system

Abstract

We provide the system. [Solution] A user input means for registering tasks, An artificial intelligence tool for evaluating and determining the priority of tasks, A means of managing the progress of tasks, Methods for assigning task managers, A means of generating and sending reminder notifications, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In a modern business environment, many tasks and projects are in progress simultaneously, and it is difficult to manage tasks appropriately. In particular, due to a wide variety of complicated operations such as task prioritization, progress management, assignment of responders, and reminders before deadlines, individual tasks are easily overlooked. This may result in project delays and failure to address important tasks. There is a need for an efficient task management system to solve such problems.

Means for Solving the Problems

[0005] The present invention solves the above problems by providing the following means in a task management system.

[0006] 1. The user registers a task using a user input method and enters its detailed information (title, details, deadline, priority, responsible person, etc.).

[0007] 2. Artificial intelligence is used to evaluate the priority of registered tasks and determine the priority level. Furthermore, the priority level is re-evaluated based on the task attributes (deadline and importance) and updated as necessary.

[0008] 3. The progress management system allows users to update the progress of their tasks, and this information is stored in a database.

[0009] 4. The task assignment mechanism allows users to assign a person to handle a task. Furthermore, artificial intelligence analyzes the schedules and skill sets of the assigned person to suggest the most suitable candidate.

[0010] 5. The server periodically checks task deadlines and progress using a reminder notification system, and generates and sends reminder notifications to users for tasks that are nearing their deadline or are behind schedule.

[0011] This allows users to efficiently manage tasks and prevent project delays and unattended important tasks.

[0012] A "task" is a work item that requires actions or procedures to achieve a specific goal.

[0013] A "user" is the entity that operates the system and registers and manages tasks.

[0014] An "input method" refers to an interface that allows a user to register detailed task information into the system.

[0015] "Artificial intelligence" refers to algorithms that evaluate the priority of tasks within a system and determine and re-evaluate those priorities.

[0016] "Priority" refers to an indicator that shows the importance and urgency of a task.

[0017] "Progress management" refers to activities that track the progress of a task and manage the current state.

[0018] "Responsible person" refers to an individual or group who is in charge of a specific task and has the responsibility to complete it.

[0019] "Assign" refers to the act of allocating a responsible person to a specific task.

[0020] "Reminder notification" refers to a notification for prompting the user's attention based on the deadline or progress status of a task.

[0021] "Database" refers to an electronic storage device for systematically storing and managing tasks and related information.

[0022] "Server" refers to a central computer that monitors the entire system and processes various tasks.

Brief Description of Drawings

[0023] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2, which combines an emotion engine. [Modes for carrying out the invention]

[0024] Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings.

[0025] First, let's explain the terminology used in the following explanation.

[0026] In the following embodiments, the signed processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Furthermore, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include CPU (Central Processing Unit), GPU (Graphics Processing Unit), GPGPU (General-Purpose computing on Graphics Processing Units), and APU (Accelerated Processing Unit).

[0027] In the following embodiments, signed RAM (Random Access Memory) is a memory that temporarily stores information and is used as work memory by the processor.

[0028] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0029] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0030] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0031] [First Embodiment]

[0032] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0033] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0034] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0035] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0036] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0037] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0038] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0039] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0040] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0041] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0042] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0043] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0044] The present invention relates to a task management system and is implemented in the following specific manner.

[0045] 1. Register the task

[0046] User

[0047] The user launches the task management application on their device and registers a new task. When registering a task, they enter detailed information such as the title, description, due date, priority, and assigned person. This information is entered through the user interface.

[0048] server

[0049] The server receives task information from users and stores it in the database. At this time, a unique identifier for each task is generated and stored in the database. This allows tasks to be identified later.

[0050] Specific example:

[0051] "If a user creates a task titled 'Prepare Documents,' sets the details to 'Materials for next week', the due date to '2023-10-10', and the priority to 'High', the server will receive this and save it to the database."

[0052] 2. Prioritizing tasks

[0053] server

[0054] The server periodically scans the database to analyze the priority, due date, and progress of registered tasks. An artificial intelligence (AI) algorithm determines task priorities based on these attributes. Priorities are updated in the database, ensuring users always have access to the latest information.

[0055] Specific example:

[0056] "The server scans the task database and sets a higher priority for the 'Document Creation' task because its deadline is approaching."

[0057] 3. Progress Management

[0058] User

[0059] The user selects a task from the application on their device and updates its progress. After updating, the user presses the "Update" button, which sends the progress information to the server.

[0060] server

[0061] The server stores received progress information in a database and manages the progress of tasks. Based on the progress, reminder notifications and re-evaluation of priorities are performed.

[0062] Specific example:

[0063] "When a user updates the progress of a 'Document Creation' task to 50% and presses the submit button, the server saves the new progress information."

[0064] 4. Assignment of a person to handle the situation.

[0065] User

[0066] The user selects and assigns a suitable person to the task. The selection of a suitable person can be done by the user themselves or by receiving suggestions from the system.

[0067] server

[0068] The server stores the contact person information selected by the user in a database. It also has a function where AI analyzes the contact person's schedule and skill set to suggest the most suitable contact person to the user.

[0069] Specific example:

[0070] "When a user selects 'Tanaka' as the person responsible for the 'Document Creation' task and presses the assign button, the server saves the person's information."

[0071] 5. Reminder notifications

[0072] server

[0073] The server periodically checks the task database to monitor the deadlines and progress of each task. For tasks with approaching deadlines or those behind schedule, it generates and sends reminder notifications to the user.

[0074] Specific example:

[0075] The server detects that the deadline for the 'Document Creation' task is approaching in three days, generates a reminder notification, and sends it to the user.

[0076] This system allows users to efficiently register, prioritize, manage progress, assign tasks, and manage reminder notifications. This helps prevent project delays and unattended important tasks.

[0077] The following describes the processing flow.

[0078] Task registration

[0079] Processing steps

[0080] Step 1:

[0081] User

[0082] The user opens a task management application on their device.

[0083] Step 2:

[0084] User

[0085] The user clicks the "Add New Task" button.

[0086] Step 3:

[0087] User

[0088] The user enters the task title, details, due date, priority, and responsible party.

[0089] Step 4:

[0090] User

[0091] The user clicks the "Save" button.

[0092] Step 5:

[0093] server

[0094] The server saves the received task information to the database.

[0095] Step 6:

[0096] server

[0097] The server generates a unique identifier (ID) for each task and stores it in the database.

[0098] Task prioritization

[0099] Processing steps

[0100] Step 1:

[0101] server

[0102] The server periodically scans the task database.

[0103] Step 2:

[0104] server

[0105] The server analyzes the priority, deadline, and progress of each task.

[0106] Step 3:

[0107] server

[0108] The AI ​​algorithm uses this information to calculate the priority of tasks.

[0109] Step 4:

[0110] server

[0111] The server updates the database with the new priority.

[0112] Progress management

[0113] Processing steps

[0114] Step 1:

[0115] User

[0116] The user opens a task management application on their device.

[0117] Step 2:

[0118] User

[0119] The user selects a task and enters its progress.

[0120] Step 3:

[0121] User

[0122] The user clicks the "Update" button.

[0123] Step 4:

[0124] server

[0125] The server saves the received progress information to the database.

[0126] Step 5:

[0127] server

[0128] The server will send appropriate notifications and change priorities based on the progress of the tasks.

[0129] Assignment of responders

[0130] Processing steps

[0131] Step 1:

[0132] User

[0133] The user opens a task management application on their device.

[0134] Step 2:

[0135] User

[0136] The user selects a task and then selects a person to handle it.

[0137] Step 3:

[0138] User

[0139] The user clicks the "Assign" button.

[0140] Step 4:

[0141] server

[0142] The server saves the contact information it receives to the database.

[0143] Step 5:

[0144] server

[0145] The server's AI analyzes the schedules and skill sets of the responders and suggests the most suitable responder.

[0146] Reminder notification

[0147] Processing steps

[0148] Step 1:

[0149] server

[0150] The server periodically checks the task database.

[0151] Step 2:

[0152] server

[0153] The server checks the deadline and progress of each task.

[0154] Step 3:

[0155] server

[0156] Identify tasks that are nearing their deadline or are behind schedule.

[0157] Step 4:

[0158] server

[0159] The server generates a reminder notification.

[0160] Step 5:

[0161] server

[0162] The server sends reminder notifications to users via email or push notifications.

[0163] (Example 1)

[0164] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0165] Traditional task management systems make efficient task management difficult due to the cumbersome process of prioritizing tasks, tracking progress, assigning tasks to individuals, and managing reminder notifications. Furthermore, the lack of features such as re-evaluating priorities and suggesting appropriate assignees increases the risk of project delays and missed tasks.

[0166] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0167] In this invention, the server includes a user input means for registering tasks, an artificial intelligence means for evaluating and determining the priority of tasks, a means for managing the progress of tasks, a means for assigning a person to handle a task, a means for generating and sending reminder notifications, a means for sending task information from a user terminal to the server, a means for the server to receive task information and store it in a database, a means for the server to periodically scan the database and update priorities, a means for receiving reminder notifications and priorities, a means for scanning the database and generating notifications based on the progress, and a means for analyzing the schedule and skill set of a person to handle a task and suggesting the most suitable person to handle it. This makes it possible to efficiently perform a series of task management tasks, from task registration to progress management, person assignment, and reminder notifications.

[0168] A "task" refers to any work or activity necessary to achieve a specific objective.

[0169] "Users" refer to individuals or organizations that use the system to manage tasks.

[0170] "Input means" refers to the interface or device that allows users to input information into a system.

[0171] "Priority" refers to an indicator that shows the importance or urgency of a task.

[0172] "Artificial intelligence tools" refer to machine learning algorithms and data analysis methods used to evaluate tasks and determine priorities.

[0173] "Progress status" refers to the state or status that indicates how much of a task has been completed.

[0174] "Management means" refers to methods or devices for monitoring and recording task progress and other information within a system.

[0175] "Responsible party" refers to an individual or team responsible for a specific task.

[0176] "Means of assignment" refers to the method or process of assigning a person to handle a task.

[0177] A "reminder notification" refers to a notification that informs the user of task deadlines or important actions.

[0178] "Means of transmission" refers to the technologies and methods used to transmit information and data both inside and outside a system.

[0179] "User terminal" refers to a device used by a user to access the system (e.g., smartphone, personal computer, etc.).

[0180] A "server" is a central computer or network device in a system that stores and processes data.

[0181] A "database" refers to a system or software used to organize and store tasks and other information.

[0182] "Scanning methods" refer to technologies and methods that periodically check information within a database and perform necessary updates and processing.

[0183] "Methods for suggesting the optimal responder" refers to methods and algorithms for analyzing the schedules and skill sets of responders and selecting and suggesting the most suitable person or team.

[0184] This invention relates to a task management system and provides a specific method for users to effectively manage tasks. The system is implemented by combining user input means, artificial intelligence means, a database, and a server.

[0185] Task registration

[0186] User

[0187] The user launches a task management application installed on their device (e.g., smartphone, computer) and enters new task information. Specifically, they enter information such as title, details, due date, priority, and assigned person.

[0188] terminal

[0189] The terminal collects user input information and sends it to the server. The data is sent, for example, in JSON format, using the HTTP or HTTPS protocol.

[0190] server

[0191] The server processes the received task information, generates a unique identifier, and stores it in a database (e.g., MySQL®). This process makes the task identifiable later on.

[0192] Specific example

[0193] Suppose a user registers a task with the title "Create Documents," sets the details to "Materials for next week's meeting," the deadline to "2023-10-10," the priority to "High," and assigns the task to "Yamada." The terminal sends this information to the server, which then saves it to the database.

[0194] Task prioritization

[0195] server

[0196] The server periodically scans the database to analyze the priority, due date, and progress of registered tasks. This is done using artificial intelligence tools (e.g., TENSORFLOW®, PyTorch).

[0197] server

[0198] The server uses an AI model to determine task priorities and updates the database with that information. This ensures that users always see the latest priorities when they launch the application.

[0199] Specific example

[0200] The server scans the task database and sets a high priority for the "Create Document" task because its deadline is approaching.

[0201] Progress management

[0202] User

[0203] Users can use their devices to operate a task management application and update the progress of specific tasks. By entering the progress percentage and pressing the "Update" button, the information is sent to the server.

[0204] server

[0205] The server receives this progress information and stores it in the database. Based on the progress, reminder notifications and prioritization are performed.

[0206] Specific example

[0207] When a user updates the progress of a "Document Creation" task to 50% and presses the submit button, the server saves the new progress information to the database.

[0208] Assignment of responders

[0209] User

[0210] Users can assign tasks to individuals using a task management application. Users can select the individuals themselves or receive suggestions from the system.

[0211] server

[0212] The server stores user-selected contact information in a database and also has a function to suggest the most suitable contact using artificial intelligence. This is done by analyzing the contact person's schedule and skill set.

[0213] Specific example

[0214] When a user selects "Tanaka" as the person responsible for the "Document Creation" task and presses the assign button, the server saves the person's information to the database.

[0215] Reminder notification

[0216] server

[0217] The server periodically checks the task database to monitor the deadlines and progress of each task. For tasks with approaching deadlines or those behind schedule, it generates reminder notifications and sends them to the user.

[0218] Specific example

[0219] The server detects that the deadline for the "Document Creation" task is approaching in three days, generates a reminder notification, and sends it to the user.

[0220] Example of a prompt

[0221] Example prompt for task registration:

[0222] The user adds a task titled "Prepare Documents." The deadline is "2023-10-10," the priority is "High," the details are "Materials for next week's meeting," and the person responsible is "Tanaka."

[0223] Example prompts for prioritizing tasks:

[0224] The server scans the task database and uses AI to determine task priorities. For example, the "Document Creation" task is given a high priority because its deadline is approaching.

[0225] This system allows users to efficiently manage tasks and easily track progress. Furthermore, by automatically suggesting the optimal person to handle a task and its priority, the system can prevent project delays.

[0226] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0227] Step 1: Register the task

[0228] Input: The user enters task information (title, details, due date, priority, and assigned person) into the application on their device.

[0229] Operation:

[0230] The user launches a task management application on their device (smartphone, PC, etc.) and enters task information.

[0231] Specific example: Enter "Document Creation" as the title, "Materials for next week's meeting" as the details, "2023-10-10" as the deadline, "High" as the priority, and "Yamada" as the person responsible.

[0232] Output: The terminal sends the entered task information to the server.

[0233] Step 2: Save task information to the database.

[0234] Input: Task information sent from the terminal to the server.

[0235] Operation:

[0236] The server receives task information.

[0237] The server generates a unique identifier (such as a UUID).

[0238] The server saves task information to the database.

[0239] Specific example: Based on the information received by the server, a unique identifier is generated and stored in a database (e.g., MySQL). For example, task information is stored along with the UUID "123e4567-e89b-12d3-a456-426614174000".

[0240] Output: Information about the new task is saved to the database.

[0241] Step 3: Prioritize tasks

[0242] Input: Task information from the database (priority, due date, progress).

[0243] Operation:

[0244] The server periodically scans the database.

[0245] The server uses an AI model (e.g., TensorFlow, PyTorch) to determine the priority of tasks.

[0246] Specific example: The AI ​​calculates a score based on the task's deadline, progress, and priority, and then determines the priority. For example, because the deadline for the "Document Creation" task is approaching, it is given a high priority.

[0247] Output: Task information with updated priorities is saved to the database.

[0248] Step 4: Update progress

[0249] Input: Progress data updated by the user on their device.

[0250] Operation:

[0251] The user selects a target task from the application and updates its progress.

[0252] The user presses the "Update" button.

[0253] The device sends update progress information to the server.

[0254] Specific example: A user sets the progress of the "Create Document" task to 50% and presses the "Update" button.

[0255] Output: New progress information is sent to the server.

[0256] Step 5: Save progress information to database

[0257] Input: Progress data sent to the server.

[0258] Operation:

[0259] The server saves the received progress information to the database.

[0260] The server will send reminder notifications and re-evaluate priorities based on the progress.

[0261] Specific example: The server updates the database with the received progress information (50%) as a task record.

[0262] Output: The latest progress information is saved to the database.

[0263] Step 6: Assigning a responder

[0264] Input: Information about the person the user interacts with, entered on their device.

[0265] Operation:

[0266] The user selects and assigns a responder from the application.

[0267] The user presses the "Assign" button.

[0268] The device sends the responder information to the server.

[0269] The server saves the contact person information to the database.

[0270] The server uses AI to analyze the schedules and skill sets of potential respondents and suggests the most suitable person for the task.

[0271] Specific example: The user selects "Tanaka" as the person responsible for the "Document Creation" task and presses the "Assign" button.

[0272] Output: Responder information is saved in the database, and the most suitable responder is suggested.

[0273] Step 7: Generate reminder notifications

[0274] Input: Task information (deadline, progress) from the database.

[0275] Operation:

[0276] The server periodically checks the task database.

[0277] The server checks the deadlines and progress of each task.

[0278] The server generates reminder notifications for tasks with approaching deadlines or those that are behind schedule.

[0279] Specific example: The server detects that the deadline for the "Create Document" task is 3 days away and generates a reminder notification.

[0280] Output: A reminder notification is generated.

[0281] Step 8: Sending the reminder notification

[0282] Input: The generated reminder notification data.

[0283] Operation:

[0284] The server sends the reminder notification to the user.

[0285] Specific example: Use email or in-app notifications to send the reminder notification to the user terminal. For example, notify the user that the deadline for the "document creation" task is in 3 days.

[0286] Output: The reminder notification is sent to the user.

[0287] The above are the processing steps of the system program and the specific operations in each step. With this system, it is possible to efficiently manage the entire process from task registration to prioritization, progress management, assignee assignment, and generation and sending of reminder notifications.

