System

Abstract

To provide an effective system for improving the efficiency and productivity of an entire team in a business environment.SOLUTION: Means for receiving detailed information of a task from a user and storing the detailed information in a database, means for periodically acquiring a progress status of the task from the database and calculating a progress rate to generate visualization data, means for displaying the generated visualization data on a terminal of the user in real time, means for analyzing importance and urgency of the task and setting a priority of the task in consideration of a skill set and a load status of each member, and means for allocating the task to an appropriate member, A system, comprising: means for notifying a terminal of a user of an assigned task; means for automatically calculating resource information of a project and generating a resource list and a budget; and means for sharing messages and files among members in real time.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In today's business environment, efficient management of projects and tasks and improving productivity are important challenges. Problems such as the complexity of task management, lack of communication within teams, efficient resource allocation, difficulty in prioritizing tasks, and balancing the skills and workloads of each team member are particularly prominent. Effective systems are needed to solve these problems and improve the efficiency and productivity of the entire team. [Means for solving the problem]

[0005] In order to solve the above-mentioned problems, the present invention provides the following means: A means for receiving detailed task information from a user and storing the information in a database; A means for periodically obtaining the progress status of the task from the database, calculating the progress rate, and generating visualization data; and A means for displaying the generated visualization data on the user's terminal in real time.

[0006] In addition, it provides a means for analyzing the importance and urgency of tasks, setting task priorities taking into consideration the skill sets and workloads of each member, assigning tasks to appropriate members, and notifying users of assigned tasks via their terminals.It also includes a means for automatically calculating project resource information and generating a resource list and budget.

[0007] Furthermore, the system provides a means for members to share messages and files in real time, thereby dramatically improving the efficiency of task management. This system integrates task progress management, priority setting, communication support, and resource management, thereby improving work efficiency and productivity.

[0008] A "task" refers to a specific task or activity that needs to be accomplished in a project or business.

[0009] "User" refers to an individual or group that uses the system to input and manage tasks, check progress, and so on.

[0010] "Terminal" refers to a device (e.g., a PC, smartphone, tablet, etc.) that a user uses to access and operate the system.

[0011] "Server" refers to a central computer that manages and processes data for the entire system.

[0012] "Database" refers to an electronic data repository for systematically storing and managing task information, progress status, resource information, etc.

[0013] "Progress" refers to information indicating the current state of execution and degree of completion of a task.

[0014] "Progress rate" refers to an indicator that indicates the degree to which a task has been completed as a percentage.

[0015] "Visualized data" refers to data that represents task progress and other important information in visual formats such as charts and graphs.

[0016] "Importance" refers to a criterion for evaluating the relative importance of a task.

[0017] "Urgency" refers to a criterion for assessing how urgent a task is.

[0018] A "skill set" refers to the collection of specific skills and knowledge that each member possesses.

[0019] "Load status" refers to the amount of work and burden each member currently has.

[0020] "Priority" refers to the criteria for determining the order in which various tasks should be executed.

[0021] "Resource information" refers to information such as materials, personnel, and budget required to carry out a project.

[0022] A "resource list" refers to a list of specifically required resources.

[0023] A "budget" refers to the total amount of expenses required to carry out a project or task.

[0024] "Message" refers to text-based communication exchanged between users.

[0025] "File sharing" refers to the mutual sending and receiving of electronic files between users and their joint use.

[0026] An "AI engine" is a program that uses artificial intelligence to analyze data and automatically assign tasks. [Brief explanation of the drawings]

[0027] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12]FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0028] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0029] First, the terms used in the following description will be explained.

[0030] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0031] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0032] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0033] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0034] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0035] [First embodiment]

[0036] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0037] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0038] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0039] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0040] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0041] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0042] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0043] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0044] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0045] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0046] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0047] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0048] This invention is an AI task management system that aims to efficiently manage projects and work and improve productivity. The system consists of a server and a client (user device). Users can access the interface via a browser or mobile app to manage tasks, check progress, and communicate. The specific operation of the system is described in detail below.

[0049] System configuration

[0050] The system consists of the following main functional modules:

[0051] 1. Task Entry Module: Used by the user to enter a new task.

[0052] 2. Database management module: A database for storing and managing task information, progress status, resource information, etc.

[0053] 3. Progress management module: Manages the progress of tasks and generates visualization data.

[0054] 4. AI engine: Analyzes the importance and urgency of the task, as well as the skill sets and workload of members.

[0055] 5. Task allocation module: Based on the analysis results of the AI ​​engine, tasks are prioritized and assigned to the appropriate members.

[0056] 6. Resource Management Module: Automatically calculates the resources required for a project and generates a resource list and budget.

[0057] 7. Communication module: Supports messaging and file sharing among members.

[0058] Creating and entering a new task

[0059] User: Opens a browser or mobile app and accesses the task management screen.

[0060] User: Enter the details of the new task, specifying the task name, detailed description, due date, priority, etc.

[0061] Terminal: Sends the task information entered by the user to the server in JSON format.

[0062] Server: Parse the received JSON data and store it in the database.

[0063] Tracking task progress

[0064] Server: Periodically retrieves task progress data from the database, calculates the progress rate, and generates visualization data.

[0065] On the device: Retrieves progress data from the server and displays progress bars and graphs on the user's dashboard.

[0066] Examples:

[0067] User: Clicks the "Update Task A progress" button.

[0068] Terminal: Sends a progress update request to the server.

[0069] Server: Updates the progress field in the database and distributes the latest progress to other users.

[0070] Terminal: Shows an updated progress bar.

[0071] Task assignment and prioritization

[0072] Server: When a new task is added, the AI ​​engine analyzes the task details.

[0073] Server: Sets the priority of tasks taking into account the importance, urgency, skill sets of members, and workload status of the task.

[0074] Server: Assigns the task to the appropriate member.

[0075] On your device: The new task will appear in the assigned member's task list and a notification will be sent.

[0076] Examples:

[0077] User: Add a new task "Create Report".

[0078] Server: The AI ​​engine analyzes the task details and determines that it is highly important.

[0079] Server: Member A is available, so the task is assigned to Member A.

[0080] Terminal: "Create a report" is added to member A's task list.

[0081] Resource management assistance

[0082] Users: Enter the required resource information at the start of the project.

[0083] Terminal: Sends the entered information to the server.

[0084] Server: Automatically calculates required resources and generates resource lists and budgets.

[0085] Terminal: Display resource list and budget to project manager.

[0086] Examples:

[0087] User: Starts a "New Project" and enters the required resources.

[0088] Server: Generates a budget and a list of materials needed based on resource requirements.

[0089] Terminal: Display resource list and budget on the project manager's screen.

[0090] Real-time communication support

[0091] User: Opens the messaging screen and enters a message.

[0092] Terminal: Sends a message to the server.

[0093] Server: Receives messages and distributes them to designated members in real time.

[0094] Terminal: Display received messages in the chat window.

[0095] Examples:

[0096] User: In the "Question" chat, type "When is this task due?"

[0097] Terminal: Sends a message to the server.

[0098] Server: Forwards the message to the target member.

[0099] Terminal: Display a message in the target member's chat window.

[0100] summary

[0101] This AI task management system integrates progress management, task allocation and prioritization, resource management, and real-time communication support. The server utilizes an AI engine to manage tasks, and the device provides real-time information to the user. Through these specific operations, the system improves work efficiency and productivity.

[0102] The processing flow will be explained below.

[0103] Creating and entering a new task

[0104] Step 1:

[0105] User: Opens a browser or mobile app and accesses the task management screen.

[0106] Step 2:

[0107] User: Enter the details of the new task, specifying the task name, detailed description, due date, priority, etc.

[0108] Step 3:

[0109] Terminal: Sends the task information entered by the user to the server in JSON format.

[0110] Step 4:

[0111] Server: Parse the received JSON data and store it in the database.

[0112] Tracking task progress

[0113] Step 1:

[0114] Server: Periodically retrieves task progress data from the database.

[0115] Step 2:

[0116] Server: Based on the progress status data, calculates the progress rate of the task and generates visualization data.

[0117] Step 3:

[0118] On the device: Retrieves progress data from the server and displays progress bars and graphs on the user's dashboard.

[0119] Examples:

[0120] Step 1:

[0121] User: Clicks the "Update Task A progress" button.

[0122] Step 2:

[0123] Terminal: Sends a progress update request to the server.

[0124] Step 3:

[0125] Server: Updates the progress field in the database and distributes the latest progress to other users.

[0126] Step 4:

[0127] Terminal: Shows an updated progress bar.

[0128] Task assignment and prioritization

[0129] Step 1:

[0130] Server: When a new task is added, the AI ​​engine analyzes the task details.

[0131] Step 2:

[0132] Server: Sets the priority of tasks taking into account the importance, urgency, skill sets of members, and workload status of the task.

[0133] Step 3:

[0134] Server: Assigns the task to the appropriate member.

[0135] Step 4:

[0136] On your device: The new task will appear in the assigned member's task list and a notification will be sent.

[0137] Examples:

[0138] Step 1:

[0139] User: Add a new task "Create Report".

[0140] Step 2:

[0141] Server: The AI ​​engine analyzes the task details and determines that it is highly important.

[0142] Step 3:

[0143] Server: Member A is available, so the task is assigned to Member A.

[0144] Step 4:

[0145] Terminal: "Create a report" is added to member A's task list.

[0146] Resource management assistance

[0147] Step 1:

[0148] Users: Enter the required resource information at the start of the project.

[0149] Step 2:

[0150] Terminal: Sends the entered information to the server.

[0151] Step 3:

[0152] Server: Automatically calculates required resources and generates resource lists and budgets.

[0153] Step 4:

[0154] Terminal: Display resource list and budget to project manager.

[0155] Examples:

[0156] Step 1:

[0157] User: Starts a "New Project" and enters the required resources.

[0158] Step 2:

[0159] Server: Generates a budget and a list of materials needed based on resource requirements.

[0160] Step 3:

[0161] Terminal: Display resource list and budget on the project manager's screen.

[0162] Real-time communication support

[0163] Step 1:

[0164] User: Opens the messaging screen and enters a message.

[0165] Step 2:

[0166] Terminal: Sends a message to the server.

[0167] Step 3:

[0168] Server: Receives messages and distributes them to designated members in real time.

[0169] Step 4:

[0170] Terminal: Display received messages in the chat window.

[0171] Examples:

[0172] Step 1:

[0173] User: In the "Question" chat, type "When is this task due?"

[0174] Step 2:

[0175] Terminal: Sends a message to the server.

[0176] Step 3:

[0177] Server: Forwards the message to the target member.

[0178] Step 4:

[0179] Terminal: Display a message in the target member's chat window.

[0180] Example 1

[0181] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0182] Modern project management requires consistent and efficient operation, from task entry to progress visualization, task prioritization and assignment, resource management, and communication between team members. However, few systems offer these functions in an integrated and automated manner, and manual management or the use of multiple tools is often required. This results in problems such as duplicated work and reduced efficiency. Furthermore, optimal task assignment based on task importance and team member skill sets requires advanced analytical capabilities, which traditional systems often lack. To address these challenges, there is a need for systems that optimize task management by automating and streamlining the entire business process and incorporating generative AI models.

[0183] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0184] In this invention, the server includes means for receiving detailed task information from a user and storing the information in a database, means for periodically obtaining the task progress status from the database, calculating the progress rate, and generating visualization data, and means for displaying the generated visualization data on the user's terminal in real time, thereby enabling detailed task management and visualization and real-time display of the progress status.

[0185] The server also includes: a means for analyzing the importance and urgency of tasks and prioritizing the tasks while taking into account the technical requirements and workload of each member; a means for assigning tasks to appropriate members and notifying the users of the assigned tasks on their terminals; a means for automatically calculating project resource information and generating a resource list and budget; a means for sharing messages and files between members in real time; a means for outputting task analysis results using a generative AI model; and a means for automatically generating task details using prompt text as input. This enables task prioritization and allocation optimization, automated resource management, and real-time communication.

[0186] "Detailed task information" refers to information such as the content, deadline, priority, and explanation of specific tasks that a user should manage in a project or business.

[0187] A "database" is a storage medium and its management system for systematically storing and managing data required within the system, such as detailed task information, progress status, member information, and resource information.

[0188] "Completion" refers to how much of a particular task or project is complete, usually expressed as a percentage.

[0189] "Visualized data" is data that is presented in a visual form, such as a graph or chart, so that users can easily understand the data intuitively.

[0190] A "user terminal" is an electronic device such as a computer, tablet, or smartphone that a user uses to access and operate the system.

[0191] "Task importance" is an index that indicates how important a particular task is compared to other tasks.

[0192] "Urgency" is a measure of how quickly a particular task should be addressed.

[0193] "Technical requirements" are requirements such as specific skills, knowledge, and experience required to perform a task.

[0194] "Load status" refers to the status that indicates how much work a particular member or resource is currently doing.

[0195] "Priority" is the order that determines which task or project should be done first among multiple tasks or projects.

[0196] "Resource information" refers to information such as personnel, equipment, and budget required to carry out a project or task.

[0197] A "generative AI model" is an algorithm and its implementation that uses artificial intelligence to generate analytical results and predictions from input data.

[0198] A "prompt sentence" is text data given as input to a generative AI model, and contains specific instructions for analysis and generation.

[0199] "Analysis results" are decision information such as task allocation and priority setting that the generative AI model outputs based on prompt statements and other input data.

[0200] This invention is an AI task management system aimed at efficient management of projects and work and improving productivity. The system consists of a server and a client (user device), and users can access the interface via a browser or mobile app to manage tasks, check progress, and communicate. The specific operation of the system is described in detail below.

[0201] System configuration

[0202] The system consists of the following main functional modules:

[0203] 1. Task Entry Module: Used by the user to enter a new task.

[0204] 2. Database Management Module: A database for storing and managing task information, progress, and resource information.

[0205] 3. Progress management module: Manages the progress of tasks and generates visualization data.

[0206] 4. Generative AI model: Analyzes the importance and urgency of the task, as well as the technical requirements and workload of members.

[0207] 5. Task assignment module: Based on the analysis results of the generative AI model, tasks are prioritized and assigned to appropriate members.

[0208] 6. Resource Management Module: Automatically calculates the resources required for a project and generates a resource list and budget.

[0209] 7. Communication module: Supports messaging and file sharing among members.

[0210] Specific operation of the system

[0211] A user opens a browser or mobile app and accesses the task management screen. When adding a task, they enter details such as the task name, detailed description, due date, and priority into a form. This sends JSON format data from the device to the server. The server parses the received data and stores it in a database.

[0212] Specific examples

[0213] For example, if a user enters a task name of "Report Creation," a deadline of "2023-12-31," and a priority of "High," the device sends this information in JSON format to the server, which receives the data and stores it in a database.

[0214] The server periodically retrieves task progress data from the database, calculates the progress rate, and generates visualization data, which is displayed in real time on the user's dashboard.

[0215] Specific examples

[0216] When the user clicks the progress update button, the device sends a progress update request to the server. The server updates the database with the new progress and distributes this latest data to other users. The device then displays the updated progress bar on the user's dashboard.

[0217] When a new task is added, the server's generative AI model analyzes the task details and prioritizes it, taking into account the task's importance, urgency, technical requirements of members, and workload.

[0218] Specific examples

[0219] For example, a new task "Write a report" is added, and the generative AI model analyzes the task and determines that it is of high importance. Since member A is currently free, the task is assigned to member A. The device sends a notification to member A and adds the task to the task list.

[0220] The user inputs the necessary resource information at the start of a project. The terminal sends the information to the server, which then automatically calculates and generates the resource list and budget. This information is then displayed on the project manager's terminal.

[0221] Specific examples

[0222] When a user starts a "new project" and enters the required resources as "PC, software license, and budget of 300,000 yen," the server automatically calculates the budget and materials list based on that information and displays the results to the project manager on the terminal.

[0223] With the messaging function, users can enter and send messages on the messaging screen. The device sends the message to the server, which then distributes it to other members in real time. Received messages are displayed in the chat window on the device.

[0224] Specific examples

[0225] When a user types "When is the deadline for this task?" into the chat window and sends it, the device sends the message to the server, which then forwards the message to the target member, who then sees the message in their chat window.

[0226] A prompt is a text instruction given as input to a generative AI model to analyze and automatically generate a task. For example, a prompt might be, "Please write an important report. The deadline is December 31, 2023."

[0227] In this way, the AI ​​task management system integrates progress management, task allocation and priority setting, resource management, and real-time communication support. The server uses generated AI models to manage tasks, and the terminal provides information to the user in real time, thereby improving work efficiency and productivity.

[0228] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0229] The flow of this system's program processing

[0230] Step 1: User enters task

[0231] Input: A user opens a browser or mobile app, accesses the task management screen, and enters task details such as the task name, detailed description, due date, and priority.

[0232] Processing: The terminal converts the input information into JSON format.

[0233] Output: The generated JSON data is sent to the server.

[0234] Specific operation: The user enters the task name "Create report", the due date "2023-12-31", and the priority "High". The device sends this to the server in the format {"task_name": "Create report", "due_date": "2023-12-31", "priority": "High"}.

[0235] Step 2: Receiving and saving task data

[0236] Input: Task data in JSON format sent from the device.

[0237] Processing: The server parses the received JSON data, maps it to the appropriate fields, and stores it in the database.

[0238] Output: Task information is saved to the database.

[0239] Specific operation: The server receives the data {"task_name": "Create Report", "due_date": "2023-12-31", "priority": "High"}, parses it, and saves it to the database.

[0240] Step 3: Managing and visualizing task progress

[0241] Input: Task progress data retrieved periodically from the database.

[0242] Processing: The server calculates the progress rate and generates visualization data (graphs and bars).

[0243] Output: The generated visualization data is sent to the user's terminal and displayed in real time.

[0244] Specific operation: The server obtains the progress data and generates a progress bar when the progress of "Task A" is 50%. The device receives this information and displays it on the user's dashboard.

[0245] Step 4: Analysis and task prioritization by generative AI model

[0246] Input: New task details.

[0247] Processing: The server-generated AI model analyzes the importance and urgency of tasks, as well as the technical requirements and workload of each member. Task priorities are set based on the analysis results.

[0248] Output: Task information assigned to the appropriate members is generated.

[0249] Specific operation: The AI ​​model analyzes the "Report Creation" task and determines that it is of high importance. Since member A has a low workload, the model assigns this task to member A.

[0250] Step 5: Task assignment and notifications

[0251] Input: Task assignment information from the generative AI model.

[0252] Processing: The server assigns the task to an appropriate member and notifies the user's terminal of this information.

[0253] Output: The task list is updated on the user's device and a notification is displayed.

[0254] Specific behavior: When you assign the task "Create a report" to member A, a notification will be sent to the device and member A's task list will be updated.

[0255] Step 6: Enter and manage resource information

[0256] Input: Users enter the required resource information at the start of a project.

[0257] Processing: The terminal sends the information to the server, which automatically calculates the required resources and generates a resource list and budget.

[0258] Output: The generated resource list and budget are displayed on the project manager's terminal.

[0259] Specific operation: When a user enters "PC, software license, budget 300,000 yen," the server automatically calculates and displays the results to the project manager.

[0260] Step 7: Real-time communication

[0261] Input: The message the user types in the messaging screen.

[0262] Processing: The terminal sends a message to the server, which then forwards it to the designated members in real time.

[0263] Output: The message will be displayed in the member's chat window.

[0264] Specific operation: The user types "When is the deadline for this task?" into the chat and sends it. The device sends it to the server, which then forwards it to the target member and displays it.

[0265] Specific examples

[0266] For example, the generative AI model is used with the prompt "Please prepare an important report. The deadline is December 31, 2023." In this case, the AI ​​model analyzes the content of the prompt and automatically generates detailed information about the task. As a result, the system assigns the task to an appropriate member and displays basic information on the user's device.

[0267] (Application example 1)

[0268] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0269] Conventional factory task management and resource management often require a lot of human intervention and are inefficient. Furthermore, it is not possible to monitor the robot's operating status or progress in real time, making it difficult to respond quickly when an error occurs. This has led to problems such as reduced productivity and increased costs. The present invention aims to solve these problems and improve the efficiency of task management, progress monitoring, and resource management within a factory.

[0270] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0271] In this invention, the server includes means for receiving detailed task information from a user and storing it in an information storage device, means for periodically obtaining task progress status from the information storage device, calculating the progress rate, and generating visualization data, means for displaying the generated visualization data on a user's terminal in real time, means for analyzing the importance and urgency of tasks and prioritizing tasks taking into account the skill sets and workloads of each worker, means for assigning tasks to appropriate workers and notifying the users of the assigned tasks, means for automatically calculating resource information within the factory and generating a resource list and budget, means for sharing messages and files among workers in real time, means for monitoring the operating status of robots in real time and notifying a smartphone or head-mounted display of task progress and errors, and means for generating resource requests for the project and calculating an optimal budget. This enables efficient task management and progress monitoring within the factory and immediate response.

[0272] "Task detailed information" is specific information about a task, such as the name, content, deadline, and priority of a specific task.

[0273] A "user" is an individual or person in charge who operates the system to input tasks and monitor progress.

[0274] An "information storage device" is a database or storage system for saving and managing data such as detailed task information and progress status.

[0275] "Progress" refers to the state of how much of a particular task has been completed.

[0276] "Visualized data" is data that visually shows progress, such as numbers, graphs, and progress bars.

[0277] A "terminal" is a device used by a user, such as a smartphone, tablet, or head-mounted display.

[0278] "Task importance" is a factor that indicates the business importance of a specific task.

[0279] "Urgency" is a factor that indicates how quickly a particular task should be addressed.

[0280] A "skill set" is the collection of skills and abilities that each member possesses.

[0281] "Load status" refers to the tasks and workload currently handled by each member.

[0282] "Constituents" are people or teams to whom tasks are assigned by the system.

[0283] "Resource information" refers to information such as materials, personnel, and equipment required to carry out a project or task.

[0284] A "resource list" is a list of required resources.

[0285] A "budget" is an estimate of how much a project or task will cost.

[0286] "Message and file sharing" refers to the act of sending and receiving text messages and documents between members.

[0287] "Robot operating status" is information on whether the corresponding robot in the factory is available, in operation, or in an error state.

[0288] An "error" is a problem or failure that occurs within a robot or system.

[0289] A "project resource request" is a requirement that specifies the resources needed to complete a particular project or task.

[0290] The "optimal budget" is the most efficient cost estimate calculated based on the resource information and resource list.

[0291] The present invention is a system for efficiently managing tasks, progress, and resources within a factory. This system is realized through the cooperation of a server, terminals, and users.

[0292] System configuration

[0293] The system consists of the following main functional modules:

[0294] 1. Task input module: Used by users to input new tasks.

[0295] 2. Database management module: An information storage device for storing and managing task information, progress status, resource information, etc.

[0296] 3. Progress management module: Manages the progress of tasks and generates visualization data.

[0297] 4. AI engine: Analyzes the importance and urgency of the task, the skill sets of the members, and the workload situation.

[0298] 5. Task allocation module: Based on the analysis results of the AI ​​engine, it sets the priority of tasks and assigns them to the appropriate members.

[0299] 6. Resource management module: Automatically calculates resource information within the factory and generates resource lists and budgets.

[0300] 7. Communication module: Supports messaging and file sharing among members.

[0301] 8. Robot monitoring module: Monitors the robot's operating status in real time and notifies the operating status and errors to a smartphone or head-mounted display.

[0302] Creating and entering a new task

[0303] User: Opens a smartphone or head-mounted display and accesses the task management screen.

[0304] User: Enter the details of the new task, specifying the task name, detailed description, due date, importance, etc.

[0305] Terminal: Sends task information entered by the user to the server.

[0306] Server: Analyzes the received task information and stores it in an information storage device.

[0307] Tracking task progress

[0308] Server: Periodically obtains task progress data from the information storage device, calculates the progress rate, and generates visualization data.

