute tasks to prevent excessive workload imbalances among members. The task management department visualizes project progress in real time and monitors the progress of each task. This allows project managers to quickly understand which tasks are behind schedule and which members need support. Furthermore, the task management department uses AI to analyze past project data and identify factors that affect task progress. This allows for the prediction of project risks in advance and the implementation of appropriate countermeasures. For example, if past data reveals that a particular task is prone to delays, measures such as allocating additional resources to that task will be taken. The task management department also includes features to facilitate communication among members, providing chat and file sharing functions for sharing task-related information. This allows the task management department to streamline project progress and improve overall team productivity.

[0032] The Meeting Support Department automates meeting scheduling and automatically generates meeting minutes. Specifically, it checks each member's schedule in real time and suggests the optimal meeting time. For example, it synchronizes each member's calendar and automatically selects a time slot when everyone can participate. It also has a function to automatically send meeting invitations and confirm participant attendance. Once a meeting begins, the Meeting Support Department records the meeting content in real time and generates a summary using natural language processing technology. This automatically creates meeting minutes, which are then shared with participants. Furthermore, the Meeting Support Department can translate the meeting content in real time and generate multilingual minutes. This enables smooth communication even among members who speak different languages. The Meeting Support Department also has a function to analyze the meeting content using AI and extract important points and action items. This allows for efficient post-meeting follow-up and smoother task progress. In addition, the Meeting Support Department provides a function to analyze past meeting data and evaluate the effectiveness of meetings. This allows for the identification of areas for improvement to enhance the quality of meetings and to be reflected in future meetings. This allows the meeting support department to improve the efficiency and quality of meetings, thereby increasing the overall productivity of the team.

[0033] The Communication Facilitation Department analyzes communication patterns within teams and proposes improvements. Specifically, it monitors the frequency and content of each member's communication in real time to understand the state of interaction within the team. For example, if there is a lack of communication between certain members, it will propose encouraging interaction among those members. It can also propose training and workshops to improve the quality of communication. The Communication Facilitation Department uses AI to analyze the content of communication and identify problems and areas for improvement within the team. For example, it analyzes frequently appearing keywords and phrases in conversations to understand common issues and concerns within the team. It can also analyze the tone and emotion of communication to evaluate the team's atmosphere and members' stress levels. This allows the Communication Facilitation Department to make concrete suggestions to smooth communication within the team and improve member motivation and engagement. Furthermore, the Communication Facilitation Department has a function to regularly review the communication situation and evaluate the effectiveness of improvements. This enables continuous improvement and enhances team performance.

[0034] The Security Measures Department implements secure data sharing and access management. Specifically, the Security Measures Department strictly manages access rights to confidential information and prevents unauthorized access. For example, it sets appropriate access rights for each user and restricts access to confidential information. It also has a function that records access history in detail and issues an immediate warning if abnormal access is detected. The Security Measures Department uses AI to analyze access history and detect signs of unauthorized access in real time. For example, if there is access from an unusual time or location, it automatically blocks the access and notifies the administrator. The Security Measures Department also ensures secure data sharing by using data encryption and secure communication protocols. This minimizes the risk of data being intercepted by third parties. Furthermore, the Security Measures Department regularly reviews security policies and takes measures to address new threats. For example, if a new security threat is discovered, it quickly shares the information and updates the system and applies patches. It is also important to provide security education to users to improve security awareness. In this way, the Security Measures Department can maintain the security of the entire system and ensure the safety of data.

[0035] The service provider allows users to enter a virtual meeting room and conduct video conferences with other members. The service provider constructs the virtual meeting room using 3D modeling technology and includes interactive elements. The service provider uses WebRTC technology for conducting video conferences. The service provider uses video streaming technology to achieve high-quality video conferencing. This enables video conferencing in the virtual meeting room and facilitates communication for remote work. Some or all of the above processing in the service provider may be performed using, for example, generative AI, or not using generative AI. For example, the service provider can have generative AI perform 3D modeling of the virtual meeting room.

[0036] The task management unit monitors project progress in real time and automatically adjusts task allocation. For example, the task management unit monitors project progress in real time and automatically adjusts task allocation. The task management unit visualizes project progress in real time and monitors task progress. The task management unit optimizes task allocation using AI algorithms. The task management unit automatically adjusts task allocation using a rule-based system. The task management unit visualizes project progress in real time using a dashboard. This allows for real-time monitoring of project progress and optimization of task allocation. Some or all of the above processes in the task management unit may be performed using, for example, generative AI, or without generative AI. For example, the task management unit can have generative AI perform the visualization of project progress.

[0037] The meeting support department summarizes the meeting content using natural language processing technology and shares it as meeting minutes. For example, the meeting support department summarizes the meeting content using natural language processing technology and shares it as meeting minutes. The meeting support department summarizes the meeting content using morphological analysis. The meeting support department summarizes the meeting content using grammatical analysis. The meeting support department summarizes the meeting content using semantic analysis. The meeting support department considers the length of the text and the importance of the information to be summarized as criteria for summarization. By summarizing the meeting content and sharing it as meeting minutes, the meeting support department aims to improve the efficiency of meetings. Some or all of the above processing in the meeting support department may be performed using, for example, generative AI, or not using generative AI. For example, the meeting support department can have generative AI perform the summarization of the meeting content.

[0038] The Communication Promotion Department will propose ways to encourage communication at appropriate times if there is insufficient interaction among team members. For example, the Communication Promotion Department will propose ways to encourage communication at appropriate times if there is insufficient interaction among team members. The Communication Promotion Department will determine if there is insufficient interaction based on the frequency of interaction. The Communication Promotion Department will analyze communication logs to determine if there is insufficient interaction. The Communication Promotion Department will propose ways to encourage communication at appropriate times, taking into account working hours and project progress. This will promote interaction among team members and enable smooth information sharing. Some or all of the above processes in the Communication Promotion Department may be performed using, for example, generative AI, or not using generative AI. For example, the Communication Promotion Department may have generative AI perform the analysis of interaction frequency.

[0039] The Security Measures Department strictly manages access rights to confidential information and prevents unauthorized access. For example, the Security Measures Department strictly manages access rights to confidential information and prevents unauthorized access. The Security Measures Department manages access rights to confidential information using access control lists. The Security Measures Department manages access rights to confidential information using role-based access control. The Security Measures Department prevents unauthorized access using intrusion detection systems. The Security Measures Department prevents unauthorized access using firewalls. This ensures strict management of access rights to confidential information and prevents unauthorized access. Some or all of the above processes in the Security Measures Department may be performed using, for example, generative AI, or without generative AI. For example, the Security Measures Department can have generative AI manage access control lists.

[0040] The service provider analyzes the user's past virtual office usage history and proposes the optimal communication method. For example, the service provider prioritizes suggesting communication tools that the user has frequently used in the past. The service provider suggests similar methods based on the user's past successful communication patterns. The service provider prompts communication at the optimal time based on the user's past usage history. In this way, the service provider proposes the optimal communication method based on the user's past usage history. Some or all of the above processing in the service provider may be performed using, for example, generative AI, or without generative AI. For example, the service provider can have generative AI perform the analysis of past usage history.

[0041] The service provider analyzes user behavior patterns in the virtual office space and designs efficient movement paths. For example, the service provider identifies areas that users frequently move to and designs movement paths that allow them to travel the shortest distance. The service provider places frequently used functions and tools close together and designs movement paths that are easily accessible. Based on user behavior patterns, the service provider designs movement paths that avoid congestion. In this way, by analyzing user behavior patterns and designing efficient movement paths, work efficiency is improved. Some or all of the above processes in the service provider may be performed using, for example, generative AI, or not using generative AI. For example, the service provider can have generative AI perform the analysis of behavior patterns.

[0042] The service provider proposes optimal communication timing, taking into account the user's geographical location within the virtual office space. For example, if the user is in a different time zone, the service provider proposes the optimal communication time. If the user is on the move, the service provider proposes refraining from communication until the move is complete. If the user is in a specific location, the service provider proposes a communication method appropriate for that location. This allows the service provider to propose optimal communication timing, taking into account the user's geographical location. Some or all of the above processing in the service provider may be performed using, for example, generative AI, or without generative AI. For example, the service provider can have generative AI perform the analysis of geographical location information.