[0288] (Application Example 1)

[0289] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart device 14 is referred to as the "terminal".

[0290] In modern factories, there is a demand for improving the efficiency of work using robots. However, due to manual task management, it is easy for task prioritization and progress management to become complicated. In addition, the lack of appropriate assignee assignment and timely reminder notifications may cause work delays. To solve these problems, a system that automates task prioritization, progress management, assignee assignment, and reminder notifications is necessary.

[0291] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0292] In this invention, the server includes an information input means for registering tasks, an intelligent algorithm means for evaluating and determining the priority of tasks, a status management means for managing the progress of tasks, a personnel allocation means for assigning personnel to handle tasks, an information notification means for generating and sending reminder notifications, a means for calculating task priority using AI, and an intelligent allocation means for proposing the optimal allocation of personnel. This enables automation of tasks in factories, optimization of priorities, effective management of progress, appropriate personnel allocation, and timely reminder notifications.

[0293] An "information input device" is a device that provides an interface for users to register tasks.

[0294] An "intelligent algorithmic means" is a device that executes an artificial intelligence algorithm to evaluate the priority of tasks and determine those priorities.

[0295] A "status management device" is a device used to track and manage the progress of a task.

[0296] A "personnel assignment tool" is a device that assigns the appropriate person to handle a task.

[0297] An "information notification means" is a device that generates and sends reminder notifications to users.

[0298] "Methods for calculation using AI" refers to devices that allow artificial intelligence to calculate the priority of tasks.

[0299] An "intelligent deployment system" is a device that uses AI to propose the optimal deployment of personnel.

[0300] As a form for implementing this invention, the configuration of a task management system for factory robots is shown below.

[0301] Configuration

[0302] 1. Information input means:

[0303] The user inputs task information through a terminal such as a smartphone or a tablet. Specifically, information such as the title, details, deadline, priority, and assignee of the task is input. As a result, the task is registered in the server.

[0304] 2. Intelligent algorithm means:

[0305] The server evaluates the priority of the task and determines the priority order using an artificial intelligence algorithm. Examples of artificial intelligence algorithms to be used include Scikit-learn and TensorFlow.

[0306] 3. Situation management means:

[0307] The user updates the progress status of the task through the terminal. The server receives this progress information and stores it in the database. Based on the progress status, the system performs reminder notifications and re-evaluates the priority order of the tasks.

[0308] 4. Personnel allocation means:

[0309] The user selects the optimal assignee for the task or assigns it after receiving the system's proposal. The server analyzes the schedule and skill set of the assignees and executes an artificial intelligence algorithm for proposing the optimal assignee.

[0310] 5. Information notification means:

[0311] The server periodically checks the deadline and progress status of the task, generates reminder notifications, and sends them to the user. As notification services, Firebase and SendGrid can be used.

[0312] Specific example

[0313] 1. Task registration:

[0314] The user registers a task on their smartphone with the title "Assemble Part A," setting the details to "Complete assembly by the end of the month," the deadline to "2023-10-31," and the priority to "High."

[0315] 2. Progress update:

[0316] The user updates the progress of the "Assemble Part A" task to 50% and presses the submit button. The new progress information is saved to the server.

[0317] 3. Assigning a person to handle the issue:

[0318] The user selects Mr. Tanaka as the person responsible for the task and saves this information to the database.

[0319] 4. Reminder notifications:

[0320] The server detects that the deadline for the "assemble part A" task is approaching in 3 days and generates a reminder notification.

[0321] Example of a prompt

[0322] Task registration prompt message:

[0323] Title: Assembly of Part A, Details: Assembly to be completed by the end of the month, Deadline: 2023-10-31, Priority: High, Person in Charge: Tanaka

[0324] Progress update prompt message:

[0325] Task ID: 123, Progress: 50%

[0326] Respondent assignment prompt message:

[0327] Task ID: 123, Responsible Person: Tanaka

[0328] Thus, by using appropriate hardware and software as the means of implementing the invention, it is possible to improve the efficiency of task management in factories.

[0329] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0330] Step 1:

[0331] The user enters and registers task information using a terminal. The entered task information includes title, details, due date, priority, and assigned person. This information is sent to the server and stored in the database. As output, a new task record with a unique identifier is generated.

[0332] Step 2:

[0333] The server periodically scans registered tasks and uses intelligent algorithms to calculate task priorities. The input is task information retrieved from a database, and attributes such as task due dates and importance are considered when calculating priorities. The output is the determined priority for each task, which is then updated in the database.

[0334] Step 3:

[0335] The user updates the task progress via their device. The user sends the progress data entered on the device (e.g., 50% complete), and the server receives it. The server stores the progress data in a database and sends reminder notifications or re-evaluates priorities as needed.

[0336] Step 4:

[0337] The server uses intelligent assignment mechanisms to suggest the most suitable responder to the task, proposing the optimal responder to the user. The input is data on the responder's schedule and skills, and the output is a suggestion of the most suitable responder. The user reviews this, selects the most suitable responder, and assigns them.

[0338] Step 5:

[0339] The server checks task deadlines and progress and generates reminder notifications. The input is task information stored in the database, targeting tasks with approaching deadlines or insufficient progress. The output is a generated reminder notification, which is sent to the corresponding user.

[0340] In this way, a task management system for factory robots is realized through specific actions at each step.

[0341] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0342] This invention combines an emotion engine with a task management system to optimize task prioritization and reminder notifications. It is implemented in the following specific way:

[0343] 1. Register the task

[0344] User

[0345] The user launches the task management application on their device and registers a new task. When registering a task, they enter detailed information such as the title, description, due date, priority, and assigned person. This information is entered through the user interface.

[0346] server

[0347] The server receives task information from users and stores it in the database. At this time, a unique identifier for each task is generated and stored in the database. This allows tasks to be identified later.

[0348] Specific example:

[0349] "If a user creates a task titled 'Prepare Documents,' sets the details to 'Materials for next week', the due date to '2023-10-10', and the priority to 'High', the server will receive this and save it to the database."

[0350] 2. Prioritizing tasks

[0351] server

[0352] The server periodically scans the database to analyze the priority, due date, and progress of registered tasks. An artificial intelligence (AI) algorithm determines task priorities based on these attributes. Priorities are updated in the database, ensuring users always have access to the latest information.

[0353] Emotional Engine

[0354] The emotion engine recognizes the user's emotions and sends that information to the server. The server's AI adjusts task priorities based on the user's emotions.

[0355] Specific example:

[0356] "The server scans the task database and sets a high priority for the 'Document Creation' task because its deadline is approaching. Furthermore, if the emotion engine detects user stress, its priority is increased even further."

[0357] 3. Progress Management

[0358] User

[0359] The user selects a task from the application on their device and updates its progress. After updating, the user presses the "Update" button, which sends the progress information to the server.

[0360] server

[0361] The server stores received progress information in a database and manages the progress of tasks. Based on the progress, reminder notifications and re-evaluation of priorities are performed.

[0362] Specific example:

[0363] "When a user updates the progress of a 'Document Creation' task to 50% and presses the submit button, the server saves the new progress information."

[0364] 4. Assignment of a person to handle the situation.

[0365] User

[0366] The user selects and assigns a suitable person to the task. The selection of a suitable person can be done by the user themselves or by receiving suggestions from the system.

[0367] server

[0368] The server stores the contact person information selected by the user in a database. It also has a function where AI analyzes the contact person's schedule and skill set to suggest the most suitable contact person to the user.

[0369] Specific example:

[0370] "When a user selects 'Tanaka' as the person responsible for the 'Document Creation' task and presses the assign button, the server saves the person's information."

[0371] 5. Reminder notifications

[0372] server

[0373] The server periodically checks the task database to monitor the deadlines and progress of each task. For tasks with approaching deadlines or those behind schedule, it generates and sends reminder notifications to the user.

[0374] Emotional Engine

[0375] The emotion engine optimizes the content and timing of reminder notifications based on the user's emotions. For example, if the user is feeling stressed, it will soften the content of the reminder notification or adjust the frequency of notifications.

[0376] Specific example:

[0377] "The server detects that the 'Document Creation' task is due in three days and generates and sends a reminder notification to the user. If the emotion engine detects user stress, it changes the content of the reminder notification to an encouraging message."

[0378] This system allows users to efficiently register, prioritize, manage progress, assign tasks, and manage reminder notifications. Furthermore, the emotion engine enables task management that takes the user's emotional state into account, more effectively preventing project delays and unattended important tasks.

[0379] The following describes the processing flow.

[0380] Task registration

[0381] Processing steps

[0382] Step 1:

[0383] User

[0384] The user opens a task management application on their device.

[0385] Step 2:

[0386] User

[0387] The user clicks the "Add New Task" button.

[0388] Step 3:

[0389] User

[0390] The user enters the task title, details, due date, priority, and responsible party.

[0391] Step 4:

[0392] User

[0393] The user clicks the "Save" button.

[0394] Step 5:

[0395] server

[0396] The server saves the received task information to the database.

[0397] Step 6:

[0398] server

[0399] The server generates a unique identifier (ID) for each task and stores it in the database.

[0400] Task prioritization

[0401] Processing steps

[0402] Step 1:

[0403] server

[0404] The server periodically scans the task database.

[0405] Step 2:

[0406] server

[0407] The server analyzes the priority, deadline, and progress of each task.

[0408] Step 3:

[0409] server

[0410] The AI ​​algorithm uses this information to calculate the priority of tasks.

[0411] Step 4:

[0412] server

[0413] The server updates the database with the new priority.

[0414] Step 5:

[0415] Emotional Engine

[0416] The emotion engine recognizes the user's emotions.

[0417] Step 6:

[0418] server

[0419] The server's AI adjusts task priorities based on emotional data received from the emotion engine.

[0420] Progress management

[0421] Processing steps

[0422] Step 1:

[0423] User

[0424] The user opens a task management application on their device.

[0425] Step 2:

[0426] User

[0427] The user selects a task and enters its progress.

[0428] Step 3:

[0429] User

[0430] The user clicks the "Update" button.

[0431] Step 4:

[0432] server

[0433] The server saves the received progress information to the database.

[0434] Step 5:

[0435] server

[0436] The server will send appropriate notifications and change priorities based on the progress of the tasks.

[0437] Assignment of responders

[0438] Processing steps

[0439] Step 1:

[0440] User

[0441] The user opens a task management application on their device.

[0442] Step 2:

[0443] User

[0444] The user selects a task and then selects a person to handle it.

[0445] Step 3:

[0446] User

[0447] The user clicks the "Assign" button.

[0448] Step 4:

[0449] server

[0450] The server saves the contact information it receives to the database.

[0451] Step 5:

[0452] server

[0453] The server's AI analyzes the schedules and skill sets of the responders and suggests the most suitable responder.

[0454] Reminder notification

[0455] Processing steps

[0456] Step 1:

[0457] server

[0458] The server periodically checks the task database.

[0459] Step 2:

[0460] server

[0461] The server checks the deadline and progress of each task.

[0462] Step 3:

[0463] server

[0464] Identify tasks that are nearing their deadline or are behind schedule.

[0465] Step 4:

[0466] server

[0467] The server generates a reminder notification.

[0468] Step 5:

[0469] server

[0470] The server sends reminder notifications to users via email or push notifications.

[0471] Step 6:

[0472] Emotional Engine

[0473] The emotion engine recognizes the user's emotions.

[0474] Step 7:

[0475] server

[0476] The server adjusts the content and timing of reminder notifications based on the emotional data received from the emotion engine.

[0477] (Example 2)

[0478] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0479] Traditional task management systems often struggle to accurately prioritize tasks and lack the flexibility to manage tasks based on users' emotional states. Furthermore, task assignment and reminder notifications are frequently not adequately optimized. This can lead to project delays, unattended important tasks, and decreased work efficiency.

[0480] In Example 2, the identification processing by the identification processing unit 290 of the data processing device 12 is realized by the following means. In this invention, the server includes a user input means for registering tasks, an artificial intelligence means for evaluating the priority of tasks and determining the priority, an emotion analysis means for analyzing the user's emotional state and adjusting the task priority, a means for managing the progress of tasks, a means for assigning a person to handle the task, and a means for generating and sending reminder notifications. This makes it possible to manage tasks while taking into account the user's emotional state, and by optimizing the task priority and the content of reminder notifications, it becomes possible to effectively prevent project delays and unattended important tasks.

[0481] A "user input means for registering tasks" is an interface for users to input task information and register it in the system.

[0482] "An artificial intelligence means for evaluating and determining task priority" refers to artificial intelligence technology that analyzes registered task information and determines task priority based on its importance and urgency.

[0483] "An emotion analysis method that analyzes a user's emotional state and adjusts task priorities" refers to a technology that analyzes a user's emotional data and dynamically adjusts task priorities based on the results.

[0484] "Means for managing task progress" refers to a system for tracking the progress of a task and updating that progress as needed.

[0485] "A means of assigning a person to a task" refers to a function for selecting a person suitable for a task and saving that information linked to the task.

[0486] "Means for generating and sending reminder notifications" refers to a system for creating and sending reminder notifications to users based on the progress and deadline of a task.

[0487] This invention relates to a system for users to efficiently manage tasks. This system includes user input means, artificial intelligence means, sentiment analysis means, progress management means, person assignment means, and reminder notification generation means to achieve task prioritization and optimization of reminder notifications.

[0488] This system consists of the following components:

[0489] User input method:

[0490] Users enter task information through a task management application on their device. This information includes title, details, due date, priority, and assigned person. This information is entered using a user interface (e.g., React, Vue.js). For example, a user might register a task called "Document Creation," setting the details to "Documents for next week's meeting," the due date to "2023-10-10," and the priority to "High." This information is then sent from the device to the server.

[0491] Artificial intelligence tools:

[0492] The server stores the received task information in a database (e.g., MySQL, PostgreSQL). The server scans the database for tasks at regular intervals and uses artificial intelligence algorithms (e.g., TensorFlow, PyTorch) to determine task priorities. For example, if the server detects that the deadline for a "document creation" task is approaching, it sets a higher priority.

[0493] Emotion analysis means:

[0494] The emotion engine analyzes the user's emotional state in real time and sends that information to the server. The emotion analysis uses an emotion analysis API (e.g., Microsoft® Azure® Cognitive Services). For example, if the emotion engine detects user stress, the server uses that information to further prioritize tasks.

[0495] Progress management methods:

[0496] Users update task progress through an application on their device. After entering the progress and pressing the submit button, the information is sent to the server. The server saves the new progress information to its database. For example, if a user sets the progress of the "Document Creation" task to 50% and presses the submit button, the server saves the new progress information.

[0497] Method for assigning a responder:

[0498] The user selects a suitable person to handle a task and sends the person's information to the server. The server stores this information in a database. The server's AI also analyzes the person's schedule and skill set and suggests the most suitable person to the user. For example, if the user selects "Tanaka" as the person to handle the "document creation" task, the server will save that information.

[0499] Reminder notification generation method:

[0500] The server periodically scans the task database to identify tasks with approaching deadlines or those behind schedule. It generates and sends reminder notifications using a reminder notification system (e.g., Twilio API). Furthermore, an emotion engine analyzes the user's emotional state before sending notifications, optimizing the content and timing. For example, if the server detects that the "Create Document" task is due in three days, it generates a reminder notification and sends it to the user. If the emotion engine detects user stress, it changes the notification content to an encouraging message.

[0501] Example of a prompt

[0502] "Explain how a system that assists users with task management uses an emotion engine to optimize task priorities and notification content."

[0503] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0504] Step 1: Enter task information

[0505] User:

[0506] The user launches a task management application on their device and enters task information. Specifically, they enter the task title, details, due date, priority, and assigned person.

[0507] Input: Task title, details, deadline, priority, responsible party, and other relevant information.

[0508] Output: Input task information

[0509] Specific action: The user registers a task with the title "Create Documents," sets the details to "Materials for next week's meeting," the deadline to "2023-10-10," and the priority to "High."

[0510] Step 2: Submit task information

[0511] Terminal:

[0512] The terminal sends the entered task information to the server. This is done using an API endpoint (e.g., a POST request).

[0513] Input: Task information entered by the user

[0514] Output: Request to send to server

[0515] Specific action: The terminal sends the user's input information to the server.

[0516] Step 3: Save task information

[0517] server:

[0518] The server saves the received task information to the database. During this process, a unique identifier is generated and assigned to each task.

[0519] Input: Task information sent from the device

[0520] Output: Task information and unique identifier stored in the database

[0521] Specific operation: The server saves the "Create Document" task to the database and generates a unique identifier.

[0522] Step 4: Scan the database and determine task priorities.

[0523] server:

[0524] The server scans the database at regular intervals to analyze task deadlines, priorities, and progress. An artificial intelligence algorithm is used to determine task priorities.

[0525] Input: Task information in the database

[0526] Output: Prioritized task information

[0527] Specific action: The server detects that the deadline for the "Document Creation" task is approaching and sets it to a higher priority.

[0528] Step 5: Analyze user sentiment and readjust priorities

[0529] Emotional engine:

[0530] The emotion engine analyzes the user's emotional state in real time and sends that information to the server.

[0531] Input: User sentiment data

[0532] Output: Sentiment data including analysis results

[0533] Specific operation: The emotion engine detects the user's stress level and sends that information to the server.

[0534] server:

[0535] The server readjusts task priorities based on information received from the emotion engine.

[0536] Input: Sentiment data and existing task information

[0537] Output: Re-adjusted priority

[0538] Specific action: The server further increases the priority of the task.

[0539] Step 6: Update progress

[0540] User:

[0541] The user updates the task progress by entering progress information in the application on their device.

[0542] Input: Latest progress of the task

[0543] Output: Update Request

[0544] Specific action: The user sets the progress of the "Create Document" task to 50%.