[0309] Terminal: Retrieves progress data from the server and displays progress bars and graphs on the user's dashboard.

[0310] Task assignment and prioritization

[0311] Server: When a new task is added, the AI ​​engine analyzes the task details.

[0312] Server: Sets the priority of tasks taking into account the importance and urgency of the tasks, the skill sets of members, and the workload situation.

[0313] Server: Assigns tasks to appropriate members. For example, when a new task, "assembling machine parts," is added, the AI ​​engine determines that the task has high priority and assigns it to member A, whose skill set is suitable.

[0314] Terminal: Adds new tasks to assigned members' task lists and sends notifications.

[0315] Resource Management

[0316] User: Enters the required resource information at the start of the project.

[0317] Terminal: Sends the entered information to the server.

[0318] Server: Automatically calculates required resources and generates resource lists and budgets.

[0319] Terminal: Display resource lists and budgets to project managers in real time.

[0320] Real-time communication

[0321] User: Open the messaging screen and enter a message.

[0322] Terminal: Sends a message to the server.

[0323] Server: Receives messages and distributes them to designated members in real time.

[0324] Terminal: Display received messages in the chat window.

[0325] Monitoring the operating status of robots

[0326] Server: Monitors the robot's operating status in real time, checking progress and errors.

[0327] Device: A notification is displayed on a smartphone or head-mounted display to notify the user.

[0328] Examples of concrete examples and prompts

[0329] For example, a factory supervisor can input a new task, "Transport parts," on their smartphone, and the AI ​​engine analyzes it and assigns the task to the appropriate robot. The supervisor can then monitor the robot's progress in real time on their smartphone and immediately respond to any problems that arise.

[0330] Example prompt for generative AI model:

[0331] "Assign the following task to the most suitable robot. Task information: Parts transport, Deadline: 2023-12-31, Priority: High. Robot list: Robot 1, Robot 2, Robot 3. Consider the current operational status and skill set of the robots."

[0332] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0333] Step 1:

[0334] Entering task details

[0335] The user inputs details of a new task using a smartphone or head-mounted display, including the task name, detailed description, deadline, and importance.

[0336] Input: Task details entered by the user

[0337] The terminal sends the entered information to the server in JSON format.

[0338] Output: Sends detailed task information in JSON format to the server

[0339] Step 2:

[0340] Storing task information

[0341] The server analyzes the received JSON format task information and stores it in an information storage device (database).

[0342] Input: JSON formatted task details sent from the device

[0343] Data processing: Parsing JSON data

[0344] Output: Detailed task information stored in the database

[0345] Step 3:

[0346] Obtaining and managing task progress

[0347] The server periodically retrieves task progress status data from the database, calculates the progress rate, and generates visualization data.

[0348] Input: Progress data retrieved from the database

[0349] Data calculation: Calculating progress rate and generating visualization data

[0350] Output: The generated visualization data

[0351] Step 4:

[0352] Viewing progress data

[0353] The device retrieves progress data from the server and displays it on the user's dashboard in the form of a progress bar or graph.

[0354] Input: Visualization data obtained from the server

[0355] Output: Progress displayed on the device dashboard

[0356] Step 5:

[0357] Task analysis by AI engine

[0358] The server uses an AI engine to analyze the importance and urgency of tasks and prioritizes them, taking into account each member's skill set and workload.

[0359] Input: Task details, member skill sets and workload status

[0360] Data calculation: Analyzing the importance and urgency of tasks and setting priorities

[0361] Output: Prioritized task information

[0362] Step 6:

[0363] Task assignment

[0364] The server assigns prioritized tasks to appropriate members.

[0365] Input: Priority-set task information, member skills and workload information

[0366] Data calculation: Selecting the best members

[0367] Output: Task list notification to assigned members

[0368] Step 7:

[0369] Resource Management

[0370] At the start of a project, the user inputs the necessary resource information, and the terminal sends this to the server.

[0371] Input: Required resource information

[0372] The terminal transmits the input resource information to the server.

[0373] Output: Resource information sent to the server

[0374] Step 8:

[0375] Calculating and displaying resource information

[0376] The server automatically calculates the required resources, generates a resource list and budget, and displays them to the project manager.

[0377] Input: Resource information submitted by the user

[0378] Data calculation: Automatic calculation of resources and generation of resource lists and budgets

[0379] Output: Display resource list and budget on the project manager screen

[0380] Step 9:

[0381] Real-time communication

[0382] The user opens the messaging screen and enters a message, which the device then sends to the server.

[0383] Input: The message entered by the user

[0384] The terminal sends a message to the server, which then distributes it to the designated members in real time.

[0385] Output: Message displayed in the chat window of the specified member

[0386] Step 10:

[0387] Monitoring the operating status of robots

[0388] The server monitors the robot's operating status in real time, checking for progress and errors.

[0389] Input: Robot operating status data

[0390] The device notifies the smartphone or head-mounted display of progress and errors.

[0391] Output: Robot progress and error notifications displayed on the user's terminal

[0392] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0393] This invention combines an AI task management system, which aims to efficiently manage projects and work and improve productivity, with an emotion engine that recognizes user emotions, enabling more advanced task management. The system consists of a server and a client (user device). Users can access the interface via a browser or mobile app to manage tasks, check progress, and communicate. The specific operation of the system is described in detail below.

[0394] System configuration

[0395] The system consists of the following main functional modules:

[0396] 1. Task Entry Module: Used by the user to enter a new task.

[0397] 2. Database management module: A database for storing and managing task information, progress status, resource information, etc.

[0398] 3. Progress management module: Manages the progress of tasks and generates visualization data.

[0399] 4. AI engine: Analyzes the importance and urgency of the task, as well as the skill sets and workload of members.

[0400] 5. Task allocation module: Based on the analysis results of the AI ​​engine, tasks are prioritized and assigned to the appropriate members.

[0401] 6. Resource Management Module: Automatically calculates the resources required for a project and generates a resource list and budget.

[0402] 7. Communication module: Supports messaging and file sharing among members.

[0403] 8. Emotion Engine: Recognizes user emotions and reflects them in the task management process.

[0404] Recognizing and reflecting user emotions

[0405] The emotion engine analyzes the user's emotional state and adjusts task allocation and priorities based on the results. For example, if a user is feeling stressed, it will adjust the task allocation to reduce the user's workload.

[0406] Emotion recognition processing flow

[0407] User: Providing emotional input feedback when interacting with messaging and task management screens, or extracted from sensor data such as facial recognition and voice analysis.

[0408] Terminal: Analyzes the user's emotional information and sends it to the server in JSON format.

[0409] Server: Analyzes the received emotion data and adjusts task priorities and assignments based on the emotion engine.

[0410] Creating and entering a new task

[0411] User: Opens a browser or mobile app and accesses the task management screen.

[0412] User: Enter the details of the new task, specifying the task name, detailed description, due date, priority, etc.

[0413] Terminal: Sends the task information entered by the user to the server in JSON format.

[0414] Server: Parse the received JSON data and store it in the database.

[0415] Tracking task progress

[0416] Server: Periodically retrieves task progress data from the database, calculates the progress rate, and generates visualization data.

[0417] On the device: Retrieves progress data from the server and displays progress bars and graphs on the user's dashboard.

[0418] Examples:

[0419] User: Clicks the "Update Task A progress" button.

[0420] Terminal: Sends a progress update request to the server.

[0421] Server: Updates the progress field in the database and distributes the latest progress to other users.

[0422] Terminal: Shows an updated progress bar.

[0423] Task assignment and prioritization

[0424] Server: When a new task is added, the AI ​​engine analyzes the task details.

[0425] Server: Sets the priority of tasks taking into account the importance, urgency, skill sets of members, and workload status of the task.

[0426] Server: Assigns the task to the appropriate member.

[0427] On your device: The new task will appear in the assigned member's task list and a notification will be sent.

[0428] Examples:

[0429] User: Add a new task "Create Report".

[0430] Server: The AI ​​engine analyzes the task details and determines that it is highly important.

[0431] Server: Member A is available, so the task is assigned to Member A.

[0432] Terminal: "Create a report" is added to member A's task list.

[0433] Resource management assistance

[0434] Users: Enter the required resource information at the start of the project.

[0435] Terminal: Sends the entered information to the server.

[0436] Server: Automatically calculates required resources and generates resource lists and budgets.

[0437] Terminal: Display resource list and budget to project manager.

[0438] Examples:

[0439] User: Starts a "New Project" and enters the required resources.

[0440] Server: Generates a budget and a list of materials needed based on resource requirements.

[0441] Terminal: Display resource list and budget on the project manager's screen.

[0442] Real-time communication support

[0443] User: Opens the messaging screen and enters a message.

[0444] Terminal: Sends a message to the server.

[0445] Server: Receives messages and distributes them to designated members in real time.

[0446] Terminal: Display received messages in the chat window.

[0447] Examples:

[0448] User: In the "Question" chat, type "When is this task due?"

[0449] Terminal: Sends a message to the server.

[0450] Server: Forwards the message to the target member.

[0451] Terminal: Display a message in the target member's chat window.

[0452] Specific examples of using the emotion engine

[0453] Examples:

[0454] User: In the messaging screen, types "This task is very stressful."

[0455] Device: An emotion engine analyzes the user's messages and detects increased stress.

[0456] Server: Based on the analysis results from the emotion engine, adjusts the user's task allocation. It also shares this information with other members to encourage their support.

[0457] Terminal: The adjusted task list is displayed to the user in real time.

[0458] This AI task management system incorporates an emotion engine to reflect the user's psychological state and achieve more effective task management. The server utilizes the AI ​​engine and emotion engine to manage tasks, and the device provides real-time information to the user. Through this specific operation, the system aims to improve work efficiency and productivity.

[0459] The processing flow will be explained below.

[0460] Specific usage flow of the emotion engine

[0461] Recognizing User Emotions and Adjusting Task Allocation

[0462] Step 1:

[0463] User: In the messaging screen, types "This task is very stressful."

[0464] Step 2:

[0465] Terminal: Formats message data in JSON format to send messages about emotions entered by the user to the emotion engine.

[0466] Step 3:

[0467] Terminal: Sends formatted JSON data to the server.

[0468] Step 4:

[0469] Server: Analyzes the received message data and sends it to the emotion engine.

[0470] Step 5:

[0471] Server: The emotion engine analyzes the message content and determines the user's emotional state as "high stress."

[0472] Step 6:

[0473] Server: Based on the analysis results from the emotion engine, instructs the AI ​​engine to review task allocation.

[0474] Step 7:

[0475] Server: The AI ​​engine reallocates current tasks to other members to reduce the user's workload.

[0476] Step 8:

[0477] Terminal: Receives new task lists from the server and displays them in real time on the user's dashboard.

[0478] Emotional evaluation upon task completion and member workload adjustment

[0479] Step 1:

[0480] User: Clicks the Complete button to report "Task B completed."

[0481] Step 2:

[0482] Terminal: Input the user's emotional state "feeling accomplished" along with the task completion report.

[0483] Step 3:

[0484] Terminal: Sends this information to the server in JSON format.

[0485] Step 4:

[0486] Server: Analyzes the received data and records task completion reports in a database.

[0487] Step 5:

[0488] Server: The emotion engine recognizes the user's emotional state as "feeling accomplished."

[0489] Step 6:

[0490] Server: Based on the evaluation from the emotion engine, the AI ​​engine optimizes future task allocation to the user.

[0491] Step 7:

[0492] Server: For example, if a user shows a high sense of accomplishment, it decides to prioritize the next complex task.

[0493] Step 8:

[0494] Terminal: The adjusted task list is displayed in real time on the user's dashboard.

[0495] Emotion-based adaptive communication

[0496] Step 1:

[0497] User: Type "I need team help" in the chat window.

[0498] Step 2:

[0499] Terminal: The emotion engine analyzes the message content and sends data in JSON format to the server to determine the emotional state.

[0500] Step 3:

[0501] Server: The emotion engine recognizes the user's emotional state as "cooperation needed."

[0502] Step 4:

[0503] Server: The emotion engine notifies the AI ​​engine, instructing it to reevaluate the task and ask team members for help.

[0504] Step 5:

[0505] Server: The AI ​​engine reevaluates the task and allocates the necessary resources.

[0506] Step 6:

[0507] Server: Based on the analysis results of the emotion engine, it sends messages requesting cooperation to other team members.

[0508] Step 7:

[0509] Terminal: A real-time message requesting cooperation will appear in the chat window of your team members.

[0510] This process flow enables the AI ​​task management system to adaptively allocate tasks, adjust priorities, and manage team communication while taking into account the user's emotional state. The server utilizes the AI ​​engine and emotion engine to perform efficient task management, while the device provides information to the user in real time, thereby improving work efficiency and productivity.

[0511] Example 2

[0512] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0513] While conventional task management systems can set task progress and priorities, they struggle to provide flexible task management that reflects the user's emotional state. Furthermore, support for real-time communication between users is limited, leaving challenges in improving work efficiency and productivity. Furthermore, resource management and appropriate task allocation are not adequately optimized, which can affect the productivity of the entire team.

[0514] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0515] In this invention, the server includes means for receiving detailed task information from a user and storing the information in a database, means for periodically obtaining the progress status of the task from the database, calculating the progress rate, and generating visualization data, and means for displaying the generated visualization data on the user's terminal in real time. This allows the detailed task information to be managed appropriately, and the progress status of the task to be grasped in real time.

[0516] The server further includes a means for analyzing the importance and urgency of tasks and prioritizing them based on each member's skill set and workload, a means for assigning tasks to appropriate members and notifying users of the assigned tasks, a means for automatically calculating project resource information and generating a resource list and budget, a means for sharing messages and files between members in real time, and a means for receiving, analyzing, and reflecting users' emotional information in task management. This optimizes task prioritization and assignment to members, enabling resource management and real-time communication. It also enables flexible task management that takes users' emotional states into account.

[0517] "Detailed task information" refers to specific information about a task, such as the task name, description, deadline, and priority.

[0518] "User" refers to an individual or organization that uses the task management system to create, manage, and check the progress of tasks.

[0519] "Database" refers to a system for structuring and storing and managing data such as task information, progress status, and resource information.

[0520] "Progress rate" refers to an indicator that shows how much of a task has been completed as a percentage.

[0521] "Visualized data" refers to data that displays progress rates, task progress, etc. in a visual format such as graphs or charts.

[0522] "Member" refers to an individual user or team member assigned to perform a task.

[0523] A "skill set" refers to the collection of skills, knowledge, and experience that a member possesses.

[0524] "Load status" refers to the status that indicates the current workload of a member.

[0525] "Resource information" refers to information such as materials, personnel, equipment, and budget required to carry out a project.

[0526] "Resource list" refers to an itemized list of resources required to carry out a project.

[0527] "Budget" refers to the total amount of costs and expenses planned for the operation of a project.

[0528] "Emotional information" refers to data about a user's emotional state (e.g., stress, satisfaction, dissatisfaction, etc.).

[0529] "Artificial intelligence engine" refers to an artificial intelligence system for analyzing the importance and urgency of tasks, setting priorities, and assigning tasks to members.

[0530] "Task management" refers to the act of managing the entire life cycle of a task, including creating, assigning, checking progress, and reporting completion.

[0531] This invention combines an AI task management system, which aims to efficiently manage projects and work and improve productivity, with an emotion engine that recognizes user emotions, enabling more advanced task management. This system is composed of a server and a client (user device).

[0532] The user can access the interface through a browser or a mobile app to manage tasks, check progress, and communicate. Specific embodiments of the present invention will be described below.

[0533] System configuration

[0534] The system consists of the following main functional modules:

[0535] 1. Task Entry Module: Used by the user to enter a new task.

[0536] 2. Database management module: A database for storing and managing task information, progress status, resource information, etc.

[0537] 3. Progress management module: Manages the progress of tasks and generates visualization data.

[0538] 4. AI engine: Analyzes the importance and urgency of the task, as well as the skill sets and workload of members.

[0539] 5. Task allocation module: Based on the analysis results of the AI ​​engine, tasks are prioritized and assigned to the appropriate members.

[0540] 6. Resource Management Module: Automatically calculates the resources required for a project and generates a resource list and budget.

[0541] 7. Communication module: Supports messaging and file sharing among members.

[0542] 8. Emotion Engine: Recognizes user emotions and reflects them in the task management process.

[0543] Recognizing and reflecting user emotions

[0544] The emotion engine analyzes the user's emotional state and adjusts task allocation and priorities based on the results. For example, if a user is feeling stressed, it will adjust the task allocation to reduce the user's workload.

[0545] Emotion recognition processing flow

[0546] User: Providing emotional input feedback when interacting with messaging and task management screens, or extracted from sensor data such as facial recognition and voice analysis.

[0547] Terminal: Analyzes the user's emotional information and sends it to the server in JSON format.

[0548] Server: Analyzes the received emotion data and adjusts task priorities and assignments based on the emotion engine.

[0549] Creating and entering a new task

[0550] User: Opens a browser or mobile app and accesses the task management screen.

[0551] User: Enter the details of the new task, specifying the task name, detailed description, due date, priority, etc.

[0552] Terminal: Sends the task information entered by the user to the server in JSON format.

[0553] Server: Parse the received JSON data and store it in the database.

[0554] Tracking task progress

[0555] Server: Periodically retrieves task progress data from the database, calculates the progress rate, and generates visualization data.

[0556] On the device: Retrieves progress data from the server and displays progress bars and graphs on the user's dashboard.

[0557] Examples:

[0558] User: Clicks the "Update Task A progress" button.

[0559] Terminal: Sends a progress update request to the server.

[0560] Server: Updates the progress field in the database and distributes the latest progress to other users.

[0561] Terminal: Shows an updated progress bar.

[0562] Task assignment and prioritization

[0563] Server: When a new task is added, the AI ​​engine analyzes the task details.

[0564] Server: Sets the priority of tasks taking into account the importance, urgency, skill sets of members, and workload status of the task.

[0565] Server: Assigns the task to the appropriate member.

[0566] On your device: The new task will appear in the assigned member's task list and a notification will be sent.

[0567] Examples:

[0568] User: Add a new task "Create Report".

[0569] Server: The AI ​​engine analyzes the task details and determines that it is highly important.

[0570] Server: Member A is available, so the task is assigned to Member A.

[0571] Terminal: "Create a report" is added to member A's task list.

[0572] Resource management assistance

[0573] Users: Enter the required resource information at the start of the project.

[0574] Terminal: Sends the entered information to the server.

[0575] Server: Automatically calculates required resources and generates resource lists and budgets.

[0576] Terminal: Display resource list and budget to project manager.

[0577] Examples:

[0578] User: Starts a "New Project" and enters the required resources.

[0579] Server: Generates a budget and a list of materials needed based on resource requirements.

[0580] Terminal: Display resource list and budget on the project manager's screen.

[0581] Real-time communication support

[0582] User: Opens the messaging screen and types a message.

[0583] Terminal: Sends a message to the server.

[0584] Server: Receives messages and distributes them to designated members in real time.

[0585] Terminal: Display received messages in the chat window.

[0586] Examples:

[0587] User: In the "Question" chat, type "When is this task due?"

[0588] Terminal: Sends a message to the server.

[0589] Server: Forwards the message to the target member.

[0590] Terminal: Display a message in the target member's chat window.

[0591] Specific examples of using the emotion engine

[0592] Examples:

[0593] User: In the messaging screen, types "This task is very stressful."

[0594] Device: An emotion engine analyzes the user's messages and detects increased stress.

[0595] Server: Based on the analysis results from the emotion engine, adjusts the user's task allocation. It also shares this information with other members to encourage their support.

[0596] Terminal: The adjusted task list is displayed to the user in real time.

[0597] This AI task management system incorporates an emotion engine to reflect the user's psychological state and achieve more effective task management. The server utilizes the AI ​​engine and emotion engine to manage tasks, and the device provides real-time information to the user. Through this specific operation, the system aims to improve work efficiency and productivity.

[0598] Prompt Sentence Examples

[0599] "What operations are required to track task progress within the system?"

[0600] "How does the Emotion Engine work?"

[0601] How do I add a new task?

[0602] The above is a specific description of the embodiment of the present invention.

[0603] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0604] Step 1:

[0605] A user opens a browser or mobile app and accesses the task management screen.

[0606] Specific operation: The user opens the device's browser, enters the specified URL, and logs in to the task management system. If the user uses the mobile app, they launch the app and access the login screen.

[0607] Input: User authentication information (username, password)

[0608] Output: The user is authenticated successfully and the task management screen is displayed.

[0609] Step 2:

[0610] The user enters the details of the new task (task name, detailed description, due date, priority, etc.).

[0611] Specific operation: The user enters the task name "Create monthly report", the description "Compile monthly reports", the deadline "2023-10-31", and the priority "High".

[0612] Input: Task details (task name, detailed description, deadline, priority)

[0613] Output: The entered task information is reflected in the task input form.

[0614] Step 3:

[0615] The device sends the task information entered by the user to the server in JSON format.

[0616] Specific operation: When the user clicks the "Send" button, the device converts the task information into task_data.json format and sends an HTTP request to the server.

[0617] Input: JSON data of task information

[0618] Output: The server receives the JSON data.

[0619] Step 4:

[0620] The server parses the received JSON data and stores it in the database.

[0621] Specific behavior: The server parses the received JSON data and saves the task name, details, due date, and priority to the database.

[0622] Input: JSON data of task information

[0623] Output: Task information is stored in the database.

[0624] Step 5:

[0625] The server periodically retrieves task progress status data from the database, calculates the progress rate, and generates visualization data.

[0626] What it does: The server queries the database every day to get the progress, calculates the progress rate, and generates visualization data in the form of bar graphs and charts.

[0627] Input: Task progress data retrieved from the database

[0628] Output: Generated visualization data (progress rate, etc.)

[0629] Step 6:

[0630] The device retrieves progress data from the server and displays progress bars and graphs on the user's dashboard.

[0631] Specific operation: When a user opens the dashboard screen, the device sends a request to the server, receives the latest progress data, and displays it as a progress bar and graph.

[0632] Input: Visualization data from the server

[0633] Output: Progress bars and graphs displayed on a dashboard

[0634] Step 7:

[0635] The server analyzes the importance and urgency of the task, the skill sets and workload of the members, sets the priority of the task, and assigns the task to an appropriate member.

[0636] How it works: When a new task is added, the AI ​​engine analyzes the task details, evaluates the importance and urgency of the task, sets a priority taking into account each member's skill set and current workload, and assigns it to the appropriate member.

[0637] Input: New task information, member skill sets and workload status

[0638] Output: A new task is added to the assigned member's task list

[0639] Step 8:

[0640] The new task will be displayed in the task list of the member to whom the device is assigned and a notification will be sent.

[0641] Specific operation: After the task assignment is determined, the terminal adds "Create a report" to member A's task list and notifies member A that a new task has been assigned via the notification function.

[0642] Input: Task assignment information

[0643] Output: New tasks and notifications added to members' task lists

[0644] Step 9:

[0645] Users enter the required resource information at the start of a project.

[0646] Specific operation: A user starts a "new project" and inputs resource information such as required personnel, equipment, and budget.

[0647] Input: Project resource information

[0648] Output: The input resource information is displayed.

[0649] Step 10:

[0650] The terminal transmits the input information to the server.

[0651] Specific operation: After the user enters the resource information, he clicks the "Send" button, and the terminal sends the information to the server in JSON format.

[0652] Input: JSON data of resource information

[0653] Output: The server receives the data

[0654] Step 11:

[0655] The server automatically calculates the required resources and generates a resource list and budget.

[0656] Specific operation: Based on the resource information received by the server, the server calculates the resources required to carry out the project and generates a resource list and budget.

[0657] Input: Resource information

[0658] Output: Generated resource list and budget

[0659] Step 12:

[0660] The terminal displays the resource list and budget to the project manager.

[0661] Specific operation: The resource list and budget data generated by the server are sent to the terminal and displayed on the project manager's screen.