[0043] The service provider analyzes users' social media activity in the virtual office space and provides relevant information. For example, the service provider suggests relevant projects and tasks based on information shared by users on social media. The service provider provides information based on users' interests and preferences from their social media activity. The service provider makes suggestions to facilitate communication with members that users have interacted with on social media. In this way, by analyzing users' social media activity and providing relevant information, work efficiency is improved. Some or all of the above processing in the service provider may be performed using, for example, generative AI, or not using generative AI. For example, the service provider can have generative AI perform the analysis of social media activity.

[0044] The task management department analyzes each member's skill set in detail and optimizes task allocation. For example, the task management department assigns the most suitable tasks based on each member's skills. The task management department analyzes each member's past performance and assigns appropriate tasks. The task management department considers each member's skill set and assigns tasks in a way that balances the entire team. This allows for a detailed analysis of each member's skill set and optimizes task allocation. Some or all of the above processes in the task management department may be performed using, for example, generative AI, or not. For example, the task management department can have generative AI perform the skill set analysis.

[0045] The task management department visualizes project progress in real time and monitors task progress. For example, the task management department visualizes project progress using graphs and charts. The task management department updates task progress in real time and notifies members. The task management department automatically adjusts task priorities according to project progress. This allows for real-time visualization of project progress and monitoring of task progress. Some or all of the above processes in the task management department may be performed using, for example, generative AI, or without generative AI. For example, the task management department can have generative AI perform the visualization of progress.

[0046] The task management unit assigns the most suitable tasks to users, taking into account their geographical location information. For example, if a user is in a different time zone, the task management unit assigns the most suitable tasks. If a user is on the move, the task management unit suggests withholding tasks until the move is complete. If a user is in a specific location, the task management unit assigns tasks appropriate to that location. In this way, the task management unit assigns the most suitable tasks, taking into account the user's geographical location information. Some or all of the above processes in the task management unit may be performed using, for example, a generative AI, or not using a generative AI. For example, the task management unit can have a generative AI perform the analysis of geographical location information.

[0047] The task management unit analyzes the user's social media activity and suggests relevant tasks during task management. For example, the task management unit suggests relevant tasks based on information shared by the user on social media. The task management unit suggests tasks based on the user's interests and preferences from their social media activity. The task management unit suggests collaborative tasks with members the user has interacted with on social media. By analyzing the user's social media activity and suggesting relevant tasks, the task management unit improves work efficiency. Some or all of the above processes in the task management unit may be performed using, for example, generative AI, or without generative AI. For example, the task management unit can have generative AI perform the analysis of social media activity.

[0048] The meeting support department translates meeting content in real time and generates multilingual meeting minutes. For example, the meeting support department translates meeting content in real time and provides it to participants. The meeting support department automatically generates and shares multilingual meeting minutes. The meeting support department summarizes meeting content and provides summaries in each language. This facilitates communication among international teams by translating meeting content in real time and generating multilingual meeting minutes. Some or all of the above processes in the meeting support department may be performed using, for example, generative AI, or not using generative AI. For example, the meeting support department can have generative AI perform real-time translation.

[0049] The meeting support department analyzes the frequency of participation in meetings to promote balanced discussion. For example, the meeting support department makes suggestions to encourage participants who speak infrequently to speak more. The meeting support department also suggests to participants who speak frequently that they listen to the opinions of other participants. The meeting support department visualizes participation frequency in real time to promote balanced discussion. In this way, the quality of meetings is improved by analyzing the participation frequency of participants and promoting balanced discussion. Some or all of the above processing in the meeting support department may be performed using, for example, generative AI, or not using generative AI. For example, the meeting support department can have generative AI perform the analysis of participation frequency.

[0050] The meeting support unit, when providing meeting support, proposes the optimal meeting time, taking into account the user's geographical location. For example, if the user is in a different time zone, the meeting support unit proposes the optimal meeting time. If the user is traveling, the meeting support unit proposes postponing the meeting until the travel is complete. If the user is in a specific location, the meeting support unit proposes a meeting time appropriate for that location. In this way, by proposing the optimal meeting time, taking into account the user's geographical location, the efficiency of the meeting is improved. Some or all of the above processing in the meeting support unit may be performed using, for example, generative AI, or without generative AI. For example, the meeting support unit can have generative AI perform the analysis of geographical location information.

[0051] The meeting support department analyzes users' social media activity and proposes relevant agenda items during meeting support. For example, the meeting support department proposes relevant agenda items based on information shared by users on social media. The meeting support department proposes agenda items based on users' interests and preferences from their social media activity. The meeting support department proposes joint agenda items with members that users have interacted with on social media. In this way, the efficiency of meetings is improved by analyzing users' social media activity and proposing relevant agenda items. Some or all of the above processes in the meeting support department may be performed using, for example, generative AI, or not using generative AI. For example, the meeting support department can have generative AI perform the analysis of social media activity.

[0052] The Communication Facilitation Department analyzes the team's communication patterns in detail and proposes the most suitable communication methods. For example, the Communication Facilitation Department prioritizes suggesting the most frequently used communication tools within the team. The Communication Facilitation Department analyzes the communication frequency of team members and proposes the optimal timing for communication. Based on the team's communication patterns, the Communication Facilitation Department proposes efficient information sharing methods. In this way, smooth information sharing is achieved by analyzing the team's communication patterns in detail and proposing the most suitable communication methods. Some or all of the above processes in the Communication Facilitation Department may be performed using, for example, generative AI, or not. For example, the Communication Facilitation Department can have generative AI perform the analysis of communication patterns.

[0053] The Communication Facilitation Department monitors the frequency of interaction among team members in real time and facilitates interaction at appropriate times. For example, if the frequency of interaction among team members is low, the Communication Facilitation Department sends a notification to encourage interaction. If the frequency of interaction among team members is high, the Communication Facilitation Department suggests that interaction be reduced. The Communication Facilitation Department visualizes the frequency of interaction among team members in real time and facilitates interaction at appropriate times. This enables smooth information sharing by monitoring the frequency of interaction among team members in real time and facilitating interaction at appropriate times. Some or all of the above processes in the Communication Facilitation Department may be performed using, for example, a generative AI, or not using a generative AI. For example, the Communication Facilitation Department can have a generative AI perform the monitoring of interaction frequency.

[0054] The communication facilitator, when facilitating communication, considers the user's geographical location information and proposes the optimal method of interaction. For example, if the user is in a different time zone, the communication facilitator proposes the optimal interaction time. If the user is on the move, the communication facilitator proposes refraining from interaction until the user has completed their journey. If the user is in a specific location, the communication facilitator proposes an interaction method appropriate for that location. In this way, smooth communication is achieved by proposing the optimal method of interaction considering the user's geographical location information. Some or all of the above processing in the communication facilitator may be performed using, for example, generative AI, or without generative AI. For example, the communication facilitator can have generative AI perform the analysis of geographical location information.

[0055] The Communication Facilitation Department analyzes the user's social media activity and proposes relevant interaction methods during communication facilitation. For example, the Communication Facilitation Department proposes relevant interaction methods based on information shared by the user on social media. The Communication Facilitation Department proposes interaction methods based on the user's interests and preferences from their social media activity. The Communication Facilitation Department proposes methods for collaborative interaction with members the user has interacted with on social media. In this way, smooth communication is achieved by analyzing the user's social media activity and proposing relevant interaction methods. Some or all of the above processing in the Communication Facilitation Department may be performed using, for example, generative AI, or without generative AI. For example, the Communication Facilitation Department can have generative AI perform the analysis of social media activity.

[0056] The Security Measures Department analyzes data access history in detail and detects signs of unauthorized access in real time. For example, the Security Measures Department monitors data access history in real time and detects signs of unauthorized access. If signs of unauthorized access are detected, the Security Measures Department immediately sends a notification. Based on the data access history, the Security Measures Department identifies abnormal access patterns. This strengthens security by analyzing data access history in detail and detecting signs of unauthorized access in real time. Some or all of the above processes in the Security Measures Department may be performed using, for example, generative AI, or without generative AI. For example, the Security Measures Department can have generative AI perform the analysis of access history.

[0057] The Security Measures Department automatically updates policies regarding the handling of confidential information to maintain security levels. For example, the Security Measures Department periodically reviews policies regarding the handling of confidential information and updates them to align with the latest security standards. The Security Measures Department immediately updates policies when new security risks arise. The Security Measures Department automatically applies policies regarding the handling of confidential information to maintain security levels. This ensures that policies regarding the handling of confidential information are automatically updated to maintain security levels. Some or all of the above processes in the Security Measures Department may be performed, for example, using generative AI, or without generative AI. For example, the Security Measures Department can have generative AI perform policy updates.