[0545] Terminal:

[0546] The device sends progress information to the server.

[0547] Input: Updated progress information

[0548] Output: Request to send to server

[0549] Specific action: The device sends progress information to the server.

[0550] server:

[0551] The server saves the new progress information to the database.

[0552] Input: Progress information sent from the device

[0553] Output: Latest progress information stored in the database

[0554] Specific action: The server saves the new progress information.

[0555] Step 7: Assigning a responder

[0556] User:

[0557] The user selects the appropriate person to handle the task and enters the assignment information.

[0558] Input: Information of the person in charge

[0559] Output: Assignment Request

[0560] Specific action: The user selects "Tanaka" as the person responsible for the "Document Creation" task.

[0561] Terminal:

[0562] The device sends the responder information to the server.

[0563] Input: Person in charge information

[0564] Output: Request to send to server

[0565] Specific action: The device sends the responder's information to the server.

[0566] server:

[0567] The server stores contact information in a database, and the AI ​​suggests the most suitable contact person.

[0568] Input: Respondent information sent from the device

[0569] Output: Responder information stored in the database, suggested best responder

[0570] Specific operation: The server stores contact information, and the AI ​​suggests the most suitable contact person.

[0571] Step 8: Generate and send reminder notifications

[0572] server:

[0573] The server periodically scans the task database to identify tasks that are nearing their deadline or are behind schedule.

[0574] Input: Task information in the database

[0575] Output: Verification result

[0576] Specific action: The server detects that the deadline for the "Document Creation" task is approaching.

[0577] server:

[0578] Based on the confirmation results, a reminder notification is generated and sent to the user.

[0579] Input: Confirmation result

[0580] Output: Reminder notification

[0581] Specific operation: The server generates a reminder notification and sends it to the user.

[0582] Emotional engine:

[0583] Before sending a reminder notification, the emotion engine analyzes the user's emotional state and adjusts the timing and content to the optimal level.

[0584] Input: User sentiment data

[0585] Output: Adjustment of notification content based on analysis results.

[0586] Specific operation: The emotion engine detects the user's stress level and changes the notification content to an encouraging message.

[0587] (Application Example 2)

[0588] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0589] In modern industrial settings, managing complex tasks and setting appropriate priorities are critical challenges. In particular, the lack of task management that considers workers' emotions and stress levels can lead to decreased productivity. Furthermore, when multiple robots work together, inefficient communication and task redistribution between robots can result in task delays and the neglect of critical tasks. To solve this problem, a system is needed that allows numerous robots to efficiently perform tasks in industrial applications while also considering user emotions.

[0590] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a user input means for registering tasks, an artificial intelligence means for evaluating the priority of tasks and determining the priority, an emotion engine means for recognizing emotions and adjusting the priority using that information, a means for managing the progress of tasks, a means for assigning a person to handle a task, a communication means for realizing cooperation with multiple work robots in industrial applications, and a means for generating and transmitting reminder notifications. This enables effective task management that takes into account the user's emotional state and realizes efficient coordinated work of multiple work robots in industrial applications.

[0591] A "user input device" is an interface device used by a user to input information in order to register a task.

[0592] "Artificial intelligence tools" refer to algorithms and systems that analyze input task information, evaluate task priority and progress, and provide the optimal response.

[0593] An "emotional engine" is a technology that recognizes a user's emotions and adjusts task priorities based on that information.

[0594] "Means for managing task progress" refers to systems or devices for checking the progress status of registered tasks and recording and monitoring their progress.

[0595] "A means of assigning a person to a task" refers to a function that selects the most suitable person to handle a registered task and assigns that task to them.

[0596] "Means for generating and sending reminder notifications" refers to a system that creates reminder notifications based on task deadlines and progress, and notifies users or responsible parties at the appropriate time.

[0597] "Communication methods" refer to protocols and hardware used to exchange information necessary for multiple work robots to cooperate and perform tasks.

[0598] In this invention, the following systems and processes are introduced in a task management system for a factory, in order to achieve effective task management that takes into account the emotional states of multiple work robots and users.

[0599] Hardware and software used

[0600] Hardware: Work robots, cloud servers, user terminals

[0601] Software: MySQL database, TensorFlow, Affectiva SDK, Twilio API

[0602] System components and their functions

[0603] 1. User input method for registering tasks:

[0604] The server provides an interface for users to register new tasks through a task management application. Users enter information such as the task title, details, due date, priority, and assigned person. This information is sent to the server and stored in the database.

[0605] Specific example:

[0606] The user registers a task titled "Equipment Maintenance," setting the details to "Maintenance work scheduled for the weekend," the deadline to "2023-12-01," and the priority to "High." This information is sent to the server.

[0607] 2. Artificial intelligence methods for evaluating task priority:

[0608] The server periodically scans the database and uses TensorFlow to evaluate the priority of registered tasks. An AI algorithm analyzes task deadlines, progress, and other factors to determine priority.

[0609] Specific example:

[0610] The server uses AI to detect when the deadline for "equipment maintenance" tasks is approaching and sets them to a higher priority.

[0611] 3. Means of managing task progress:

[0612] As the robot completes a task, it sends real-time progress information to the server. The server stores this information in a database and monitors the task's progress.

[0613] Specific example:

[0614] The robot updates the progress of the "equipment maintenance" task up to 50% and sends that information to the server.

[0615] 4. Methods for assigning task managers:

[0616] The server selects the most suitable robot and assigns it tasks. AI analyzes each robot's schedule and skill set to suggest the optimal assignment.

[0617] Specific example:

[0618] The server suggests the most suitable robot for the "equipment maintenance" task and assigns the task to that robot.

[0619] 5. Means for generating and sending reminder notifications:

[0620] The server checks task deadlines and progress and generates reminder notifications. It uses the Twilio API to send notifications to administrators and robots. It uses the Affectiva SDK to detect the user's emotional state and adjust the content and timing of reminders accordingly.

[0621] Specific example:

[0622] The server detects that the deadline for the "equipment maintenance" task is approaching in three days and generates and sends a reminder notification to the user. If the emotion engine detects that the user is stressed, the content of the reminder notification is made gentler.

[0623] Program processing

[0624] The server integrates all of the above methods and runs the overall task management system. MySQL is used for the database, and TensorFlow is used for the AI ​​algorithm. Affectiva SDK is used for sentiment analysis, and the Twilio API is used for reminder notifications.

[0625] Example of a prompt:

[0626] "Please provide Python code that adjusts task priorities based on stress levels and sends appropriate reminder notifications."

[0627] The above describes the embodiments for carrying out the present invention. This enables task management that takes into account the user's emotional state, and allows for the effective and efficient operation of multiple work robots.

[0628] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0629] Step 1:

[0630] The user launches the task management application on their device and registers a new task. The user enters information such as the task title, details, due date, priority, and assigned person. This information is sent to the server and stored in a MySQL database.

[0631] input:

[0632] Task information registered by the user (title, details, deadline, priority, responsible party)

[0633] output:

[0634] Task data stored on the server

[0635] Specific operation:

[0636] The user enters "Equipment maintenance," sets the details as "Maintenance work scheduled for the weekend," the deadline as "2023-12-01," and the priority as "High," and then submits the form.

[0637] Step 2:

[0638] The server periodically scans the database and evaluates the priority of registered tasks. It uses TensorFlow's AI algorithm to analyze task deadlines and progress to determine priorities. The results are updated in the database.

[0639] input:

[0640] Task information stored in the database

[0641] output:

[0642] Task data with re-evaluated priorities

[0643] Specific operation:

[0644] The server uses AI to analyze that the deadline for the "equipment maintenance" task is approaching and resets its priority to "highest."

[0645] Step 3:

[0646] Users update the progress of ongoing tasks using their terminals. Users enter the progress percentage and send it to the server. This progress information is stored in a database.

[0647] input:

[0648] User-updated progress information

[0649] output:

[0650] Progress data stored on the server

[0651] Specific operation:

[0652] The user updates the "Equipment Maintenance" progress to 50% and presses the submit button.

[0653] Step 4:

[0654] The server uses an emotion engine to recognize the user's emotions and adjusts task priorities based on that information. It uses the Affectiva SDK to perform emotion analysis and saves the results to a database.

[0655] input:

[0656] User sentiment data

[0657] output:

[0658] Task prioritization adjusted based on emotional data

[0659] Specific operation:

[0660] The emotion engine detects when the user's stress level is high and further increases the task's priority.

[0661] Step 5:

[0662] The server assigns the most suitable robot based on progress information and priority. The server uses AI to evaluate each robot's schedule and skill set and assign tasks accordingly.

[0663] input:

[0664] Task priority, schedule and skill set information for each robot.

[0665] output:

[0666] Robot assignment information optimized for each task

[0667] Specific operation:

[0668] The server selects robot A, which is best suited for the "equipment maintenance" task, and sends a notification to that robot.

[0669] Step 6:

[0670] The server generates and sends reminder notifications to the user based on task deadlines and progress. It uses the Twilio API to send notifications and the Affectiva SDK to adjust the notification content based on the user's emotional state.

[0671] input:

[0672] Task deadlines, progress information, and user sentiment data

[0673] output:

[0674] Reminder notifications sent to users

[0675] Specific operation:

[0676] The server detects that the deadline for the "equipment maintenance" task is approaching in three days and, sensing the user's stress, sends a notification containing a kind and encouraging message.

[0677] Through each of the above steps, this system effectively manages tasks and integrates robots while taking into account the user's emotional state.

[0678] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0679] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0680] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0681] [Second Embodiment]

[0682] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0683] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0684] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0685] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0686] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0687] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0688] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0689] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0690] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0691] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0692] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0693] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0694] The present invention relates to a task management system and is implemented in the following specific manner.

[0695] 1. Register the task

[0696] User

[0697] The user launches the task management application on their device and registers a new task. When registering a task, they enter detailed information such as the title, description, due date, priority, and assigned person. This information is entered through the user interface.

[0698] server

[0699] The server receives task information from users and stores it in the database. At this time, a unique identifier for each task is generated and stored in the database. This allows tasks to be identified later.

[0700] Specific example:

[0701] "If a user creates a task titled 'Prepare Documents,' sets the details to 'Materials for next week', the due date to '2023-10-10', and the priority to 'High', the server will receive this and save it to the database."

[0702] 2. Prioritizing tasks

[0703] server

[0704] The server periodically scans the database to analyze the priority, due date, and progress of registered tasks. An artificial intelligence (AI) algorithm determines task priorities based on these attributes. Priorities are updated in the database, ensuring users always have access to the latest information.

[0705] Specific example:

[0706] "The server scans the task database and sets a higher priority for the 'Document Creation' task because its deadline is approaching."

[0707] 3. Progress Management

[0708] User

[0709] The user selects a task from the application on their device and updates its progress. After updating, the user presses the "Update" button, which sends the progress information to the server.

[0710] server

[0711] The server stores received progress information in a database and manages the progress of tasks. Based on the progress, reminder notifications and re-evaluation of priorities are performed.

[0712] Specific example:

[0713] "When a user updates the progress of a 'Document Creation' task to 50% and presses the submit button, the server saves the new progress information."

[0714] 4. Assignment of a person to handle the situation.

[0715] User

[0716] The user selects and assigns a suitable person to the task. The selection of a suitable person can be done by the user themselves or by receiving suggestions from the system.

[0717] server

[0718] The server stores the contact person information selected by the user in a database. It also has a function where AI analyzes the contact person's schedule and skill set to suggest the most suitable contact person to the user.

[0719] Specific example:

[0720] "When a user selects 'Tanaka' as the person responsible for the 'Document Creation' task and presses the assign button, the server saves the person's information."

[0721] 5. Reminder notifications

[0722] server

[0723] The server periodically checks the task database to monitor the deadlines and progress of each task. For tasks with approaching deadlines or those behind schedule, it generates and sends reminder notifications to the user.

[0724] Specific example:

[0725] The server detects that the deadline for the 'Document Creation' task is approaching in three days, generates a reminder notification, and sends it to the user.

[0726] This system allows users to efficiently register, prioritize, manage progress, assign tasks, and manage reminder notifications. This helps prevent project delays and unattended important tasks.

[0727] The following describes the processing flow.

[0728] Task registration

[0729] Processing steps

[0730] Step 1:

[0731] User

[0732] The user opens a task management application on their device.

[0733] Step 2:

[0734] User

[0735] The user clicks the "Add New Task" button.

[0736] Step 3:

[0737] User

[0738] The user enters the task title, details, due date, priority, and responsible party.

[0739] Step 4:

[0740] User

[0741] The user clicks the "Save" button.

[0742] Step 5:

[0743] server

[0744] The server saves the received task information to the database.

[0745] Step 6:

[0746] server

[0747] The server generates a unique identifier (ID) for each task and stores it in the database.

[0748] Task prioritization

[0749] Processing steps

[0750] Step 1:

[0751] server

[0752] The server periodically scans the task database.

[0753] Step 2:

[0754] server

[0755] The server analyzes the priority, deadline, and progress of each task.

[0756] Step 3:

[0757] server

[0758] The AI ​​algorithm uses this information to calculate the priority of tasks.

[0759] Step 4:

[0760] server

[0761] The server updates the database with the new priority.

[0762] Progress management

[0763] Processing steps

[0764] Step 1:

[0765] User

[0766] The user opens a task management application on their device.

[0767] Step 2:

[0768] User

[0769] The user selects a task and enters its progress.

[0770] Step 3:

[0771] User

[0772] The user clicks the "Update" button.

[0773] Step 4:

[0774] server

[0775] The server saves the received progress information to the database.

[0776] Step 5:

[0777] server

[0778] The server will send appropriate notifications and change priorities based on the progress of the tasks.

[0779] Assignment of responders

[0780] Processing steps

[0781] Step 1:

[0782] User

[0783] The user opens a task management application on their device.

[0784] Step 2:

[0785] User

[0786] The user selects a task and then selects a person to handle it.

[0787] Step 3:

[0788] User

[0789] The user clicks the "Assign" button.

[0790] Step 4:

[0791] server

[0792] The server saves the contact information it receives to the database.

[0793] Step 5:

[0794] server

[0795] The server's AI analyzes the schedules and skill sets of the responders and suggests the most suitable responder.

[0796] Reminder notification

[0797] Processing steps

[0798] Step 1:

[0799] server

[0800] The server periodically checks the task database.

[0801] Step 2:

[0802] server

[0803] The server checks the deadline and progress of each task.

[0804] Step 3:

[0805] server

[0806] Identify tasks that are nearing their deadline or are behind schedule.

[0807] Step 4:

[0808] server

[0809] The server generates a reminder notification.

[0810] Step 5:

[0811] server

[0812] The server sends reminder notifications to users via email or push notifications.

[0813] (Example 1)

[0814] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0815] Traditional task management systems make efficient task management difficult due to the cumbersome process of prioritizing tasks, tracking progress, assigning tasks to individuals, and managing reminder notifications. Furthermore, the lack of features such as re-evaluating priorities and suggesting appropriate assignees increases the risk of project delays and missed tasks.

[0816] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0817] In this invention, the server includes a user input means for registering tasks, an artificial intelligence means for evaluating and determining the priority of tasks, a means for managing the progress of tasks, a means for assigning a person to handle a task, a means for generating and sending reminder notifications, a means for sending task information from a user terminal to the server, a means for the server to receive task information and store it in a database, a means for the server to periodically scan the database and update priorities, a means for receiving reminder notifications and priorities, a means for scanning the database and generating notifications based on the progress, and a means for analyzing the schedule and skill set of a person to handle a task and suggesting the most suitable person to handle it. This makes it possible to efficiently perform a series of task management tasks, from task registration to progress management, person assignment, and reminder notifications.

[0818] A "task" refers to any work or activity necessary to achieve a specific objective.

[0819] "Users" refer to individuals or organizations that use the system to manage tasks.

[0820] "Input means" refers to the interface or device that allows users to input information into a system.

[0821] "Priority" refers to an indicator that shows the importance or urgency of a task.

[0822] "Artificial intelligence tools" refer to machine learning algorithms and data analysis methods used to evaluate tasks and determine priorities.

[0823] "Progress status" refers to the state or status that indicates how much of a task has been completed.

[0824] "Management means" refers to methods or devices for monitoring and recording task progress and other information within a system.

[0825] "Responsible party" refers to an individual or team responsible for a specific task.

[0826] "Means of assignment" refers to the method or process of assigning a person to handle a task.

[0827] A "reminder notification" refers to a notification that informs the user of task deadlines or important actions.

[0828] "Means of transmission" refers to the technologies and methods used to transmit information and data both inside and outside a system.

[0829] "User terminal" refers to a device used by a user to access the system (e.g., smartphone, personal computer, etc.).

[0830] A "server" is a central computer or network device in a system that stores and processes data.

[0831] A "database" refers to a system or software used to organize and store tasks and other information.

[0832] "Scanning methods" refer to technologies and methods that periodically check information within a database and perform necessary updates and processing.

[0833] "Methods for suggesting the optimal responder" refers to methods and algorithms for analyzing the schedules and skill sets of responders and selecting and suggesting the most suitable person or team.

[0834] This invention relates to a task management system and provides a specific method for users to effectively manage tasks. The system is implemented by combining user input means, artificial intelligence means, a database, and a server.

[0835] Task registration

[0836] User

[0837] The user launches a task management application installed on their device (e.g., smartphone, computer) and enters new task information. Specifically, they enter information such as title, details, due date, priority, and assigned person.

[0838] terminal

[0839] The terminal collects user input information and sends it to the server. The data is sent, for example, in JSON format, using the HTTP or HTTPS protocol.

[0840] server

[0841] The server processes the received task information, generates a unique identifier, and stores it in a database (e.g., MySQL). This process makes the task identifiable later on.