[0662] Input: Resource list and budget data

[0663] Output: Resource list and budget displayed on the project manager's screen

[0664] Step 13:

[0665] The user opens the messaging screen and types a message.

[0666] What happens: A user uses the messaging feature to type a question: "When is this task due?"

[0667] Input: Message

[0668] Output: The displayed input message

[0669] Step 14:

[0670] The device sends a message to the server.

[0671] Specific operation: The user clicks the "Send" button, and the device sends the message to the server.

[0672] Input: Message data

[0673] Output: The server receives the message

[0674] Step 15:

[0675] The server receives the message and distributes it to the specified members in real time.

[0676] Specific operation: The server analyzes the received message, identifies the destination member, and forwards the message to that member.

[0677] Input: Incoming message

[0678] Output: Message delivery to specified members

[0679] Step 16:

[0680] Displays messages received by the device in the chat window.

[0681] Specific operation: The specified member's device will receive the message and display it in the chat window.

[0682] Input: Message data from the server

[0683] Output: Message displayed in the chat window

[0684] Step 17:

[0685] The user provides emotional input feedback or sensor data such as facial recognition or voice analysis.

[0686] Specific behavior: The user types "This task is very stressful" or provides emotional data using the smartphone's camera or microphone.

[0687] Input: Emotion data

[0688] Output: Emotional feedback displayed on the device

[0689] Step 18:

[0690] The device analyzes the user's emotional information and sends it to the server in JSON format.

[0691] Specific operation: The device analyzes the user's emotional feedback, converts the type and intensity of the emotion into JSON format, and sends it to the server.

[0692] Input: JSON data of emotion information

[0693] Output: The server receives the emotion data.

[0694] Step 19:

[0695] The server analyzes the received emotion data and adjusts task priorities and allocations based on the emotion engine.

[0696] Specific operation: The server uses an emotion engine to analyze emotional data, and if it determines that the user's stress level is high, it adjusts task allocation and priorities.

[0697] Input: Emotion data

[0698] Output: Adjusted task assignments and priorities

[0699] (Application example 2)

[0700] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0701] Conventional task management systems assign and prioritize tasks without considering the user's emotional state, which increases the user's psychological burden and makes efficient task management difficult. Furthermore, in security services, there was a lack of a mechanism for grasping the emotional state of security guards and security staff in real time and dynamically adjusting tasks based on that information, making it difficult to respond appropriately in emergencies. The present invention addresses these issues.

[0702] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0703] In this invention, the server includes means for receiving detailed task information from a user and storing it in a database, means for periodically obtaining task progress from the database, calculating the progress rate, and generating visualization data, means for displaying the generated visualization data on the user's terminal in real time, means for analyzing the importance and urgency of tasks and setting task priorities taking into account the skill set and workload of each member, means for assigning tasks to appropriate members and notifying the user's terminal of the assigned tasks, means for automatically calculating project resource information and generating a resource list and budget, means for sharing messages and files among members in real time, and means for recognizing the emotional state of security staff, transmitting that data to the server, and adjusting task priorities and assignments based on an emotion engine. This enables efficient task management and appropriate security response that reflects the user's emotional state.

[0704] "Detailed task information" is specific information such as the name, description, deadline, and priority of a task input by the user.

[0705] A "database" is a system for structuring and storing and managing task information, progress status, resource information, and the like.

[0706] "Visualization data" refers to data such as graphs and charts that visually represent task progress and other information.

[0707] "Task importance" is an indicator of how important a particular task is to the project or business as a whole.

[0708] "Urgency" is a measure of how quickly a particular task should be addressed.

[0709] "Skill set" is a collective term for the techniques, knowledge, and experience that each member possesses.

[0710] "Load status" is information that indicates the amount of tasks currently assigned to each member and the degree to which the goal must be achieved.

[0711] "Resource information" refers to detailed information about personnel, equipment, materials, and budget required to carry out a project.

[0712] The "emotion engine" is a software module that recognizes the user's emotional state and reflects the analysis results in the task management process.

[0713] "Security staff" refers to security guards and guards who work to ensure the safety of facilities, events, etc.

[0714] "Task priority" refers to the order of task execution that is set based on the importance, urgency, skill set, and load status of the task.

[0715] The present invention is a system that monitors the emotional state of security staff in real time and dynamically adjusts task allocation and priorities based on the monitoring results. Specific embodiments will be described below.

[0716] System configuration

[0717] The system consists of a series of software and hardware components, including an emotion recognition engine, a task management engine, a database, a user interface, and a communication module.

[0718] Hardware and Software Details

[0719] Smart glasses: equipped with cameras to provide a video feed for monitoring the emotional state of security staff.

[0720] Emotion recognition engine: A software module used to recognize user emotions from video in real time (e.g., EmotionRecognizer).

[0721] AI task management engine: Analyzes the importance and urgency of tasks and prioritizes them based on resources and sentiment information.

[0722] Database: A system that structures and stores task information, progress, emotional data, etc.

[0723] Communication module: A module for transmitting data in real time between a user terminal and a server (e.g., the Requests library).

[0724] User emotion recognition and data transmission

[0725] User: Wears smart glasses, the camera captures the video feed.

[0726] Terminal: Analyzes the user's emotional state from the camera feed of the smart glasses using an emotion recognition engine and sends the results to the server.

[0727] Server: Analyzes the received emotional data and adjusts task allocation and priorities using an AI task management engine.

[0728] Task assignment and prioritization

[0729] Server: The AI ​​engine and emotion engine work together to prioritize tasks, taking into account the importance and urgency of the task and the emotional state of the security staff.

[0730] Server: Assign tasks to the appropriate security staff based on set priorities. Assign important and urgent tasks to staff with stable emotional states.

[0731] Devices: Assigned tasks are notified to staff members' smartphones or other devices.

[0732] Specific examples

[0733] User: Security staff wear smart glasses and patrol the area.

[0734] Device: The smart glasses capture video and the emotion recognition engine analyzes emotions in real time. For example, if it detects "anxiety" or "tension," it sends the data to the server.

[0735] Server: Based on the received emotional data, it assigns high-priority tasks to other emotionally stable staff members.

[0736] Device: The task is notified to the assigned staff member's smartphone.

[0737] This system will enable effective task management that takes into account the emotional state of security staff, enabling appropriate responses in emergencies. It will also promote real-time communication between staff, improving work efficiency and safety.

[0738] Prompt Sentence Examples

[0739] Sample prompt: "I want to build a system that uses facial recognition to analyze emotions in real time and adjust security task assignments based on that information. Specifically, I would use smart glasses to capture camera footage and EmotionRecognizer to recognize emotions, so that stressed guards are not assigned urgent tasks and instead are assigned to other guards."

[0740] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0741] Step 1:

[0742] A user puts on the smart glasses and starts the camera feed.

[0743] Input: Real-time video data from smart glasses.

[0744] Output: A real-time video feed is generated, which serves as input to the emotion recognition engine.

[0745] How it works: Security staff wear smart glasses and patrol the surveillance area, and the camera in the smart glasses captures images of the surrounding area.

[0746] Step 2:

[0747] The device uses an emotion recognition engine to analyze the user's emotions in real time from the camera feed of the smart glasses.

[0748] Input: Real-time video feed.

[0749] Output: Data representing the user's emotional state (e.g., stressed, nervous, calm, etc.).

[0750] Specific operation: The device uses EmotionRecognizer to analyze video data and recognize emotions from the user's facial expressions and slight body movements. For example, it identifies emotions such as "stress" and "anxiety."

[0751] Step 3:

[0752] The device sends the results of the emotion recognition engine to the server in JSON format.

[0753] Input: Data representing the user's emotional state.

[0754] Output: Emotion data in JSON format is sent to the server.

[0755] Specific operation: The device converts the analyzed data into JSON format and sends it to the server as an HTTP request. This data also includes a timestamp and user ID.

[0756] Step 4:

[0757] The server analyzes the received emotional data and calls an AI task management engine to respond appropriately.

[0758] Input: Emotion data in JSON format.

[0759] Output: Analysis results of task priorities and allocation settings.

[0760] Specific operation: The server analyzes the received emotional data and passes the results to the AI ​​task management engine, which then reevaluates task priorities and allocations according to the emotional state.

[0761] Step 5:

[0762] The server assigns tasks to appropriate security staff based on the analysis results of the AI ​​task management engine.

[0763] Input: Analysis results (task priorities and assignments).

[0764] Output: Task assignment notification.

[0765] Specific operation: Based on the analysis results, the server decides to avoid urgent tasks for stressed staff and assign tasks to other emotionally stable staff.

[0766] Step 6:

[0767] The server notifies the user's terminal of the assigned task.

[0768] Input: Task assignment information.

[0769] Output: Task notification sent to user device.

[0770] Specific operation: The server sends the allocation information to the corresponding security staff terminal in real time, and the staff receives the notification and confirms their next action.

[0771] Step 7:

[0772] The user performs the assigned task and reports progress to the terminal.

[0773] Input: Task progress.

[0774] Output: Progress data is sent to the server.

[0775] Specific operation: Security staff carry out assigned tasks and report their progress and completion status via their terminals. The reported data is sent to the server and shared throughout the system.

[0776] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0777] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0778] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0779] [Second embodiment]

[0780] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0781] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0782] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0783] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0784] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0785] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0786] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0787] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0788] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0789] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0790] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0791] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0792] This invention is an AI task management system that aims to efficiently manage projects and work and improve productivity. The system consists of a server and a client (user device). Users can access the interface via a browser or mobile app to manage tasks, check progress, and communicate. The specific operation of the system is described in detail below.

[0793] System configuration

[0794] The system consists of the following main functional modules:

[0795] 1. Task Entry Module: Used by the user to enter a new task.

[0796] 2. Database management module: A database for storing and managing task information, progress status, resource information, etc.

[0797] 3. Progress management module: Manages the progress of tasks and generates visualization data.

[0798] 4. AI engine: Analyzes the importance and urgency of the task, as well as the skill sets and workload of members.

[0799] 5. Task allocation module: Based on the analysis results of the AI ​​engine, tasks are prioritized and assigned to the appropriate members.

[0800] 6. Resource Management Module: Automatically calculates the resources required for a project and generates a resource list and budget.

[0801] 7. Communication module: Supports messaging and file sharing among members.

[0802] Creating and entering a new task

[0803] User: Opens a browser or mobile app and accesses the task management screen.

[0804] User: Enter the details of the new task, specifying the task name, detailed description, due date, priority, etc.

[0805] Terminal: Sends the task information entered by the user to the server in JSON format.

[0806] Server: Parse the received JSON data and store it in the database.

[0807] Tracking task progress

[0808] Server: Periodically retrieves task progress data from the database, calculates the progress rate, and generates visualization data.

[0809] On the device: Retrieves progress data from the server and displays progress bars and graphs on the user's dashboard.

[0810] Examples:

[0811] User: Clicks the "Update Task A progress" button.

[0812] Terminal: Sends a progress update request to the server.

[0813] Server: Updates the progress field in the database and distributes the latest progress to other users.

[0814] Terminal: Shows an updated progress bar.

[0815] Task assignment and prioritization

[0816] Server: When a new task is added, the AI ​​engine analyzes the task details.

[0817] Server: Sets the priority of tasks taking into account the importance, urgency, skill sets of members, and workload status of the task.

[0818] Server: Assigns the task to the appropriate member.

[0819] On your device: The new task will appear in the assigned member's task list and a notification will be sent.

[0820] Examples:

[0821] User: Add a new task "Create Report".

[0822] Server: The AI ​​engine analyzes the task details and determines that it is highly important.

[0823] Server: Member A is available, so the task is assigned to Member A.

[0824] Terminal: "Create a report" is added to member A's task list.

[0825] Resource management assistance

[0826] Users: Enter the required resource information at the start of the project.

[0827] Terminal: Sends the entered information to the server.

[0828] Server: Automatically calculates required resources and generates resource lists and budgets.

[0829] Terminal: Display resource list and budget to project manager.

[0830] Examples:

[0831] User: Starts a "New Project" and enters the required resources.

[0832] Server: Generates a budget and a list of materials needed based on resource requirements.

[0833] Terminal: Display resource list and budget on the project manager's screen.

[0834] Real-time communication support

[0835] User: Opens the messaging screen and enters a message.

[0836] Terminal: Sends a message to the server.

[0837] Server: Receives messages and distributes them to designated members in real time.

[0838] Terminal: Display received messages in the chat window.

[0839] Examples:

[0840] User: In the "Question" chat, type "When is this task due?"

[0841] Terminal: Sends a message to the server.

[0842] Server: Forwards the message to the target member.

[0843] Terminal: Display a message in the target member's chat window.

[0844] summary

[0845] This AI task management system integrates progress management, task allocation and prioritization, resource management, and real-time communication support. The server utilizes an AI engine to manage tasks, and the device provides real-time information to the user. Through these specific operations, the system improves work efficiency and productivity.

[0846] The processing flow will be explained below.

[0847] Creating and entering a new task

[0848] Step 1:

[0849] User: Opens a browser or mobile app and accesses the task management screen.

[0850] Step 2:

[0851] User: Enter the details of the new task, specifying the task name, detailed description, due date, priority, etc.

[0852] Step 3:

[0853] Terminal: Sends the task information entered by the user to the server in JSON format.

[0854] Step 4:

[0855] Server: Parse the received JSON data and store it in the database.

[0856] Tracking task progress

[0857] Step 1:

[0858] Server: Periodically retrieves task progress data from the database.

[0859] Step 2:

[0860] Server: Based on the progress status data, calculates the progress rate of the task and generates visualization data.

[0861] Step 3:

[0862] On the device: Retrieves progress data from the server and displays progress bars and graphs on the user's dashboard.

[0863] Examples:

[0864] Step 1:

[0865] User: Clicks the "Update Task A progress" button.

[0866] Step 2:

[0867] Terminal: Sends a progress update request to the server.

[0868] Step 3:

[0869] Server: Updates the progress field in the database and distributes the latest progress to other users.

[0870] Step 4:

[0871] Terminal: Shows an updated progress bar.

[0872] Task assignment and prioritization

[0873] Step 1:

[0874] Server: When a new task is added, the AI ​​engine analyzes the task details.

[0875] Step 2:

[0876] Server: Sets the priority of tasks taking into account the importance, urgency, skill sets of members, and workload status of the task.

[0877] Step 3:

[0878] Server: Assigns the task to the appropriate member.

[0879] Step 4:

[0880] On your device: The new task will appear in the assigned member's task list and a notification will be sent.

[0881] Examples:

[0882] Step 1:

[0883] User: Add a new task "Create Report".

[0884] Step 2:

[0885] Server: The AI ​​engine analyzes the task details and determines that it is highly important.

[0886] Step 3:

[0887] Server: Member A is available, so the task is assigned to Member A.

[0888] Step 4:

[0889] Terminal: "Create a report" is added to member A's task list.

[0890] Resource management assistance

[0891] Step 1:

[0892] Users: Enter the required resource information at the start of the project.

[0893] Step 2:

[0894] Terminal: Sends the entered information to the server.

[0895] Step 3:

[0896] Server: Automatically calculates required resources and generates resource lists and budgets.

[0897] Step 4:

[0898] Terminal: Display resource list and budget to project manager.

[0899] Examples:

[0900] Step 1:

[0901] User: Starts a "New Project" and enters the required resources.

[0902] Step 2:

[0903] Server: Generates a budget and a list of materials needed based on resource requirements.

[0904] Step 3:

[0905] Terminal: Display resource list and budget on the project manager's screen.

[0906] Real-time communication support

[0907] Step 1:

[0908] User: Opens the messaging screen and enters a message.

[0909] Step 2:

[0910] Terminal: Sends a message to the server.

[0911] Step 3:

[0912] Server: Receives messages and distributes them to designated members in real time.

[0913] Step 4:

[0914] Terminal: Display received messages in the chat window.

[0915] Examples:

[0916] Step 1:

[0917] User: In the "Question" chat, type "When is this task due?"

[0918] Step 2:

[0919] Terminal: Sends a message to the server.

[0920] Step 3:

[0921] Server: Forwards the message to the target member.

[0922] Step 4:

[0923] Terminal: Display a message in the target member's chat window.

[0924] Example 1

[0925] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0926] Modern project management requires consistent and efficient operation, from task entry to progress visualization, task prioritization and assignment, resource management, and communication between team members. However, few systems offer these functions in an integrated and automated manner, and manual management or the use of multiple tools is often required. This results in problems such as duplicated work and reduced efficiency. Furthermore, optimal task assignment based on task importance and team member skill sets requires advanced analytical capabilities, which traditional systems often lack. To address these challenges, there is a need for systems that optimize task management by automating and streamlining the entire business process and incorporating generative AI models.

[0927] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0928] In this invention, the server includes means for receiving detailed task information from a user and storing the information in a database, means for periodically obtaining the task progress status from the database, calculating the progress rate, and generating visualization data, and means for displaying the generated visualization data on the user's terminal in real time, thereby enabling detailed task management and visualization and real-time display of the progress status.

[0929] The server also includes: a means for analyzing the importance and urgency of tasks and prioritizing the tasks while taking into account the technical requirements and workload of each member; a means for assigning tasks to appropriate members and notifying the users of the assigned tasks on their terminals; a means for automatically calculating project resource information and generating a resource list and budget; a means for sharing messages and files between members in real time; a means for outputting task analysis results using a generative AI model; and a means for automatically generating task details using prompt text as input. This enables task prioritization and allocation optimization, automated resource management, and real-time communication.

[0930] "Detailed task information" refers to information such as the content, deadline, priority, and explanation of specific tasks that a user should manage in a project or business.

[0931] A "database" is a storage medium and its management system for systematically storing and managing data required within the system, such as detailed task information, progress status, member information, and resource information.

[0932] "Completion" refers to how much of a particular task or project is complete, usually expressed as a percentage.

[0933] "Visualized data" is data that is presented in a visual form, such as a graph or chart, so that users can easily understand the data intuitively.

[0934] A "user terminal" is an electronic device such as a computer, tablet, or smartphone that a user uses to access and operate the system.

[0935] "Task importance" is an index that indicates how important a particular task is compared to other tasks.

[0936] "Urgency" is a measure of how quickly a particular task should be addressed.

[0937] "Technical requirements" are requirements such as specific skills, knowledge, and experience required to perform a task.

[0938] "Load status" refers to the status that indicates how much work a particular member or resource is currently doing.

[0939] "Priority" is the order that determines which task or project should be done first among multiple tasks or projects.

[0940] "Resource information" refers to information such as personnel, equipment, and budget required to carry out a project or task.

[0941] A "generative AI model" is an algorithm and its implementation that uses artificial intelligence to generate analytical results and predictions from input data.

[0942] A "prompt sentence" is text data given as input to a generative AI model, and contains specific instructions for analysis and generation.

[0943] "Analysis results" are decision information such as task allocation and priority setting that the generative AI model outputs based on prompt statements and other input data.

[0944] This invention is an AI task management system aimed at efficient management of projects and work and improving productivity. The system consists of a server and a client (user device), and users can access the interface via a browser or mobile app to manage tasks, check progress, and communicate. The specific operation of the system is described in detail below.

[0945] System configuration

[0946] The system consists of the following main functional modules:

[0947] 1. Task Entry Module: Used by the user to enter a new task.

[0948] 2. Database Management Module: A database for storing and managing task information, progress, and resource information.

[0949] 3. Progress management module: Manages the progress of tasks and generates visualization data.

[0950] 4. Generative AI model: Analyzes the importance and urgency of the task, as well as the technical requirements and workload of members.

[0951] 5. Task assignment module: Based on the analysis results of the generative AI model, tasks are prioritized and assigned to appropriate members.

[0952] 6. Resource Management Module: Automatically calculates the resources required for a project and generates a resource list and budget.

[0953] 7. Communication module: Supports messaging and file sharing among members.

[0954] Specific operation of the system

[0955] A user opens a browser or mobile app and accesses the task management screen. When adding a task, they enter details such as the task name, detailed description, due date, and priority into a form. This sends JSON format data from the device to the server. The server parses the received data and stores it in a database.

[0956] Specific examples

[0957] For example, if a user enters a task name of "Report Creation," a deadline of "2023-12-31," and a priority of "High," the device sends this information in JSON format to the server, which receives the data and stores it in a database.

[0958] The server periodically retrieves task progress data from the database, calculates the progress rate, and generates visualization data, which is displayed in real time on the user's dashboard.

[0959] Specific examples

[0960] When the user clicks the progress update button, the device sends a progress update request to the server. The server updates the database with the new progress and distributes this latest data to other users. The device then displays the updated progress bar on the user's dashboard.

[0961] When a new task is added, the server's generative AI model analyzes the task details and prioritizes it, taking into account the task's importance, urgency, technical requirements of members, and workload.

[0962] Specific examples

[0963] For example, a new task "Write a report" is added, and the generative AI model analyzes the task and determines that it is of high importance. Since member A is currently free, the task is assigned to member A. The device sends a notification to member A and adds the task to the task list.

[0964] The user inputs the necessary resource information at the start of a project. The terminal sends the information to the server, which then automatically calculates and generates the resource list and budget. This information is then displayed on the project manager's terminal.

[0965] Specific examples

[0966] When a user starts a "new project" and enters the required resources as "PC, software license, and budget of 300,000 yen," the server automatically calculates the budget and materials list based on that information and displays the results to the project manager on the terminal.

[0967] With the messaging function, users can enter and send messages on the messaging screen. The device sends the message to the server, which then distributes it to other members in real time. Received messages are displayed in the chat window on the device.

[0968] Specific examples

[0969] When a user types "When is the deadline for this task?" into the chat window and sends it, the device sends the message to the server, which then forwards the message to the target member, who then sees the message in their chat window.

[0970] A prompt is a text instruction given as input to a generative AI model to analyze and automatically generate a task. For example, a prompt might be, "Please write an important report. The deadline is December 31, 2023."

[0971] In this way, the AI ​​task management system integrates progress management, task allocation and priority setting, resource management, and real-time communication support. The server uses generated AI models to manage tasks, and the terminal provides information to the user in real time, thereby improving work efficiency and productivity.

[0972] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0973] The flow of this system's program processing

[0974] Step 1: User enters task

[0975] Input: A user opens a browser or mobile app, accesses the task management screen, and enters task details such as the task name, detailed description, due date, and priority.

[0976] Processing: The terminal converts the input information into JSON format.

[0977] Output: The generated JSON data is sent to the server.

[0978] Specific operation: The user enters the task name "Create report", the due date "2023-12-31", and the priority "High". The device sends this to the server in the format {"task_name": "Create report", "due_date": "2023-12-31", "priority": "High"}.

[0979] Step 2: Receiving and saving task data

[0980] Input: Task data in JSON format sent from the device.

[0981] Processing: The server parses the received JSON data, maps it to the appropriate fields, and stores it in the database.

[0982] Output: Task information is saved to the database.

[0983] Specific operation: The server receives the data {"task_name": "Create Report", "due_date": "2023-12-31", "priority": "High"}, parses it, and saves it to the database.

[0984] Step 3: Managing and visualizing task progress

[0985] Input: Task progress data retrieved periodically from the database.

[0986] Processing: The server calculates the progress rate and generates visualization data (graphs and bars).

[0987] Output: The generated visualization data is sent to the user's terminal and displayed in real time.

[0988] Specific operation: The server obtains the progress data and generates a progress bar when the progress of "Task A" is 50%. The device receives this information and displays it on the user's dashboard.

[0989] Step 4: Analysis and task prioritization by generative AI model

[0990] Input: New task details.

[0991] Processing: The server-generated AI model analyzes the importance and urgency of tasks, as well as the technical requirements and workload of each member. Task priorities are set based on the analysis results.

[0992] Output: Task information assigned to the appropriate members is generated.

[0993] Specific operation: The AI ​​model analyzes the "Report Creation" task and determines that it is of high importance. Since member A has a low workload, the model assigns this task to member A.