[0058] The Security Measures Department implements optimal security measures, taking into account the user's geographical location. For example, if the user is in a different time zone, the Security Measures Department will suggest the most appropriate security measures. If the user is on the move, the Security Measures Department will suggest withholding security measures until the move is complete. If the user is in a specific location, the Security Measures Department will implement security measures appropriate for that location. This enhances security by implementing optimal security measures while considering the user's geographical location. Some or all of the above processes in the Security Measures Department may be performed using, for example, generative AI, or without generative AI. For example, the Security Measures Department may have generative AI perform the analysis of geographical location information.

[0059] The Security Measures Department analyzes users' social media activity and identifies relevant security risks when implementing security measures. For example, the Security Measures Department identifies relevant security risks based on information shared by users on social media. The Security Measures Department identifies potential security risks from users' social media activity. The Security Measures Department identifies security risks from the relationships users have with members they interact with on social media. By analyzing users' social media activity and identifying relevant security risks, security is strengthened. Some or all of the above processes in the Security Measures Department may be performed using, for example, generative AI, or without generative AI. For example, the Security Measures Department can have generative AI perform the analysis of social media activity.

[0060] The system according to the embodiment is not limited to the example described above, and various modifications are possible, for example, as follows.

[0061] The service provider can analyze a user's past virtual office usage history and propose the most suitable communication method. For example, it can prioritize suggesting communication tools that the user has frequently used in the past. It can also suggest similar methods based on the user's past successful communication patterns. Based on the user's past usage history, it can encourage communication at the most optimal time. In this way, it can propose the most suitable communication method based on the user's past usage history.

[0062] The service provider can analyze user behavior patterns in the virtual office space and design efficient movement paths. For example, it can identify areas that users frequently move through and design movement paths that allow them to travel the shortest distance. It can also design movement paths that are easily accessible by placing frequently used functions and tools close together. Based on user behavior patterns, it can design movement paths that avoid congestion. In this way, by analyzing user behavior patterns and designing efficient movement paths, work efficiency can be improved.

[0063] The task management department can analyze each member's skill set in detail and optimize task assignments. For example, it can assign the most suitable tasks based on each member's skills. It can analyze each member's past performance and assign appropriate tasks. It can assign tasks in a way that balances the entire team, taking each member's skill set into consideration. This allows for a detailed analysis of each member's skill set and optimizes task assignments.

[0064] The meeting support department can translate meeting content in real time and generate multilingual meeting minutes. For example, it can translate meeting content in real time and provide it to participants. It can automatically generate and share multilingual meeting minutes. It can summarize meeting content and provide summaries in each language. In this way, by translating meeting content in real time and generating multilingual meeting minutes, it can facilitate communication among international teams.

[0065] The security department can analyze data access history in detail and detect signs of unauthorized access in real time. For example, it can monitor data access history in real time and detect signs of unauthorized access. If signs of unauthorized access are detected, it can immediately send a notification. Based on data access history, it can identify abnormal access patterns. This allows for enhanced security by analyzing data access history in detail and detecting signs of unauthorized access in real time.

[0066] The following briefly describes the processing flow for example form 1.

[0067] Step 1: The service provider enables users to access a virtual office space and communicate with other team members in real time. For example, a user can enter a virtual meeting room and conduct a video conference with other members. The service provider provides the interface for users to access the virtual office space. Step 2: The task management department analyzes each member's skills and workload and optimally distributes tasks. For example, it monitors project progress in real time and automatically adjusts task assignments. The task management department visualizes project progress in real time and monitors the progress of tasks. Step 3: The meeting support department automates meeting scheduling and automatically generates meeting minutes. For example, it summarizes meeting content using natural language processing technology and shares it as meeting minutes. The meeting support department also translates meeting content in real time and generates multilingual meeting minutes. Step 4: The Communication Facilitation Department analyzes the communication patterns within the team and makes suggestions for improvement. For example, if there is insufficient interaction among team members, they will suggest ways to encourage communication at appropriate times. The Communication Facilitation Department monitors the frequency of interaction among team members in real time and facilitates interaction at appropriate times. Step 5: The Security Measures Department implements secure data sharing and access management. For example, it strictly manages access rights to confidential information to prevent unauthorized access. The Security Measures Department analyzes data access history in detail and detects signs of unauthorized access in real time.

[0068] (Example of form 2) The system according to an embodiment of the present invention is an AI agent that streamlines remote work on the metaverse. This system supports improved productivity in remote work by providing a virtual office space, facilitating communication between teams, and managing tasks. For example, the system provides a virtual office environment in which users can access a virtual office space and communicate with other team members in real time. The system provides a communication environment similar to that of a physical office. The system has a task management function that analyzes the skills and workload of each member and optimally distributes tasks. For example, the system grasps the progress of a project in real time and automatically adjusts task assignments. The system provides a meeting support function that automates meeting scheduling and minute-taking. For example, the system summarizes the content of a meeting using natural language processing technology and shares it as minutes. The system has a communication promotion function that facilitates interaction and information sharing among team members. For example, the system analyzes communication patterns within a team and makes suggestions for improvement. The system provides security measures that ensure the secure sharing and access management of data. For example, the system strictly manages access rights to confidential information and prevents unauthorized access. This allows the system to streamline remote work on the metaverse and improve productivity.

[0069] The system according to this embodiment comprises a provisioning unit, a task management unit, a meeting support unit, a communication promotion unit, and a security measures unit. The provisioning unit allows users to access a virtual office space and communicate with other team members in real time. For example, the provisioning unit allows users to enter a virtual meeting room and conduct video conferences with other members. The provisioning unit provides an interface for users to access the virtual office space. The task management unit analyzes the skills and workload of each member and optimally distributes tasks. For example, the task management unit grasps the progress of a project in real time and automatically adjusts task assignments. The task management unit visualizes the progress of a project in real time and monitors the progress of tasks. The meeting support unit automates scheduling meetings and automatically generates meeting minutes. For example, the meeting support unit summarizes the content of a meeting using natural language processing technology and shares it as meeting minutes. The meeting support unit translates the content of a meeting in real time and generates multilingual meeting minutes. The communication promotion unit analyzes communication patterns within the team and makes improvement suggestions. The Communication Promotion Department, for example, will propose ways to encourage communication at the appropriate time if there is insufficient interaction among team members. The Communication Promotion Department will monitor the frequency of interaction among team members in real time and promote interaction at the appropriate time. The Security Measures Department will implement secure data sharing and access management. For example, the Security Measures Department will strictly manage access rights to confidential information and prevent unauthorized access. The Security Measures Department will analyze data access history in detail and detect signs of unauthorized access in real time. As a result, the system according to the embodiment can streamline remote work on the metaverse and improve productivity.

[0070] The service provider enables users to access a virtual office space and communicate with other team members in real time. Specifically, the service provider provides an interface for users to enter a virtual meeting room and conduct video conferences with other members. This interface is designed for ease of use, allowing users to access the virtual space intuitively. For example, users can control their avatar to move around the virtual office and interact with other members' avatars. During video conferences, camera footage and audio are synchronized in real time, enabling natural communication. The service provider also provides chat and file sharing functions within the virtual space, allowing users to quickly share necessary information. Furthermore, the service provider monitors user access in real time and provides support as needed. For example, if the connection is unstable, the service provider will automatically retry the connection to ensure that users can continue to communicate smoothly. The service provider can also analyze user usage and suggest optimizations for the layout and functions of the virtual space. In this way, the service provider supports users in comfortably using the virtual office space and facilitates smooth communication throughout the team.

[0071] The task management department analyzes each member's skills and workload to optimally distribute tasks. Specifically, it monitors each member's skill set and current workload in real time and automatically adjusts task allocation according to the project's progress. For example, if a member possesses a particular skill, tasks that utilize that skill will be prioritized. It also has a function to evenly distribute tasks to prevent excessive workload imbalances among members. The task management department visualizes project progress in real time and monitors the progress of each task. This allows project managers to quickly understand which tasks are behind schedule and which members need support. Furthermore, the task management department uses AI to analyze past project data and identify factors that affect task progress. This allows for the prediction of project risks in advance and the implementation of appropriate countermeasures. For example, if past data reveals that a particular task is prone to delays, measures such as allocating additional resources to that task will be taken. The task management department also includes features to facilitate communication among members, providing chat and file sharing functions for sharing task-related information. This allows the task management department to streamline project progress and improve overall team productivity.