[0842] Specific example

[0843] Suppose a user registers a task with the title "Create Documents," sets the details to "Materials for next week's meeting," the deadline to "2023-10-10," the priority to "High," and assigns the task to "Yamada." The terminal sends this information to the server, which then saves it to the database.

[0844] Task prioritization

[0845] server

[0846] The server periodically scans the database to analyze the priority, due date, and progress of registered tasks. This is done using artificial intelligence tools (e.g., TensorFlow, PyTorch).

[0847] server

[0848] The server uses an AI model to determine task priorities and updates the database with that information. This ensures that users always see the latest priorities when they launch the application.

[0849] Specific example

[0850] The server scans the task database and sets a high priority for the "Create Document" task because its deadline is approaching.

[0851] Progress management

[0852] User

[0853] Users can use their devices to operate a task management application and update the progress of specific tasks. By entering the progress percentage and pressing the "Update" button, the information is sent to the server.

[0854] server

[0855] The server receives this progress information and stores it in the database. Based on the progress, reminder notifications and prioritization are performed.

[0856] Specific example

[0857] When a user updates the progress of a "Document Creation" task to 50% and presses the submit button, the server saves the new progress information to the database.

[0858] Assignment of responders

[0859] User

[0860] Users can assign tasks to individuals using a task management application. Users can select the individuals themselves or receive suggestions from the system.

[0861] server

[0862] The server stores user-selected contact information in a database and also has a function to suggest the most suitable contact using artificial intelligence. This is done by analyzing the contact person's schedule and skill set.

[0863] Specific example

[0864] When a user selects "Tanaka" as the person responsible for the "Document Creation" task and presses the assign button, the server saves the person's information to the database.

[0865] Reminder notification

[0866] server

[0867] The server periodically checks the task database to monitor the deadlines and progress of each task. For tasks with approaching deadlines or those behind schedule, it generates reminder notifications and sends them to the user.

[0868] Specific example

[0869] The server detects that the deadline for the "Document Creation" task is approaching in three days, generates a reminder notification, and sends it to the user.

[0870] Example of a prompt

[0871] Example prompt for task registration:

[0872] The user adds a task titled "Prepare Documents." The deadline is "2023-10-10," the priority is "High," the details are "Materials for next week's meeting," and the person responsible is "Tanaka."

[0873] Example prompts for prioritizing tasks:

[0874] The server scans the task database and uses AI to determine task priorities. For example, the "Document Creation" task is given a high priority because its deadline is approaching.

[0875] This system allows users to efficiently manage tasks and easily track progress. Furthermore, by automatically suggesting the optimal person to handle a task and its priority, the system can prevent project delays.

[0876] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0877] Step 1: Register the task

[0878] Input: The user enters task information (title, details, due date, priority, and assigned person) into the application on their device.

[0879] Operation:

[0880] The user launches a task management application on their device (smartphone, PC, etc.) and enters task information.

[0881] Specific example: Enter "Document Creation" as the title, "Materials for next week's meeting" as the details, "2023-10-10" as the deadline, "High" as the priority, and "Yamada" as the person responsible.

[0882] Output: The terminal sends the entered task information to the server.

[0883] Step 2: Save task information to the database.

[0884] Input: Task information sent from the terminal to the server.

[0885] Operation:

[0886] The server receives task information.

[0887] The server generates a unique identifier (such as a UUID).

[0888] The server saves task information to the database.

[0889] Specific example: Based on the information received by the server, a unique identifier is generated and stored in a database (e.g., MySQL). For example, task information is stored along with the UUID "123e4567-e89b-12d3-a456-426614174000".

[0890] Output: Information about the new task is saved to the database.

[0891] Step 3: Prioritize tasks

[0892] Input: Task information from the database (priority, due date, progress).

[0893] Operation:

[0894] The server periodically scans the database.

[0895] The server uses an AI model (e.g., TensorFlow, PyTorch) to determine the priority of tasks.

[0896] Specific example: The AI ​​calculates a score based on the task's deadline, progress, and priority, and then determines the priority. For example, because the deadline for the "Document Creation" task is approaching, it is given a high priority.

[0897] Output: Task information with updated priorities is saved to the database.

[0898] Step 4: Update progress

[0899] Input: Progress data updated by the user on their device.

[0900] Operation:

[0901] The user selects a target task from the application and updates its progress.

[0902] The user presses the "Update" button.

[0903] The device sends update progress information to the server.

[0904] Specific example: A user sets the progress of the "Create Document" task to 50% and presses the "Update" button.

[0905] Output: New progress information is sent to the server.

[0906] Step 5: Save progress information to database

[0907] Input: Progress data sent to the server.

[0908] Operation:

[0909] The server saves the received progress information to the database.

[0910] The server will send reminder notifications and re-evaluate priorities based on the progress.

[0911] Specific example: The server updates the database with the received progress information (50%) as a task record.

[0912] Output: The latest progress information is saved to the database.

[0913] Step 6: Assigning a responder

[0914] Input: Information about the person the user interacts with, entered on their device.

[0915] Operation:

[0916] The user selects and assigns a responder from the application.

[0917] The user presses the "Assign" button.

[0918] The device sends the responder information to the server.

[0919] The server saves the contact person information to the database.

[0920] The server uses AI to analyze the schedules and skill sets of potential respondents and suggests the most suitable person for the task.

[0921] Specific example: The user selects "Tanaka" as the person responsible for the "Document Creation" task and presses the "Assign" button.

[0922] Output: Responder information is saved in the database, and the most suitable responder is suggested.

[0923] Step 7: Generate reminder notifications

[0924] Input: Task information (deadline, progress) from the database.

[0925] Operation:

[0926] The server periodically checks the task database.

[0927] The server checks the deadlines and progress of each task.

[0928] The server generates reminder notifications for tasks with approaching deadlines or those that are behind schedule.

[0929] Specific example: The server detects that the deadline for the "Create Document" task is 3 days away and generates a reminder notification.

[0930] Output: A reminder notification is generated.

[0931] Step 8: Sending a reminder notification

[0932] Input: Generated reminder notification data.

[0933] Operation:

[0934] The server sends a reminder notification to the user.

[0935] Specific example: Send reminder notifications to the user's device using email or in-app notifications. For example, notify the user that the deadline for the "Create Document" task is in 3 days.

[0936] Output: A reminder notification is sent to the user.

[0937] The above describes the system's program processing steps and the specific actions performed at each step. This system enables efficient management of the entire process, from task registration and prioritization to progress management, assignment of personnel, and generation and sending of reminder notifications.

[0938] (Application Example 1)

[0939] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0940] In modern factories, there is a demand for increased efficiency through the use of robots. However, manual task management often leads to cumbersome prioritization and progress tracking. Furthermore, the lack of appropriate personnel assignment and timely reminder notifications can cause work delays. To address these challenges, a system is needed that automates task prioritization, progress tracking, personnel assignment, and reminder notifications.

[0941] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0942] In this invention, the server includes an information input means for registering tasks, an intelligent algorithm means for evaluating and determining the priority of tasks, a status management means for managing the progress of tasks, a personnel allocation means for assigning personnel to handle tasks, an information notification means for generating and sending reminder notifications, a means for calculating task priority using AI, and an intelligent allocation means for proposing the optimal allocation of personnel. This enables automation of tasks in factories, optimization of priorities, effective management of progress, appropriate personnel allocation, and timely reminder notifications.

[0943] An "information input device" is a device that provides an interface for users to register tasks.

[0944] An "intelligent algorithmic means" is a device that executes an artificial intelligence algorithm to evaluate the priority of tasks and determine those priorities.

[0945] A "status management device" is a device used to track and manage the progress of a task.

[0946] A "personnel assignment tool" is a device that assigns the appropriate person to handle a task.

[0947] An "information notification means" is a device that generates and sends reminder notifications to users.

[0948] "Methods for calculation using AI" refers to devices that allow artificial intelligence to calculate the priority of tasks.

[0949] An "intelligent deployment system" is a device that uses AI to propose the optimal deployment of personnel.

[0950] As an embodiment for carrying out this invention, the configuration of a task management system for a factory robot is shown below.

[0951] composition

[0952] 1. Information input means:

[0953] Users input task information via devices such as smartphones and tablets. Specifically, they enter information such as the task title, details, deadline, priority, and assigned person. This registers the task on the server.

[0954] 2. Intelligent algorithmic means:

[0955] The server evaluates the priority of tasks and uses artificial intelligence algorithms to determine the priority. Examples of AI algorithms used include Scikit-learn and TensorFlow.

[0956] 3. Situation management measures:

[0957] Users update task progress via their devices. The server receives this progress information and stores it in a database. Based on the progress, the system sends reminder notifications and re-evaluates task priorities.

[0958] 4. Personnel allocation methods:

[0959] The user selects or accepts system suggestions to assign the most suitable person to a task. The server analyzes the responders' schedules and skill sets and runs an artificial intelligence algorithm to suggest the best person.

[0960] 5. Information Notification Means:

[0961] The server periodically checks task deadlines and progress, generates reminder notifications, and sends them to users. Firebase or SendGrid can be used as notification services.

[0962] Specific example

[0963] 1. Task registration:

[0964] The user registers a task on their smartphone with the title "Assemble Part A," setting the details to "Complete assembly by the end of the month," the deadline to "2023-10-31," and the priority to "High."

[0965] 2. Progress update:

[0966] The user updates the progress of the "Assemble Part A" task to 50% and presses the submit button. The new progress information is saved to the server.

[0967] 3. Assigning a person to handle the issue:

[0968] The user selects Mr. Tanaka as the person responsible for the task and saves this information to the database.

[0969] 4. Reminder notifications:

[0970] The server detects that the deadline for the "assemble part A" task is approaching in 3 days and generates a reminder notification.

[0971] Example of a prompt

[0972] Task registration prompt message:

[0973] Title: Assembly of Part A, Details: Assembly to be completed by the end of the month, Deadline: 2023-10-31, Priority: High, Person in Charge: Tanaka

[0974] Progress update prompt message:

[0975] Task ID: 123, Progress: 50%

[0976] Respondent assignment prompt message:

[0977] Task ID: 123, Responsible Person: Tanaka

[0978] Thus, by using appropriate hardware and software as the means of implementing the invention, it is possible to improve the efficiency of task management in factories.

[0979] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0980] Step 1:

[0981] The user enters and registers task information using a terminal. The entered task information includes title, details, due date, priority, and assigned person. This information is sent to the server and stored in the database. As output, a new task record with a unique identifier is generated.

[0982] Step 2:

[0983] The server periodically scans registered tasks and uses intelligent algorithms to calculate task priorities. The input is task information retrieved from a database, and attributes such as task due dates and importance are considered when calculating priorities. The output is the determined priority for each task, which is then updated in the database.

[0984] Step 3:

[0985] The user updates the task progress via their device. The user sends the progress data entered on the device (e.g., 50% complete), and the server receives it. The server stores the progress data in a database and sends reminder notifications or re-evaluates priorities as needed.

[0986] Step 4:

[0987] The server uses intelligent assignment mechanisms to suggest the most suitable responder to the task, proposing the optimal responder to the user. The input is data on the responder's schedule and skills, and the output is a suggestion of the most suitable responder. The user reviews this, selects the most suitable responder, and assigns them.

[0988] Step 5:

[0989] The server checks task deadlines and progress and generates reminder notifications. The input is task information stored in the database, targeting tasks with approaching deadlines or insufficient progress. The output is a generated reminder notification, which is sent to the corresponding user.

[0990] In this way, a task management system for factory robots is realized through specific actions at each step.

[0991] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0992] This invention combines an emotion engine with a task management system to optimize task prioritization and reminder notifications. It is implemented in the following specific way:

[0993] 1. Register the task

[0994] User

[0995] The user launches the task management application on their device and registers a new task. When registering a task, they enter detailed information such as the title, description, due date, priority, and assigned person. This information is entered through the user interface.

[0996] server

[0997] The server receives task information from users and stores it in the database. At this time, a unique identifier for each task is generated and stored in the database. This allows tasks to be identified later.

[0998] Specific example:

[0999] "If a user creates a task titled 'Prepare Documents,' sets the details to 'Materials for next week', the due date to '2023-10-10', and the priority to 'High', the server will receive this and save it to the database."

[1000] 2. Prioritizing tasks

[1001] server

[1002] The server periodically scans the database to analyze the priority, due date, and progress of registered tasks. An artificial intelligence (AI) algorithm determines task priorities based on these attributes. Priorities are updated in the database, ensuring users always have access to the latest information.

[1003] Emotional Engine

[1004] The emotion engine recognizes the user's emotions and sends that information to the server. The server's AI adjusts task priorities based on the user's emotions.

[1005] Specific example:

[1006] "The server scans the task database and sets a high priority for the 'Document Creation' task because its deadline is approaching. Furthermore, if the emotion engine detects user stress, its priority is increased even further."

[1007] 3. Progress Management

[1008] User

[1009] The user selects a task from the application on their device and updates its progress. After updating, the user presses the "Update" button, which sends the progress information to the server.

[1010] server

[1011] The server stores received progress information in a database and manages the progress of tasks. Based on the progress, reminder notifications and re-evaluation of priorities are performed.

[1012] Specific example:

[1013] "When a user updates the progress of a 'Document Creation' task to 50% and presses the submit button, the server saves the new progress information."

[1014] 4. Assignment of a person to handle the situation.

[1015] User

[1016] The user selects and assigns a suitable person to the task. The selection of a suitable person can be done by the user themselves or by receiving suggestions from the system.

[1017] server

[1018] The server stores the contact person information selected by the user in a database. It also has a function where AI analyzes the contact person's schedule and skill set to suggest the most suitable contact person to the user.

[1019] Specific example:

[1020] "When a user selects 'Tanaka' as the person responsible for the 'Document Creation' task and presses the assign button, the server saves the person's information."

[1021] 5. Reminder notifications

[1022] server

[1023] The server periodically checks the task database to monitor the deadlines and progress of each task. For tasks with approaching deadlines or those behind schedule, it generates and sends reminder notifications to the user.

[1024] Emotional Engine

[1025] The emotion engine optimizes the content and timing of reminder notifications based on the user's emotions. For example, if the user is feeling stressed, it will soften the content of the reminder notification or adjust the frequency of notifications.

[1026] Specific example:

[1027] "The server detects that the 'Document Creation' task is due in three days and generates and sends a reminder notification to the user. If the emotion engine detects user stress, it changes the content of the reminder notification to an encouraging message."

[1028] This system allows users to efficiently register, prioritize, manage progress, assign tasks, and manage reminder notifications. Furthermore, the emotion engine enables task management that takes the user's emotional state into account, more effectively preventing project delays and unattended important tasks.

[1029] The following describes the processing flow.

[1030] Task registration

[1031] Processing steps

[1032] Step 1:

[1033] User

[1034] The user opens a task management application on their device.

[1035] Step 2:

[1036] User

[1037] The user clicks the "Add New Task" button.

[1038] Step 3:

[1039] User

[1040] The user enters the task title, details, due date, priority, and responsible party.

[1041] Step 4:

[1042] User

[1043] The user clicks the "Save" button.

[1044] Step 5:

[1045] server

[1046] The server saves the received task information to the database.

[1047] Step 6:

[1048] server

[1049] The server generates a unique identifier (ID) for each task and stores it in the database.

[1050] Task prioritization

[1051] Processing steps

[1052] Step 1:

[1053] server

[1054] The server periodically scans the task database.

[1055] Step 2:

[1056] server

[1057] The server analyzes the priority, deadline, and progress of each task.

[1058] Step 3:

[1059] server

[1060] The AI ​​algorithm uses this information to calculate the priority of tasks.

[1061] Step 4:

[1062] server

[1063] The server updates the database with the new priority.

[1064] Step 5:

[1065] Emotional Engine

[1066] The emotion engine recognizes the user's emotions.

[1067] Step 6:

[1068] server

[1069] The server's AI adjusts task priorities based on emotional data received from the emotion engine.

[1070] Progress management

[1071] Processing steps

[1072] Step 1:

[1073] User

[1074] The user opens a task management application on their device.

[1075] Step 2:

[1076] User

[1077] The user selects a task and enters its progress.

[1078] Step 3:

[1079] User

[1080] The user clicks the "Update" button.

[1081] Step 4:

[1082] server

[1083] The server saves the received progress information to the database.

[1084] Step 5:

[1085] server

[1086] The server will send appropriate notifications and change priorities based on the progress of the tasks.

[1087] Assignment of responders

[1088] Processing steps

[1089] Step 1:

[1090] User

[1091] The user opens a task management application on their device.

[1092] Step 2:

[1093] User

[1094] The user selects a task and then selects a person to handle it.

[1095] Step 3:

[1096] User

[1097] The user clicks the "Assign" button.

[1098] Step 4:

[1099] server

[1100] The server saves the contact information it receives to the database.

[1101] Step 5:

[1102] server

[1103] The server's AI analyzes the schedules and skill sets of the responders and suggests the most suitable responder.

[1104] Reminder notification

[1105] Processing steps

[1106] Step 1:

[1107] server

[1108] The server periodically checks the task database.

[1109] Step 2:

[1110] server

[1111] The server checks the deadline and progress of each task.

[1112] Step 3:

[1113] server

[1114] Identify tasks that are nearing their deadline or are behind schedule.

[1115] Step 4:

[1116] server

[1117] The server generates a reminder notification.

[1118] Step 5:

[1119] server

[1120] The server sends reminder notifications to users via email or push notifications.

[1121] Step 6:

[1122] Emotional Engine

[1123] The emotion engine recognizes the user's emotions.

[1124] Step 7:

[1125] server

[1126] The server adjusts the content and timing of reminder notifications based on the emotional data received from the emotion engine.