[0994] Step 5: Task assignment and notifications

[0995] Input: Task assignment information from the generative AI model.

[0996] Processing: The server assigns the task to an appropriate member and notifies the user's terminal of this information.

[0997] Output: The task list is updated on the user's device and a notification is displayed.

[0998] Specific behavior: When you assign the task "Create a report" to member A, a notification will be sent to the device and member A's task list will be updated.

[0999] Step 6: Enter and manage resource information

[1000] Input: Users enter the required resource information at the start of a project.

[1001] Processing: The terminal sends the information to the server, which automatically calculates the required resources and generates a resource list and budget.

[1002] Output: The generated resource list and budget are displayed on the project manager's terminal.

[1003] Specific operation: When a user enters "PC, software license, budget 300,000 yen," the server automatically calculates and displays the results to the project manager.

[1004] Step 7: Real-time communication

[1005] Input: The message the user types in the messaging screen.

[1006] Processing: The terminal sends a message to the server, which then forwards it to the designated members in real time.

[1007] Output: The message will be displayed in the member's chat window.

[1008] Specific operation: The user types "When is the deadline for this task?" into the chat and sends it. The device sends it to the server, which then forwards it to the target member and displays it.

[1009] Specific examples

[1010] For example, the generative AI model is used with the prompt "Please prepare an important report. The deadline is December 31, 2023." In this case, the AI ​​model analyzes the content of the prompt and automatically generates detailed information about the task. As a result, the system assigns the task to an appropriate member and displays basic information on the user's device.

[1011] (Application example 1)

[1012] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1013] Conventional factory task management and resource management often require a lot of human intervention and are inefficient. Furthermore, it is not possible to monitor the robot's operating status or progress in real time, making it difficult to respond quickly when an error occurs. This has led to problems such as reduced productivity and increased costs. The present invention aims to solve these problems and improve the efficiency of task management, progress monitoring, and resource management within a factory.

[1014] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1015] In this invention, the server includes means for receiving detailed task information from a user and storing it in an information storage device, means for periodically obtaining task progress status from the information storage device, calculating the progress rate, and generating visualization data, means for displaying the generated visualization data on a user's terminal in real time, means for analyzing the importance and urgency of tasks and prioritizing tasks taking into account the skill sets and workloads of each worker, means for assigning tasks to appropriate workers and notifying the users of the assigned tasks, means for automatically calculating resource information within the factory and generating a resource list and budget, means for sharing messages and files among workers in real time, means for monitoring the operating status of robots in real time and notifying a smartphone or head-mounted display of task progress and errors, and means for generating resource requests for the project and calculating an optimal budget. This enables efficient task management and progress monitoring within the factory and immediate response.

[1016] "Task detailed information" is specific information about a task, such as the name, content, deadline, and priority of a specific task.

[1017] A "user" is an individual or person in charge who operates the system to input tasks and monitor progress.

[1018] An "information storage device" is a database or storage system for saving and managing data such as detailed task information and progress status.

[1019] "Progress" refers to the state of how much of a particular task has been completed.

[1020] "Visualized data" is data that visually shows progress, such as numbers, graphs, and progress bars.

[1021] A "terminal" is a device used by a user, such as a smartphone, tablet, or head-mounted display.

[1022] "Task importance" is a factor that indicates the business importance of a specific task.

[1023] "Urgency" is a factor that indicates how quickly a particular task should be addressed.

[1024] A "skill set" is the collection of skills and abilities that each member possesses.

[1025] "Load status" refers to the tasks and workload currently handled by each member.

[1026] "Constituents" are people or teams to whom tasks are assigned by the system.

[1027] "Resource information" refers to information such as materials, personnel, and equipment required to carry out a project or task.

[1028] A "resource list" is a list of required resources.

[1029] A "budget" is an estimate of how much a project or task will cost.

[1030] "Message and file sharing" refers to the act of sending and receiving text messages and documents between members.

[1031] "Robot operating status" is information on whether the corresponding robot in the factory is available, in operation, or in an error state.

[1032] An "error" is a problem or failure that occurs within a robot or system.

[1033] A "project resource request" is a requirement that specifies the resources needed to complete a particular project or task.

[1034] The "optimal budget" is the most efficient cost estimate calculated based on the resource information and resource list.

[1035] The present invention is a system for efficiently managing tasks, progress, and resources within a factory. This system is realized through the cooperation of a server, terminals, and users.

[1036] System configuration

[1037] The system consists of the following main functional modules:

[1038] 1. Task input module: Used by users to input new tasks.

[1039] 2. Database management module: An information storage device for storing and managing task information, progress status, resource information, etc.

[1040] 3. Progress management module: Manages the progress of tasks and generates visualization data.

[1041] 4. AI engine: Analyzes the importance and urgency of the task, the skill sets of the members, and the workload situation.

[1042] 5. Task allocation module: Based on the analysis results of the AI ​​engine, it sets the priority of tasks and assigns them to the appropriate members.

[1043] 6. Resource management module: Automatically calculates resource information within the factory and generates resource lists and budgets.

[1044] 7. Communication module: Supports messaging and file sharing among members.

[1045] 8. Robot monitoring module: Monitors the robot's operating status in real time and notifies the operating status and errors to a smartphone or head-mounted display.

[1046] Creating and entering a new task

[1047] User: Opens a smartphone or head-mounted display and accesses the task management screen.

[1048] User: Enter the details of the new task, specifying the task name, detailed description, due date, importance, etc.

[1049] Terminal: Sends task information entered by the user to the server.

[1050] Server: Analyzes the received task information and stores it in an information storage device.

[1051] Tracking task progress

[1052] Server: Periodically obtains task progress data from the information storage device, calculates the progress rate, and generates visualization data.

[1053] Terminal: Retrieves progress data from the server and displays progress bars and graphs on the user's dashboard.

[1054] Task assignment and prioritization

[1055] Server: When a new task is added, the AI ​​engine analyzes the task details.

[1056] Server: Sets the priority of tasks taking into account the importance and urgency of the tasks, the skill sets of members, and the workload situation.

[1057] Server: Assigns tasks to appropriate members. For example, when a new task, "assembling machine parts," is added, the AI ​​engine determines that the task has high priority and assigns it to member A, whose skill set is suitable.

[1058] Terminal: Adds new tasks to assigned members' task lists and sends notifications.

[1059] Resource Management

[1060] User: Enters the required resource information at the start of the project.

[1061] Terminal: Sends the entered information to the server.

[1062] Server: Automatically calculates required resources and generates resource lists and budgets.

[1063] Terminal: Display resource lists and budgets to project managers in real time.

[1064] Real-time communication

[1065] User: Open the messaging screen and enter a message.

[1066] Terminal: Sends a message to the server.

[1067] Server: Receives messages and distributes them to designated members in real time.

[1068] Terminal: Display received messages in the chat window.

[1069] Monitoring the operating status of robots

[1070] Server: Monitors the robot's operating status in real time, checking progress and errors.

[1071] Device: A notification is displayed on a smartphone or head-mounted display to notify the user.

[1072] Examples of concrete examples and prompts

[1073] For example, a factory supervisor can input a new task, "Transport parts," on their smartphone, and the AI ​​engine analyzes it and assigns the task to the appropriate robot. The supervisor can then monitor the robot's progress in real time on their smartphone and immediately respond to any problems that arise.

[1074] Example prompt for generative AI model:

[1075] "Assign the following task to the most suitable robot. Task information: Parts transport, Deadline: 2023-12-31, Priority: High. Robot list: Robot 1, Robot 2, Robot 3. Consider the current operational status and skill set of the robots."

[1076] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1077] Step 1:

[1078] Entering task details

[1079] The user inputs details of a new task using a smartphone or head-mounted display, including the task name, detailed description, deadline, and importance.

[1080] Input: Task details entered by the user

[1081] The terminal sends the entered information to the server in JSON format.

[1082] Output: Sends detailed task information in JSON format to the server

[1083] Step 2:

[1084] Storing task information

[1085] The server analyzes the received JSON format task information and stores it in an information storage device (database).

[1086] Input: JSON formatted task details sent from the device

[1087] Data processing: Parsing JSON data

[1088] Output: Detailed task information stored in the database

[1089] Step 3:

[1090] Obtaining and managing task progress

[1091] The server periodically retrieves task progress status data from the database, calculates the progress rate, and generates visualization data.

[1092] Input: Progress data retrieved from the database

[1093] Data calculation: Calculating progress rate and generating visualization data

[1094] Output: The generated visualization data

[1095] Step 4:

[1096] Viewing progress data

[1097] The device retrieves progress data from the server and displays it on the user's dashboard in the form of a progress bar or graph.

[1098] Input: Visualization data obtained from the server

[1099] Output: Progress displayed on the device dashboard

[1100] Step 5:

[1101] Task analysis by AI engine

[1102] The server uses an AI engine to analyze the importance and urgency of tasks and prioritizes them, taking into account each member's skill set and workload.

[1103] Input: Task details, member skill sets and workload status

[1104] Data calculation: Analyzing the importance and urgency of tasks and setting priorities

[1105] Output: Prioritized task information

[1106] Step 6:

[1107] Task assignment

[1108] The server assigns prioritized tasks to appropriate members.

[1109] Input: Priority-set task information, member skills and workload information

[1110] Data calculation: Selecting the best members

[1111] Output: Task list notification to assigned members

[1112] Step 7:

[1113] Resource Management

[1114] At the start of a project, the user inputs the necessary resource information, and the terminal sends this to the server.

[1115] Input: Required resource information

[1116] The terminal transmits the input resource information to the server.

[1117] Output: Resource information sent to the server

[1118] Step 8:

[1119] Calculating and displaying resource information

[1120] The server automatically calculates the required resources, generates a resource list and budget, and displays them to the project manager.

[1121] Input: Resource information submitted by the user

[1122] Data calculation: Automatic calculation of resources and generation of resource lists and budgets

[1123] Output: Display resource list and budget on the project manager screen

[1124] Step 9:

[1125] Real-time communication

[1126] The user opens the messaging screen and enters a message, which the device then sends to the server.

[1127] Input: The message entered by the user

[1128] The terminal sends a message to the server, which then distributes it to the designated members in real time.

[1129] Output: Message displayed in the chat window of the specified member

[1130] Step 10:

[1131] Monitoring the operating status of robots

[1132] The server monitors the robot's operating status in real time, checking for progress and errors.

[1133] Input: Robot operating status data

[1134] The device notifies the smartphone or head-mounted display of progress and errors.

[1135] Output: Robot progress and error notifications displayed on the user's terminal

[1136] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1137] This invention combines an AI task management system, which aims to efficiently manage projects and work and improve productivity, with an emotion engine that recognizes user emotions, enabling more advanced task management. The system consists of a server and a client (user device). Users can access the interface via a browser or mobile app to manage tasks, check progress, and communicate. The specific operation of the system is described in detail below.

[1138] System configuration

[1139] The system consists of the following main functional modules:

[1140] 1. Task Entry Module: Used by the user to enter a new task.

[1141] 2. Database management module: A database for storing and managing task information, progress status, resource information, etc.

[1142] 3. Progress management module: Manages the progress of tasks and generates visualization data.

[1143] 4. AI engine: Analyzes the importance and urgency of the task, as well as the skill sets and workload of members.

[1144] 5. Task allocation module: Based on the analysis results of the AI ​​engine, tasks are prioritized and assigned to the appropriate members.

[1145] 6. Resource Management Module: Automatically calculates the resources required for a project and generates a resource list and budget.

[1146] 7. Communication module: Supports messaging and file sharing among members.

[1147] 8. Emotion Engine: Recognizes user emotions and reflects them in the task management process.

[1148] Recognizing and reflecting user emotions

[1149] The emotion engine analyzes the user's emotional state and adjusts task allocation and priorities based on the results. For example, if a user is feeling stressed, it will adjust the task allocation to reduce the user's workload.

[1150] Emotion recognition processing flow

[1151] User: Providing emotional input feedback when interacting with messaging and task management screens, or extracted from sensor data such as facial recognition and voice analysis.

[1152] Terminal: Analyzes the user's emotional information and sends it to the server in JSON format.

[1153] Server: Analyzes the received emotion data and adjusts task priorities and assignments based on the emotion engine.

[1154] Creating and entering a new task

[1155] User: Opens a browser or mobile app and accesses the task management screen.

[1156] User: Enter the details of the new task, specifying the task name, detailed description, due date, priority, etc.

[1157] Terminal: Sends the task information entered by the user to the server in JSON format.

[1158] Server: Parse the received JSON data and store it in the database.

[1159] Tracking task progress

[1160] Server: Periodically retrieves task progress data from the database, calculates the progress rate, and generates visualization data.

[1161] On the device: Retrieves progress data from the server and displays progress bars and graphs on the user's dashboard.

[1162] Examples:

[1163] User: Clicks the "Update Task A progress" button.

[1164] Terminal: Sends a progress update request to the server.

[1165] Server: Updates the progress field in the database and distributes the latest progress to other users.

[1166] Terminal: Shows an updated progress bar.

[1167] Task assignment and prioritization

[1168] Server: When a new task is added, the AI ​​engine analyzes the task details.

[1169] Server: Sets the priority of tasks taking into account the importance, urgency, skill sets of members, and workload status of the task.

[1170] Server: Assigns the task to the appropriate member.

[1171] On your device: The new task will appear in the assigned member's task list and a notification will be sent.

[1172] Examples:

[1173] User: Add a new task "Create Report".

[1174] Server: The AI ​​engine analyzes the task details and determines that it is highly important.

[1175] Server: Member A is available, so the task is assigned to Member A.

[1176] Terminal: "Create a report" is added to member A's task list.

[1177] Resource management assistance

[1178] Users: Enter the required resource information at the start of the project.

[1179] Terminal: Sends the entered information to the server.

[1180] Server: Automatically calculates required resources and generates resource lists and budgets.

[1181] Terminal: Display resource list and budget to project manager.

[1182] Examples:

[1183] User: Starts a "New Project" and enters the required resources.

[1184] Server: Generates a budget and a list of materials needed based on resource requirements.

[1185] Terminal: Display resource list and budget on the project manager's screen.

[1186] Real-time communication support

[1187] User: Opens the messaging screen and enters a message.

[1188] Terminal: Sends a message to the server.

[1189] Server: Receives messages and distributes them to designated members in real time.

[1190] Terminal: Display received messages in the chat window.

[1191] Examples:

[1192] User: In the "Question" chat, type "When is this task due?"

[1193] Terminal: Sends a message to the server.

[1194] Server: Forwards the message to the target member.

[1195] Terminal: Display a message in the target member's chat window.

[1196] Specific examples of using the emotion engine

[1197] Examples:

[1198] User: In the messaging screen, types "This task is very stressful."

[1199] Device: An emotion engine analyzes the user's messages and detects increased stress.

[1200] Server: Based on the analysis results from the emotion engine, adjusts the user's task allocation. It also shares this information with other members to encourage their support.

[1201] Terminal: The adjusted task list is displayed to the user in real time.

[1202] This AI task management system incorporates an emotion engine to reflect the user's psychological state and achieve more effective task management. The server utilizes the AI ​​engine and emotion engine to manage tasks, and the device provides real-time information to the user. Through this specific operation, the system aims to improve work efficiency and productivity.

[1203] The processing flow will be explained below.

[1204] Specific usage flow of the emotion engine

[1205] Recognizing User Emotions and Adjusting Task Allocation

[1206] Step 1:

[1207] User: In the messaging screen, types "This task is very stressful."

[1208] Step 2:

[1209] Terminal: Formats message data in JSON format to send messages about emotions entered by the user to the emotion engine.

[1210] Step 3:

[1211] Terminal: Sends formatted JSON data to the server.

[1212] Step 4:

[1213] Server: Analyzes the received message data and sends it to the emotion engine.

[1214] Step 5:

[1215] Server: The emotion engine analyzes the message content and determines the user's emotional state as "high stress."

[1216] Step 6:

[1217] Server: Based on the analysis results from the emotion engine, instructs the AI ​​engine to review task allocation.

[1218] Step 7:

[1219] Server: The AI ​​engine reallocates current tasks to other members to reduce the user's workload.

[1220] Step 8:

[1221] Terminal: Receives new task lists from the server and displays them in real time on the user's dashboard.

[1222] Emotional evaluation upon task completion and member workload adjustment

[1223] Step 1:

[1224] User: Clicks the Complete button to report "Task B completed."

[1225] Step 2:

[1226] Terminal: Input the user's emotional state "feeling accomplished" along with the task completion report.

[1227] Step 3:

[1228] Terminal: Sends this information to the server in JSON format.

[1229] Step 4:

[1230] Server: Analyzes the received data and records task completion reports in a database.

[1231] Step 5:

[1232] Server: The emotion engine recognizes the user's emotional state as "feeling accomplished."

[1233] Step 6:

[1234] Server: Based on the evaluation from the emotion engine, the AI ​​engine optimizes future task allocation to the user.

[1235] Step 7:

[1236] Server: For example, if a user shows a high sense of accomplishment, it decides to prioritize the next complex task.

[1237] Step 8:

[1238] Terminal: The adjusted task list is displayed in real time on the user's dashboard.

[1239] Emotion-based adaptive communication

[1240] Step 1:

[1241] User: Type "I need team help" in the chat window.

[1242] Step 2:

[1243] Terminal: The emotion engine analyzes the message content and sends data in JSON format to the server to determine the emotional state.

[1244] Step 3:

[1245] Server: The emotion engine recognizes the user's emotional state as "cooperation needed."

[1246] Step 4:

[1247] Server: The emotion engine notifies the AI ​​engine, instructing it to reevaluate the task and ask team members for help.

[1248] Step 5:

[1249] Server: The AI ​​engine reevaluates the task and allocates the necessary resources.

[1250] Step 6:

[1251] Server: Based on the analysis results of the emotion engine, it sends messages requesting cooperation to other team members.

[1252] Step 7:

[1253] Terminal: A real-time message requesting cooperation will appear in the chat window of your team members.

[1254] This process flow enables the AI ​​task management system to adaptively allocate tasks, adjust priorities, and manage team communication while taking into account the user's emotional state. The server utilizes the AI ​​engine and emotion engine to perform efficient task management, while the device provides information to the user in real time, thereby improving work efficiency and productivity.

[1255] Example 2

[1256] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1257] While conventional task management systems can set task progress and priorities, they struggle to provide flexible task management that reflects the user's emotional state. Furthermore, support for real-time communication between users is limited, leaving challenges in improving work efficiency and productivity. Furthermore, resource management and appropriate task allocation are not adequately optimized, which can affect the productivity of the entire team.

[1258] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1259] In this invention, the server includes means for receiving detailed task information from a user and storing the information in a database, means for periodically obtaining the progress status of the task from the database, calculating the progress rate, and generating visualization data, and means for displaying the generated visualization data on the user's terminal in real time. This allows the detailed task information to be managed appropriately, and the progress status of the task to be grasped in real time.

[1260] The server further includes a means for analyzing the importance and urgency of tasks and prioritizing them based on each member's skill set and workload, a means for assigning tasks to appropriate members and notifying users of the assigned tasks, a means for automatically calculating project resource information and generating a resource list and budget, a means for sharing messages and files between members in real time, and a means for receiving, analyzing, and reflecting users' emotional information in task management. This optimizes task prioritization and assignment to members, enabling resource management and real-time communication. It also enables flexible task management that takes users' emotional states into account.

[1261] "Detailed task information" refers to specific information about a task, such as the task name, description, deadline, and priority.

[1262] "User" refers to an individual or organization that uses the task management system to create, manage, and check the progress of tasks.

[1263] "Database" refers to a system for structuring and storing and managing data such as task information, progress status, and resource information.

[1264] "Progress rate" refers to an indicator that shows how much of a task has been completed as a percentage.

[1265] "Visualized data" refers to data that displays progress rates, task progress, etc. in a visual format such as graphs or charts.

[1266] "Member" refers to an individual user or team member assigned to perform a task.

[1267] A "skill set" refers to the collection of skills, knowledge, and experience that a member possesses.

[1268] "Load status" refers to the status that indicates the current workload of a member.

[1269] "Resource information" refers to information such as materials, personnel, equipment, and budget required to carry out a project.

[1270] "Resource list" refers to an itemized list of resources required to carry out a project.

[1271] "Budget" refers to the total amount of costs and expenses planned for the operation of a project.

[1272] "Emotional information" refers to data about a user's emotional state (e.g., stress, satisfaction, dissatisfaction, etc.).

[1273] "Artificial intelligence engine" refers to an artificial intelligence system for analyzing the importance and urgency of tasks, setting priorities, and assigning tasks to members.

[1274] "Task management" refers to the act of managing the entire life cycle of a task, including creating, assigning, checking progress, and reporting completion.

[1275] This invention combines an AI task management system, which aims to efficiently manage projects and work and improve productivity, with an emotion engine that recognizes user emotions, enabling more advanced task management. This system is composed of a server and a client (user device).

[1276] The user can access the interface through a browser or a mobile app to manage tasks, check progress, and communicate. Specific embodiments of the present invention will be described below.

[1277] System configuration

[1278] The system consists of the following main functional modules:

[1279] 1. Task Entry Module: Used by the user to enter a new task.

[1280] 2. Database management module: A database for storing and managing task information, progress status, resource information, etc.

[1281] 3. Progress management module: Manages the progress of tasks and generates visualization data.

[1282] 4. AI engine: Analyzes the importance and urgency of the task, as well as the skill sets and workload of members.

[1283] 5. Task allocation module: Based on the analysis results of the AI ​​engine, tasks are prioritized and assigned to the appropriate members.

[1284] 6. Resource Management Module: Automatically calculates the resources required for a project and generates a resource list and budget.

[1285] 7. Communication module: Supports messaging and file sharing among members.

[1286] 8. Emotion Engine: Recognizes user emotions and reflects them in the task management process.

[1287] Recognizing and reflecting user emotions

[1288] The emotion engine analyzes the user's emotional state and adjusts task allocation and priorities based on the results. For example, if a user is feeling stressed, it will adjust the task allocation to reduce the user's workload.

[1289] Emotion recognition processing flow

[1290] User: Providing emotional input feedback when interacting with messaging and task management screens, or extracted from sensor data such as facial recognition and voice analysis.

[1291] Terminal: Analyzes the user's emotional information and sends it to the server in JSON format.

[1292] Server: Analyzes the received emotion data and adjusts task priorities and assignments based on the emotion engine.

[1293] Creating and entering a new task

[1294] User: Opens a browser or mobile app and accesses the task management screen.

[1295] User: Enter the details of the new task, specifying the task name, detailed description, due date, priority, etc.

[1296] Terminal: Sends the task information entered by the user to the server in JSON format.

[1297] Server: Parse the received JSON data and store it in the database.

[1298] Tracking task progress

[1299] Server: Periodically retrieves task progress data from the database, calculates the progress rate, and generates visualization data.

[1300] On the device: Retrieves progress data from the server and displays progress bars and graphs on the user's dashboard.

[1301] Examples:

[1302] User: Clicks the "Update Task A progress" button.

[1303] Terminal: Sends a progress update request to the server.

[1304] Server: Updates the progress field in the database and distributes the latest progress to other users.

[1305] Terminal: Shows an updated progress bar.

[1306] Task assignment and prioritization

[1307] Server: When a new task is added, the AI ​​engine analyzes the task details.

[1308] Server: Sets the priority of tasks taking into account the importance, urgency, skill sets of members, and workload status of the task.

[1309] Server: Assigns the task to the appropriate member.

[1310] On your device: The new task will appear in the assigned member's task list and a notification will be sent.

[1311] Examples:

[1312] User: Add a new task "Create Report".

[1313] Server: The AI ​​engine analyzes the task details and determines that it is highly important.

[1314] Server: Member A is available, so the task is assigned to Member A.

[1315] Terminal: "Create a report" is added to member A's task list.

[1316] Resource management assistance

[1317] Users: Enter the required resource information at the start of the project.