[0072] The Meeting Support Department automates meeting scheduling and automatically generates meeting minutes. Specifically, it checks each member's schedule in real time and suggests the optimal meeting time. For example, it synchronizes each member's calendar and automatically selects a time slot when everyone can participate. It also has a function to automatically send meeting invitations and confirm participant attendance. Once a meeting begins, the Meeting Support Department records the meeting content in real time and generates a summary using natural language processing technology. This automatically creates meeting minutes, which are then shared with participants. Furthermore, the Meeting Support Department can translate the meeting content in real time and generate multilingual minutes. This enables smooth communication even among members who speak different languages. The Meeting Support Department also has a function to analyze the meeting content using AI and extract important points and action items. This allows for efficient post-meeting follow-up and smoother task progress. In addition, the Meeting Support Department provides a function to analyze past meeting data and evaluate the effectiveness of meetings. This allows for the identification of areas for improvement to enhance the quality of meetings and to be reflected in future meetings. This allows the meeting support department to improve the efficiency and quality of meetings, thereby increasing the overall productivity of the team.

[0073] The Communication Facilitation Department analyzes communication patterns within teams and proposes improvements. Specifically, it monitors the frequency and content of each member's communication in real time to understand the state of interaction within the team. For example, if there is a lack of communication between certain members, it will propose encouraging interaction among those members. It can also propose training and workshops to improve the quality of communication. The Communication Facilitation Department uses AI to analyze the content of communication and identify problems and areas for improvement within the team. For example, it analyzes frequently appearing keywords and phrases in conversations to understand common issues and concerns within the team. It can also analyze the tone and emotion of communication to evaluate the team's atmosphere and members' stress levels. This allows the Communication Facilitation Department to make concrete suggestions to smooth communication within the team and improve member motivation and engagement. Furthermore, the Communication Facilitation Department has a function to regularly review the communication situation and evaluate the effectiveness of improvements. This enables continuous improvement and enhances team performance.

[0074] The Security Measures Department implements secure data sharing and access management. Specifically, the Security Measures Department strictly manages access rights to confidential information and prevents unauthorized access. For example, it sets appropriate access rights for each user and restricts access to confidential information. It also has a function that records access history in detail and issues an immediate warning if abnormal access is detected. The Security Measures Department uses AI to analyze access history and detect signs of unauthorized access in real time. For example, if there is access from an unusual time or location, it automatically blocks the access and notifies the administrator. The Security Measures Department also ensures secure data sharing by using data encryption and secure communication protocols. This minimizes the risk of data being intercepted by third parties. Furthermore, the Security Measures Department regularly reviews security policies and takes measures to address new threats. For example, if a new security threat is discovered, it quickly shares the information and updates the system and applies patches. It is also important to provide security education to users to improve security awareness. In this way, the Security Measures Department can maintain the security of the entire system and ensure the safety of data.

[0075] The service provider allows users to enter a virtual meeting room and conduct video conferences with other members. The service provider constructs the virtual meeting room using 3D modeling technology and includes interactive elements. The service provider uses WebRTC technology for conducting video conferences. The service provider uses video streaming technology to achieve high-quality video conferencing. This enables video conferencing in the virtual meeting room and facilitates communication for remote work. Some or all of the above processing in the service provider may be performed using, for example, generative AI, or not using generative AI. For example, the service provider can have generative AI perform 3D modeling of the virtual meeting room.

[0076] The task management unit monitors project progress in real time and automatically adjusts task allocation. For example, the task management unit monitors project progress in real time and automatically adjusts task allocation. The task management unit visualizes project progress in real time and monitors task progress. The task management unit optimizes task allocation using AI algorithms. The task management unit automatically adjusts task allocation using a rule-based system. The task management unit visualizes project progress in real time using a dashboard. This allows for real-time monitoring of project progress and optimization of task allocation. Some or all of the above processes in the task management unit may be performed using, for example, generative AI, or without generative AI. For example, the task management unit can have generative AI perform the visualization of project progress.

[0077] The meeting support department summarizes the meeting content using natural language processing technology and shares it as meeting minutes. For example, the meeting support department summarizes the meeting content using natural language processing technology and shares it as meeting minutes. The meeting support department summarizes the meeting content using morphological analysis. The meeting support department summarizes the meeting content using grammatical analysis. The meeting support department summarizes the meeting content using semantic analysis. The meeting support department considers the length of the text and the importance of the information to be summarized as criteria for summarization. By summarizing the meeting content and sharing it as meeting minutes, the meeting support department aims to improve the efficiency of meetings. Some or all of the above processing in the meeting support department may be performed using, for example, generative AI, or not using generative AI. For example, the meeting support department can have generative AI perform the summarization of the meeting content.

[0078] The Communication Promotion Department will propose ways to encourage communication at appropriate times if there is insufficient interaction among team members. For example, the Communication Promotion Department will propose ways to encourage communication at appropriate times if there is insufficient interaction among team members. The Communication Promotion Department will determine if there is insufficient interaction based on the frequency of interaction. The Communication Promotion Department will analyze communication logs to determine if there is insufficient interaction. The Communication Promotion Department will propose ways to encourage communication at appropriate times, taking into account working hours and project progress. This will promote interaction among team members and enable smooth information sharing. Some or all of the above processes in the Communication Promotion Department may be performed using, for example, generative AI, or not using generative AI. For example, the Communication Promotion Department may have generative AI perform the analysis of interaction frequency.

[0079] The Security Measures Department strictly manages access rights to confidential information and prevents unauthorized access. For example, the Security Measures Department strictly manages access rights to confidential information and prevents unauthorized access. The Security Measures Department manages access rights to confidential information using access control lists. The Security Measures Department manages access rights to confidential information using role-based access control. The Security Measures Department prevents unauthorized access using intrusion detection systems. The Security Measures Department prevents unauthorized access using firewalls. This ensures strict management of access rights to confidential information and prevents unauthorized access. Some or all of the above processes in the Security Measures Department may be performed using, for example, generative AI, or without generative AI. For example, the Security Measures Department can have generative AI manage access control lists.

[0080] The service provider estimates the user's emotions and adjusts the layout of the virtual office space based on the estimated emotions. For example, if the user is feeling stressed, the service provider changes the layout to one with relaxing colors and designs. If the user wants to concentrate, the service provider changes the layout to one that is simple and uncluttered. If the user is in a sociable mood, the service provider changes the layout to one that facilitates interaction with other members. In this way, the service provider adjusts the layout of the virtual office space according to the user's emotions and provides a comfortable working environment. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the service provider may be performed using, for example, generative AI, or not using generative AI. For example, the service provider can have a generative AI perform the estimation of the user's emotions.

[0081] The service provider analyzes the user's past virtual office usage history and proposes the optimal communication method. For example, the service provider prioritizes suggesting communication tools that the user has frequently used in the past. The service provider suggests similar methods based on the user's past successful communication patterns. The service provider prompts communication at the optimal time based on the user's past usage history. In this way, the service provider proposes the optimal communication method based on the user's past usage history. Some or all of the above processing in the service provider may be performed using, for example, generative AI, or without generative AI. For example, the service provider can have generative AI perform the analysis of past usage history.

[0082] The service provider analyzes user behavior patterns in the virtual office space and designs efficient movement paths. For example, the service provider identifies areas that users frequently move to and designs movement paths that allow them to travel the shortest distance. The service provider places frequently used functions and tools close together and designs movement paths that are easily accessible. Based on user behavior patterns, the service provider designs movement paths that avoid congestion. In this way, by analyzing user behavior patterns and designing efficient movement paths, work efficiency is improved. Some or all of the above processes in the service provider may be performed using, for example, generative AI, or not using generative AI. For example, the service provider can have generative AI perform the analysis of behavior patterns.

[0083] The service provider estimates the user's emotions and changes the background of the virtual meeting room based on the estimated emotions. For example, if the user wants to relax, the service provider sets the background to a natural landscape. If the user wants to concentrate, the service provider changes the background to a simple one. If the user is in a sociable mood, the service provider changes the background to a casual one. In this way, the service provider changes the background of the virtual meeting room according to the user's emotions and provides a comfortable meeting environment. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the service provider may be performed using a generative AI, for example, or not using a generative AI. For example, the service provider can have a generative AI perform the change of the virtual meeting room background.