[1127] (Example 2)

[1128] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[1129] Traditional task management systems often struggle to accurately prioritize tasks and lack the flexibility to manage tasks based on users' emotional states. Furthermore, task assignment and reminder notifications are frequently not adequately optimized. This can lead to project delays, unattended important tasks, and decreased work efficiency.

[1130] In Example 2, the identification processing by the identification processing unit 290 of the data processing device 12 is realized by the following means. In this invention, the server includes a user input means for registering tasks, an artificial intelligence means for evaluating the priority of tasks and determining the priority, an emotion analysis means for analyzing the user's emotional state and adjusting the task priority, a means for managing the progress of tasks, a means for assigning a person to handle the task, and a means for generating and sending reminder notifications. This makes it possible to manage tasks while taking into account the user's emotional state, and by optimizing the task priority and the content of reminder notifications, it becomes possible to effectively prevent project delays and unattended important tasks.

[1131] A "user input means for registering tasks" is an interface for users to input task information and register it in the system.

[1132] "An artificial intelligence means for evaluating and determining task priority" refers to artificial intelligence technology that analyzes registered task information and determines task priority based on its importance and urgency.

[1133] "An emotion analysis method that analyzes a user's emotional state and adjusts task priorities" refers to a technology that analyzes a user's emotional data and dynamically adjusts task priorities based on the results.

[1134] "Means for managing task progress" refers to a system for tracking the progress of a task and updating that progress as needed.

[1135] "A means of assigning a person to a task" refers to a function for selecting a person suitable for a task and saving that information linked to the task.

[1136] "Means for generating and sending reminder notifications" refers to a system for creating and sending reminder notifications to users based on the progress and deadline of a task.

[1137] This invention relates to a system for users to efficiently manage tasks. This system includes user input means, artificial intelligence means, sentiment analysis means, progress management means, person assignment means, and reminder notification generation means to achieve task prioritization and optimization of reminder notifications.

[1138] This system consists of the following components:

[1139] User input method:

[1140] Users enter task information through a task management application on their device. This information includes title, details, due date, priority, and assigned person. This information is entered using a user interface (e.g., React, Vue.js). For example, a user might register a task called "Document Creation," setting the details to "Documents for next week's meeting," the due date to "2023-10-10," and the priority to "High." This information is then sent from the device to the server.

[1141] Artificial intelligence tools:

[1142] The server stores the received task information in a database (e.g., MySQL, PostgreSQL). The server scans the database for tasks at regular intervals and uses artificial intelligence algorithms (e.g., TensorFlow, PyTorch) to determine task priorities. For example, if the server detects that the deadline for a "document creation" task is approaching, it sets a higher priority.

[1143] Emotion analysis means:

[1144] The emotion engine analyzes the user's emotional state in real time and sends that information to the server. The emotion analysis uses an emotion analysis API (e.g., Microsoft Azure Cognitive Services). For example, if the emotion engine detects user stress, the server uses that information to further prioritize tasks.

[1145] Progress management methods:

[1146] Users update task progress through an application on their device. After entering the progress and pressing the submit button, the information is sent to the server. The server saves the new progress information to its database. For example, if a user sets the progress of the "Document Creation" task to 50% and presses the submit button, the server saves the new progress information.

[1147] Method for assigning a responder:

[1148] The user selects a suitable person to handle a task and sends the person's information to the server. The server stores this information in a database. The server's AI also analyzes the person's schedule and skill set and suggests the most suitable person to the user. For example, if the user selects "Tanaka" as the person to handle the "document creation" task, the server will save that information.

[1149] Reminder notification generation method:

[1150] The server periodically scans the task database to identify tasks with approaching deadlines or those behind schedule. It generates and sends reminder notifications using a reminder notification system (e.g., Twilio API). Furthermore, an emotion engine analyzes the user's emotional state before sending notifications, optimizing the content and timing. For example, if the server detects that the "Create Document" task is due in three days, it generates a reminder notification and sends it to the user. If the emotion engine detects user stress, it changes the notification content to an encouraging message.

[1151] Example of a prompt

[1152] "Explain how a system that assists users with task management uses an emotion engine to optimize task priorities and notification content."

[1153] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1154] Step 1: Enter task information

[1155] User:

[1156] The user launches a task management application on their device and enters task information. Specifically, they enter the task title, details, due date, priority, and assigned person.

[1157] Input: Task title, details, deadline, priority, responsible party, and other relevant information.

[1158] Output: Input task information

[1159] Specific action: The user registers a task with the title "Create Documents," sets the details to "Materials for next week's meeting," the deadline to "2023-10-10," and the priority to "High."

[1160] Step 2: Submit task information

[1161] Terminal:

[1162] The terminal sends the entered task information to the server. This is done using an API endpoint (e.g., a POST request).

[1163] Input: Task information entered by the user

[1164] Output: Request to send to server

[1165] Specific action: The terminal sends the user's input information to the server.

[1166] Step 3: Save task information

[1167] server:

[1168] The server saves the received task information to the database. During this process, a unique identifier is generated and assigned to each task.

[1169] Input: Task information sent from the device

[1170] Output: Task information and unique identifier stored in the database

[1171] Specific operation: The server saves the "Create Document" task to the database and generates a unique identifier.

[1172] Step 4: Scan the database and determine task priorities.

[1173] server:

[1174] The server scans the database at regular intervals to analyze task deadlines, priorities, and progress. An artificial intelligence algorithm is used to determine task priorities.

[1175] Input: Task information in the database

[1176] Output: Prioritized task information

[1177] Specific action: The server detects that the deadline for the "Document Creation" task is approaching and sets it to a higher priority.

[1178] Step 5: Analyze user sentiment and readjust priorities

[1179] Emotional engine:

[1180] The emotion engine analyzes the user's emotional state in real time and sends that information to the server.

[1181] Input: User sentiment data

[1182] Output: Sentiment data including analysis results

[1183] Specific operation: The emotion engine detects the user's stress level and sends that information to the server.

[1184] server:

[1185] The server readjusts task priorities based on information received from the emotion engine.

[1186] Input: Sentiment data and existing task information

[1187] Output: Re-adjusted priority

[1188] Specific action: The server further increases the priority of the task.

[1189] Step 6: Update progress

[1190] User:

[1191] The user updates the task progress by entering progress information in the application on their device.

[1192] Input: Latest progress of the task

[1193] Output: Update Request

[1194] Specific action: The user sets the progress of the "Create Document" task to 50%.

[1195] Terminal:

[1196] The device sends progress information to the server.

[1197] Input: Updated progress information

[1198] Output: Request to send to server

[1199] Specific action: The device sends progress information to the server.

[1200] server:

[1201] The server saves the new progress information to the database.

[1202] Input: Progress information sent from the device

[1203] Output: Latest progress information stored in the database

[1204] Specific action: The server saves the new progress information.

[1205] Step 7: Assigning a responder

[1206] User:

[1207] The user selects the appropriate person to handle the task and enters the assignment information.

[1208] Input: Information of the person in charge

[1209] Output: Assignment Request

[1210] Specific action: The user selects "Tanaka" as the person responsible for the "Document Creation" task.

[1211] Terminal:

[1212] The device sends the responder information to the server.

[1213] Input: Person in charge information

[1214] Output: Request to send to server

[1215] Specific action: The device sends the responder's information to the server.

[1216] server:

[1217] The server stores contact information in a database, and the AI ​​suggests the most suitable contact person.

[1218] Input: Respondent information sent from the device

[1219] Output: Responder information stored in the database, suggested best responder

[1220] Specific operation: The server stores contact information, and the AI ​​suggests the most suitable contact person.

[1221] Step 8: Generate and send reminder notifications

[1222] server:

[1223] The server periodically scans the task database to identify tasks that are nearing their deadline or are behind schedule.

[1224] Input: Task information in the database

[1225] Output: Verification result

[1226] Specific action: The server detects that the deadline for the "Document Creation" task is approaching.

[1227] server:

[1228] Based on the confirmation results, a reminder notification is generated and sent to the user.

[1229] Input: Confirmation result

[1230] Output: Reminder notification

[1231] Specific operation: The server generates a reminder notification and sends it to the user.

[1232] Emotional engine:

[1233] Before sending a reminder notification, the emotion engine analyzes the user's emotional state and adjusts the timing and content to the optimal level.

[1234] Input: User sentiment data

[1235] Output: Adjustment of notification content based on analysis results.

[1236] Specific operation: The emotion engine detects the user's stress level and changes the notification content to an encouraging message.

[1237] (Application Example 2)

[1238] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[1239] In modern industrial settings, managing complex tasks and setting appropriate priorities are critical challenges. In particular, the lack of task management that considers workers' emotions and stress levels can lead to decreased productivity. Furthermore, when multiple robots work together, inefficient communication and task redistribution between robots can result in task delays and the neglect of critical tasks. To solve this problem, a system is needed that allows numerous robots to efficiently perform tasks in industrial applications while also considering user emotions.

[1240] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a user input means for registering tasks, an artificial intelligence means for evaluating the priority of tasks and determining the priority, an emotion engine means for recognizing emotions and adjusting the priority using that information, a means for managing the progress of tasks, a means for assigning a person to handle a task, a communication means for realizing cooperation with multiple work robots in industrial applications, and a means for generating and transmitting reminder notifications. This enables effective task management that takes into account the user's emotional state and realizes efficient coordinated work of multiple work robots in industrial applications.

[1241] A "user input device" is an interface device used by a user to input information in order to register a task.

[1242] "Artificial intelligence tools" refer to algorithms and systems that analyze input task information, evaluate task priority and progress, and provide the optimal response.

[1243] An "emotional engine" is a technology that recognizes a user's emotions and adjusts task priorities based on that information.

[1244] "Means for managing task progress" refers to systems or devices for checking the progress status of registered tasks and recording and monitoring their progress.

[1245] "A means of assigning a person to a task" refers to a function that selects the most suitable person to handle a registered task and assigns that task to them.

[1246] "Means for generating and sending reminder notifications" refers to a system that creates reminder notifications based on task deadlines and progress, and notifies users or responsible parties at the appropriate time.

[1247] "Communication methods" refer to protocols and hardware used to exchange information necessary for multiple work robots to cooperate and perform tasks.

[1248] In this invention, the following systems and processes are introduced in a task management system for a factory, in order to achieve effective task management that takes into account the emotional states of multiple work robots and users.

[1249] Hardware and software used

[1250] Hardware: Work robots, cloud servers, user terminals

[1251] Software: MySQL database, TensorFlow, Affectiva SDK, Twilio API

[1252] System components and their functions

[1253] 1. User input method for registering tasks:

[1254] The server provides an interface for users to register new tasks through a task management application. Users enter information such as the task title, details, due date, priority, and assigned person. This information is sent to the server and stored in the database.

[1255] Specific example:

[1256] The user registers a task titled "Equipment Maintenance," setting the details to "Maintenance work scheduled for the weekend," the deadline to "2023-12-01," and the priority to "High." This information is sent to the server.

[1257] 2. Artificial intelligence methods for evaluating task priority:

[1258] The server periodically scans the database and uses TensorFlow to evaluate the priority of registered tasks. An AI algorithm analyzes task deadlines, progress, and other factors to determine priority.

[1259] Specific example:

[1260] The server uses AI to detect when the deadline for "equipment maintenance" tasks is approaching and sets them to a higher priority.

[1261] 3. Means of managing task progress:

[1262] As the robot completes a task, it sends real-time progress information to the server. The server stores this information in a database and monitors the task's progress.

[1263] Specific example:

[1264] The robot updates the progress of the "equipment maintenance" task up to 50% and sends that information to the server.

[1265] 4. Methods for assigning task managers:

[1266] The server selects the most suitable robot and assigns it tasks. AI analyzes each robot's schedule and skill set to suggest the optimal assignment.

[1267] Specific example:

[1268] The server suggests the most suitable robot for the "equipment maintenance" task and assigns the task to that robot.

[1269] 5. Means for generating and sending reminder notifications:

[1270] The server checks task deadlines and progress and generates reminder notifications. It uses the Twilio API to send notifications to administrators and robots. It uses the Affectiva SDK to detect the user's emotional state and adjust the content and timing of reminders accordingly.

[1271] Specific example:

[1272] The server detects that the deadline for the "equipment maintenance" task is approaching in three days and generates and sends a reminder notification to the user. If the emotion engine detects that the user is stressed, the content of the reminder notification is made gentler.

[1273] Program processing

[1274] The server integrates all of the above methods and runs the overall task management system. MySQL is used for the database, and TensorFlow is used for the AI ​​algorithm. Affectiva SDK is used for sentiment analysis, and the Twilio API is used for reminder notifications.

[1275] Example of a prompt:

[1276] "Please provide Python code that adjusts task priorities based on stress levels and sends appropriate reminder notifications."

[1277] The above describes the embodiments for carrying out the present invention. This enables task management that takes into account the user's emotional state, and allows for the effective and efficient operation of multiple work robots.

[1278] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1279] Step 1:

[1280] The user launches the task management application on their device and registers a new task. The user enters information such as the task title, details, due date, priority, and assigned person. This information is sent to the server and stored in a MySQL database.

[1281] input:

[1282] Task information registered by the user (title, details, deadline, priority, responsible party)

[1283] output:

[1284] Task data stored on the server

[1285] Specific operation:

[1286] The user enters "Equipment maintenance," sets the details as "Maintenance work scheduled for the weekend," the deadline as "2023-12-01," and the priority as "High," and then submits the form.

[1287] Step 2:

[1288] The server periodically scans the database and evaluates the priority of registered tasks. It uses TensorFlow's AI algorithm to analyze task deadlines and progress to determine priorities. The results are updated in the database.

[1289] input:

[1290] Task information stored in the database

[1291] output:

[1292] Task data with re-evaluated priorities

[1293] Specific operation:

[1294] The server uses AI to analyze that the deadline for the "equipment maintenance" task is approaching and resets its priority to "highest."

[1295] Step 3:

[1296] Users update the progress of ongoing tasks using their terminals. Users enter the progress percentage and send it to the server. This progress information is stored in a database.

[1297] input:

[1298] User-updated progress information

[1299] output:

[1300] Progress data stored on the server

[1301] Specific operation:

[1302] The user updates the "Equipment Maintenance" progress to 50% and presses the submit button.

[1303] Step 4:

[1304] The server uses an emotion engine to recognize the user's emotions and adjusts task priorities based on that information. It uses the Affectiva SDK to perform emotion analysis and saves the results to a database.

[1305] input:

[1306] User sentiment data

[1307] output:

[1308] Task prioritization adjusted based on emotional data

[1309] Specific operation:

[1310] The emotion engine detects when the user's stress level is high and further increases the task's priority.

[1311] Step 5:

[1312] The server assigns the most suitable robot based on progress information and priority. The server uses AI to evaluate each robot's schedule and skill set and assign tasks accordingly.

[1313] input:

[1314] Task priority, schedule and skill set information for each robot.

[1315] output:

[1316] Robot assignment information optimized for each task

[1317] Specific operation:

[1318] The server selects robot A, which is best suited for the "equipment maintenance" task, and sends a notification to that robot.

[1319] Step 6:

[1320] The server generates and sends reminder notifications to the user based on task deadlines and progress. It uses the Twilio API to send notifications and the Affectiva SDK to adjust the notification content based on the user's emotional state.

[1321] input:

[1322] Task deadlines, progress information, and user sentiment data

[1323] output:

[1324] Reminder notifications sent to users

[1325] Specific operation:

[1326] The server detects that the deadline for the "equipment maintenance" task is approaching in three days and, sensing the user's stress, sends a notification containing a kind and encouraging message.

[1327] Through each of the above steps, this system effectively manages tasks and integrates robots while taking into account the user's emotional state.

[1328] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1329] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1330] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[1331] [Third Embodiment]

[1332] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[1333] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1334] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1335] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[1336] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1337] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1338] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1339] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1340] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1341] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1342] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1343] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[1344] The present invention relates to a task management system and is implemented in the following specific manner.

[1345] 1. Register the task

[1346] User

[1347] The user launches the task management application on their device and registers a new task. When registering a task, they enter detailed information such as the title, description, due date, priority, and assigned person. This information is entered through the user interface.

[1348] server

[1349] The server receives task information from users and stores it in the database. At this time, a unique identifier for each task is generated and stored in the database. This allows tasks to be identified later.

[1350] Specific example:

[1351] "If a user creates a task titled 'Prepare Documents,' sets the details to 'Materials for next week', the due date to '2023-10-10', and the priority to 'High', the server will receive this and save it to the database."

[1352] 2. Prioritizing tasks

[1353] server

[1354] The server periodically scans the database to analyze the priority, due date, and progress of registered tasks. An artificial intelligence (AI) algorithm determines task priorities based on these attributes. Priorities are updated in the database, ensuring users always have access to the latest information.

[1355] Specific example:

[1356] "The server scans the task database and sets a higher priority for the 'Document Creation' task because its deadline is approaching."

[1357] 3. Progress Management

[1358] User

[1359] The user selects a task from the application on their device and updates its progress. After updating, the user presses the "Update" button, which sends the progress information to the server.

[1360] server

[1361] The server stores received progress information in a database and manages the progress of tasks. Based on the progress, reminder notifications and re-evaluation of priorities are performed.

[1362] Specific example:

[1363] "When a user updates the progress of a 'Document Creation' task to 50% and presses the submit button, the server saves the new progress information."

[1364] 4. Assignment of a person to handle the situation.

[1365] User

[1366] The user selects and assigns a suitable person to the task. The selection of a suitable person can be done by the user themselves or by receiving suggestions from the system.

[1367] server

[1368] The server stores the contact person information selected by the user in a database. It also has a function where AI analyzes the contact person's schedule and skill set to suggest the most suitable contact person to the user.