[1318] Terminal: Sends the entered information to the server.

[1319] Server: Automatically calculates required resources and generates resource lists and budgets.

[1320] Terminal: Display resource list and budget to project manager.

[1321] Examples:

[1322] User: Starts a "New Project" and enters the required resources.

[1323] Server: Generates a budget and a list of materials needed based on resource requirements.

[1324] Terminal: Display resource list and budget on the project manager's screen.

[1325] Real-time communication support

[1326] User: Opens the messaging screen and types a message.

[1327] Terminal: Sends a message to the server.

[1328] Server: Receives messages and distributes them to designated members in real time.

[1329] Terminal: Display received messages in the chat window.

[1330] Examples:

[1331] User: In the "Question" chat, type "When is this task due?"

[1332] Terminal: Sends a message to the server.

[1333] Server: Forwards the message to the target member.

[1334] Terminal: Display a message in the target member's chat window.

[1335] Specific examples of using the emotion engine

[1336] Examples:

[1337] User: In the messaging screen, types "This task is very stressful."

[1338] Device: An emotion engine analyzes the user's messages and detects increased stress.

[1339] Server: Based on the analysis results from the emotion engine, adjusts the user's task allocation. It also shares this information with other members to encourage their support.

[1340] Terminal: The adjusted task list is displayed to the user in real time.

[1341] This AI task management system incorporates an emotion engine to reflect the user's psychological state and achieve more effective task management. The server utilizes the AI ​​engine and emotion engine to manage tasks, and the device provides real-time information to the user. Through this specific operation, the system aims to improve work efficiency and productivity.

[1342] Prompt Sentence Examples

[1343] "What operations are required to track task progress within the system?"

[1344] "How does the Emotion Engine work?"

[1345] How do I add a new task?

[1346] The above is a specific description of the embodiment of the present invention.

[1347] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1348] Step 1:

[1349] A user opens a browser or mobile app and accesses the task management screen.

[1350] Specific operation: The user opens the device's browser, enters the specified URL, and logs in to the task management system. If the user uses the mobile app, they launch the app and access the login screen.

[1351] Input: User authentication information (username, password)

[1352] Output: The user is authenticated successfully and the task management screen is displayed.

[1353] Step 2:

[1354] The user enters the details of the new task (task name, detailed description, due date, priority, etc.).

[1355] Specific operation: The user enters the task name "Create monthly report", the description "Compile monthly reports", the deadline "2023-10-31", and the priority "High".

[1356] Input: Task details (task name, detailed description, deadline, priority)

[1357] Output: The entered task information is reflected in the task input form.

[1358] Step 3:

[1359] The device sends the task information entered by the user to the server in JSON format.

[1360] Specific operation: When the user clicks the "Send" button, the device converts the task information into task_data.json format and sends an HTTP request to the server.

[1361] Input: JSON data of task information

[1362] Output: The server receives the JSON data.

[1363] Step 4:

[1364] The server parses the received JSON data and stores it in the database.

[1365] Specific behavior: The server parses the received JSON data and saves the task name, details, due date, and priority to the database.

[1366] Input: JSON data of task information

[1367] Output: Task information is stored in the database.

[1368] Step 5:

[1369] The server periodically retrieves task progress status data from the database, calculates the progress rate, and generates visualization data.

[1370] What it does: The server queries the database every day to get the progress, calculates the progress rate, and generates visualization data in the form of bar graphs and charts.

[1371] Input: Task progress data retrieved from the database

[1372] Output: Generated visualization data (progress rate, etc.)

[1373] Step 6:

[1374] The device retrieves progress data from the server and displays progress bars and graphs on the user's dashboard.

[1375] Specific operation: When a user opens the dashboard screen, the device sends a request to the server, receives the latest progress data, and displays it as a progress bar and graph.

[1376] Input: Visualization data from the server

[1377] Output: Progress bars and graphs displayed on a dashboard

[1378] Step 7:

[1379] The server analyzes the importance and urgency of the task, the skill sets and workload of the members, sets the priority of the task, and assigns the task to an appropriate member.

[1380] How it works: When a new task is added, the AI ​​engine analyzes the task details, evaluates the importance and urgency of the task, sets a priority taking into account each member's skill set and current workload, and assigns it to the appropriate member.

[1381] Input: New task information, member skill sets and workload status

[1382] Output: A new task is added to the assigned member's task list

[1383] Step 8:

[1384] The new task will be displayed in the task list of the member to whom the device is assigned and a notification will be sent.

[1385] Specific operation: After the task assignment is determined, the terminal adds "Create a report" to member A's task list and notifies member A that a new task has been assigned via the notification function.

[1386] Input: Task assignment information

[1387] Output: New tasks and notifications added to members' task lists

[1388] Step 9:

[1389] Users enter the required resource information at the start of a project.

[1390] Specific operation: A user starts a "new project" and inputs resource information such as required personnel, equipment, and budget.

[1391] Input: Project resource information

[1392] Output: The input resource information is displayed.

[1393] Step 10:

[1394] The terminal transmits the input information to the server.

[1395] Specific operation: After the user enters the resource information, he clicks the "Send" button, and the terminal sends the information to the server in JSON format.

[1396] Input: JSON data of resource information

[1397] Output: The server receives the data

[1398] Step 11:

[1399] The server automatically calculates the required resources and generates a resource list and budget.

[1400] Specific operation: Based on the resource information received by the server, the server calculates the resources required to carry out the project and generates a resource list and budget.

[1401] Input: Resource information

[1402] Output: Generated resource list and budget

[1403] Step 12:

[1404] The terminal displays the resource list and budget to the project manager.

[1405] Specific operation: The resource list and budget data generated by the server are sent to the terminal and displayed on the project manager's screen.

[1406] Input: Resource list and budget data

[1407] Output: Resource list and budget displayed on the project manager's screen

[1408] Step 13:

[1409] The user opens the messaging screen and types a message.

[1410] What happens: A user uses the messaging feature to type a question: "When is this task due?"

[1411] Input: Message

[1412] Output: The displayed input message

[1413] Step 14:

[1414] The device sends a message to the server.

[1415] Specific operation: The user clicks the "Send" button, and the device sends the message to the server.

[1416] Input: Message data

[1417] Output: The server receives the message

[1418] Step 15:

[1419] The server receives the message and distributes it to the specified members in real time.

[1420] Specific operation: The server analyzes the received message, identifies the destination member, and forwards the message to that member.

[1421] Input: Incoming message

[1422] Output: Message delivery to specified members

[1423] Step 16:

[1424] Displays messages received by the device in the chat window.

[1425] Specific operation: The specified member's device will receive the message and display it in the chat window.

[1426] Input: Message data from the server

[1427] Output: Message displayed in the chat window

[1428] Step 17:

[1429] The user provides emotional input feedback or sensor data such as facial recognition or voice analysis.

[1430] Specific behavior: The user types "This task is very stressful" or provides emotional data using the smartphone's camera or microphone.

[1431] Input: Emotion data

[1432] Output: Emotional feedback displayed on the device

[1433] Step 18:

[1434] The device analyzes the user's emotional information and sends it to the server in JSON format.

[1435] Specific operation: The device analyzes the user's emotional feedback, converts the type and intensity of the emotion into JSON format, and sends it to the server.

[1436] Input: JSON data of emotion information

[1437] Output: The server receives the emotion data.

[1438] Step 19:

[1439] The server analyzes the received emotion data and adjusts task priorities and allocations based on the emotion engine.

[1440] Specific operation: The server uses an emotion engine to analyze emotional data, and if it determines that the user's stress level is high, it adjusts task allocation and priorities.

[1441] Input: Emotion data

[1442] Output: Adjusted task assignments and priorities

[1443] (Application example 2)

[1444] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1445] Conventional task management systems assign and prioritize tasks without considering the user's emotional state, which increases the user's psychological burden and makes efficient task management difficult. Furthermore, in security services, there was a lack of a mechanism for grasping the emotional state of security guards and security staff in real time and dynamically adjusting tasks based on that information, making it difficult to respond appropriately in emergencies. The present invention addresses these issues.

[1446] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1447] In this invention, the server includes means for receiving detailed task information from a user and storing it in a database, means for periodically obtaining task progress from the database, calculating the progress rate, and generating visualization data, means for displaying the generated visualization data on the user's terminal in real time, means for analyzing the importance and urgency of tasks and setting task priorities taking into account the skill set and workload of each member, means for assigning tasks to appropriate members and notifying the user's terminal of the assigned tasks, means for automatically calculating project resource information and generating a resource list and budget, means for sharing messages and files among members in real time, and means for recognizing the emotional state of security staff, transmitting that data to the server, and adjusting task priorities and assignments based on an emotion engine. This enables efficient task management and appropriate security response that reflects the user's emotional state.

[1448] "Detailed task information" is specific information such as the name, description, deadline, and priority of a task input by the user.

[1449] A "database" is a system for structuring and storing and managing task information, progress status, resource information, and the like.

[1450] "Visualization data" refers to data such as graphs and charts that visually represent task progress and other information.

[1451] "Task importance" is an indicator of how important a particular task is to the project or business as a whole.

[1452] "Urgency" is a measure of how quickly a particular task should be addressed.

[1453] "Skill set" is a collective term for the techniques, knowledge, and experience that each member possesses.

[1454] "Load status" is information that indicates the amount of tasks currently assigned to each member and the degree to which the goal must be achieved.

[1455] "Resource information" refers to detailed information about personnel, equipment, materials, and budget required to carry out a project.

[1456] The "emotion engine" is a software module that recognizes the user's emotional state and reflects the analysis results in the task management process.

[1457] "Security staff" refers to security guards and guards who work to ensure the safety of facilities, events, etc.

[1458] "Task priority" refers to the order of task execution that is set based on the importance, urgency, skill set, and load status of the task.

[1459] The present invention is a system that monitors the emotional state of security staff in real time and dynamically adjusts task allocation and priorities based on the monitoring results. Specific embodiments will be described below.

[1460] System configuration

[1461] The system consists of a series of software and hardware components, including an emotion recognition engine, a task management engine, a database, a user interface, and a communication module.

[1462] Hardware and Software Details

[1463] Smart glasses: equipped with cameras to provide a video feed for monitoring the emotional state of security staff.

[1464] Emotion recognition engine: A software module used to recognize user emotions from video in real time (e.g., EmotionRecognizer).

[1465] AI task management engine: Analyzes the importance and urgency of tasks and prioritizes them based on resources and sentiment information.

[1466] Database: A system that structures and stores task information, progress, emotional data, etc.

[1467] Communication module: A module for transmitting data in real time between a user terminal and a server (e.g., the Requests library).

[1468] User emotion recognition and data transmission

[1469] User: Wears smart glasses, the camera captures the video feed.

[1470] Terminal: Analyzes the user's emotional state from the camera feed of the smart glasses using an emotion recognition engine and sends the results to the server.

[1471] Server: Analyzes the received emotional data and adjusts task allocation and priorities using an AI task management engine.

[1472] Task assignment and prioritization

[1473] Server: The AI ​​engine and emotion engine work together to prioritize tasks, taking into account the importance and urgency of the task and the emotional state of the security staff.

[1474] Server: Assign tasks to the appropriate security staff based on set priorities. Assign important and urgent tasks to staff with stable emotional states.

[1475] Devices: Assigned tasks are notified to staff members' smartphones or other devices.

[1476] Specific examples

[1477] User: Security staff wear smart glasses and patrol the area.

[1478] Device: The smart glasses capture video and the emotion recognition engine analyzes emotions in real time. For example, if it detects "anxiety" or "tension," it sends the data to the server.

[1479] Server: Based on the received emotional data, it assigns high-priority tasks to other emotionally stable staff members.

[1480] Device: The task is notified to the assigned staff member's smartphone.

[1481] This system will enable effective task management that takes into account the emotional state of security staff, enabling appropriate responses in emergencies. It will also promote real-time communication between staff, improving work efficiency and safety.

[1482] Prompt Sentence Examples

[1483] Sample prompt: "I want to build a system that uses facial recognition to analyze emotions in real time and adjust security task assignments based on that information. Specifically, I would use smart glasses to capture camera footage and EmotionRecognizer to recognize emotions, so that stressed guards are not assigned urgent tasks and instead are assigned to other guards."

[1484] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1485] Step 1:

[1486] A user puts on the smart glasses and starts the camera feed.

[1487] Input: Real-time video data from smart glasses.

[1488] Output: A real-time video feed is generated, which serves as input to the emotion recognition engine.

[1489] How it works: Security staff wear smart glasses and patrol the surveillance area, and the camera in the smart glasses captures images of the surrounding area.

[1490] Step 2:

[1491] The device uses an emotion recognition engine to analyze the user's emotions in real time from the camera feed of the smart glasses.

[1492] Input: Real-time video feed.

[1493] Output: Data representing the user's emotional state (e.g., stressed, nervous, calm, etc.).

[1494] Specific operation: The device uses EmotionRecognizer to analyze video data and recognize emotions from the user's facial expressions and slight body movements. For example, it identifies emotions such as "stress" and "anxiety."

[1495] Step 3:

[1496] The device sends the results of the emotion recognition engine to the server in JSON format.

[1497] Input: Data representing the user's emotional state.

[1498] Output: Emotion data in JSON format is sent to the server.

[1499] Specific operation: The device converts the analyzed data into JSON format and sends it to the server as an HTTP request. This data also includes a timestamp and user ID.

[1500] Step 4:

[1501] The server analyzes the received emotional data and calls an AI task management engine to respond appropriately.

[1502] Input: Emotion data in JSON format.

[1503] Output: Analysis results of task priorities and allocation settings.

[1504] Specific operation: The server analyzes the received emotional data and passes the results to the AI ​​task management engine, which then reevaluates task priorities and allocations according to the emotional state.

[1505] Step 5:

[1506] The server assigns tasks to appropriate security staff based on the analysis results of the AI ​​task management engine.

[1507] Input: Analysis results (task priorities and assignments).

[1508] Output: Task assignment notification.

[1509] Specific operation: Based on the analysis results, the server decides to avoid urgent tasks for stressed staff and assign tasks to other emotionally stable staff.

[1510] Step 6:

[1511] The server notifies the user's terminal of the assigned task.

[1512] Input: Task assignment information.

[1513] Output: Task notification sent to user device.

[1514] Specific operation: The server sends the allocation information to the corresponding security staff terminal in real time, and the staff receives the notification and confirms their next action.

[1515] Step 7:

[1516] The user performs the assigned task and reports progress to the terminal.

[1517] Input: Task progress.

[1518] Output: Progress data is sent to the server.

[1519] Specific operation: Security staff carry out assigned tasks and report their progress and completion status via their terminals. The reported data is sent to the server and shared throughout the system.

[1520] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1521] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1522] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1523] [Third embodiment]

[1524] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1525] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1526] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1527] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1528] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1529] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1530] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1531] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1532] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1533] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1534] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1535] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1536] This invention is an AI task management system that aims to efficiently manage projects and work and improve productivity. The system consists of a server and a client (user device). Users can access the interface via a browser or mobile app to manage tasks, check progress, and communicate. The specific operation of the system is described in detail below.

[1537] System configuration

[1538] The system consists of the following main functional modules:

[1539] 1. Task Entry Module: Used by the user to enter a new task.

[1540] 2. Database management module: A database for storing and managing task information, progress status, resource information, etc.

[1541] 3. Progress management module: Manages the progress of tasks and generates visualization data.

[1542] 4. AI engine: Analyzes the importance and urgency of the task, as well as the skill sets and workload of members.

[1543] 5. Task allocation module: Based on the analysis results of the AI ​​engine, tasks are prioritized and assigned to the appropriate members.

[1544] 6. Resource Management Module: Automatically calculates the resources required for a project and generates a resource list and budget.

[1545] 7. Communication module: Supports messaging and file sharing among members.

[1546] Creating and entering a new task

[1547] User: Opens a browser or mobile app and accesses the task management screen.

[1548] User: Enter the details of the new task, specifying the task name, detailed description, due date, priority, etc.

[1549] Terminal: Sends the task information entered by the user to the server in JSON format.

[1550] Server: Parse the received JSON data and store it in the database.

[1551] Tracking task progress

[1552] Server: Periodically retrieves task progress data from the database, calculates the progress rate, and generates visualization data.

[1553] On the device: Retrieves progress data from the server and displays progress bars and graphs on the user's dashboard.

[1554] Examples:

[1555] User: Clicks the "Update Task A progress" button.

[1556] Terminal: Sends a progress update request to the server.

[1557] Server: Updates the progress field in the database and distributes the latest progress to other users.

[1558] Terminal: Shows an updated progress bar.

[1559] Task assignment and prioritization

[1560] Server: When a new task is added, the AI ​​engine analyzes the task details.

[1561] Server: Sets the priority of tasks taking into account the importance, urgency, skill sets of members, and workload status of the task.

[1562] Server: Assigns the task to the appropriate member.

[1563] On your device: The new task will appear in the assigned member's task list and a notification will be sent.

[1564] Examples:

[1565] User: Add a new task "Create Report".

[1566] Server: The AI ​​engine analyzes the task details and determines that it is highly important.

[1567] Server: Member A is available, so the task is assigned to Member A.

[1568] Terminal: "Create a report" is added to member A's task list.

[1569] Resource management assistance

[1570] Users: Enter the required resource information at the start of the project.

[1571] Terminal: Sends the entered information to the server.

[1572] Server: Automatically calculates required resources and generates resource lists and budgets.

[1573] Terminal: Display resource list and budget to project manager.

[1574] Examples:

[1575] User: Starts a "New Project" and enters the required resources.

[1576] Server: Generates a budget and a list of materials needed based on resource requirements.

[1577] Terminal: Display resource list and budget on the project manager's screen.

[1578] Real-time communication support

[1579] User: Opens the messaging screen and enters a message.

[1580] Terminal: Sends a message to the server.

[1581] Server: Receives messages and distributes them to designated members in real time.

[1582] Terminal: Display received messages in the chat window.

[1583] Examples:

[1584] User: In the "Question" chat, type "When is this task due?"

[1585] Terminal: Sends a message to the server.

[1586] Server: Forwards the message to the target member.

[1587] Terminal: Display a message in the target member's chat window.

[1588] summary

[1589] This AI task management system integrates progress management, task allocation and prioritization, resource management, and real-time communication support. The server utilizes an AI engine to manage tasks, and the device provides real-time information to the user. Through these specific operations, the system improves work efficiency and productivity.

[1590] The processing flow will be explained below.

[1591] Creating and entering a new task

[1592] Step 1:

[1593] User: Opens a browser or mobile app and accesses the task management screen.

[1594] Step 2:

[1595] User: Enter the details of the new task, specifying the task name, detailed description, due date, priority, etc.

[1596] Step 3:

[1597] Terminal: Sends the task information entered by the user to the server in JSON format.

[1598] Step 4:

[1599] Server: Parse the received JSON data and store it in the database.

[1600] Tracking task progress

[1601] Step 1:

[1602] Server: Periodically retrieves task progress data from the database.

[1603] Step 2:

[1604] Server: Based on the progress status data, calculates the progress rate of the task and generates visualization data.

[1605] Step 3:

[1606] On the device: Retrieves progress data from the server and displays progress bars and graphs on the user's dashboard.

[1607] Examples:

[1608] Step 1:

[1609] User: Clicks the "Update Task A progress" button.

[1610] Step 2:

[1611] Terminal: Sends a progress update request to the server.

[1612] Step 3:

[1613] Server: Updates the progress field in the database and distributes the latest progress to other users.

[1614] Step 4:

[1615] Terminal: Shows an updated progress bar.

[1616] Task assignment and prioritization

[1617] Step 1:

[1618] Server: When a new task is added, the AI ​​engine analyzes the task details.

[1619] Step 2:

[1620] Server: Sets the priority of tasks taking into account the importance, urgency, skill sets of members, and workload status of the task.

[1621] Step 3:

[1622] Server: Assigns the task to the appropriate member.

[1623] Step 4:

[1624] On your device: The new task will appear in the assigned member's task list and a notification will be sent.

[1625] Examples:

[1626] Step 1:

[1627] User: Add a new task "Create Report".

[1628] Step 2:

[1629] Server: The AI ​​engine analyzes the task details and determines that it is highly important.

[1630] Step 3:

[1631] Server: Member A is available, so the task is assigned to Member A.

[1632] Step 4:

[1633] Terminal: "Create a report" is added to member A's task list.

[1634] Resource management assistance

[1635] Step 1:

[1636] Users: Enter the required resource information at the start of the project.

[1637] Step 2:

[1638] Terminal: Sends the entered information to the server.

[1639] Step 3:

[1640] Server: Automatically calculates required resources and generates resource lists and budgets.

[1641] Step 4:

[1642] Terminal: Display resource list and budget to project manager.

[1643] Examples:

[1644] Step 1:

[1645] User: Starts a "New Project" and enters the required resources.

[1646] Step 2:

[1647] Server: Generates a budget and a list of materials needed based on resource requirements.

[1648] Step 3:

[1649] Terminal: Display resource list and budget on the project manager's screen.

[1650] Real-time communication support

[1651] Step 1:

[1652] User: Opens the messaging screen and enters a message.

[1653] Step 2:

[1654] Terminal: Sends a message to the server.

[1655] Step 3:

[1656] Server: Receives messages and distributes them to designated members in real time.

[1657] Step 4:

[1658] Terminal: Display received messages in the chat window.

[1659] Examples:

[1660] Step 1:

[1661] User: In the "Question" chat, type "When is this task due?"

[1662] Step 2:

[1663] Terminal: Sends a message to the server.

[1664] Step 3:

[1665] Server: Forwards the message to the target member.

[1666] Step 4:

[1667] Terminal: Display a message in the target member's chat window.

[1668] Example 1

[1669] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1670] Modern project management requires consistent and efficient operation, from task entry to progress visualization, task prioritization and assignment, resource management, and communication between team members. However, few systems offer these functions in an integrated and automated manner, and manual management or the use of multiple tools is often required. This results in problems such as duplicated work and reduced efficiency. Furthermore, optimal task assignment based on task importance and team member skill sets requires advanced analytical capabilities, which traditional systems often lack. To address these challenges, there is a need for systems that optimize task management by automating and streamlining the entire business process and incorporating generative AI models.

[1671] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1672] In this invention, the server includes means for receiving detailed task information from a user and storing the information in a database, means for periodically obtaining the task progress status from the database, calculating the progress rate, and generating visualization data, and means for displaying the generated visualization data on the user's terminal in real time, thereby enabling detailed task management and visualization and real-time display of the progress status.

[1673] The server also includes: a means for analyzing the importance and urgency of tasks and prioritizing the tasks while taking into account the technical requirements and workload of each member; a means for assigning tasks to appropriate members and notifying the users of the assigned tasks on their terminals; a means for automatically calculating project resource information and generating a resource list and budget; a means for sharing messages and files between members in real time; a means for outputting task analysis results using a generative AI model; and a means for automatically generating task details using prompt text as input. This enables task prioritization and allocation optimization, automated resource management, and real-time communication.

[1674] "Detailed task information" refers to information such as the content, deadline, priority, and explanation of specific tasks that a user should manage in a project or business.

[1675] A "database" is a storage medium and its management system for systematically storing and managing data required within the system, such as detailed task information, progress status, member information, and resource information.

[1676] "Completion" refers to how much of a particular task or project is complete, usually expressed as a percentage.

[1677] "Visualized data" is data that is presented in a visual form, such as a graph or chart, so that users can easily understand the data intuitively.

[1678] A "user terminal" is an electronic device such as a computer, tablet, or smartphone that a user uses to access and operate the system.

[1679] "Task importance" is an index that indicates how important a particular task is compared to other tasks.

[1680] "Urgency" is a measure of how quickly a particular task should be addressed.

[1681] "Technical requirements" are requirements such as specific skills, knowledge, and experience required to perform a task.

[1682] "Load status" refers to the status that indicates how much work a particular member or resource is currently doing.