[0084] The service provider proposes optimal communication timing, taking into account the user's geographical location within the virtual office space. For example, if the user is in a different time zone, the service provider proposes the optimal communication time. If the user is on the move, the service provider proposes refraining from communication until the move is complete. If the user is in a specific location, the service provider proposes a communication method appropriate for that location. This allows the service provider to propose optimal communication timing, taking into account the user's geographical location. Some or all of the above processing in the service provider may be performed using, for example, generative AI, or without generative AI. For example, the service provider can have generative AI perform the analysis of geographical location information.

[0085] The service provider analyzes users' social media activity in the virtual office space and provides relevant information. For example, the service provider suggests relevant projects and tasks based on information shared by users on social media. The service provider provides information based on users' interests and preferences from their social media activity. The service provider makes suggestions to facilitate communication with members that users have interacted with on social media. In this way, by analyzing users' social media activity and providing relevant information, work efficiency is improved. Some or all of the above processing in the service provider may be performed using, for example, generative AI, or not using generative AI. For example, the service provider can have generative AI perform the analysis of social media activity.

[0086] The task management unit estimates the user's emotions and adjusts task priorities based on the estimated emotions. For example, if the user is stressed, the task management unit prioritizes assigning easy tasks. If the user is focused, the task management unit prioritizes assigning important tasks. If the user is tired, the task management unit assigns tasks that encourage breaks. This adjusts task priorities according to the user's emotions and improves work efficiency. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the task management unit may be performed using, for example, generative AI, or not using generative AI. For example, the task management unit can have a generative AI perform the adjustment of task priorities.

[0087] The task management department analyzes each member's skill set in detail and optimizes task allocation. For example, the task management department assigns the most suitable tasks based on each member's skills. The task management department analyzes each member's past performance and assigns appropriate tasks. The task management department considers each member's skill set and assigns tasks in a way that balances the entire team. This allows for a detailed analysis of each member's skill set and optimizes task allocation. Some or all of the above processes in the task management department may be performed using, for example, generative AI, or not. For example, the task management department can have generative AI perform the skill set analysis.

[0088] The task management department visualizes project progress in real time and monitors task progress. For example, the task management department visualizes project progress using graphs and charts. The task management department updates task progress in real time and notifies members. The task management department automatically adjusts task priorities according to project progress. This allows for real-time visualization of project progress and monitoring of task progress. Some or all of the above processes in the task management department may be performed using, for example, generative AI, or without generative AI. For example, the task management department can have generative AI perform the visualization of progress.

[0089] The task management unit estimates the user's emotions and adjusts the difficulty of tasks based on the estimated emotions. For example, if the user is stressed, the task management unit prioritizes assigning easy tasks. If the user is focused, the task management unit assigns difficult tasks. If the user is tired, the task management unit assigns tasks that encourage breaks. This adjusts the difficulty of tasks according to the user's emotions and improves work efficiency. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the task management unit may be performed using, for example, generative AI, or not using generative AI. For example, the task management unit can have the generative AI perform the adjustment of task difficulty.

[0090] The task management unit assigns the most suitable tasks to users, taking into account their geographical location information. For example, if a user is in a different time zone, the task management unit assigns the most suitable tasks. If a user is on the move, the task management unit suggests withholding tasks until the move is complete. If a user is in a specific location, the task management unit assigns tasks appropriate to that location. In this way, the task management unit assigns the most suitable tasks, taking into account the user's geographical location information. Some or all of the above processes in the task management unit may be performed using, for example, a generative AI, or not using a generative AI. For example, the task management unit can have a generative AI perform the analysis of geographical location information.

[0091] The task management unit analyzes the user's social media activity and suggests relevant tasks during task management. For example, the task management unit suggests relevant tasks based on information shared by the user on social media. The task management unit suggests tasks based on the user's interests and preferences from their social media activity. The task management unit suggests collaborative tasks with members the user has interacted with on social media. By analyzing the user's social media activity and suggesting relevant tasks, the task management unit improves work efficiency. Some or all of the above processes in the task management unit may be performed using, for example, generative AI, or without generative AI. For example, the task management unit can have generative AI perform the analysis of social media activity.

[0092] The meeting support unit estimates the user's emotions and adjusts the meeting's progress based on those emotions. For example, if the user is nervous, the meeting support unit suggests a relaxing approach. If the user is focused, the meeting support unit suggests an efficient approach. If the user is tired, the meeting support unit suggests a approach that includes breaks. This adjusts the meeting's progress according to the user's emotions, improving the meeting's efficiency. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI may be, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above-described processes in the meeting support unit may be performed using, for example, generative AI, or not. For example, the meeting support unit can have a generative AI adjust the meeting's progress.

[0093] The meeting support department translates meeting content in real time and generates multilingual meeting minutes. For example, the meeting support department translates meeting content in real time and provides it to participants. The meeting support department automatically generates and shares multilingual meeting minutes. The meeting support department summarizes meeting content and provides summaries in each language. This facilitates communication among international teams by translating meeting content in real time and generating multilingual meeting minutes. Some or all of the above processes in the meeting support department may be performed using, for example, generative AI, or not using generative AI. For example, the meeting support department can have generative AI perform real-time translation.

[0094] The meeting support department analyzes the frequency of participation in meetings to promote balanced discussion. For example, the meeting support department makes suggestions to encourage participants who speak infrequently to speak more. The meeting support department also suggests to participants who speak frequently that they listen to the opinions of other participants. The meeting support department visualizes participation frequency in real time to promote balanced discussion. In this way, the quality of meetings is improved by analyzing the participation frequency of participants and promoting balanced discussion. Some or all of the above processing in the meeting support department may be performed using, for example, generative AI, or not using generative AI. For example, the meeting support department can have generative AI perform the analysis of participation frequency.

[0095] The meeting support unit estimates the user's emotions and adjusts the meeting agenda based on the estimated emotions. For example, if the user is nervous, the meeting support unit suggests relaxing topics. If the user is focused, the meeting support unit prioritizes suggesting important topics. If the user is tired, the meeting support unit suggests lighter topics. This adjusts the meeting agenda according to the user's emotions and improves the efficiency of the meeting. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the meeting support unit may be performed using generative AI, for example, or without generative AI. For example, the meeting support unit can have generative AI perform the adjustment of the meeting agenda.

[0096] The meeting support unit, when providing meeting support, proposes the optimal meeting time, taking into account the user's geographical location. For example, if the user is in a different time zone, the meeting support unit proposes the optimal meeting time. If the user is traveling, the meeting support unit proposes postponing the meeting until the travel is complete. If the user is in a specific location, the meeting support unit proposes a meeting time appropriate for that location. In this way, by proposing the optimal meeting time, taking into account the user's geographical location, the efficiency of the meeting is improved. Some or all of the above processing in the meeting support unit may be performed using, for example, generative AI, or without generative AI. For example, the meeting support unit can have generative AI perform the analysis of geographical location information.

[0097] The meeting support department analyzes users' social media activity and proposes relevant agenda items during meeting support. For example, the meeting support department proposes relevant agenda items based on information shared by users on social media. The meeting support department proposes agenda items based on users' interests and preferences from their social media activity. The meeting support department proposes joint agenda items with members that users have interacted with on social media. In this way, the efficiency of meetings is improved by analyzing users' social media activity and proposing relevant agenda items. Some or all of the above processes in the meeting support department may be performed using, for example, generative AI, or not using generative AI. For example, the meeting support department can have generative AI perform the analysis of social media activity.

[0098] The communication facilitation unit estimates the user's emotions and adjusts the communication method based on the estimated emotions. For example, if the user is stressed, the communication facilitation unit suggests a relaxing communication method. If the user is focused, the communication facilitation unit suggests an efficient communication method. If the user is tired, the communication facilitation unit suggests a communication method that encourages a break. In this way, the communication method is adjusted according to the user's emotions, achieving smooth communication. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the communication facilitation unit may be performed using, for example, generative AI, or not using generative AI. For example, the communication facilitation unit can have the generative AI perform the adjustment of the communication method.