[1369] Specific example:

[1370] "When a user selects 'Tanaka' as the person responsible for the 'Document Creation' task and presses the assign button, the server saves the person's information."

[1371] 5. Reminder notifications

[1372] server

[1373] The server periodically checks the task database to monitor the deadlines and progress of each task. For tasks with approaching deadlines or those behind schedule, it generates and sends reminder notifications to the user.

[1374] Specific example:

[1375] The server detects that the deadline for the 'Document Creation' task is approaching in three days, generates a reminder notification, and sends it to the user.

[1376] This system allows users to efficiently register, prioritize, manage progress, assign tasks, and manage reminder notifications. This helps prevent project delays and unattended important tasks.

[1377] The following describes the processing flow.

[1378] Task registration

[1379] Processing steps

[1380] Step 1:

[1381] User

[1382] The user opens a task management application on their device.

[1383] Step 2:

[1384] User

[1385] The user clicks the "Add New Task" button.

[1386] Step 3:

[1387] User

[1388] The user enters the task title, details, due date, priority, and responsible party.

[1389] Step 4:

[1390] User

[1391] The user clicks the "Save" button.

[1392] Step 5:

[1393] server

[1394] The server saves the received task information to the database.

[1395] Step 6:

[1396] server

[1397] The server generates a unique identifier (ID) for each task and stores it in the database.

[1398] Task prioritization

[1399] Processing steps

[1400] Step 1:

[1401] server

[1402] The server periodically scans the task database.

[1403] Step 2:

[1404] server

[1405] The server analyzes the priority, deadline, and progress of each task.

[1406] Step 3:

[1407] server

[1408] The AI ​​algorithm uses this information to calculate the priority of tasks.

[1409] Step 4:

[1410] server

[1411] The server updates the database with the new priority.

[1412] Progress management

[1413] Processing steps

[1414] Step 1:

[1415] User

[1416] The user opens a task management application on their device.

[1417] Step 2:

[1418] User

[1419] The user selects a task and enters its progress.

[1420] Step 3:

[1421] User

[1422] The user clicks the "Update" button.

[1423] Step 4:

[1424] server

[1425] The server saves the received progress information to the database.

[1426] Step 5:

[1427] server

[1428] The server will send appropriate notifications and change priorities based on the progress of the tasks.

[1429] Assignment of responders

[1430] Processing steps

[1431] Step 1:

[1432] User

[1433] The user opens a task management application on their device.

[1434] Step 2:

[1435] User

[1436] The user selects a task and then selects a person to handle it.

[1437] Step 3:

[1438] User

[1439] The user clicks the "Assign" button.

[1440] Step 4:

[1441] server

[1442] The server saves the contact information it receives to the database.

[1443] Step 5:

[1444] server

[1445] The server's AI analyzes the schedules and skill sets of the responders and suggests the most suitable responder.

[1446] Reminder notification

[1447] Processing steps

[1448] Step 1:

[1449] server

[1450] The server periodically checks the task database.

[1451] Step 2:

[1452] server

[1453] The server checks the deadline and progress of each task.

[1454] Step 3:

[1455] server

[1456] Identify tasks that are nearing their deadline or are behind schedule.

[1457] Step 4:

[1458] server

[1459] The server generates a reminder notification.

[1460] Step 5:

[1461] server

[1462] The server sends reminder notifications to users via email or push notifications.

[1463] (Example 1)

[1464] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1465] Traditional task management systems make efficient task management difficult due to the cumbersome process of prioritizing tasks, tracking progress, assigning tasks to individuals, and managing reminder notifications. Furthermore, the lack of features such as re-evaluating priorities and suggesting appropriate assignees increases the risk of project delays and missed tasks.

[1466] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1467] In this invention, the server includes a user input means for registering tasks, an artificial intelligence means for evaluating and determining the priority of tasks, a means for managing the progress of tasks, a means for assigning a person to handle a task, a means for generating and sending reminder notifications, a means for sending task information from a user terminal to the server, a means for the server to receive task information and store it in a database, a means for the server to periodically scan the database and update priorities, a means for receiving reminder notifications and priorities, a means for scanning the database and generating notifications based on the progress, and a means for analyzing the schedule and skill set of a person to handle a task and suggesting the most suitable person to handle it. This makes it possible to efficiently perform a series of task management tasks, from task registration to progress management, person assignment, and reminder notifications.

[1468] A "task" refers to any work or activity necessary to achieve a specific objective.

[1469] "Users" refer to individuals or organizations that use the system to manage tasks.

[1470] "Input means" refers to the interface or device that allows users to input information into a system.

[1471] "Priority" refers to an indicator that shows the importance or urgency of a task.

[1472] "Artificial intelligence tools" refer to machine learning algorithms and data analysis methods used to evaluate tasks and determine priorities.

[1473] "Progress status" refers to the state or status that indicates how much of a task has been completed.

[1474] "Management means" refers to methods or devices for monitoring and recording task progress and other information within a system.

[1475] "Responsible party" refers to an individual or team responsible for a specific task.

[1476] "Means of assignment" refers to the method or process of assigning a person to handle a task.

[1477] A "reminder notification" refers to a notification that informs the user of task deadlines or important actions.

[1478] "Means of transmission" refers to the technologies and methods used to transmit information and data both inside and outside a system.

[1479] "User terminal" refers to a device used by a user to access the system (e.g., smartphone, personal computer, etc.).

[1480] A "server" is a central computer or network device in a system that stores and processes data.

[1481] A "database" refers to a system or software used to organize and store tasks and other information.

[1482] "Scanning methods" refer to technologies and methods that periodically check information within a database and perform necessary updates and processing.

[1483] "Methods for suggesting the optimal responder" refers to methods and algorithms for analyzing the schedules and skill sets of responders and selecting and suggesting the most suitable person or team.

[1484] This invention relates to a task management system and provides a specific method for users to effectively manage tasks. The system is implemented by combining user input means, artificial intelligence means, a database, and a server.

[1485] Task registration

[1486] User

[1487] The user launches a task management application installed on their device (e.g., smartphone, computer) and enters new task information. Specifically, they enter information such as title, details, due date, priority, and assigned person.

[1488] terminal

[1489] The terminal collects user input information and sends it to the server. The data is sent, for example, in JSON format, using the HTTP or HTTPS protocol.

[1490] server

[1491] The server processes the received task information, generates a unique identifier, and stores it in a database (e.g., MySQL). This process makes the task identifiable later on.

[1492] Specific example

[1493] Suppose a user registers a task with the title "Create Documents," sets the details to "Materials for next week's meeting," the deadline to "2023-10-10," the priority to "High," and assigns the task to "Yamada." The terminal sends this information to the server, which then saves it to the database.

[1494] Task prioritization

[1495] server

[1496] The server periodically scans the database to analyze the priority, due date, and progress of registered tasks. This is done using artificial intelligence tools (e.g., TensorFlow, PyTorch).

[1497] server

[1498] The server uses an AI model to determine task priorities and updates the database with that information. This ensures that users always see the latest priorities when they launch the application.

[1499] Specific example

[1500] The server scans the task database and sets a high priority for the "Create Document" task because its deadline is approaching.

[1501] Progress management

[1502] User

[1503] Users can use their devices to operate a task management application and update the progress of specific tasks. By entering the progress percentage and pressing the "Update" button, the information is sent to the server.

[1504] server

[1505] The server receives this progress information and stores it in the database. Based on the progress, reminder notifications and prioritization are performed.

[1506] Specific example

[1507] When a user updates the progress of a "Document Creation" task to 50% and presses the submit button, the server saves the new progress information to the database.

[1508] Assignment of responders

[1509] User

[1510] Users can assign tasks to individuals using a task management application. Users can select the individuals themselves or receive suggestions from the system.

[1511] server

[1512] The server stores user-selected contact information in a database and also has a function to suggest the most suitable contact using artificial intelligence. This is done by analyzing the contact person's schedule and skill set.

[1513] Specific example

[1514] When a user selects "Tanaka" as the person responsible for the "Document Creation" task and presses the assign button, the server saves the person's information to the database.

[1515] Reminder notification

[1516] server

[1517] The server periodically checks the task database to monitor the deadlines and progress of each task. For tasks with approaching deadlines or those behind schedule, it generates reminder notifications and sends them to the user.

[1518] Specific example

[1519] The server detects that the deadline for the "Document Creation" task is approaching in three days, generates a reminder notification, and sends it to the user.

[1520] Example of a prompt

[1521] Example prompt for task registration:

[1522] The user adds a task titled "Prepare Documents." The deadline is "2023-10-10," the priority is "High," the details are "Materials for next week's meeting," and the person responsible is "Tanaka."

[1523] Example prompts for prioritizing tasks:

[1524] The server scans the task database and uses AI to determine task priorities. For example, the "Document Creation" task is given a high priority because its deadline is approaching.

[1525] This system allows users to efficiently manage tasks and easily track progress. Furthermore, by automatically suggesting the optimal person to handle a task and its priority, the system can prevent project delays.

[1526] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1527] Step 1: Register the task

[1528] Input: The user enters task information (title, details, due date, priority, and assigned person) into the application on their device.

[1529] Operation:

[1530] The user launches a task management application on their device (smartphone, PC, etc.) and enters task information.

[1531] Specific example: Enter "Document Creation" as the title, "Materials for next week's meeting" as the details, "2023-10-10" as the deadline, "High" as the priority, and "Yamada" as the person responsible.

[1532] Output: The terminal sends the entered task information to the server.

[1533] Step 2: Save task information to the database.

[1534] Input: Task information sent from the terminal to the server.

[1535] Operation:

[1536] The server receives task information.

[1537] The server generates a unique identifier (such as a UUID).

[1538] The server saves task information to the database.

[1539] Specific example: Based on the information received by the server, a unique identifier is generated and stored in a database (e.g., MySQL). For example, task information is stored along with the UUID "123e4567-e89b-12d3-a456-426614174000".

[1540] Output: Information about the new task is saved to the database.

[1541] Step 3: Prioritize tasks

[1542] Input: Task information from the database (priority, due date, progress).

[1543] Operation:

[1544] The server periodically scans the database.

[1545] The server uses an AI model (e.g., TensorFlow, PyTorch) to determine the priority of tasks.

[1546] Specific example: The AI ​​calculates a score based on the task's deadline, progress, and priority, and then determines the priority. For example, because the deadline for the "Document Creation" task is approaching, it is given a high priority.

[1547] Output: Task information with updated priorities is saved to the database.

[1548] Step 4: Update progress

[1549] Input: Progress data updated by the user on their device.

[1550] Operation:

[1551] The user selects a target task from the application and updates its progress.

[1552] The user presses the "Update" button.

[1553] The device sends update progress information to the server.

[1554] Specific example: A user sets the progress of the "Create Document" task to 50% and presses the "Update" button.

[1555] Output: New progress information is sent to the server.

[1556] Step 5: Save progress information to database

[1557] Input: Progress data sent to the server.

[1558] Operation:

[1559] The server saves the received progress information to the database.

[1560] The server will send reminder notifications and re-evaluate priorities based on the progress.

[1561] Specific example: The server updates the database with the received progress information (50%) as a task record.

[1562] Output: The latest progress information is saved to the database.

[1563] Step 6: Assigning a responder

[1564] Input: Information about the person the user interacts with, entered on their device.

[1565] Operation:

[1566] The user selects and assigns a responder from the application.

[1567] The user presses the "Assign" button.

[1568] The device sends the responder information to the server.

[1569] The server saves the contact person information to the database.

[1570] The server uses AI to analyze the schedules and skill sets of potential respondents and suggests the most suitable person for the task.

[1571] Specific example: The user selects "Tanaka" as the person responsible for the "Document Creation" task and presses the "Assign" button.

[1572] Output: Responder information is saved in the database, and the most suitable responder is suggested.

[1573] Step 7: Generate reminder notifications

[1574] Input: Task information (deadline, progress) from the database.

[1575] Operation:

[1576] The server periodically checks the task database.

[1577] The server checks the deadlines and progress of each task.

[1578] The server generates reminder notifications for tasks with approaching deadlines or those that are behind schedule.

[1579] Specific example: The server detects that the deadline for the "Create Document" task is 3 days away and generates a reminder notification.

[1580] Output: A reminder notification is generated.

[1581] Step 8: Sending a reminder notification

[1582] Input: Generated reminder notification data.

[1583] Operation:

[1584] The server sends a reminder notification to the user.

[1585] Specific example: Send reminder notifications to the user's device using email or in-app notifications. For example, notify the user that the deadline for the "Create Document" task is in 3 days.

[1586] Output: A reminder notification is sent to the user.

[1587] The above describes the system's program processing steps and the specific actions performed at each step. This system enables efficient management of the entire process, from task registration and prioritization to progress management, assignment of personnel, and generation and sending of reminder notifications.

[1588] (Application Example 1)

[1589] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1590] In modern factories, there is a demand for increased efficiency through the use of robots. However, manual task management often leads to cumbersome prioritization and progress tracking. Furthermore, the lack of appropriate personnel assignment and timely reminder notifications can cause work delays. To address these challenges, a system is needed that automates task prioritization, progress tracking, personnel assignment, and reminder notifications.

[1591] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1592] In this invention, the server includes an information input means for registering tasks, an intelligent algorithm means for evaluating and determining the priority of tasks, a status management means for managing the progress of tasks, a personnel allocation means for assigning personnel to handle tasks, an information notification means for generating and sending reminder notifications, a means for calculating task priority using AI, and an intelligent allocation means for proposing the optimal allocation of personnel. This enables automation of tasks in factories, optimization of priorities, effective management of progress, appropriate personnel allocation, and timely reminder notifications.

[1593] An "information input device" is a device that provides an interface for users to register tasks.

[1594] An "intelligent algorithmic means" is a device that executes an artificial intelligence algorithm to evaluate the priority of tasks and determine those priorities.

[1595] A "status management device" is a device used to track and manage the progress of a task.

[1596] A "personnel assignment tool" is a device that assigns the appropriate person to handle a task.

[1597] An "information notification means" is a device that generates and sends reminder notifications to users.

[1598] "Methods for calculation using AI" refers to devices that allow artificial intelligence to calculate the priority of tasks.

[1599] An "intelligent deployment system" is a device that uses AI to propose the optimal deployment of personnel.

[1600] As an embodiment for carrying out this invention, the configuration of a task management system for a factory robot is shown below.

[1601] composition

[1602] 1. Information input means:

[1603] Users input task information via devices such as smartphones and tablets. Specifically, they enter information such as the task title, details, deadline, priority, and assigned person. This registers the task on the server.

[1604] 2. Intelligent algorithmic means:

[1605] The server evaluates the priority of tasks and uses artificial intelligence algorithms to determine the priority. Examples of AI algorithms used include Scikit-learn and TensorFlow.

[1606] 3. Situation management measures:

[1607] Users update task progress via their devices. The server receives this progress information and stores it in a database. Based on the progress, the system sends reminder notifications and re-evaluates task priorities.

[1608] 4. Personnel allocation methods:

[1609] The user selects or accepts system suggestions to assign the most suitable person to a task. The server analyzes the responders' schedules and skill sets and runs an artificial intelligence algorithm to suggest the best person.

[1610] 5. Information Notification Means:

[1611] The server periodically checks task deadlines and progress, generates reminder notifications, and sends them to users. Firebase or SendGrid can be used as notification services.

[1612] Specific example

[1613] 1. Task registration:

[1614] The user registers a task on their smartphone with the title "Assemble Part A," setting the details to "Complete assembly by the end of the month," the deadline to "2023-10-31," and the priority to "High."

[1615] 2. Progress update:

[1616] The user updates the progress of the "Assemble Part A" task to 50% and presses the submit button. The new progress information is saved to the server.

[1617] 3. Assigning a person to handle the issue:

[1618] The user selects Mr. Tanaka as the person responsible for the task and saves this information to the database.

[1619] 4. Reminder notifications:

[1620] The server detects that the deadline for the "assemble part A" task is approaching in 3 days and generates a reminder notification.

[1621] Example of a prompt

[1622] Task registration prompt message:

[1623] Title: Assembly of Part A, Details: Assembly to be completed by the end of the month, Deadline: 2023-10-31, Priority: High, Person in Charge: Tanaka

[1624] Progress update prompt message:

[1625] Task ID: 123, Progress: 50%

[1626] Respondent assignment prompt message:

[1627] Task ID: 123, Responsible Person: Tanaka

[1628] Thus, by using appropriate hardware and software as the means of implementing the invention, it is possible to improve the efficiency of task management in factories.

[1629] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1630] Step 1:

[1631] The user enters and registers task information using a terminal. The entered task information includes title, details, due date, priority, and assigned person. This information is sent to the server and stored in the database. As output, a new task record with a unique identifier is generated.

[1632] Step 2:

[1633] The server periodically scans registered tasks and uses intelligent algorithms to calculate task priorities. The input is task information retrieved from a database, and attributes such as task due dates and importance are considered when calculating priorities. The output is the determined priority for each task, which is then updated in the database.

[1634] Step 3:

[1635] The user updates the task progress via their device. The user sends the progress data entered on the device (e.g., 50% complete), and the server receives it. The server stores the progress data in a database and sends reminder notifications or re-evaluates priorities as needed.

[1636] Step 4:

[1637] The server uses intelligent assignment mechanisms to suggest the most suitable responder to the task, proposing the optimal responder to the user. The input is data on the responder's schedule and skills, and the output is a suggestion of the most suitable responder. The user reviews this, selects the most suitable responder, and assigns them.

[1638] Step 5:

[1639] The server checks task deadlines and progress and generates reminder notifications. The input is task information stored in the database, targeting tasks with approaching deadlines or insufficient progress. The output is a generated reminder notification, which is sent to the corresponding user.