[1683] "Priority" is the order that determines which task or project should be done first among multiple tasks or projects.

[1684] "Resource information" refers to information such as personnel, equipment, and budget required to carry out a project or task.

[1685] A "generative AI model" is an algorithm and its implementation that uses artificial intelligence to generate analytical results and predictions from input data.

[1686] A "prompt sentence" is text data given as input to a generative AI model, and contains specific instructions for analysis and generation.

[1687] "Analysis results" are decision information such as task allocation and priority setting that the generative AI model outputs based on prompt statements and other input data.

[1688] This invention is an AI task management system aimed at efficient management of projects and work and improving productivity. The system consists of a server and a client (user device), and users can access the interface via a browser or mobile app to manage tasks, check progress, and communicate. The specific operation of the system is described in detail below.

[1689] System configuration

[1690] The system consists of the following main functional modules:

[1691] 1. Task Entry Module: Used by the user to enter a new task.

[1692] 2. Database Management Module: A database for storing and managing task information, progress, and resource information.

[1693] 3. Progress management module: Manages the progress of tasks and generates visualization data.

[1694] 4. Generative AI model: Analyzes the importance and urgency of the task, as well as the technical requirements and workload of members.

[1695] 5. Task assignment module: Based on the analysis results of the generative AI model, tasks are prioritized and assigned to appropriate members.

[1696] 6. Resource Management Module: Automatically calculates the resources required for a project and generates a resource list and budget.

[1697] 7. Communication module: Supports messaging and file sharing among members.

[1698] Specific operation of the system

[1699] A user opens a browser or mobile app and accesses the task management screen. When adding a task, they enter details such as the task name, detailed description, due date, and priority into a form. This sends JSON format data from the device to the server. The server parses the received data and stores it in a database.

[1700] Specific examples

[1701] For example, if a user enters a task name of "Report Creation," a deadline of "2023-12-31," and a priority of "High," the device sends this information in JSON format to the server, which receives the data and stores it in a database.

[1702] The server periodically retrieves task progress data from the database, calculates the progress rate, and generates visualization data, which is displayed in real time on the user's dashboard.

[1703] Specific examples

[1704] When the user clicks the progress update button, the device sends a progress update request to the server. The server updates the database with the new progress and distributes this latest data to other users. The device then displays the updated progress bar on the user's dashboard.

[1705] When a new task is added, the server's generative AI model analyzes the task details and prioritizes it, taking into account the task's importance, urgency, technical requirements of members, and workload.

[1706] Specific examples

[1707] For example, a new task "Write a report" is added, and the generative AI model analyzes the task and determines that it is of high importance. Since member A is currently free, the task is assigned to member A. The device sends a notification to member A and adds the task to the task list.

[1708] The user inputs the necessary resource information at the start of a project. The terminal sends the information to the server, which then automatically calculates and generates the resource list and budget. This information is then displayed on the project manager's terminal.

[1709] Specific examples

[1710] When a user starts a "new project" and enters the required resources as "PC, software license, and budget of 300,000 yen," the server automatically calculates the budget and materials list based on that information and displays the results to the project manager on the terminal.

[1711] With the messaging function, users can enter and send messages on the messaging screen. The device sends the message to the server, which then distributes it to other members in real time. Received messages are displayed in the chat window on the device.

[1712] Specific examples

[1713] When a user types "When is the deadline for this task?" into the chat window and sends it, the device sends the message to the server, which then forwards the message to the target member, who then sees the message in their chat window.

[1714] A prompt is a text instruction given as input to a generative AI model to analyze and automatically generate a task. For example, a prompt might be, "Please write an important report. The deadline is December 31, 2023."

[1715] In this way, the AI ​​task management system integrates progress management, task allocation and priority setting, resource management, and real-time communication support. The server uses generated AI models to manage tasks, and the terminal provides information to the user in real time, thereby improving work efficiency and productivity.

[1716] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1717] The flow of this system's program processing

[1718] Step 1: User enters task

[1719] Input: A user opens a browser or mobile app, accesses the task management screen, and enters task details such as the task name, detailed description, due date, and priority.

[1720] Processing: The terminal converts the input information into JSON format.

[1721] Output: The generated JSON data is sent to the server.

[1722] Specific operation: The user enters the task name "Create report", the due date "2023-12-31", and the priority "High". The device sends this to the server in the format {"task_name": "Create report", "due_date": "2023-12-31", "priority": "High"}.

[1723] Step 2: Receiving and saving task data

[1724] Input: Task data in JSON format sent from the device.

[1725] Processing: The server parses the received JSON data, maps it to the appropriate fields, and stores it in the database.

[1726] Output: Task information is saved to the database.

[1727] Specific operation: The server receives the data {"task_name": "Create Report", "due_date": "2023-12-31", "priority": "High"}, parses it, and saves it to the database.

[1728] Step 3: Managing and visualizing task progress

[1729] Input: Task progress data retrieved periodically from the database.

[1730] Processing: The server calculates the progress rate and generates visualization data (graphs and bars).

[1731] Output: The generated visualization data is sent to the user's terminal and displayed in real time.

[1732] Specific operation: The server obtains the progress data and generates a progress bar when the progress of "Task A" is 50%. The device receives this information and displays it on the user's dashboard.

[1733] Step 4: Analysis and task prioritization by generative AI model

[1734] Input: New task details.

[1735] Processing: The server-generated AI model analyzes the importance and urgency of tasks, as well as the technical requirements and workload of each member. Task priorities are set based on the analysis results.

[1736] Output: Task information assigned to the appropriate members is generated.

[1737] Specific operation: The AI ​​model analyzes the "Report Creation" task and determines that it is of high importance. Since member A has a low workload, the model assigns this task to member A.

[1738] Step 5: Task assignment and notifications

[1739] Input: Task assignment information from the generative AI model.

[1740] Processing: The server assigns the task to an appropriate member and notifies the user's terminal of this information.

[1741] Output: The task list is updated on the user's device and a notification is displayed.

[1742] Specific behavior: When you assign the task "Create a report" to member A, a notification will be sent to the device and member A's task list will be updated.

[1743] Step 6: Enter and manage resource information

[1744] Input: Users enter the required resource information at the start of a project.

[1745] Processing: The terminal sends the information to the server, which automatically calculates the required resources and generates a resource list and budget.

[1746] Output: The generated resource list and budget are displayed on the project manager's terminal.

[1747] Specific operation: When a user enters "PC, software license, budget 300,000 yen," the server automatically calculates and displays the results to the project manager.

[1748] Step 7: Real-time communication

[1749] Input: The message the user types in the messaging screen.

[1750] Processing: The terminal sends a message to the server, which then forwards it to the designated members in real time.

[1751] Output: The message will be displayed in the member's chat window.

[1752] Specific operation: The user types "When is the deadline for this task?" into the chat and sends it. The device sends it to the server, which then forwards it to the target member and displays it.

[1753] Specific examples

[1754] For example, the generative AI model is used with the prompt "Please prepare an important report. The deadline is December 31, 2023." In this case, the AI ​​model analyzes the content of the prompt and automatically generates detailed information about the task. As a result, the system assigns the task to an appropriate member and displays basic information on the user's device.

[1755] (Application example 1)

[1756] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1757] Conventional factory task management and resource management often require a lot of human intervention and are inefficient. Furthermore, it is not possible to monitor the robot's operating status or progress in real time, making it difficult to respond quickly when an error occurs. This has led to problems such as reduced productivity and increased costs. The present invention aims to solve these problems and improve the efficiency of task management, progress monitoring, and resource management within a factory.

[1758] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1759] In this invention, the server includes means for receiving detailed task information from a user and storing it in an information storage device, means for periodically obtaining task progress status from the information storage device, calculating the progress rate, and generating visualization data, means for displaying the generated visualization data on a user's terminal in real time, means for analyzing the importance and urgency of tasks and prioritizing tasks taking into account the skill sets and workloads of each worker, means for assigning tasks to appropriate workers and notifying the users of the assigned tasks, means for automatically calculating resource information within the factory and generating a resource list and budget, means for sharing messages and files among workers in real time, means for monitoring the operating status of robots in real time and notifying a smartphone or head-mounted display of task progress and errors, and means for generating resource requests for the project and calculating an optimal budget. This enables efficient task management and progress monitoring within the factory and immediate response.

[1760] "Task detailed information" is specific information about a task, such as the name, content, deadline, and priority of a specific task.

[1761] A "user" is an individual or person in charge who operates the system to input tasks and monitor progress.

[1762] An "information storage device" is a database or storage system for saving and managing data such as detailed task information and progress status.

[1763] "Progress" refers to the state of how much of a particular task has been completed.

[1764] "Visualized data" is data that visually shows progress, such as numbers, graphs, and progress bars.

[1765] A "terminal" is a device used by a user, such as a smartphone, tablet, or head-mounted display.

[1766] "Task importance" is a factor that indicates the business importance of a specific task.

[1767] "Urgency" is a factor that indicates how quickly a particular task should be addressed.

[1768] A "skill set" is the collection of skills and abilities that each member possesses.

[1769] "Load status" refers to the tasks and workload currently handled by each member.

[1770] "Constituents" are people or teams to whom tasks are assigned by the system.

[1771] "Resource information" refers to information such as materials, personnel, and equipment required to carry out a project or task.

[1772] A "resource list" is a list of required resources.

[1773] A "budget" is an estimate of how much a project or task will cost.

[1774] "Message and file sharing" refers to the act of sending and receiving text messages and documents between members.

[1775] "Robot operating status" is information on whether the corresponding robot in the factory is available, in operation, or in an error state.

[1776] An "error" is a problem or failure that occurs within a robot or system.

[1777] A "project resource request" is a requirement that specifies the resources needed to complete a particular project or task.

[1778] The "optimal budget" is the most efficient cost estimate calculated based on the resource information and resource list.

[1779] The present invention is a system for efficiently managing tasks, progress, and resources within a factory. This system is realized through the cooperation of a server, terminals, and users.

[1780] System configuration

[1781] The system consists of the following main functional modules:

[1782] 1. Task input module: Used by users to input new tasks.

[1783] 2. Database management module: An information storage device for storing and managing task information, progress status, resource information, etc.

[1784] 3. Progress management module: Manages the progress of tasks and generates visualization data.

[1785] 4. AI engine: Analyzes the importance and urgency of the task, the skill sets of the members, and the workload situation.

[1786] 5. Task allocation module: Based on the analysis results of the AI ​​engine, it sets the priority of tasks and assigns them to the appropriate members.

[1787] 6. Resource management module: Automatically calculates resource information within the factory and generates resource lists and budgets.

[1788] 7. Communication module: Supports messaging and file sharing among members.

[1789] 8. Robot monitoring module: Monitors the robot's operating status in real time and notifies the operating status and errors to a smartphone or head-mounted display.

[1790] Creating and entering a new task

[1791] User: Opens a smartphone or head-mounted display and accesses the task management screen.

[1792] User: Enter the details of the new task, specifying the task name, detailed description, due date, importance, etc.

[1793] Terminal: Sends task information entered by the user to the server.

[1794] Server: Analyzes the received task information and stores it in an information storage device.

[1795] Tracking task progress

[1796] Server: Periodically obtains task progress data from the information storage device, calculates the progress rate, and generates visualization data.

[1797] Terminal: Retrieves progress data from the server and displays progress bars and graphs on the user's dashboard.

[1798] Task assignment and prioritization

[1799] Server: When a new task is added, the AI ​​engine analyzes the task details.

[1800] Server: Sets the priority of tasks taking into account the importance and urgency of the tasks, the skill sets of members, and the workload situation.

[1801] Server: Assigns tasks to appropriate members. For example, when a new task, "assembling machine parts," is added, the AI ​​engine determines that the task has high priority and assigns it to member A, whose skill set is suitable.

[1802] Terminal: Adds new tasks to assigned members' task lists and sends notifications.

[1803] Resource Management

[1804] User: Enters the required resource information at the start of the project.

[1805] Terminal: Sends the entered information to the server.

[1806] Server: Automatically calculates required resources and generates resource lists and budgets.

[1807] Terminal: Display resource lists and budgets to project managers in real time.

[1808] Real-time communication

[1809] User: Open the messaging screen and enter a message.

[1810] Terminal: Sends a message to the server.

[1811] Server: Receives messages and distributes them to designated members in real time.

[1812] Terminal: Display received messages in the chat window.

[1813] Monitoring the operating status of robots

[1814] Server: Monitors the robot's operating status in real time, checking progress and errors.

[1815] Device: A notification is displayed on a smartphone or head-mounted display to notify the user.

[1816] Examples of concrete examples and prompts

[1817] For example, a factory supervisor can input a new task, "Transport parts," on their smartphone, and the AI ​​engine analyzes it and assigns the task to the appropriate robot. The supervisor can then monitor the robot's progress in real time on their smartphone and immediately respond to any problems that arise.

[1818] Example prompt for generative AI model:

[1819] "Assign the following task to the most suitable robot. Task information: Parts transport, Deadline: 2023-12-31, Priority: High. Robot list: Robot 1, Robot 2, Robot 3. Consider the current operational status and skill set of the robots."

[1820] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1821] Step 1:

[1822] Entering task details

[1823] The user inputs details of a new task using a smartphone or head-mounted display, including the task name, detailed description, deadline, and importance.

[1824] Input: Task details entered by the user

[1825] The terminal sends the entered information to the server in JSON format.

[1826] Output: Sends detailed task information in JSON format to the server

[1827] Step 2:

[1828] Storing task information

[1829] The server analyzes the received JSON format task information and stores it in an information storage device (database).

[1830] Input: JSON formatted task details sent from the device

[1831] Data processing: Parsing JSON data

[1832] Output: Detailed task information stored in the database

[1833] Step 3:

[1834] Obtaining and managing task progress

[1835] The server periodically retrieves task progress status data from the database, calculates the progress rate, and generates visualization data.

[1836] Input: Progress data retrieved from the database

[1837] Data calculation: Calculating progress rate and generating visualization data

[1838] Output: The generated visualization data

[1839] Step 4:

[1840] Viewing progress data

[1841] The device retrieves progress data from the server and displays it on the user's dashboard in the form of a progress bar or graph.

[1842] Input: Visualization data obtained from the server

[1843] Output: Progress displayed on the device dashboard

[1844] Step 5:

[1845] Task analysis by AI engine

[1846] The server uses an AI engine to analyze the importance and urgency of tasks and prioritizes them, taking into account each member's skill set and workload.

[1847] Input: Task details, member skill sets and workload status

[1848] Data calculation: Analyzing the importance and urgency of tasks and setting priorities

[1849] Output: Prioritized task information

[1850] Step 6:

[1851] Task assignment

[1852] The server assigns prioritized tasks to appropriate members.

[1853] Input: Priority-set task information, member skills and workload information

[1854] Data calculation: Selecting the best members

[1855] Output: Task list notification to assigned members

[1856] Step 7:

[1857] Resource Management

[1858] At the start of a project, the user inputs the necessary resource information, and the terminal sends this to the server.

[1859] Input: Required resource information

[1860] The terminal transmits the input resource information to the server.

[1861] Output: Resource information sent to the server

[1862] Step 8:

[1863] Calculating and displaying resource information

[1864] The server automatically calculates the required resources, generates a resource list and budget, and displays them to the project manager.

[1865] Input: Resource information submitted by the user

[1866] Data calculation: Automatic calculation of resources and generation of resource lists and budgets

[1867] Output: Display resource list and budget on the project manager screen

[1868] Step 9:

[1869] Real-time communication

[1870] The user opens the messaging screen and enters a message, which the device then sends to the server.

[1871] Input: The message entered by the user

[1872] The terminal sends a message to the server, which then distributes it to the designated members in real time.

[1873] Output: Message displayed in the chat window of the specified member

[1874] Step 10:

[1875] Monitoring the operating status of robots

[1876] The server monitors the robot's operating status in real time, checking for progress and errors.

[1877] Input: Robot operating status data

[1878] The device notifies the smartphone or head-mounted display of progress and errors.

[1879] Output: Robot progress and error notifications displayed on the user's terminal

[1880] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1881] This invention combines an AI task management system, which aims to efficiently manage projects and work and improve productivity, with an emotion engine that recognizes user emotions, enabling more advanced task management. The system consists of a server and a client (user device). Users can access the interface via a browser or mobile app to manage tasks, check progress, and communicate. The specific operation of the system is described in detail below.

[1882] System configuration

[1883] The system consists of the following main functional modules:

[1884] 1. Task Entry Module: Used by the user to enter a new task.

[1885] 2. Database management module: A database for storing and managing task information, progress status, resource information, etc.

[1886] 3. Progress management module: Manages the progress of tasks and generates visualization data.

[1887] 4. AI engine: Analyzes the importance and urgency of the task, as well as the skill sets and workload of members.

[1888] 5. Task allocation module: Based on the analysis results of the AI ​​engine, tasks are prioritized and assigned to the appropriate members.

[1889] 6. Resource Management Module: Automatically calculates the resources required for a project and generates a resource list and budget.

[1890] 7. Communication module: Supports messaging and file sharing among members.

[1891] 8. Emotion Engine: Recognizes user emotions and reflects them in the task management process.

[1892] Recognizing and reflecting user emotions

[1893] The emotion engine analyzes the user's emotional state and adjusts task allocation and priorities based on the results. For example, if a user is feeling stressed, it will adjust the task allocation to reduce the user's workload.

[1894] Emotion recognition processing flow

[1895] User: Providing emotional input feedback when interacting with messaging and task management screens, or extracted from sensor data such as facial recognition and voice analysis.

[1896] Terminal: Analyzes the user's emotional information and sends it to the server in JSON format.

[1897] Server: Analyzes the received emotion data and adjusts task priorities and assignments based on the emotion engine.

[1898] Creating and entering a new task

[1899] User: Opens a browser or mobile app and accesses the task management screen.

[1900] User: Enter the details of the new task, specifying the task name, detailed description, due date, priority, etc.

[1901] Terminal: Sends the task information entered by the user to the server in JSON format.

[1902] Server: Parse the received JSON data and store it in the database.

[1903] Tracking task progress

[1904] Server: Periodically retrieves task progress data from the database, calculates the progress rate, and generates visualization data.

[1905] On the device: Retrieves progress data from the server and displays progress bars and graphs on the user's dashboard.

[1906] Examples:

[1907] User: Clicks the "Update Task A progress" button.

[1908] Terminal: Sends a progress update request to the server.

[1909] Server: Updates the progress field in the database and distributes the latest progress to other users.

[1910] Terminal: Shows an updated progress bar.

[1911] Task assignment and prioritization

[1912] Server: When a new task is added, the AI ​​engine analyzes the task details.

[1913] Server: Sets the priority of tasks taking into account the importance, urgency, skill sets of members, and workload status of the task.

[1914] Server: Assigns the task to the appropriate member.

[1915] On your device: The new task will appear in the assigned member's task list and a notification will be sent.

[1916] Examples:

[1917] User: Add a new task "Create Report".

[1918] Server: The AI ​​engine analyzes the task details and determines that it is highly important.

[1919] Server: Member A is available, so the task is assigned to Member A.

[1920] Terminal: "Create a report" is added to member A's task list.

[1921] Resource management assistance

[1922] Users: Enter the required resource information at the start of the project.

[1923] Terminal: Sends the entered information to the server.

[1924] Server: Automatically calculates required resources and generates resource lists and budgets.

[1925] Terminal: Display resource list and budget to project manager.

[1926] Examples:

[1927] User: Starts a "New Project" and enters the required resources.

[1928] Server: Generates a budget and a list of materials needed based on resource requirements.

[1929] Terminal: Display resource list and budget on the project manager's screen.

[1930] Real-time communication support

[1931] User: Opens the messaging screen and enters a message.

[1932] Terminal: Sends a message to the server.

[1933] Server: Receives messages and distributes them to designated members in real time.

[1934] Terminal: Display received messages in the chat window.

[1935] Examples:

[1936] User: In the "Question" chat, type "When is this task due?"

[1937] Terminal: Sends a message to the server.

[1938] Server: Forwards the message to the target member.

[1939] Terminal: Display a message in the target member's chat window.

[1940] Specific examples of using the emotion engine

[1941] Examples:

[1942] User: In the messaging screen, types "This task is very stressful."

[1943] Device: An emotion engine analyzes the user's messages and detects increased stress.

[1944] Server: Based on the analysis results from the emotion engine, adjusts the user's task allocation. It also shares this information with other members to encourage their support.

[1945] Terminal: The adjusted task list is displayed to the user in real time.

[1946] This AI task management system incorporates an emotion engine to reflect the user's psychological state and achieve more effective task management. The server utilizes the AI ​​engine and emotion engine to manage tasks, and the device provides real-time information to the user. Through this specific operation, the system aims to improve work efficiency and productivity.

[1947] The processing flow will be explained below.

[1948] Specific usage flow of the emotion engine

[1949] Recognizing User Emotions and Adjusting Task Allocation

[1950] Step 1:

[1951] User: In the messaging screen, types "This task is very stressful."

[1952] Step 2:

[1953] Terminal: Formats message data in JSON format to send messages about emotions entered by the user to the emotion engine.

[1954] Step 3:

[1955] Terminal: Sends formatted JSON data to the server.

[1956] Step 4:

[1957] Server: Analyzes the received message data and sends it to the emotion engine.

[1958] Step 5:

[1959] Server: The emotion engine analyzes the message content and determines the user's emotional state as "high stress."

[1960] Step 6:

[1961] Server: Based on the analysis results from the emotion engine, instructs the AI ​​engine to review task allocation.

[1962] Step 7:

[1963] Server: The AI ​​engine reallocates current tasks to other members to reduce the user's workload.

[1964] Step 8:

[1965] Terminal: Receives new task lists from the server and displays them in real time on the user's dashboard.

[1966] Emotional evaluation upon task completion and member workload adjustment

[1967] Step 1:

[1968] User: Clicks the Complete button to report "Task B completed."

[1969] Step 2:

[1970] Terminal: Input the user's emotional state "feeling accomplished" along with the task completion report.

[1971] Step 3:

[1972] Terminal: Sends this information to the server in JSON format.

[1973] Step 4:

[1974] Server: Analyzes the received data and records task completion reports in a database.

[1975] Step 5:

[1976] Server: The emotion engine recognizes the user's emotional state as "feeling accomplished."

[1977] Step 6:

[1978] Server: Based on the evaluation from the emotion engine, the AI ​​engine optimizes future task allocation to the user.

[1979] Step 7:

[1980] Server: For example, if a user shows a high sense of accomplishment, it decides to prioritize the next complex task.

[1981] Step 8:

[1982] Terminal: The adjusted task list is displayed in real time on the user's dashboard.

[1983] Emotion-based adaptive communication

[1984] Step 1:

[1985] User: Type "I need team help" in the chat window.

[1986] Step 2:

[1987] Terminal: The emotion engine analyzes the message content and sends data in JSON format to the server to determine the emotional state.

[1988] Step 3:

[1989] Server: The emotion engine recognizes the user's emotional state as "cooperation needed."

[1990] Step 4:

[1991] Server: The emotion engine notifies the AI ​​engine, instructing it to reevaluate the task and ask team members for help.

[1992] Step 5:

[1993] Server: The AI ​​engine reevaluates the task and allocates the necessary resources.

[1994] Step 6:

[1995] Server: Based on the analysis results of the emotion engine, it sends messages requesting cooperation to other team members.

[1996] Step 7:

[1997] Terminal: A real-time message requesting cooperation will appear in the chat window of your team members.

[1998] This process flow enables the AI ​​task management system to adaptively allocate tasks, adjust priorities, and manage team communication while taking into account the user's emotional state. The server utilizes the AI ​​engine and emotion engine to perform efficient task management, while the device provides information to the user in real time, thereby improving work efficiency and productivity.