[0099] The Communication Facilitation Department analyzes the team's communication patterns in detail and proposes the most suitable communication methods. For example, the Communication Facilitation Department prioritizes suggesting the most frequently used communication tools within the team. The Communication Facilitation Department analyzes the communication frequency of team members and proposes the optimal timing for communication. Based on the team's communication patterns, the Communication Facilitation Department proposes efficient information sharing methods. In this way, smooth information sharing is achieved by analyzing the team's communication patterns in detail and proposing the most suitable communication methods. Some or all of the above processes in the Communication Facilitation Department may be performed using, for example, generative AI, or not. For example, the Communication Facilitation Department can have generative AI perform the analysis of communication patterns.

[0100] The Communication Facilitation Department monitors the frequency of interaction among team members in real time and facilitates interaction at appropriate times. For example, if the frequency of interaction among team members is low, the Communication Facilitation Department sends a notification to encourage interaction. If the frequency of interaction among team members is high, the Communication Facilitation Department suggests that interaction be reduced. The Communication Facilitation Department visualizes the frequency of interaction among team members in real time and facilitates interaction at appropriate times. This enables smooth information sharing by monitoring the frequency of interaction among team members in real time and facilitating interaction at appropriate times. Some or all of the above processes in the Communication Facilitation Department may be performed using, for example, a generative AI, or not using a generative AI. For example, the Communication Facilitation Department can have a generative AI perform the monitoring of interaction frequency.

[0101] The communication facilitation unit estimates the user's emotions and adjusts the frequency of communication based on the estimated emotions. For example, if the user is stressed, the communication facilitation unit reduces the frequency of communication. If the user is concentrating, the communication facilitation unit prioritizes only important communication. If the user is tired, the communication facilitation unit reduces the frequency of communication to encourage them to take a break. In this way, the frequency of communication is adjusted according to the user's emotions, enabling smooth communication. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the communication facilitation unit may be performed using, for example, generative AI, or not using generative AI. For example, the communication facilitation unit can have the generative AI perform the adjustment of communication frequency.

[0102] The communication facilitator, when facilitating communication, considers the user's geographical location information and proposes the optimal method of interaction. For example, if the user is in a different time zone, the communication facilitator proposes the optimal interaction time. If the user is on the move, the communication facilitator proposes refraining from interaction until the user has completed their journey. If the user is in a specific location, the communication facilitator proposes an interaction method appropriate for that location. In this way, smooth communication is achieved by proposing the optimal method of interaction considering the user's geographical location information. Some or all of the above processing in the communication facilitator may be performed using, for example, generative AI, or without generative AI. For example, the communication facilitator can have generative AI perform the analysis of geographical location information.

[0103] The Communication Facilitation Department analyzes the user's social media activity and proposes relevant interaction methods during communication facilitation. For example, the Communication Facilitation Department proposes relevant interaction methods based on information shared by the user on social media. The Communication Facilitation Department proposes interaction methods based on the user's interests and preferences from their social media activity. The Communication Facilitation Department proposes methods for collaborative interaction with members the user has interacted with on social media. In this way, smooth communication is achieved by analyzing the user's social media activity and proposing relevant interaction methods. Some or all of the above processing in the Communication Facilitation Department may be performed using, for example, generative AI, or without generative AI. For example, the Communication Facilitation Department can have generative AI perform the analysis of social media activity.

[0104] The security department estimates the user's emotions and adjusts access permissions based on the estimated emotions. For example, if the user is stressed, the security department may temporarily restrict access permissions. If the user is focused, the security department may prioritize granting necessary access permissions. If the user is tired, the security department may restrict access to important data. This adjusts access permissions according to the user's emotions and enhances security. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI may be, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the security department may be performed using, for example, generative AI, or not using generative AI. For example, the security department may have generative AI perform the adjustment of access permissions.

[0105] The Security Measures Department analyzes data access history in detail and detects signs of unauthorized access in real time. For example, the Security Measures Department monitors data access history in real time and detects signs of unauthorized access. If signs of unauthorized access are detected, the Security Measures Department immediately sends a notification. Based on the data access history, the Security Measures Department identifies abnormal access patterns. This strengthens security by analyzing data access history in detail and detecting signs of unauthorized access in real time. Some or all of the above processes in the Security Measures Department may be performed using, for example, generative AI, or without generative AI. For example, the Security Measures Department can have generative AI perform the analysis of access history.

[0106] The Security Measures Department automatically updates policies regarding the handling of confidential information to maintain security levels. For example, the Security Measures Department periodically reviews policies regarding the handling of confidential information and updates them to align with the latest security standards. The Security Measures Department immediately updates policies when new security risks arise. The Security Measures Department automatically applies policies regarding the handling of confidential information to maintain security levels. This ensures that policies regarding the handling of confidential information are automatically updated to maintain security levels. Some or all of the above processes in the Security Measures Department may be performed, for example, using generative AI, or without generative AI. For example, the Security Measures Department can have generative AI perform policy updates.

[0107] The security department estimates the user's emotions and adjusts how data is shared based on the estimated emotions. For example, if the user is stressed, the security department may temporarily restrict data sharing. If the user is focused, the security department may prioritize sharing necessary data. If the user is tired, the security department may restrict sharing of important data. This adjusts how data is shared according to the user's emotions and enhances security. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI may be, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the security department may be performed using, for example, generative AI, or not using generative AI. For example, the security department may have generative AI perform the adjustment of how data is shared.

[0108] The Security Measures Department implements optimal security measures, taking into account the user's geographical location. For example, if the user is in a different time zone, the Security Measures Department will suggest the most appropriate security measures. If the user is on the move, the Security Measures Department will suggest withholding security measures until the move is complete. If the user is in a specific location, the Security Measures Department will implement security measures appropriate for that location. This enhances security by implementing optimal security measures while considering the user's geographical location. Some or all of the above processes in the Security Measures Department may be performed using, for example, generative AI, or without generative AI. For example, the Security Measures Department may have generative AI perform the analysis of geographical location information.

[0109] The Security Measures Department analyzes users' social media activity and identifies relevant security risks when implementing security measures. For example, the Security Measures Department identifies relevant security risks based on information shared by users on social media. The Security Measures Department identifies potential security risks from users' social media activity. The Security Measures Department identifies security risks from the relationships users have with members they interact with on social media. By analyzing users' social media activity and identifying relevant security risks, security is strengthened. Some or all of the above processes in the Security Measures Department may be performed using, for example, generative AI, or without generative AI. For example, the Security Measures Department can have generative AI perform the analysis of social media activity.

[0110] The system according to the embodiment is not limited to the example described above, and various modifications are possible, for example, as follows.

[0111] The service provider can estimate the user's emotions and adjust the layout of the virtual office space based on those emotions. For example, if the user is feeling stressed, the layout can be changed to one with relaxing colors and designs. If the user wants to concentrate, the layout can be changed to one that is simple and uncluttered. If the user is in a sociable mood, the layout can be changed to one that facilitates interaction with other members. In this way, the virtual office space layout can be adjusted according to the user's emotions, providing a comfortable work environment.

[0112] The service provider can analyze a user's past virtual office usage history and propose the most suitable communication method. For example, it can prioritize suggesting communication tools that the user has frequently used in the past. It can also suggest similar methods based on the user's past successful communication patterns. Based on the user's past usage history, it can encourage communication at the most optimal time. In this way, it can propose the most suitable communication method based on the user's past usage history.

[0113] The task management system can estimate the user's emotions and adjust task priorities based on those estimates. For example, if a user is stressed, simpler tasks can be prioritized. If a user is focused, important tasks can be prioritized. If a user is tired, tasks that encourage breaks can be assigned. This allows for adjusting task priorities according to the user's emotions, thereby improving work efficiency.

[0114] The meeting support system can estimate users' emotions and adjust the meeting's progress based on those estimates. For example, if a user is feeling tense, it can suggest a more relaxing approach. If a user is focused, it can suggest an efficient approach. If a user is tired, it can suggest a plan that includes breaks. This allows the meeting's progress to be adjusted according to the users' emotions, thereby improving meeting efficiency.

[0115] The communication enhancement unit can estimate the user's emotions and adjust the communication method based on those emotions. For example, if the user is feeling stressed, it can suggest a relaxing communication method. If the user is concentrating, it can suggest an efficient communication method. If the user is tired, it can suggest a communication method that encourages them to take a break. This allows for smooth communication by adjusting the communication method according to the user's emotions.