[1640] In this way, a task management system for factory robots is realized through specific actions at each step.

[1641] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1642] This invention combines an emotion engine with a task management system to optimize task prioritization and reminder notifications. It is implemented in the following specific way:

[1643] 1. Register the task

[1644] User

[1645] The user launches the task management application on their device and registers a new task. When registering a task, they enter detailed information such as the title, description, due date, priority, and assigned person. This information is entered through the user interface.

[1646] server

[1647] The server receives task information from users and stores it in the database. At this time, a unique identifier for each task is generated and stored in the database. This allows tasks to be identified later.

[1648] Specific example:

[1649] "If a user creates a task titled 'Prepare Documents,' sets the details to 'Materials for next week', the due date to '2023-10-10', and the priority to 'High', the server will receive this and save it to the database."

[1650] 2. Prioritizing tasks

[1651] server

[1652] The server periodically scans the database to analyze the priority, due date, and progress of registered tasks. An artificial intelligence (AI) algorithm determines task priorities based on these attributes. Priorities are updated in the database, ensuring users always have access to the latest information.

[1653] Emotional Engine

[1654] The emotion engine recognizes the user's emotions and sends that information to the server. The server's AI adjusts task priorities based on the user's emotions.

[1655] Specific example:

[1656] "The server scans the task database and sets a high priority for the 'Document Creation' task because its deadline is approaching. Furthermore, if the emotion engine detects user stress, its priority is increased even further."

[1657] 3. Progress Management

[1658] User

[1659] The user selects a task from the application on their device and updates its progress. After updating, the user presses the "Update" button, which sends the progress information to the server.

[1660] server

[1661] The server stores received progress information in a database and manages the progress of tasks. Based on the progress, reminder notifications and re-evaluation of priorities are performed.

[1662] Specific example:

[1663] "When a user updates the progress of a 'Document Creation' task to 50% and presses the submit button, the server saves the new progress information."

[1664] 4. Assignment of a person to handle the situation.

[1665] User

[1666] The user selects and assigns a suitable person to the task. The selection of a suitable person can be done by the user themselves or by receiving suggestions from the system.

[1667] server

[1668] The server stores the contact person information selected by the user in a database. It also has a function where AI analyzes the contact person's schedule and skill set to suggest the most suitable contact person to the user.

[1669] Specific example:

[1670] "When a user selects 'Tanaka' as the person responsible for the 'Document Creation' task and presses the assign button, the server saves the person's information."

[1671] 5. Reminder notifications

[1672] server

[1673] The server periodically checks the task database to monitor the deadlines and progress of each task. For tasks with approaching deadlines or those behind schedule, it generates and sends reminder notifications to the user.

[1674] Emotional Engine

[1675] The emotion engine optimizes the content and timing of reminder notifications based on the user's emotions. For example, if the user is feeling stressed, it will soften the content of the reminder notification or adjust the frequency of notifications.

[1676] Specific example:

[1677] "The server detects that the 'Document Creation' task is due in three days and generates and sends a reminder notification to the user. If the emotion engine detects user stress, it changes the content of the reminder notification to an encouraging message."

[1678] This system allows users to efficiently register, prioritize, manage progress, assign tasks, and manage reminder notifications. Furthermore, the emotion engine enables task management that takes the user's emotional state into account, more effectively preventing project delays and unattended important tasks.

[1679] The following describes the processing flow.

[1680] Task registration

[1681] Processing steps

[1682] Step 1:

[1683] User

[1684] The user opens a task management application on their device.

[1685] Step 2:

[1686] User

[1687] The user clicks the "Add New Task" button.

[1688] Step 3:

[1689] User

[1690] The user enters the task title, details, due date, priority, and responsible party.

[1691] Step 4:

[1692] User

[1693] The user clicks the "Save" button.

[1694] Step 5:

[1695] server

[1696] The server saves the received task information to the database.

[1697] Step 6:

[1698] server

[1699] The server generates a unique identifier (ID) for each task and stores it in the database.

[1700] Task prioritization

[1701] Processing steps

[1702] Step 1:

[1703] server

[1704] The server periodically scans the task database.

[1705] Step 2:

[1706] server

[1707] The server analyzes the priority, deadline, and progress of each task.

[1708] Step 3:

[1709] server

[1710] The AI ​​algorithm uses this information to calculate the priority of tasks.

[1711] Step 4:

[1712] server

[1713] The server updates the database with the new priority.

[1714] Step 5:

[1715] Emotional Engine

[1716] The emotion engine recognizes the user's emotions.

[1717] Step 6:

[1718] server

[1719] The server's AI adjusts task priorities based on emotional data received from the emotion engine.

[1720] Progress management

[1721] Processing steps

[1722] Step 1:

[1723] User

[1724] The user opens a task management application on their device.

[1725] Step 2:

[1726] User

[1727] The user selects a task and enters its progress.

[1728] Step 3:

[1729] User

[1730] The user clicks the "Update" button.

[1731] Step 4:

[1732] server

[1733] The server saves the received progress information to the database.

[1734] Step 5:

[1735] server

[1736] The server will send appropriate notifications and change priorities based on the progress of the tasks.

[1737] Assignment of responders

[1738] Processing steps

[1739] Step 1:

[1740] User

[1741] The user opens a task management application on their device.

[1742] Step 2:

[1743] User

[1744] The user selects a task and then selects a person to handle it.

[1745] Step 3:

[1746] User

[1747] The user clicks the "Assign" button.

[1748] Step 4:

[1749] server

[1750] The server saves the contact information it receives to the database.

[1751] Step 5:

[1752] server

[1753] The server's AI analyzes the schedules and skill sets of the responders and suggests the most suitable responder.

[1754] Reminder notification

[1755] Processing steps

[1756] Step 1:

[1757] server

[1758] The server periodically checks the task database.

[1759] Step 2:

[1760] server

[1761] The server checks the deadline and progress of each task.

[1762] Step 3:

[1763] server

[1764] Identify tasks that are nearing their deadline or are behind schedule.

[1765] Step 4:

[1766] server

[1767] The server generates a reminder notification.

[1768] Step 5:

[1769] server

[1770] The server sends reminder notifications to users via email or push notifications.

[1771] Step 6:

[1772] Emotional Engine

[1773] The emotion engine recognizes the user's emotions.

[1774] Step 7:

[1775] server

[1776] The server adjusts the content and timing of reminder notifications based on the emotional data received from the emotion engine.

[1777] (Example 2)

[1778] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1779] Traditional task management systems often struggle to accurately prioritize tasks and lack the flexibility to manage tasks based on users' emotional states. Furthermore, task assignment and reminder notifications are frequently not adequately optimized. This can lead to project delays, unattended important tasks, and decreased work efficiency.

[1780] In Example 2, the identification processing by the identification processing unit 290 of the data processing device 12 is realized by the following means. In this invention, the server includes a user input means for registering tasks, an artificial intelligence means for evaluating the priority of tasks and determining the priority, an emotion analysis means for analyzing the user's emotional state and adjusting the task priority, a means for managing the progress of tasks, a means for assigning a person to handle the task, and a means for generating and sending reminder notifications. This makes it possible to manage tasks while taking into account the user's emotional state, and by optimizing the task priority and the content of reminder notifications, it becomes possible to effectively prevent project delays and unattended important tasks.

[1781] A "user input means for registering tasks" is an interface for users to input task information and register it in the system.

[1782] "An artificial intelligence means for evaluating and determining task priority" refers to artificial intelligence technology that analyzes registered task information and determines task priority based on its importance and urgency.

[1783] "An emotion analysis method that analyzes a user's emotional state and adjusts task priorities" refers to a technology that analyzes a user's emotional data and dynamically adjusts task priorities based on the results.

[1784] "Means for managing task progress" refers to a system for tracking the progress of a task and updating that progress as needed.

[1785] "A means of assigning a person to a task" refers to a function for selecting a person suitable for a task and saving that information linked to the task.

[1786] "Means for generating and sending reminder notifications" refers to a system for creating and sending reminder notifications to users based on the progress and deadline of a task.

[1787] This invention relates to a system for users to efficiently manage tasks. This system includes user input means, artificial intelligence means, sentiment analysis means, progress management means, person assignment means, and reminder notification generation means to achieve task prioritization and optimization of reminder notifications.

[1788] This system consists of the following components:

[1789] User input method:

[1790] Users enter task information through a task management application on their device. This information includes title, details, due date, priority, and assigned person. This information is entered using a user interface (e.g., React, Vue.js). For example, a user might register a task called "Document Creation," setting the details to "Documents for next week's meeting," the due date to "2023-10-10," and the priority to "High." This information is then sent from the device to the server.

[1791] Artificial intelligence tools:

[1792] The server stores the received task information in a database (e.g., MySQL, PostgreSQL). The server scans the database for tasks at regular intervals and uses artificial intelligence algorithms (e.g., TensorFlow, PyTorch) to determine task priorities. For example, if the server detects that the deadline for a "document creation" task is approaching, it sets a higher priority.

[1793] Emotion analysis means:

[1794] The emotion engine analyzes the user's emotional state in real time and sends that information to the server. The emotion analysis uses an emotion analysis API (e.g., Microsoft Azure Cognitive Services). For example, if the emotion engine detects user stress, the server uses that information to further prioritize tasks.

[1795] Progress management methods:

[1796] Users update task progress through an application on their device. After entering the progress and pressing the submit button, the information is sent to the server. The server saves the new progress information to its database. For example, if a user sets the progress of the "Document Creation" task to 50% and presses the submit button, the server saves the new progress information.

[1797] Method for assigning a responder:

[1798] The user selects a suitable person to handle a task and sends the person's information to the server. The server stores this information in a database. The server's AI also analyzes the person's schedule and skill set and suggests the most suitable person to the user. For example, if the user selects "Tanaka" as the person to handle the "document creation" task, the server will save that information.

[1799] Reminder notification generation method:

[1800] The server periodically scans the task database to identify tasks with approaching deadlines or those behind schedule. It generates and sends reminder notifications using a reminder notification system (e.g., Twilio API). Furthermore, an emotion engine analyzes the user's emotional state before sending notifications, optimizing the content and timing. For example, if the server detects that the "Create Document" task is due in three days, it generates a reminder notification and sends it to the user. If the emotion engine detects user stress, it changes the notification content to an encouraging message.

[1801] Example of a prompt

[1802] "Explain how a system that assists users with task management uses an emotion engine to optimize task priorities and notification content."

[1803] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1804] Step 1: Enter task information

[1805] User:

[1806] The user launches a task management application on their device and enters task information. Specifically, they enter the task title, details, due date, priority, and assigned person.

[1807] Input: Task title, details, deadline, priority, responsible party, and other relevant information.

[1808] Output: Input task information

[1809] Specific action: The user registers a task with the title "Create Documents," sets the details to "Materials for next week's meeting," the deadline to "2023-10-10," and the priority to "High."

[1810] Step 2: Submit task information

[1811] Terminal:

[1812] The terminal sends the entered task information to the server. This is done using an API endpoint (e.g., a POST request).

[1813] Input: Task information entered by the user

[1814] Output: Request to send to server

[1815] Specific action: The terminal sends the user's input information to the server.

[1816] Step 3: Save task information

[1817] server:

[1818] The server saves the received task information to the database. During this process, a unique identifier is generated and assigned to each task.

[1819] Input: Task information sent from the device

[1820] Output: Task information and unique identifier stored in the database

[1821] Specific operation: The server saves the "Create Document" task to the database and generates a unique identifier.

[1822] Step 4: Scan the database and determine task priorities.

[1823] server:

[1824] The server scans the database at regular intervals to analyze task deadlines, priorities, and progress. An artificial intelligence algorithm is used to determine task priorities.

[1825] Input: Task information in the database

[1826] Output: Prioritized task information

[1827] Specific action: The server detects that the deadline for the "Document Creation" task is approaching and sets it to a higher priority.

[1828] Step 5: Analyze user sentiment and readjust priorities

[1829] Emotional engine:

[1830] The emotion engine analyzes the user's emotional state in real time and sends that information to the server.

[1831] Input: User sentiment data

[1832] Output: Sentiment data including analysis results

[1833] Specific operation: The emotion engine detects the user's stress level and sends that information to the server.

[1834] server:

[1835] The server readjusts task priorities based on information received from the emotion engine.

[1836] Input: Sentiment data and existing task information

[1837] Output: Re-adjusted priority

[1838] Specific action: The server further increases the priority of the task.

[1839] Step 6: Update progress

[1840] User:

[1841] The user updates the task progress by entering progress information in the application on their device.

[1842] Input: Latest progress of the task

[1843] Output: Update Request

[1844] Specific action: The user sets the progress of the "Create Document" task to 50%.

[1845] Terminal:

[1846] The device sends progress information to the server.

[1847] Input: Updated progress information

[1848] Output: Request to send to server

[1849] Specific action: The device sends progress information to the server.

[1850] server:

[1851] The server saves the new progress information to the database.

[1852] Input: Progress information sent from the device

[1853] Output: Latest progress information stored in the database

[1854] Specific action: The server saves the new progress information.

[1855] Step 7: Assigning a responder

[1856] User:

[1857] The user selects the appropriate person to handle the task and enters the assignment information.

[1858] Input: Information of the person in charge

[1859] Output: Assignment Request

[1860] Specific action: The user selects "Tanaka" as the person responsible for the "Document Creation" task.

[1861] Terminal:

[1862] The device sends the responder information to the server.

[1863] Input: Person in charge information

[1864] Output: Request to send to server

[1865] Specific action: The device sends the responder's information to the server.

[1866] server:

[1867] The server stores contact information in a database, and the AI ​​suggests the most suitable contact person.

[1868] Input: Respondent information sent from the device

[1869] Output: Responder information stored in the database, suggested best responder

[1870] Specific operation: The server stores contact information, and the AI ​​suggests the most suitable contact person.

[1871] Step 8: Generate and send reminder notifications

[1872] server:

[1873] The server periodically scans the task database to identify tasks that are nearing their deadline or are behind schedule.

[1874] Input: Task information in the database

[1875] Output: Verification result

[1876] Specific action: The server detects that the deadline for the "Document Creation" task is approaching.

[1877] server:

[1878] Based on the confirmation results, a reminder notification is generated and sent to the user.

[1879] Input: Confirmation result

[1880] Output: Reminder notification

[1881] Specific operation: The server generates a reminder notification and sends it to the user.

[1882] Emotional engine:

[1883] Before sending a reminder notification, the emotion engine analyzes the user's emotional state and adjusts the timing and content to the optimal level.

[1884] Input: User sentiment data

[1885] Output: Adjustment of notification content based on analysis results.

[1886] Specific operation: The emotion engine detects the user's stress level and changes the notification content to an encouraging message.

[1887] (Application Example 2)

[1888] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1889] In modern industrial settings, managing complex tasks and setting appropriate priorities are critical challenges. In particular, the lack of task management that considers workers' emotions and stress levels can lead to decreased productivity. Furthermore, when multiple robots work together, inefficient communication and task redistribution between robots can result in task delays and the neglect of critical tasks. To solve this problem, a system is needed that allows numerous robots to efficiently perform tasks in industrial applications while also considering user emotions.

[1890] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a user input means for registering tasks, an artificial intelligence means for evaluating the priority of tasks and determining the priority, an emotion engine means for recognizing emotions and adjusting the priority using that information, a means for managing the progress of tasks, a means for assigning a person to handle a task, a communication means for realizing cooperation with multiple work robots in industrial applications, and a means for generating and transmitting reminder notifications. This enables effective task management that takes into account the user's emotional state and realizes efficient coordinated work of multiple work robots in industrial applications.

[1891] A "user input device" is an interface device used by a user to input information in order to register a task.

[1892] "Artificial intelligence tools" refer to algorithms and systems that analyze input task information, evaluate task priority and progress, and provide the optimal response.

[1893] An "emotional engine" is a technology that recognizes a user's emotions and adjusts task priorities based on that information.

[1894] "Means for managing task progress" refers to systems or devices for checking the progress status of registered tasks and recording and monitoring their progress.

[1895] "A means of assigning a person to a task" refers to a function that selects the most suitable person to handle a registered task and assigns that task to them.

[1896] "Means for generating and sending reminder notifications" refers to a system that creates reminder notifications based on task deadlines and progress, and notifies users or responsible parties at the appropriate time.

[1897] "Communication methods" refer to protocols and hardware used to exchange information necessary for multiple work robots to cooperate and perform tasks.

[1898] In this invention, the following systems and processes are introduced in a task management system for a factory, in order to achieve effective task management that takes into account the emotional states of multiple work robots and users.

[1899] Hardware and software used

[1900] Hardware: Work robots, cloud servers, user terminals

[1901] Software: MySQL database, TensorFlow, Affectiva SDK, Twilio API

[1902] System components and their functions

[1903] 1. User input method for registering tasks:

[1904] The server provides an interface for users to register new tasks through a task management application. Users enter information such as the task title, details, due date, priority, and assigned person. This information is sent to the server and stored in the database.

[1905] Specific example:

[1906] The user registers a task titled "Equipment Maintenance," setting the details to "Maintenance work scheduled for the weekend," the deadline to "2023-12-01," and the priority to "High." This information is sent to the server.

[1907] 2. Artificial intelligence methods for evaluating task priority:

[1908] The server periodically scans the database and uses TensorFlow to evaluate the priority of registered tasks. An AI algorithm analyzes task deadlines, progress, and other factors to determine priority.

[1909] Specific example:

[1910] The server uses AI to detect when the deadline for "equipment maintenance" tasks is approaching and sets them to a higher priority.

[1911] 3. Means of managing task progress:

[1912] As the robot completes a task, it sends real-time progress information to the server. The server stores this information in a database and monitors the task's progress.