[1999] Example 2

[2000] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[2001] While conventional task management systems can set task progress and priorities, they struggle to provide flexible task management that reflects the user's emotional state. Furthermore, support for real-time communication between users is limited, leaving challenges in improving work efficiency and productivity. Furthermore, resource management and appropriate task allocation are not adequately optimized, which can affect the productivity of the entire team.

[2002] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[2003] In this invention, the server includes means for receiving detailed task information from a user and storing the information in a database, means for periodically obtaining the progress status of the task from the database, calculating the progress rate, and generating visualization data, and means for displaying the generated visualization data on the user's terminal in real time. This allows the detailed task information to be managed appropriately, and the progress status of the task to be grasped in real time.

[2004] The server further includes a means for analyzing the importance and urgency of tasks and prioritizing them based on each member's skill set and workload, a means for assigning tasks to appropriate members and notifying users of the assigned tasks, a means for automatically calculating project resource information and generating a resource list and budget, a means for sharing messages and files between members in real time, and a means for receiving, analyzing, and reflecting users' emotional information in task management. This optimizes task prioritization and assignment to members, enabling resource management and real-time communication. It also enables flexible task management that takes users' emotional states into account.

[2005] "Detailed task information" refers to specific information about a task, such as the task name, description, deadline, and priority.

[2006] "User" refers to an individual or organization that uses the task management system to create, manage, and check the progress of tasks.

[2007] "Database" refers to a system for structuring and storing and managing data such as task information, progress status, and resource information.

[2008] "Progress rate" refers to an indicator that shows how much of a task has been completed as a percentage.

[2009] "Visualized data" refers to data that displays progress rates, task progress, etc. in a visual format such as graphs or charts.

[2010] "Member" refers to an individual user or team member assigned to perform a task.

[2011] A "skill set" refers to the collection of skills, knowledge, and experience that a member possesses.

[2012] "Load status" refers to the status that indicates the current workload of a member.

[2013] "Resource information" refers to information such as materials, personnel, equipment, and budget required to carry out a project.

[2014] "Resource list" refers to an itemized list of resources required to carry out a project.

[2015] "Budget" refers to the total amount of costs and expenses planned for the operation of a project.

[2016] "Emotional information" refers to data about a user's emotional state (e.g., stress, satisfaction, dissatisfaction, etc.).

[2017] "Artificial intelligence engine" refers to an artificial intelligence system for analyzing the importance and urgency of tasks, setting priorities, and assigning tasks to members.

[2018] "Task management" refers to the act of managing the entire life cycle of a task, including creating, assigning, checking progress, and reporting completion.

[2019] This invention combines an AI task management system, which aims to efficiently manage projects and work and improve productivity, with an emotion engine that recognizes user emotions, enabling more advanced task management. This system is composed of a server and a client (user device).

[2020] The user can access the interface through a browser or a mobile app to manage tasks, check progress, and communicate. Specific embodiments of the present invention will be described below.

[2021] System configuration

[2022] The system consists of the following main functional modules:

[2023] 1. Task Entry Module: Used by the user to enter a new task.

[2024] 2. Database management module: A database for storing and managing task information, progress status, resource information, etc.

[2025] 3. Progress management module: Manages the progress of tasks and generates visualization data.

[2026] 4. AI engine: Analyzes the importance and urgency of the task, as well as the skill sets and workload of members.

[2027] 5. Task allocation module: Based on the analysis results of the AI ​​engine, tasks are prioritized and assigned to the appropriate members.

[2028] 6. Resource Management Module: Automatically calculates the resources required for a project and generates a resource list and budget.

[2029] 7. Communication module: Supports messaging and file sharing among members.

[2030] 8. Emotion Engine: Recognizes user emotions and reflects them in the task management process.

[2031] Recognizing and reflecting user emotions

[2032] The emotion engine analyzes the user's emotional state and adjusts task allocation and priorities based on the results. For example, if a user is feeling stressed, it will adjust the task allocation to reduce the user's workload.

[2033] Emotion recognition processing flow

[2034] User: Providing emotional input feedback when interacting with messaging and task management screens, or extracted from sensor data such as facial recognition and voice analysis.

[2035] Terminal: Analyzes the user's emotional information and sends it to the server in JSON format.

[2036] Server: Analyzes the received emotion data and adjusts task priorities and assignments based on the emotion engine.

[2037] Creating and entering a new task

[2038] User: Opens a browser or mobile app and accesses the task management screen.

[2039] User: Enter the details of the new task, specifying the task name, detailed description, due date, priority, etc.

[2040] Terminal: Sends the task information entered by the user to the server in JSON format.

[2041] Server: Parse the received JSON data and store it in the database.

[2042] Tracking task progress

[2043] Server: Periodically retrieves task progress data from the database, calculates the progress rate, and generates visualization data.

[2044] On the device: Retrieves progress data from the server and displays progress bars and graphs on the user's dashboard.

[2045] Examples:

[2046] User: Clicks the "Update Task A progress" button.

[2047] Terminal: Sends a progress update request to the server.

[2048] Server: Updates the progress field in the database and distributes the latest progress to other users.

[2049] Terminal: Shows an updated progress bar.

[2050] Task assignment and prioritization

[2051] Server: When a new task is added, the AI ​​engine analyzes the task details.

[2052] Server: Sets the priority of tasks taking into account the importance, urgency, skill sets of members, and workload status of the task.

[2053] Server: Assigns the task to the appropriate member.

[2054] On your device: The new task will appear in the assigned member's task list and a notification will be sent.

[2055] Examples:

[2056] User: Add a new task "Create Report".

[2057] Server: The AI ​​engine analyzes the task details and determines that it is highly important.

[2058] Server: Member A is available, so the task is assigned to Member A.

[2059] Terminal: "Create a report" is added to member A's task list.

[2060] Resource management assistance

[2061] Users: Enter the required resource information at the start of the project.

[2062] Terminal: Sends the entered information to the server.

[2063] Server: Automatically calculates required resources and generates resource lists and budgets.

[2064] Terminal: Display resource list and budget to project manager.

[2065] Examples:

[2066] User: Starts a "New Project" and enters the required resources.

[2067] Server: Generates a budget and a list of materials needed based on resource requirements.

[2068] Terminal: Display resource list and budget on the project manager's screen.

[2069] Real-time communication support

[2070] User: Opens the messaging screen and types a message.

[2071] Terminal: Sends a message to the server.

[2072] Server: Receives messages and distributes them to designated members in real time.

[2073] Terminal: Display received messages in the chat window.

[2074] Examples:

[2075] User: In the "Question" chat, type "When is this task due?"

[2076] Terminal: Sends a message to the server.

[2077] Server: Forwards the message to the target member.

[2078] Terminal: Display a message in the target member's chat window.

[2079] Specific examples of using the emotion engine

[2080] Examples:

[2081] User: In the messaging screen, types "This task is very stressful."

[2082] Device: An emotion engine analyzes the user's messages and detects increased stress.

[2083] Server: Based on the analysis results from the emotion engine, adjusts the user's task allocation. It also shares this information with other members to encourage their support.

[2084] Terminal: The adjusted task list is displayed to the user in real time.

[2085] This AI task management system incorporates an emotion engine to reflect the user's psychological state and achieve more effective task management. The server utilizes the AI ​​engine and emotion engine to manage tasks, and the device provides real-time information to the user. Through this specific operation, the system aims to improve work efficiency and productivity.

[2086] Prompt Sentence Examples

[2087] "What operations are required to track task progress within the system?"

[2088] "How does the Emotion Engine work?"

[2089] How do I add a new task?

[2090] The above is a specific description of the embodiment of the present invention.

[2091] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2092] Step 1:

[2093] A user opens a browser or mobile app and accesses the task management screen.

[2094] Specific operation: The user opens the device's browser, enters the specified URL, and logs in to the task management system. If the user uses the mobile app, they launch the app and access the login screen.

[2095] Input: User authentication information (username, password)

[2096] Output: The user is authenticated successfully and the task management screen is displayed.

[2097] Step 2:

[2098] The user enters the details of the new task (task name, detailed description, due date, priority, etc.).

[2099] Specific operation: The user enters the task name "Create monthly report", the description "Compile monthly reports", the deadline "2023-10-31", and the priority "High".

[2100] Input: Task details (task name, detailed description, deadline, priority)

[2101] Output: The entered task information is reflected in the task input form.

[2102] Step 3:

[2103] The device sends the task information entered by the user to the server in JSON format.

[2104] Specific operation: When the user clicks the "Send" button, the device converts the task information into task_data.json format and sends an HTTP request to the server.

[2105] Input: JSON data of task information

[2106] Output: The server receives the JSON data.

[2107] Step 4:

[2108] The server parses the received JSON data and stores it in the database.

[2109] Specific behavior: The server parses the received JSON data and saves the task name, details, due date, and priority to the database.

[2110] Input: JSON data of task information

[2111] Output: Task information is stored in the database.

[2112] Step 5:

[2113] The server periodically retrieves task progress status data from the database, calculates the progress rate, and generates visualization data.

[2114] What it does: The server queries the database every day to get the progress, calculates the progress rate, and generates visualization data in the form of bar graphs and charts.

[2115] Input: Task progress data retrieved from the database

[2116] Output: Generated visualization data (progress rate, etc.)

[2117] Step 6:

[2118] The device retrieves progress data from the server and displays progress bars and graphs on the user's dashboard.

[2119] Specific operation: When a user opens the dashboard screen, the device sends a request to the server, receives the latest progress data, and displays it as a progress bar and graph.

[2120] Input: Visualization data from the server

[2121] Output: Progress bars and graphs displayed on a dashboard

[2122] Step 7:

[2123] The server analyzes the importance and urgency of the task, the skill sets and workload of the members, sets the priority of the task, and assigns the task to an appropriate member.

[2124] How it works: When a new task is added, the AI ​​engine analyzes the task details, evaluates the importance and urgency of the task, sets a priority taking into account each member's skill set and current workload, and assigns it to the appropriate member.

[2125] Input: New task information, member skill sets and workload status

[2126] Output: A new task is added to the assigned member's task list

[2127] Step 8:

[2128] The new task will be displayed in the task list of the member to whom the device is assigned and a notification will be sent.

[2129] Specific operation: After the task assignment is determined, the terminal adds "Create a report" to member A's task list and notifies member A that a new task has been assigned via the notification function.

[2130] Input: Task assignment information

[2131] Output: New tasks and notifications added to members' task lists

[2132] Step 9:

[2133] Users enter the required resource information at the start of a project.

[2134] Specific operation: A user starts a "new project" and inputs resource information such as required personnel, equipment, and budget.

[2135] Input: Project resource information

[2136] Output: The input resource information is displayed.

[2137] Step 10:

[2138] The terminal transmits the input information to the server.

[2139] Specific operation: After the user enters the resource information, he clicks the "Send" button, and the terminal sends the information to the server in JSON format.

[2140] Input: JSON data of resource information

[2141] Output: The server receives the data

[2142] Step 11:

[2143] The server automatically calculates the required resources and generates a resource list and budget.

[2144] Specific operation: Based on the resource information received by the server, the server calculates the resources required to carry out the project and generates a resource list and budget.

[2145] Input: Resource information

[2146] Output: Generated resource list and budget

[2147] Step 12:

[2148] The terminal displays the resource list and budget to the project manager.

[2149] Specific operation: The resource list and budget data generated by the server are sent to the terminal and displayed on the project manager's screen.

[2150] Input: Resource list and budget data

[2151] Output: Resource list and budget displayed on the project manager's screen

[2152] Step 13:

[2153] The user opens the messaging screen and types a message.

[2154] What happens: A user uses the messaging feature to type a question: "When is this task due?"

[2155] Input: Message

[2156] Output: The displayed input message

[2157] Step 14:

[2158] The device sends a message to the server.

[2159] Specific operation: The user clicks the "Send" button, and the device sends the message to the server.

[2160] Input: Message data

[2161] Output: The server receives the message

[2162] Step 15:

[2163] The server receives the message and distributes it to the specified members in real time.

[2164] Specific operation: The server analyzes the received message, identifies the destination member, and forwards the message to that member.

[2165] Input: Incoming message

[2166] Output: Message delivery to specified members

[2167] Step 16:

[2168] Displays messages received by the device in the chat window.

[2169] Specific operation: The specified member's device will receive the message and display it in the chat window.

[2170] Input: Message data from the server

[2171] Output: Message displayed in the chat window

[2172] Step 17:

[2173] The user provides emotional input feedback or sensor data such as facial recognition or voice analysis.

[2174] Specific behavior: The user types "This task is very stressful" or provides emotional data using the smartphone's camera or microphone.

[2175] Input: Emotion data

[2176] Output: Emotional feedback displayed on the device

[2177] Step 18:

[2178] The device analyzes the user's emotional information and sends it to the server in JSON format.

[2179] Specific operation: The device analyzes the user's emotional feedback, converts the type and intensity of the emotion into JSON format, and sends it to the server.

[2180] Input: JSON data of emotion information

[2181] Output: The server receives the emotion data.

[2182] Step 19:

[2183] The server analyzes the received emotion data and adjusts task priorities and allocations based on the emotion engine.

[2184] Specific operation: The server uses an emotion engine to analyze emotional data, and if it determines that the user's stress level is high, it adjusts task allocation and priorities.

[2185] Input: Emotion data

[2186] Output: Adjusted task assignments and priorities

[2187] (Application example 2)

[2188] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[2189] Conventional task management systems assign and prioritize tasks without considering the user's emotional state, which increases the user's psychological burden and makes efficient task management difficult. Furthermore, in security services, there was a lack of a mechanism for grasping the emotional state of security guards and security staff in real time and dynamically adjusting tasks based on that information, making it difficult to respond appropriately in emergencies. The present invention addresses these issues.

[2190] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[2191] In this invention, the server includes means for receiving detailed task information from a user and storing it in a database, means for periodically obtaining task progress from the database, calculating the progress rate, and generating visualization data, means for displaying the generated visualization data on the user's terminal in real time, means for analyzing the importance and urgency of tasks and setting task priorities taking into account the skill set and workload of each member, means for assigning tasks to appropriate members and notifying the user's terminal of the assigned tasks, means for automatically calculating project resource information and generating a resource list and budget, means for sharing messages and files among members in real time, and means for recognizing the emotional state of security staff, transmitting that data to the server, and adjusting task priorities and assignments based on an emotion engine. This enables efficient task management and appropriate security response that reflects the user's emotional state.

[2192] "Detailed task information" is specific information such as the name, description, deadline, and priority of a task input by the user.

[2193] A "database" is a system for structuring and storing and managing task information, progress status, resource information, and the like.

[2194] "Visualization data" refers to data such as graphs and charts that visually represent task progress and other information.

[2195] "Task importance" is an indicator of how important a particular task is to the project or business as a whole.

[2196] "Urgency" is a measure of how quickly a particular task should be addressed.

[2197] "Skill set" is a collective term for the techniques, knowledge, and experience that each member possesses.

[2198] "Load status" is information that indicates the amount of tasks currently assigned to each member and the degree to which the goal must be achieved.

[2199] "Resource information" refers to detailed information about personnel, equipment, materials, and budget required to carry out a project.

[2200] The "emotion engine" is a software module that recognizes the user's emotional state and reflects the analysis results in the task management process.

[2201] "Security staff" refers to security guards and guards who work to ensure the safety of facilities, events, etc.

[2202] "Task priority" refers to the order of task execution that is set based on the importance, urgency, skill set, and load status of the task.

[2203] The present invention is a system that monitors the emotional state of security staff in real time and dynamically adjusts task allocation and priorities based on the monitoring results. Specific embodiments will be described below.

[2204] System configuration

[2205] The system consists of a series of software and hardware components, including an emotion recognition engine, a task management engine, a database, a user interface, and a communication module.

[2206] Hardware and Software Details

[2207] Smart glasses: equipped with cameras to provide a video feed for monitoring the emotional state of security staff.

[2208] Emotion recognition engine: A software module used to recognize user emotions from video in real time (e.g., EmotionRecognizer).

[2209] AI task management engine: Analyzes the importance and urgency of tasks and prioritizes them based on resources and sentiment information.

[2210] Database: A system that structures and stores task information, progress, emotional data, etc.

[2211] Communication module: A module for transmitting data in real time between a user terminal and a server (e.g., the Requests library).

[2212] User emotion recognition and data transmission

[2213] User: Wears smart glasses, the camera captures the video feed.

[2214] Terminal: Analyzes the user's emotional state from the camera feed of the smart glasses using an emotion recognition engine and sends the results to the server.

[2215] Server: Analyzes the received emotional data and adjusts task allocation and priorities using an AI task management engine.

[2216] Task assignment and prioritization

[2217] Server: The AI ​​engine and emotion engine work together to prioritize tasks, taking into account the importance and urgency of the task and the emotional state of the security staff.

[2218] Server: Assign tasks to the appropriate security staff based on set priorities. Assign important and urgent tasks to staff with stable emotional states.

[2219] Devices: Assigned tasks are notified to staff members' smartphones or other devices.

[2220] Specific examples

[2221] User: Security staff wear smart glasses and patrol the area.

[2222] Device: The smart glasses capture video and the emotion recognition engine analyzes emotions in real time. For example, if it detects "anxiety" or "tension," it sends the data to the server.

[2223] Server: Based on the received emotional data, it assigns high-priority tasks to other emotionally stable staff members.

[2224] Device: The task is notified to the assigned staff member's smartphone.

[2225] This system will enable effective task management that takes into account the emotional state of security staff, enabling appropriate responses in emergencies. It will also promote real-time communication between staff, improving work efficiency and safety.

[2226] Prompt Sentence Examples

[2227] Sample prompt: "I want to build a system that uses facial recognition to analyze emotions in real time and adjust security task assignments based on that information. Specifically, I would use smart glasses to capture camera footage and EmotionRecognizer to recognize emotions, so that stressed guards are not assigned urgent tasks and instead are assigned to other guards."

[2228] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2229] Step 1:

[2230] A user puts on the smart glasses and starts the camera feed.

[2231] Input: Real-time video data from smart glasses.

[2232] Output: A real-time video feed is generated, which serves as input to the emotion recognition engine.

[2233] How it works: Security staff wear smart glasses and patrol the surveillance area, and the camera in the smart glasses captures images of the surrounding area.

[2234] Step 2:

[2235] The device uses an emotion recognition engine to analyze the user's emotions in real time from the camera feed of the smart glasses.

[2236] Input: Real-time video feed.

[2237] Output: Data representing the user's emotional state (e.g., stressed, nervous, calm, etc.).

[2238] Specific operation: The device uses EmotionRecognizer to analyze video data and recognize emotions from the user's facial expressions and slight body movements. For example, it identifies emotions such as "stress" and "anxiety."

[2239] Step 3:

[2240] The device sends the results of the emotion recognition engine to the server in JSON format.

[2241] Input: Data representing the user's emotional state.

[2242] Output: Emotion data in JSON format is sent to the server.

[2243] Specific operation: The device converts the analyzed data into JSON format and sends it to the server as an HTTP request. This data also includes a timestamp and user ID.

[2244] Step 4:

[2245] The server analyzes the received emotional data and calls an AI task management engine to respond appropriately.

[2246] Input: Emotion data in JSON format.

[2247] Output: Analysis results of task priorities and allocation settings.

[2248] Specific operation: The server analyzes the received emotional data and passes the results to the AI ​​task management engine, which then reevaluates task priorities and allocations according to the emotional state.

[2249] Step 5:

[2250] The server assigns tasks to appropriate security staff based on the analysis results of the AI ​​task management engine.

[2251] Input: Analysis results (task priorities and assignments).

[2252] Output: Task assignment notification.

[2253] Specific operation: Based on the analysis results, the server decides to avoid urgent tasks for stressed staff and assign tasks to other emotionally stable staff.

[2254] Step 6:

[2255] The server notifies the user's terminal of the assigned task.

[2256] Input: Task assignment information.

[2257] Output: Task notification sent to user device.

[2258] Specific operation: The server sends the allocation information to the corresponding security staff terminal in real time, and the staff receives the notification and confirms their next action.

[2259] Step 7:

[2260] The user performs the assigned task and reports progress to the terminal.

[2261] Input: Task progress.

[2262] Output: Progress data is sent to the server.

[2263] Specific operation: Security staff carry out assigned tasks and report their progress and completion status via their terminals. The reported data is sent to the server and shared throughout the system.

[2264] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[2265] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[2266] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[2267] [Fourth embodiment]

[2268] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[2269] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[2270] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[2271] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[2272] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[2273] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[2274] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[2275] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[2276] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[2277] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[2278] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[2279] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[2280] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2281] This invention is an AI task management system that aims to efficiently manage projects and work and improve productivity. The system consists of a server and a client (user device). Users can access the interface via a browser or mobile app to manage tasks, check progress, and communicate. The specific operation of the system is described in detail below.

[2282] System configuration

[2283] The system consists of the following main functional modules:

[2284] 1. Task Entry Module: Used by the user to enter a new task.

[2285] 2. Database management module: A database for storing and managing task information, progress status, resource information, etc.

[2286] 3. Progress management module: Manages the progress of tasks and generates visualization data.

[2287] 4. AI engine: Analyzes the importance and urgency of the task, as well as the skill sets and workload of members.

[2288] 5. Task allocation module: Based on the analysis results of the AI ​​engine, tasks are prioritized and assigned to the appropriate members.

[2289] 6. Resource Management Module: Automatically calculates the resources required for a project and generates a resource list and budget.

[2290] 7. Communication module: Supports messaging and file sharing among members.

[2291] Creating and entering a new task

[2292] User: Opens a browser or mobile app and accesses the task management screen.

[2293] User: Enter the details of the new task, specifying the task name, detailed description, due date, priority, etc.

[2294] Terminal: Sends the task information entered by the user to the server in JSON format.

[2295] Server: Parse the received JSON data and store it in the database.

[2296] Tracking task progress

[2297] Server: Periodically retrieves task progress data from the database, calculates the progress rate, and generates visualization data.

[2298] On the device: Retrieves progress data from the server and displays progress bars and graphs on the user's dashboard.

[2299] Examples:

[2300] User: Clicks the "Update Task A progress" button.

[2301] Terminal: Sends a progress update request to the server.

[2302] Server: Updates the progress field in the database and distributes the latest progress to other users.

[2303] Terminal: Shows an updated progress bar.

[2304] Task assignment and prioritization

[2305] Server: When a new task is added, the AI ​​engine analyzes the task details.

[2306] Server: Sets the priority of tasks taking into account the importance, urgency, skill sets of members, and workload status of the task.

[2307] Server: Assigns the task to the appropriate member.

[2308] On your device: The new task will appear in the assigned member's task list and a notification will be sent.

[2309] Examples:

[2310] User: Add a new task "Create Report".

[2311] Server: The AI ​​engine analyzes the task details and determines that it is highly important.

[2312] Server: Member A is available, so the task is assigned to Member A.

[2313] Terminal: "Create a report" is added to member A's task list.

[2314] Resource management assistance

[2315] Users: Enter the required resource information at the start of the project.

[2316] Terminal: Sends the entered information to the server.

[2317] Server: Automatically calculates required resources and generates resource lists and budgets.

[2318] Terminal: Display resource list and budget to project manager.

[2319] Examples:

[2320] User: Starts a "New Project" and enters the required resources.

[2321] Server: Generates a budget and a list of materials needed based on resource requirements.

[2322] Terminal: Display resource list and budget on the project manager's screen.

[2323] Real-time communication support

[2324] User: Opens the messaging screen and enters a message.

[2325] Terminal: Sends a message to the server.

[2326] Server: Receives messages and distributes them to designated members in real time.

[2327] Terminal: Display received messages in the chat window.

[2328] Examples:

[2329] User: In the "Question" chat, type "When is this task due?"

[2330] Terminal: Sends a message to the server.

[2331] Server: Forwards the message to the target member.

[2332] Terminal: Display a message in the target member's chat window.

[2333] summary

[2334] This AI task management system integrates progress management, task allocation and prioritization, resource management, and real-time communication support. The server utilizes an AI engine to manage tasks, and the device provides real-time information to the user. Through these specific operations, the system improves work efficiency and productivity.