[0116] The service provider can analyze user behavior patterns in the virtual office space and design efficient movement paths. For example, it can identify areas that users frequently move through and design movement paths that allow them to travel the shortest distance. It can also design movement paths that are easily accessible by placing frequently used functions and tools close together. Based on user behavior patterns, it can design movement paths that avoid congestion. In this way, by analyzing user behavior patterns and designing efficient movement paths, work efficiency can be improved.

[0117] The task management department can analyze each member's skill set in detail and optimize task assignments. For example, it can assign the most suitable tasks based on each member's skills. It can analyze each member's past performance and assign appropriate tasks. It can assign tasks in a way that balances the entire team, taking each member's skill set into consideration. This allows for a detailed analysis of each member's skill set and optimizes task assignments.

[0118] The meeting support department can translate meeting content in real time and generate multilingual meeting minutes. For example, it can translate meeting content in real time and provide it to participants. It can automatically generate and share multilingual meeting minutes. It can summarize meeting content and provide summaries in each language. In this way, by translating meeting content in real time and generating multilingual meeting minutes, it can facilitate communication among international teams.

[0119] The security measures department can estimate a user's emotions and adjust access permissions based on those estimates. For example, if a user is stressed, access permissions can be temporarily restricted. If a user is focused, necessary access permissions can be granted preferentially. If a user is tired, access to important data can be restricted. This allows for enhanced security by adjusting access permissions according to the user's emotions.

[0120] The security department can analyze data access history in detail and detect signs of unauthorized access in real time. For example, it can monitor data access history in real time and detect signs of unauthorized access. If signs of unauthorized access are detected, it can immediately send a notification. Based on data access history, it can identify abnormal access patterns. This allows for enhanced security by analyzing data access history in detail and detecting signs of unauthorized access in real time.

[0121] The following briefly describes the processing flow for example form 2.

[0122] Step 1: The service provider enables users to access a virtual office space and communicate with other team members in real time. For example, a user can enter a virtual meeting room and conduct a video conference with other members. The service provider provides the interface for users to access the virtual office space. Step 2: The task management department analyzes each member's skills and workload and optimally distributes tasks. For example, it monitors project progress in real time and automatically adjusts task assignments. The task management department visualizes project progress in real time and monitors the progress of tasks. Step 3: The meeting support department automates meeting scheduling and automatically generates meeting minutes. For example, it summarizes meeting content using natural language processing technology and shares it as meeting minutes. The meeting support department also translates meeting content in real time and generates multilingual meeting minutes. Step 4: The Communication Facilitation Department analyzes the communication patterns within the team and makes suggestions for improvement. For example, if there is insufficient interaction among team members, they will suggest ways to encourage communication at appropriate times. The Communication Facilitation Department monitors the frequency of interaction among team members in real time and facilitates interaction at appropriate times. Step 5: The Security Measures Department implements secure data sharing and access management. For example, it strictly manages access rights to confidential information to prevent unauthorized access. The Security Measures Department analyzes data access history in detail and detects signs of unauthorized access in real time.

[0123] 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.

[0124] Data generation model 58 is a form of 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> Examples of generative AI include text generation AI, image generation AI, and multimodal generation AI. 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 (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats from audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVMs), k-means clustering, convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each of the above parts is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example.Furthermore, processing performed by AI, including generative AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by AI, including generative AI.

[0125] Furthermore, the processing performed by the data processing system 10 described above is carried out by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but it may also be carried out by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0126] Each of the multiple elements described above, including the provisioning unit, task management unit, meeting support unit, communication promotion unit, and security measures unit, is implemented by, for example, at least one of the smart device 14 and the data processing unit 12. For example, the provisioning unit is implemented by the control unit 46A of the smart device 14, allowing users to access a virtual office space and communicate with other team members in real time. The task management unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12, which analyzes the skills and workload of each member and optimally distributes tasks. The meeting support unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12, which automates meeting scheduling and minute-taking. The communication promotion unit is implemented by, for example, the control unit 46A of the smart device 14, which analyzes communication patterns within the team and makes improvement suggestions. The security measures unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12, which implements secure data sharing and access management. The correspondence between each unit and the device or control unit is not limited to the examples described above and can be changed in various ways.

[0127] [Second Embodiment] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0128] 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.

[0129] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. 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 and / or LAN.

[0130] 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.

[0131] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, 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.

[0132] 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, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0133] 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.

[0134] 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 by the processor 28. The storage 32 stores the specific processing program 56.

[0135] The processor 28 reads a 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 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0136] 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. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0137] In the smart glasses 214, specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 acting as a control unit 46A according to the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0138] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0139] 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.

[0140] The data generation model 58 is a so-called generative AI. An example of a data generation model 58 is a generative AI such as ChatGPT. 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 inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0141] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but it may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart glasses 214 or an external device, and the smart glasses 214 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0142] Each of the multiple elements described above, including the provisioning unit, task management unit, meeting support unit, communication promotion unit, and security measures unit, is implemented by, for example, at least one of the smart glasses 214 and the data processing unit 12. For example, the provisioning unit is implemented by the control unit 46A of the smart glasses 214, allowing the user to access a virtual office space and communicate with other team members in real time. The task management unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12, which analyzes the skills and workload of each member and optimally distributes tasks. The meeting support unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12, which automates meeting scheduling and minute-taking. The communication promotion unit is implemented by, for example, the control unit 46A of the smart glasses 214, which analyzes communication patterns within the team and makes improvement suggestions. The security measures unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12, which implements secure data sharing and access management. The correspondence between each unit and the devices and control units is not limited to the examples described above and can be changed in various ways.

[0143] [Third Embodiment] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0144] 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.

[0145] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. 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 and / or LAN.

[0146] 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.

[0147] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, 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.

[0148] 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, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0149] 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.

[0150] 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.

[0151] The processor 28 reads a 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 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0152] 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. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0153] In the headset terminal 314, specific processing is performed by the processor 46. The storage 50 stores a specific program 60. The processor 46 reads the specific program 60 from the storage 50 and executes the read specific program 60 on the RAM 48. The specific processing is realized by the processor 46 acting as a control unit 46A according to the specific program 60 executed on the RAM 48. The headset terminal 314 also has a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0154] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0155] 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.

[0156] The data generation model 58 is a so-called generative AI. An example of a data generation model 58 is a generative AI such as ChatGPT. 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 inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0157] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset terminal 314, but may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset terminal 314. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the headset terminal 314 or an external device, and the headset terminal 314 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0158] Each of the multiple elements described above, including the provisioning unit, task management unit, meeting support unit, communication promotion unit, and security measures unit, is implemented by, for example, at least one of the headset terminal 314 and the data processing unit 12. For example, the provisioning unit is implemented by the control unit 46A of the headset terminal 314, allowing users to access a virtual office space and communicate with other team members in real time. The task management unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12, which analyzes the skills and workload of each member and optimally distributes tasks. The meeting support unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12, which automates meeting scheduling and minute-taking. The communication promotion unit is implemented by, for example, the control unit 46A of the headset terminal 314, which analyzes communication patterns within the team and makes improvement suggestions. The security measures unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12, which implements secure data sharing and access management. The correspondence between each unit and the devices and control units is not limited to the examples described above and can be changed in various ways.

[0159] [Fourth Embodiment] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0160] 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.

[0161] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. 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 and / or LAN.

[0162] 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.

[0163] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, 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.

[0164] 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 image sensor or CCD image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0165] 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.

[0166] 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. The robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0167] 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.

[0168] The processor 28 reads a 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 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0169] 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. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0170] In robot 414, specific processing is performed by processor 46. A specific program 60 is stored in storage 50. Processor 46 reads the specific program 60 from storage 50 and executes it on RAM 48. The specific processing is achieved by processor 46 acting as a control unit 46A according to the specific program 60 executed on RAM 48. Robot 414 also has data generation model 58 and emotion identification model 59, similar to those of the robot, and can perform processing similar to that of the specific processing unit 290 using these models.

[0171] Furthermore, other devices besides the data processing device 12 may also have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0172] 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.

[0173] The data generation model 58 is a so-called generative AI. An example of a data generation model 58 is a generative AI such as ChatGPT. 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 inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0174] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but it may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the robot 414 or an external device, and the robot 414 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0175] Each of the multiple elements described above, including the provisioning unit, task management unit, meeting support unit, communication promotion unit, and security measures unit, is implemented by, for example, at least one of the robot 414 and the data processing unit 12. For example, the provisioning unit is implemented by the control unit 46A of the robot 414, allowing users to access a virtual office space and communicate with other team members in real time. The task management unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12, which analyzes the skills and workload of each member and optimally distributes tasks. The meeting support unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12, which automates meeting scheduling and minute-taking. The communication promotion unit is implemented by, for example, the control unit 46A of the robot 414, which analyzes communication patterns within the team and makes improvement suggestions. The security measures unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12, which implements secure data sharing and access management. The correspondence between each unit and the devices and control units is not limited to the examples described above and can be changed in various ways.

[0176] 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.

[0177] Figure 9 shows the 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.

[0178] 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.

[0179] 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.

[0180] 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, and motorcycles, 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 based, for example, 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.

[0181] 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."

[0182] 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.

[0183] 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 method for the specific process may be used, which includes computer 22 and multiple other computers.

[0184] 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.

[0185] 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.

[0186] 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.

[0187] 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.

[0188] 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.

[0189] 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.

[0190] 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.

[0191] Furthermore, although the above-described examples were divided into four embodiments, some or all of these embodiments may be combined. Also, the smart device 14, smart glasses 214, headset terminal 314, and robot 414 are just examples, and they may be combined, or other devices may be used. Also, although the above-described examples were divided into two embodiments, Embodiment 1 and Embodiment 2, these may be combined.

[0192] 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 other things 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.

[0193] 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.

[0194] (Note 1) The service provider offers a virtual office environment where users can access a virtual office space and communicate with other team members in real time. The task management department analyzes each member's skills and workload to optimally distribute tasks, The meeting support department automates meeting scheduling and automatically generates meeting minutes, The Communication Promotion Department analyzes communication patterns within the team and makes improvement suggestions. It includes a security measures department that implements secure data sharing and access management. A system characterized by the following features. (Note 2) The aforementioned supply unit is, Users can enter a virtual meeting room and conduct video conferences with other members. The system described in Appendix 1, characterized by the features described herein. (Note 3) The aforementioned task management unit, Monitor project progress in real time and automatically adjust task allocation. The system described in Appendix 1, characterized by the features described herein. (Note 4) The aforementioned conference support department, The meeting content will be summarized using natural language processing technology and shared as meeting minutes. The system described in Appendix 1, characterized by the features described herein. (Note 5) The aforementioned communication promotion unit, If there is a lack of communication among team members, suggest ways to encourage communication at the appropriate time. The system described in Appendix 1, characterized by the features described herein. (Note 6) The aforementioned security measures department, Strictly manage access permissions to confidential information to prevent unauthorized access. The system described in Appendix 1, characterized by the features described herein. (Note 7) The aforementioned supply unit is, It estimates the user's emotions and adjusts the layout of the virtual office space based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 8) The aforementioned supply unit is, We analyze users' past virtual office usage history and propose the optimal communication method. The system described in Appendix 1, characterized by the features described herein. (Note 9) The aforementioned supply unit is, Analyze user behavior patterns in a virtual office space and design efficient traffic flow. The system described in Appendix 1, characterized by the features described herein. (Note 10) The aforementioned supply unit is, It estimates the user's emotions and changes the background of the virtual meeting room based on the estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 11) The aforementioned supply unit is, We propose optimal communication timing by considering the user's geographical location within the virtual office space. The system described in Appendix 1, characterized by the features described herein. (Note 12) The aforementioned supply unit is, Analyze users' social media activity in a virtual office space and provide relevant information. The system described in Appendix 1, characterized by the features described herein. (Note 13) The aforementioned task management unit, It estimates the user's emotions and adjusts task priorities based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 14) The aforementioned task management unit, We will analyze each member's skill set in detail and optimize task allocation. The system described in Appendix 1, characterized by the features described herein. (Note 15) The aforementioned task management unit, Visualize project progress in real time and monitor task progress. The system described in Appendix 1, characterized by the features described herein. (Note 16) The aforementioned task management unit, It estimates the user's emotions and adjusts the task difficulty based on those emotions. The system described in Appendix 1, characterized by the features described herein. (Note 17) The aforementioned task management unit, When managing tasks, consider the user's geographical location to assign the most suitable tasks. The system described in Appendix 1, characterized by the features described herein. (Note 18) The aforementioned task management unit, During task management, the system analyzes users' social media activity and suggests relevant tasks. The system described in Appendix 1, characterized by the features described herein. (Note 19) The aforementioned conference support department, It estimates the user's emotions and adjusts the meeting's progress based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 20) The aforementioned conference support department, Translate meeting content in real time and generate multilingual meeting minutes. The system described in Appendix 1, characterized by the features described herein. (Note 21) The aforementioned conference support department, Analyze the frequency of participation in meetings to promote balanced discussions. The system described in Appendix 1, characterized by the features described herein. (Note 22) The aforementioned conference support department, Estimate the user's emotions and adjust the meeting agenda based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 23) The aforementioned conference support department, When providing meeting support, the system takes the user's geographical location into consideration and suggests the optimal meeting time. The system described in Appendix 1, characterized by the features described herein. (Note 24) The aforementioned conference support department, During meeting support, we analyze users' social media activity and propose relevant agenda items. The system described in Appendix 1, characterized by the features described herein. (Note 25) The aforementioned communication promotion unit, It estimates the user's emotions and adjusts the communication method based on the estimated user emotions. The system described in Appendix 1, characterized by the features described herein. (Note 26) The aforementioned communication promotion unit, We conduct a detailed analysis of communication patterns within the team and propose the most suitable communication methods. The system described in Appendix 1, characterized by the features described herein. (Note 27) The aforementioned communication promotion unit, The frequency of interaction among team members is monitored in real time, and communication is facilitated at the appropriate time. The system described in Appendix 1, characterized by the features described herein. (Note 28) The aforementioned communication promotion unit, It estimates the user's emotions and adjusts the frequency of communication based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 29) The aforementioned communication promotion unit, When facilitating communication, the system considers the user's geographical location to suggest the most suitable method of interaction. The system described in Appendix 1, characterized by the features described herein. (Note 30) The aforementioned communication promotion unit, When facilitating communication, we analyze users' social media activity and suggest relevant interaction methods. The system described in Appendix 1, characterized by the features described herein. (Note 31) The aforementioned security measures department, It estimates the user's emotions and adjusts access permissions based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 32) The aforementioned security measures department, By analyzing data access history in detail, signs of unauthorized access are detected in real time. The system described in Appendix 1, characterized by the features described herein. (Note 33) The aforementioned security measures department, Automatically update policies regarding the handling of confidential information to maintain security levels. The system described in Appendix 1, characterized by the features described herein. (Note 34) The aforementioned security measures department, It estimates user sentiment and adjusts how data is shared based on the estimated user sentiment. The system described in Appendix 1, characterized by the features described herein. (Note 35) The aforementioned security measures department, When implementing security measures, we take into account the user's geographical location to ensure the most appropriate security measures are in place. The system described in Appendix 1, characterized by the features described herein. (Note 36) The aforementioned security measures department, During security measures, analyze users' social media activity to identify related security risks. The system described in Appendix 1, characterized by the features described herein. [Explanation of symbols]

[0195] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots

Claims

1. The service provider offers a virtual office environment where users can access a virtual office space and communicate with other team members in real time. The task management department analyzes each member's skills and workload to optimally distribute tasks, The meeting support department automates meeting scheduling and automatically generates meeting minutes, The Communication Promotion Department analyzes communication patterns within the team and makes improvement suggestions. It includes a security measures department that implements secure data sharing and access management. A system characterized by the following features.

2. The aforementioned supply unit is, Users can enter a virtual meeting room and conduct video conferences with other members. The system according to feature 1.

3. The aforementioned task management unit, Monitor project progress in real time and automatically adjust task allocation. The system according to feature 1.

4. The aforementioned conference support department, The meeting content will be summarized using natural language processing technology and shared as meeting minutes. The system according to feature 1.

5. The aforementioned communication promotion unit, If there is a lack of communication among team members, suggest ways to encourage communication at the appropriate time. The system according to feature 1.

6. The aforementioned security measures department, Strictly manage access permissions to confidential information to prevent unauthorized access. The system according to feature 1.

7. The aforementioned supply unit is, It estimates the user's emotions and adjusts the layout of the virtual office space based on those estimated emotions. The system according to feature 1.

8. The aforementioned supply unit is, We analyze users' past virtual office usage history and propose the optimal communication method. The system according to feature 1.

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