[2335] The processing flow will be explained below.

[2336] Creating and entering a new task

[2337] Step 1:

[2338] User: Opens a browser or mobile app and accesses the task management screen.

[2339] Step 2:

[2340] User: Enter the details of the new task, specifying the task name, detailed description, due date, priority, etc.

[2341] Step 3:

[2342] Terminal: Sends the task information entered by the user to the server in JSON format.

[2343] Step 4:

[2344] Server: Parse the received JSON data and store it in the database.

[2345] Tracking task progress

[2346] Step 1:

[2347] Server: Periodically retrieves task progress data from the database.

[2348] Step 2:

[2349] Server: Based on the progress status data, calculates the progress rate of the task and generates visualization data.

[2350] Step 3:

[2351] On the device: Retrieves progress data from the server and displays progress bars and graphs on the user's dashboard.

[2352] Examples:

[2353] Step 1:

[2354] User: Clicks the "Update Task A progress" button.

[2355] Step 2:

[2356] Terminal: Sends a progress update request to the server.

[2357] Step 3:

[2358] Server: Updates the progress field in the database and distributes the latest progress to other users.

[2359] Step 4:

[2360] Terminal: Shows an updated progress bar.

[2361] Task assignment and prioritization

[2362] Step 1:

[2363] Server: When a new task is added, the AI ​​engine analyzes the task details.

[2364] Step 2:

[2365] Server: Sets the priority of tasks taking into account the importance, urgency, skill sets of members, and workload status of the task.

[2366] Step 3:

[2367] Server: Assigns the task to the appropriate member.

[2368] Step 4:

[2369] On your device: The new task will appear in the assigned member's task list and a notification will be sent.

[2370] Examples:

[2371] Step 1:

[2372] User: Add a new task "Create Report".

[2373] Step 2:

[2374] Server: The AI ​​engine analyzes the task details and determines that it is highly important.

[2375] Step 3:

[2376] Server: Member A is available, so the task is assigned to Member A.

[2377] Step 4:

[2378] Terminal: "Create a report" is added to member A's task list.

[2379] Resource management assistance

[2380] Step 1:

[2381] Users: Enter the required resource information at the start of the project.

[2382] Step 2:

[2383] Terminal: Sends the entered information to the server.

[2384] Step 3:

[2385] Server: Automatically calculates required resources and generates resource lists and budgets.

[2386] Step 4:

[2387] Terminal: Display resource list and budget to project manager.

[2388] Examples:

[2389] Step 1:

[2390] User: Starts a "New Project" and enters the required resources.

[2391] Step 2:

[2392] Server: Generates a budget and a list of materials needed based on resource requirements.

[2393] Step 3:

[2394] Terminal: Display resource list and budget on the project manager's screen.

[2395] Real-time communication support

[2396] Step 1:

[2397] User: Opens the messaging screen and enters a message.

[2398] Step 2:

[2399] Terminal: Sends a message to the server.

[2400] Step 3:

[2401] Server: Receives messages and distributes them to designated members in real time.

[2402] Step 4:

[2403] Terminal: Display received messages in the chat window.

[2404] Examples:

[2405] Step 1:

[2406] User: In the "Question" chat, type "When is this task due?"

[2407] Step 2:

[2408] Terminal: Sends a message to the server.

[2409] Step 3:

[2410] Server: Forwards the message to the target member.

[2411] Step 4:

[2412] Terminal: Display a message in the target member's chat window.

[2413] Example 1

[2414] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2415] Modern project management requires consistent and efficient operation, from task entry to progress visualization, task prioritization and assignment, resource management, and communication between team members. However, few systems offer these functions in an integrated and automated manner, and manual management or the use of multiple tools is often required. This results in problems such as duplicated work and reduced efficiency. Furthermore, optimal task assignment based on task importance and team member skill sets requires advanced analytical capabilities, which traditional systems often lack. To address these challenges, there is a need for systems that optimize task management by automating and streamlining the entire business process and incorporating generative AI models.

[2416] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[2417] In this invention, the server includes means for receiving detailed task information from a user and storing the information in a database, means for periodically obtaining the task progress status from the database, calculating the progress rate, and generating visualization data, and means for displaying the generated visualization data on the user's terminal in real time, thereby enabling detailed task management and visualization and real-time display of the progress status.

[2418] The server also includes: a means for analyzing the importance and urgency of tasks and prioritizing the tasks while taking into account the technical requirements and workload of each member; a means for assigning tasks to appropriate members and notifying the users of the assigned tasks on their terminals; a means for automatically calculating project resource information and generating a resource list and budget; a means for sharing messages and files between members in real time; a means for outputting task analysis results using a generative AI model; and a means for automatically generating task details using prompt text as input. This enables task prioritization and allocation optimization, automated resource management, and real-time communication.

[2419] "Detailed task information" refers to information such as the content, deadline, priority, and explanation of specific tasks that a user should manage in a project or business.

[2420] A "database" is a storage medium and its management system for systematically storing and managing data required within the system, such as detailed task information, progress status, member information, and resource information.

[2421] "Completion" refers to how much of a particular task or project is complete, usually expressed as a percentage.

[2422] "Visualized data" is data that is presented in a visual form, such as a graph or chart, so that users can easily understand the data intuitively.

[2423] A "user terminal" is an electronic device such as a computer, tablet, or smartphone that a user uses to access and operate the system.

[2424] "Task importance" is an index that indicates how important a particular task is compared to other tasks.

[2425] "Urgency" is a measure of how quickly a particular task should be addressed.

[2426] "Technical requirements" are requirements such as specific skills, knowledge, and experience required to perform a task.

[2427] "Load status" refers to the status that indicates how much work a particular member or resource is currently doing.

[2428] "Priority" is the order that determines which task or project should be done first among multiple tasks or projects.

[2429] "Resource information" refers to information such as personnel, equipment, and budget required to carry out a project or task.

[2430] A "generative AI model" is an algorithm and its implementation that uses artificial intelligence to generate analytical results and predictions from input data.

[2431] A "prompt sentence" is text data given as input to a generative AI model, and contains specific instructions for analysis and generation.

[2432] "Analysis results" are decision information such as task allocation and priority setting that the generative AI model outputs based on prompt statements and other input data.

[2433] This invention is an AI task management system aimed at efficient management of projects and work and improving productivity. The system consists of a server and a client (user device), and users can access the interface via a browser or mobile app to manage tasks, check progress, and communicate. The specific operation of the system is described in detail below.

[2434] System configuration

[2435] The system consists of the following main functional modules:

[2436] 1. Task Entry Module: Used by the user to enter a new task.

[2437] 2. Database Management Module: A database for storing and managing task information, progress, and resource information.

[2438] 3. Progress management module: Manages the progress of tasks and generates visualization data.

[2439] 4. Generative AI model: Analyzes the importance and urgency of the task, as well as the technical requirements and workload of members.

[2440] 5. Task assignment module: Based on the analysis results of the generative AI model, tasks are prioritized and assigned to appropriate members.

[2441] 6. Resource Management Module: Automatically calculates the resources required for a project and generates a resource list and budget.

[2442] 7. Communication module: Supports messaging and file sharing among members.

[2443] Specific operation of the system

[2444] A user opens a browser or mobile app and accesses the task management screen. When adding a task, they enter details such as the task name, detailed description, due date, and priority into a form. This sends JSON format data from the device to the server. The server parses the received data and stores it in a database.

[2445] Specific examples

[2446] For example, if a user enters a task name of "Report Creation," a deadline of "2023-12-31," and a priority of "High," the device sends this information in JSON format to the server, which receives the data and stores it in a database.

[2447] The server periodically retrieves task progress data from the database, calculates the progress rate, and generates visualization data, which is displayed in real time on the user's dashboard.

[2448] Specific examples

[2449] When the user clicks the progress update button, the device sends a progress update request to the server. The server updates the database with the new progress and distributes this latest data to other users. The device then displays the updated progress bar on the user's dashboard.

[2450] When a new task is added, the server's generative AI model analyzes the task details and prioritizes it, taking into account the task's importance, urgency, technical requirements of members, and workload.

[2451] Specific examples

[2452] For example, a new task "Write a report" is added, and the generative AI model analyzes the task and determines that it is of high importance. Since member A is currently free, the task is assigned to member A. The device sends a notification to member A and adds the task to the task list.

[2453] The user inputs the necessary resource information at the start of a project. The terminal sends the information to the server, which then automatically calculates and generates the resource list and budget. This information is then displayed on the project manager's terminal.

[2454] Specific examples

[2455] When a user starts a "new project" and enters the required resources as "PC, software license, and budget of 300,000 yen," the server automatically calculates the budget and materials list based on that information and displays the results to the project manager on the terminal.

[2456] With the messaging function, users can enter and send messages on the messaging screen. The device sends the message to the server, which then distributes it to other members in real time. Received messages are displayed in the chat window on the device.

[2457] Specific examples

[2458] When a user types "When is the deadline for this task?" into the chat window and sends it, the device sends the message to the server, which then forwards the message to the target member, who then sees the message in their chat window.

[2459] A prompt is a text instruction given as input to a generative AI model to analyze and automatically generate a task. For example, a prompt might be, "Please write an important report. The deadline is December 31, 2023."

[2460] In this way, the AI ​​task management system integrates progress management, task allocation and priority setting, resource management, and real-time communication support. The server uses generated AI models to manage tasks, and the terminal provides information to the user in real time, thereby improving work efficiency and productivity.

[2461] The flow of the identification process in the first embodiment will be described with reference to FIG.

[2462] The flow of this system's program processing

[2463] Step 1: User enters task

[2464] Input: A user opens a browser or mobile app, accesses the task management screen, and enters task details such as the task name, detailed description, due date, and priority.

[2465] Processing: The terminal converts the input information into JSON format.

[2466] Output: The generated JSON data is sent to the server.

[2467] Specific operation: The user enters the task name "Create report", the due date "2023-12-31", and the priority "High". The device sends this to the server in the format {"task_name": "Create report", "due_date": "2023-12-31", "priority": "High"}.

[2468] Step 2: Receiving and saving task data

[2469] Input: Task data in JSON format sent from the device.

[2470] Processing: The server parses the received JSON data, maps it to the appropriate fields, and stores it in the database.

[2471] Output: Task information is saved to the database.

[2472] Specific operation: The server receives the data {"task_name": "Create Report", "due_date": "2023-12-31", "priority": "High"}, parses it, and saves it to the database.

[2473] Step 3: Managing and visualizing task progress

[2474] Input: Task progress data retrieved periodically from the database.

[2475] Processing: The server calculates the progress rate and generates visualization data (graphs and bars).

[2476] Output: The generated visualization data is sent to the user's terminal and displayed in real time.

[2477] Specific operation: The server obtains the progress data and generates a progress bar when the progress of "Task A" is 50%. The device receives this information and displays it on the user's dashboard.

[2478] Step 4: Analysis and task prioritization by generative AI model

[2479] Input: New task details.

[2480] Processing: The server-generated AI model analyzes the importance and urgency of tasks, as well as the technical requirements and workload of each member. Task priorities are set based on the analysis results.

[2481] Output: Task information assigned to the appropriate members is generated.

[2482] Specific operation: The AI ​​model analyzes the "Report Creation" task and determines that it is of high importance. Since member A has a low workload, the model assigns this task to member A.

[2483] Step 5: Task assignment and notifications

[2484] Input: Task assignment information from the generative AI model.

[2485] Processing: The server assigns the task to an appropriate member and notifies the user's terminal of this information.

[2486] Output: The task list is updated on the user's device and a notification is displayed.

[2487] Specific behavior: When you assign the task "Create a report" to member A, a notification will be sent to the device and member A's task list will be updated.

[2488] Step 6: Enter and manage resource information

[2489] Input: Users enter the required resource information at the start of a project.

[2490] Processing: The terminal sends the information to the server, which automatically calculates the required resources and generates a resource list and budget.

[2491] Output: The generated resource list and budget are displayed on the project manager's terminal.

[2492] Specific operation: When a user enters "PC, software license, budget 300,000 yen," the server automatically calculates and displays the results to the project manager.

[2493] Step 7: Real-time communication

[2494] Input: The message the user types in the messaging screen.

[2495] Processing: The terminal sends a message to the server, which then forwards it to the designated members in real time.

[2496] Output: The message will be displayed in the member's chat window.

[2497] Specific operation: The user types "When is the deadline for this task?" into the chat and sends it. The device sends it to the server, which then forwards it to the target member and displays it.

[2498] Specific examples

[2499] For example, the generative AI model is used with the prompt "Please prepare an important report. The deadline is December 31, 2023." In this case, the AI ​​model analyzes the content of the prompt and automatically generates detailed information about the task. As a result, the system assigns the task to an appropriate member and displays basic information on the user's device.

[2500] (Application example 1)

[2501] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2502] Conventional factory task management and resource management often require a lot of human intervention and are inefficient. Furthermore, it is not possible to monitor the robot's operating status or progress in real time, making it difficult to respond quickly when an error occurs. This has led to problems such as reduced productivity and increased costs. The present invention aims to solve these problems and improve the efficiency of task management, progress monitoring, and resource management within a factory.

[2503] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[2504] In this invention, the server includes means for receiving detailed task information from a user and storing it in an information storage device, means for periodically obtaining task progress status from the information storage device, calculating the progress rate, and generating visualization data, means for displaying the generated visualization data on a user's terminal in real time, means for analyzing the importance and urgency of tasks and prioritizing tasks taking into account the skill sets and workloads of each worker, means for assigning tasks to appropriate workers and notifying the users of the assigned tasks, means for automatically calculating resource information within the factory and generating a resource list and budget, means for sharing messages and files among workers in real time, means for monitoring the operating status of robots in real time and notifying a smartphone or head-mounted display of task progress and errors, and means for generating resource requests for the project and calculating an optimal budget. This enables efficient task management and progress monitoring within the factory and immediate response.

[2505] "Task detailed information" is specific information about a task, such as the name, content, deadline, and priority of a specific task.

[2506] A "user" is an individual or person in charge who operates the system to input tasks and monitor progress.

[2507] An "information storage device" is a database or storage system for saving and managing data such as detailed task information and progress status.

[2508] "Progress" refers to the state of how much of a particular task has been completed.

[2509] "Visualized data" is data that visually shows progress, such as numbers, graphs, and progress bars.

[2510] A "terminal" is a device used by a user, such as a smartphone, tablet, or head-mounted display.

[2511] "Task importance" is a factor that indicates the business importance of a specific task.

[2512] "Urgency" is a factor that indicates how quickly a particular task should be addressed.

[2513] A "skill set" is the collection of skills and abilities that each member possesses.

[2514] "Load status" refers to the tasks and workload currently handled by each member.

[2515] "Constituents" are people or teams to whom tasks are assigned by the system.

[2516] "Resource information" refers to information such as materials, personnel, and equipment required to carry out a project or task.

[2517] A "resource list" is a list of required resources.

[2518] A "budget" is an estimate of how much a project or task will cost.

[2519] "Message and file sharing" refers to the act of sending and receiving text messages and documents between members.

[2520] "Robot operating status" is information on whether the corresponding robot in the factory is available, in operation, or in an error state.

[2521] An "error" is a problem or failure that occurs within a robot or system.

[2522] A "project resource request" is a requirement that specifies the resources needed to complete a particular project or task.

[2523] The "optimal budget" is the most efficient cost estimate calculated based on the resource information and resource list.

[2524] The present invention is a system for efficiently managing tasks, progress, and resources within a factory. This system is realized through the cooperation of a server, terminals, and users.

[2525] System configuration

[2526] The system consists of the following main functional modules:

[2527] 1. Task input module: Used by users to input new tasks.

[2528] 2. Database management module: An information storage device for storing and managing task information, progress status, resource information, etc.

[2529] 3. Progress management module: Manages the progress of tasks and generates visualization data.

[2530] 4. AI engine: Analyzes the importance and urgency of the task, the skill sets of the members, and the workload situation.

[2531] 5. Task allocation module: Based on the analysis results of the AI ​​engine, it sets the priority of tasks and assigns them to the appropriate members.

[2532] 6. Resource management module: Automatically calculates resource information within the factory and generates resource lists and budgets.

[2533] 7. Communication module: Supports messaging and file sharing among members.

[2534] 8. Robot monitoring module: Monitors the robot's operating status in real time and notifies the operating status and errors to a smartphone or head-mounted display.

[2535] Creating and entering a new task

[2536] User: Opens a smartphone or head-mounted display and accesses the task management screen.

[2537] User: Enter the details of the new task, specifying the task name, detailed description, due date, importance, etc.

[2538] Terminal: Sends task information entered by the user to the server.

[2539] Server: Analyzes the received task information and stores it in an information storage device.

[2540] Tracking task progress

[2541] Server: Periodically obtains task progress data from the information storage device, calculates the progress rate, and generates visualization data.

[2542] Terminal: Retrieves progress data from the server and displays progress bars and graphs on the user's dashboard.

[2543] Task assignment and prioritization

[2544] Server: When a new task is added, the AI ​​engine analyzes the task details.

[2545] Server: Sets the priority of tasks taking into account the importance and urgency of the tasks, the skill sets of members, and the workload situation.

[2546] Server: Assigns tasks to appropriate members. For example, when a new task, "assembling machine parts," is added, the AI ​​engine determines that the task has high priority and assigns it to member A, whose skill set is suitable.

[2547] Terminal: Adds new tasks to assigned members' task lists and sends notifications.

[2548] Resource Management

[2549] User: Enters the required resource information at the start of the project.

[2550] Terminal: Sends the entered information to the server.

[2551] Server: Automatically calculates required resources and generates resource lists and budgets.

[2552] Terminal: Display resource lists and budgets to project managers in real time.

[2553] Real-time communication

[2554] User: Open the messaging screen and enter a message.

[2555] Terminal: Sends a message to the server.

[2556] Server: Receives messages and distributes them to designated members in real time.

[2557] Terminal: Display received messages in the chat window.

[2558] Monitoring the operating status of robots

[2559] Server: Monitors the robot's operating status in real time, checking progress and errors.

[2560] Device: A notification is displayed on a smartphone or head-mounted display to notify the user.

[2561] Examples of concrete examples and prompts

[2562] For example, a factory supervisor can input a new task, "Transport parts," on their smartphone, and the AI ​​engine analyzes it and assigns the task to the appropriate robot. The supervisor can then monitor the robot's progress in real time on their smartphone and immediately respond to any problems that arise.

[2563] Example prompt for generative AI model:

[2564] "Assign the following task to the most suitable robot. Task information: Parts transport, Deadline: 2023-12-31, Priority: High. Robot list: Robot 1, Robot 2, Robot 3. Consider the current operational status and skill set of the robots."

[2565] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2566] Step 1:

[2567] Entering task details

[2568] The user inputs details of a new task using a smartphone or head-mounted display, including the task name, detailed description, deadline, and importance.

[2569] Input: Task details entered by the user

[2570] The terminal sends the entered information to the server in JSON format.

[2571] Output: Sends detailed task information in JSON format to the server

[2572] Step 2:

[2573] Storing task information

[2574] The server analyzes the received JSON format task information and stores it in an information storage device (database).

[2575] Input: JSON formatted task details sent from the device

[2576] Data processing: Parsing JSON data

[2577] Output: Detailed task information stored in the database

[2578] Step 3:

[2579] Obtaining and managing task progress

[2580] The server periodically retrieves task progress status data from the database, calculates the progress rate, and generates visualization data.

[2581] Input: Progress data retrieved from the database

[2582] Data calculation: Calculating progress rate and generating visualization data

[2583] Output: The generated visualization data

[2584] Step 4:

[2585] Viewing progress data

[2586] The device retrieves progress data from the server and displays it on the user's dashboard in the form of a progress bar or graph.

[2587] Input: Visualization data obtained from the server

[2588] Output: Progress displayed on the device dashboard

[2589] Step 5:

[2590] Task analysis by AI engine

[2591] The server uses an AI engine to analyze the importance and urgency of tasks and prioritizes them, taking into account each member's skill set and workload.

[2592] Input: Task details, member skill sets and workload status

[2593] Data calculation: Analyzing the importance and urgency of tasks and setting priorities

[2594] Output: Prioritized task information

[2595] Step 6:

[2596] Task assignment

[2597] The server assigns prioritized tasks to appropriate members.

[2598] Input: Priority-set task information, member skills and workload information

[2599] Data calculation: Selecting the best members

[2600] Output: Task list notification to assigned members

[2601] Step 7:

[2602] Resource Management

[2603] At the start of a project, the user inputs the necessary resource information, and the terminal sends this to the server.

[2604] Input: Required resource information

[2605] The terminal transmits the input resource information to the server.

[2606] Output: Resource information sent to the server

[2607] Step 8:

[2608] Calculating and displaying resource information

[2609] The server automatically calculates the required resources, generates a resource list and budget, and displays them to the project manager.

[2610] Input: Resource information submitted by the user

[2611] Data calculation: Automatic calculation of resources and generation of resource lists and budgets

[2612] Output: Display resource list and budget on the project manager screen

[2613] Step 9:

[2614] Real-time communication

[2615] The user opens the messaging screen and enters a message, which the device then sends to the server.

[2616] Input: The message entered by the user

[2617] The terminal sends a message to the server, which then distributes it to the designated members in real time.

[2618] Output: Message displayed in the chat window of the specified member

[2619] Step 10:

[2620] Monitoring the operating status of robots

[2621] The server monitors the robot's operating status in real time, checking for progress and errors.

[2622] Input: Robot operating status data

[2623] The device notifies the smartphone or head-mounted display of progress and errors.

[2624] Output: Robot progress and error notifications displayed on the user's terminal

[2625] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[2626] This invention combines an AI task management system, which aims to efficiently manage projects and work and improve productivity, with an emotion engine that recognizes user emotions, enabling more advanced task management. The system consists of a server and a client (user device). Users can access the interface via a browser or mobile app to manage tasks, check progress, and communicate. The specific operation of the system is described in detail below.

[2627] System configuration

[2628] The system consists of the following main functional modules:

[2629] 1. Task Entry Module: Used by the user to enter a new task.

[2630] 2. Database management module: A database for storing and managing task information, progress status, resource information, etc.

[2631] 3. Progress management module: Manages the progress of tasks and generates visualization data.

[2632] 4. AI engine: Analyzes the importance and urgency of the task, as well as the skill sets and workload of members.

[2633] 5. Task allocation module: Based on the analysis results of the AI ​​engine, tasks are prioritized and assigned to the appropriate members.

[2634] 6. Resource Management Module: Automatically calculates the resources required for a project and generates a resource list and budget.

[2635] 7. Communication module: Supports messaging and file sharing among members.

[2636] 8. Emotion Engine: Recognizes user emotions and reflects them in the task management process.

[2637] Recognizing and reflecting user emotions

[2638] The emotion engine analyzes the user's emotional state and adjusts task allocation and priorities based on the results. For example, if a user is feeling stressed, it will adjust the task allocation to reduce the user's workload. ...

Claims

1. means for receiving detailed task information from a user and storing the information in a database; a means for periodically obtaining the progress status of the task from the database, calculating the progress rate, and generating visualization data; a means for displaying the generated visualization data on a user's terminal in real time; A means for analyzing the importance and urgency of tasks and setting task priorities taking into account the skill sets and workloads of each member; A means for assigning tasks to appropriate members and notifying the assigned tasks to the user's terminal; a means for automatically calculating resource information for a project and generating a resource list and budget; A means of messaging and sharing files between members in real time; A system including:

2. The system according to claim 1 , further comprising means for receiving task completion reports, updating progress statuses, and distributing updated progress rates to terminals of other users in real time.

3. 2. The system according to claim 1, further comprising an AI engine that analyzes the importance and urgency of a task, the AI ​​engine further comprising means for setting a priority of the task and means for assigning the task to an appropriate member.

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