[1913] Specific example:

[1914] The robot updates the progress of the "equipment maintenance" task up to 50% and sends that information to the server.

[1915] 4. Methods for assigning task managers:

[1916] The server selects the most suitable robot and assigns it tasks. AI analyzes each robot's schedule and skill set to suggest the optimal assignment.

[1917] Specific example:

[1918] The server suggests the most suitable robot for the "equipment maintenance" task and assigns the task to that robot.

[1919] 5. Means for generating and sending reminder notifications:

[1920] The server checks task deadlines and progress and generates reminder notifications. It uses the Twilio API to send notifications to administrators and robots. It uses the Affectiva SDK to detect the user's emotional state and adjust the content and timing of reminders accordingly.

[1921] Specific example:

[1922] The server detects that the deadline for the "equipment maintenance" task is approaching in three days and generates and sends a reminder notification to the user. If the emotion engine detects that the user is stressed, the content of the reminder notification is made gentler.

[1923] Program processing

[1924] The server integrates all of the above methods and runs the overall task management system. MySQL is used for the database, and TensorFlow is used for the AI ​​algorithm. Affectiva SDK is used for sentiment analysis, and the Twilio API is used for reminder notifications.

[1925] Example of a prompt:

[1926] "Please provide Python code that adjusts task priorities based on stress levels and sends appropriate reminder notifications."

[1927] The above describes the embodiments for carrying out the present invention. This enables task management that takes into account the user's emotional state, and allows for the effective and efficient operation of multiple work robots.

[1928] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1929] Step 1:

[1930] The user launches the task management application on their device and registers a new task. The user enters information such as the task title, details, due date, priority, and assigned person. This information is sent to the server and stored in a MySQL database.

[1931] input:

[1932] Task information registered by the user (title, details, deadline, priority, responsible party)

[1933] output:

[1934] Task data stored on the server

[1935] Specific operation:

[1936] The user enters "Equipment maintenance," sets the details as "Maintenance work scheduled for the weekend," the deadline as "2023-12-01," and the priority as "High," and then submits the form.

[1937] Step 2:

[1938] The server periodically scans the database and evaluates the priority of registered tasks. It uses TensorFlow's AI algorithm to analyze task deadlines and progress to determine priorities. The results are updated in the database.

[1939] input:

[1940] Task information stored in the database

[1941] output:

[1942] Task data with re-evaluated priorities

[1943] Specific operation:

[1944] The server uses AI to analyze that the deadline for the "equipment maintenance" task is approaching and resets its priority to "highest."

[1945] Step 3:

[1946] Users update the progress of ongoing tasks using their terminals. Users enter the progress percentage and send it to the server. This progress information is stored in a database.

[1947] input:

[1948] User-updated progress information

[1949] output:

[1950] Progress data stored on the server

[1951] Specific operation:

[1952] The user updates the "Equipment Maintenance" progress to 50% and presses the submit button.

[1953] Step 4:

[1954] The server uses an emotion engine to recognize the user's emotions and adjusts task priorities based on that information. It uses the Affectiva SDK to perform emotion analysis and saves the results to a database.

[1955] input:

[1956] User sentiment data

[1957] output:

[1958] Task prioritization adjusted based on emotional data

[1959] Specific operation:

[1960] The emotion engine detects when the user's stress level is high and further increases the task's priority.

[1961] Step 5:

[1962] The server assigns the most suitable robot based on progress information and priority. The server uses AI to evaluate each robot's schedule and skill set and assign tasks accordingly.

[1963] input:

[1964] Task priority, schedule and skill set information for each robot.

[1965] output:

[1966] Robot assignment information optimized for each task

[1967] Specific operation:

[1968] The server selects robot A, which is best suited for the "equipment maintenance" task, and sends a notification to that robot.

[1969] Step 6:

[1970] The server generates and sends reminder notifications to the user based on task deadlines and progress. It uses the Twilio API to send notifications and the Affectiva SDK to adjust the notification content based on the user's emotional state.

[1971] input:

[1972] Task deadlines, progress information, and user sentiment data

[1973] output:

[1974] Reminder notifications sent to users

[1975] Specific operation:

[1976] The server detects that the deadline for the "equipment maintenance" task is approaching in three days and, sensing the user's stress, sends a notification containing a kind and encouraging message.

[1977] Through each of the above steps, this system effectively manages tasks and integrates robots while taking into account the user's emotional state.

[1978] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1979] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1980] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[1981] [Fourth Embodiment]

[1982] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1983] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1984] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1985] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[1986] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1987] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1988] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1989] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[1990] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1991] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1992] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1993] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1994] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1995] The present invention relates to a task management system and is implemented in the following specific manner.

[1996] 1. Register the task

[1997] User

[1998] The user launches the task management application on their device and registers a new task. When registering a task, they enter detailed information such as the title, description, due date, priority, and assigned person. This information is entered through the user interface.

[1999] server

[2000] The server receives task information from users and stores it in the database. At this time, a unique identifier for each task is generated and stored in the database. This allows tasks to be identified later.

[2001] Specific example:

[2002] "If a user creates a task titled 'Prepare Documents,' sets the details to 'Materials for next week', the due date to '2023-10-10', and the priority to 'High', the server will receive this and save it to the database."

[2003] 2. Prioritizing tasks

[2004] server

[2005] The server periodically scans the database to analyze the priority, due date, and progress of registered tasks. An artificial intelligence (AI) algorithm determines task priorities based on these attributes. Priorities are updated in the database, ensuring users always have access to the latest information.

[2006] Specific example:

[2007] "The server scans the task database and sets a higher priority for the 'Document Creation' task because its deadline is approaching."

[2008] 3. Progress Management

[2009] User

[2010] The user selects a task from the application on their device and updates its progress. After updating, the user presses the "Update" button, which sends the progress information to the server.

[2011] server

[2012] The server stores received progress information in a database and manages the progress of tasks. Based on the progress, reminder notifications and re-evaluation of priorities are performed.

[2013] Specific example:

[2014] "When a user updates the progress of a 'Document Creation' task to 50% and presses the submit button, the server saves the new progress information."

[2015] 4. Assignment of a person to handle the situation.

[2016] User

[2017] The user selects and assigns a suitable person to the task. The selection of a suitable person can be done by the user themselves or by receiving suggestions from the system.

[2018] server

[2019] The server stores the contact person information selected by the user in a database. It also has a function where AI analyzes the contact person's schedule and skill set to suggest the most suitable contact person to the user.

[2020] Specific example:

[2021] "When a user selects 'Tanaka' as the person responsible for the 'Document Creation' task and presses the assign button, the server saves the person's information."

[2022] 5. Reminder notifications

[2023] server

[2024] The server periodically checks the task database to monitor the deadlines and progress of each task. For tasks with approaching deadlines or those behind schedule, it generates and sends reminder notifications to the user.

[2025] Specific example:

[2026] The server detects that the deadline for the 'Document Creation' task is approaching in three days, generates a reminder notification, and sends it to the user.

[2027] This system allows users to efficiently register, prioritize, manage progress, assign tasks, and manage reminder notifications. This helps prevent project delays and unattended important tasks.

[2028] The following describes the processing flow.

[2029] Task registration

[2030] Processing steps

[2031] Step 1:

[2032] User

[2033] The user opens a task management application on their device.

[2034] Step 2:

[2035] User

[2036] The user clicks the "Add New Task" button.

[2037] Step 3:

[2038] User

[2039] The user enters the task title, details, due date, priority, and responsible party.

[2040] Step 4:

[2041] User

[2042] The user clicks the "Save" button.

[2043] Step 5:

[2044] server

[2045] The server saves the received task information to the database.

[2046] Step 6:

[2047] server

[2048] The server generates a unique identifier (ID) for each task and stores it in the database.

[2049] Task prioritization

[2050] Processing steps

[2051] Step 1:

[2052] server

[2053] The server periodically scans the task database.

[2054] Step 2:

[2055] server

[2056] The server analyzes the priority, deadline, and progress of each task.

[2057] Step 3:

[2058] server

[2059] The AI ​​algorithm uses this information to calculate the priority of tasks.

[2060] Step 4:

[2061] server

[2062] The server updates the database with the new priority.

[2063] Progress management

[2064] Processing steps

[2065] Step 1:

[2066] User

[2067] The user opens a task management application on their device.

[2068] Step 2:

[2069] User

[2070] The user selects a task and enters its progress.

[2071] Step 3:

[2072] User

[2073] The user clicks the "Update" button.

[2074] Step 4:

[2075] server

[2076] The server saves the received progress information to the database.

[2077] Step 5:

[2078] server

[2079] The server will send appropriate notifications and change priorities based on the progress of the tasks.

[2080] Assignment of responders

[2081] Processing steps

[2082] Step 1:

[2083] User

[2084] The user opens a task management application on their device.

[2085] Step 2:

[2086] User

[2087] The user selects a task and then selects a person to handle it.

[2088] Step 3:

[2089] User

[2090] The user clicks the "Assign" button.

[2091] Step 4:

[2092] server

[2093] The server saves the contact information it receives to the database.

[2094] Step 5:

[2095] server

[2096] The server's AI analyzes the schedules and skill sets of the responders and suggests the most suitable responder.

[2097] Reminder notification

[2098] Processing steps

[2099] Step 1:

[2100] server

[2101] The server periodically checks the task database.

[2102] Step 2:

[2103] server

[2104] The server checks the deadline and progress of each task.

[2105] Step 3:

[2106] server

[2107] Identify tasks that are nearing their deadline or are behind schedule.

[2108] Step 4:

[2109] server

[2110] The server generates a reminder notification.

[2111] Step 5:

[2112] server

[2113] The server sends reminder notifications to users via email or push notifications.

[2114] (Example 1)

[2115] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[2116] Traditional task management systems make efficient task management difficult due to the cumbersome process of prioritizing tasks, tracking progress, assigning tasks to individuals, and managing reminder notifications. Furthermore, the lack of features such as re-evaluating priorities and suggesting appropriate assignees increases the risk of project delays and missed tasks.

[2117] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[2118] In this invention, the server includes a user input means for registering tasks, an artificial intelligence means for evaluating and determining the priority of tasks, a means for managing the progress of tasks, a means for assigning a person to handle a task, a means for generating and sending reminder notifications, a means for sending task information from a user terminal to the server, a means for the server to receive task information and store it in a database, a means for the server to periodically scan the database and update priorities, a means for receiving reminder notifications and priorities, a means for scanning the database and generating notifications based on the progress, and a means for analyzing the schedule and skill set of a person to handle a task and suggesting the most suitable person to handle it. This makes it possible to efficiently perform a series of task management tasks, from task registration to progress management, person assignment, and reminder notifications.

[2119] A "task" refers to any work or activity necessary to achieve a specific objective.

[2120] "Users" refer to individuals or organizations that use the system to manage tasks.

[2121] "Input means" refers to the interface or device that allows users to input information into a system.

[2122] "Priority" refers to an indicator that shows the importance or urgency of a task.

[2123] "Artificial intelligence tools" refer to machine learning algorithms and data analysis methods used to evaluate tasks and determine priorities.

[2124] "Progress status" refers to the state or status that indicates how much of a task has been completed.

[2125] "Management means" refers to methods or devices for monitoring and recording task progress and other information within a system.

[2126] "Responsible party" refers to an individual or team responsible for a specific task.

[2127] "Means of assignment" refers to the method or process of assigning a person to handle a task.

[2128] A "reminder notification" refers to a notification that informs the user of task deadlines or important actions.

[2129] "Means of transmission" refers to the technologies and methods used to transmit information and data both inside and outside a system.

[2130] "User terminal" refers to a device used by a user to access the system (e.g., smartphone, personal computer, etc.).

[2131] A "server" is a central computer or network device in a system that stores and processes data.

[2132] A "database" refers to a system or software used to organize and store tasks and other information.

[2133] "Scanning methods" refer to technologies and methods that periodically check information within a database and perform necessary updates and processing.

[2134] "Methods for suggesting the optimal responder" refers to methods and algorithms for analyzing the schedules and skill sets of responders and selecting and suggesting the most suitable person or team.

[2135] This invention relates to a task management system and provides a specific method for users to effectively manage tasks. The system is implemented by combining user input means, artificial intelligence means, a database, and a server.

[2136] Task registration

[2137] User

[2138] The user launches a task management application installed on their device (e.g., smartphone, computer) and enters new task information. Specifically, they enter information such as title, details, due date, priority, and assigned person.

[2139] terminal

[2140] The terminal collects user input information and sends it to the server. The data is sent, for example, in JSON format, using the HTTP or HTTPS protocol.

[2141] server

[2142] The server processes the received task information, generates a unique identifier, and stores it in a database (e.g., MySQL). This process makes the task identifiable later on.

[2143] Specific example

[2144] Suppose a user registers a task with the title "Create Documents," sets the details to "Materials for next week's meeting," the deadline to "2023-10-10," the priority to "High," and assigns the task to "Yamada." The terminal sends this information to the server, which then saves it to the database.

[2145] Task prioritization

[2146] server

[2147] The server periodically scans the database to analyze the priority, due date, and progress of registered tasks. This is done using artificial intelligence tools (e.g., TensorFlow, PyTorch).

[2148] server

[2149] The server uses an AI model to determine task priorities and updates the database with that information. This ensures that users always see the latest priorities when they launch the application.

[2150] Specific example

[2151] The server scans the task database and sets a high priority for the "Create Document" task because its deadline is approaching.

[2152] Progress management

[2153] User

[2154] Users can use their devices to operate a task management application and update the progress of specific tasks. By entering the progress percentage and pressing the "Update" button, the information is sent to the server.

[2155] server

[2156] The server receives this progress information and stores it in the database. Based on the progress, reminder notifications and prioritization are performed.

[2157] Specific example

[2158] When a user updates the progress of a "Document Creation" task to 50% and presses the submit button, the server saves the new progress information to the database.

[2159] Assignment of responders

[2160] User

[2161] Users can assign tasks to individuals using a task management application. Users can select the individuals themselves or receive suggestions from the system.

[2162] server

[2163] The server stores user-selected contact information in a database and also has a function to suggest the most suitable contact using artificial intelligence. This is done by analyzing the contact person's schedule and skill set.

[2164] Specific example

[2165] When a user selects "Tanaka" as the person responsible for the "Document Creation" task and presses the assign button, the server saves the person's information to the database.

[2166] Reminder notification

[2167] server

[2168] The server periodically checks the task database to monitor the deadlines and progress of each task. For tasks with approaching deadlines or those behind schedule, it generates reminder notifications and sends them to the user.

[2169] Specific example

[2170] The server detects that the deadline for the "Document Creation" task is approaching in three days, generates a reminder notification, and sends it to the user.

[2171] Example of a prompt

[2172] Example prompt for task registration:

[2173] The user adds a task titled "Prepare Documents." The deadline is "2023-10-10," the priority is "High," the details are "Materials for next week's meeting," and the person responsible is "Tanaka."

[2174] Example prompts for prioritizing tasks:

[2175] The server scans the task database and uses AI to determine task priorities. For example, the "Document Creation" task is given a high priority because its deadline is approaching.

[2176] This system allows users to efficiently manage tasks and easily track progress. Furthermore, by automatically suggesting the optimal person to handle a task and its priority, the system can prevent project delays.

[2177] The flow of the specific processing in Example 1 will be explained using Figure 11.

[2178] Step 1: Register the task

[2179] Input: The user enters task information (title, details, due date, priority, and assigned person) into the application on their device.

[2180] Operation:

[2181] The user launches a task management application on their device (smartphone, PC, etc.) and enters task information.

[2182] Specific example: Enter "Document Creation" as the title, "Materials for next week's meeting" as the details, "2023-10-10" as the deadline, "High" as the priority, and "Yamada" as the person responsible.

[2183] Output: The terminal sends the entered task information to the server.

[2184] Step 2: Save task information to the database.

[2185] Input: Task information sent from the terminal to the server.

[2186] Operation:

[2187] The server receives task information.

[2188] The server generates a unique identifier (such as a UUID).

[2189] The server saves task information to the database.

[2190] Specific example: Based on the information received by the server, a unique identifier is generated and stored in a database (e.g., MySQL). For example, task information is stored along with the UUID "123e4567-e89b-12d3-a456-426614174000".

[2191] Output: Information about the new task is saved to the database.

[2192] Step 3: Prioritize tasks

[2193] Input: Task information from the database (priority, due date, progress).

[2194] Operation:

[2195] The server periodically scans the database.

[2196] The server uses an AI model (e.g., TensorFlow, PyTorch) to determine the priority of tasks.

[2197] Specific example: The AI ​​calculates a score based on the task's deadline, progress, and priority, and then determines the priority. For example, because the deadline for the "Document Creation" task is approaching, it is given a high priority.

[2198] Output: Task information with updated priorities is saved to the database.

[2199] Step 4: Update progress

[2200] Input: Progress data updated by the user on their device.

[2201] Operation:

[2202] The user selects a target task from the application and updates its progress.

[2203] The user presses the "Update" button.

[2204] The device sends update progress information to the server.

[2205] Specific example: A user sets the progress of the "Create Document" task to 50% and presses the "Update" button.

[2206] Output: New progress information is sent to the server.

[2207] Step 5: Save progress information to database

[2208] Input: Progress data sent to the server.

[2209] Operation:

[2210] The server saves the received progress information to the database.

[2211] The server will send reminder notifications and re-evaluate priorities based on the progress.

[2212] Specific example: The server updates the database with the received progress information (50%) as a task record.

[2213] Output: The latest progress information is saved to the database.

[2214] Step 6: Assigning a responder

[2215] Input: Information about the person the user interacts with, entered on their device.

[2216] Operation:

[2217] The user selects and assigns a responder from the application.

[2218] The user presses the "Assign" button.

[2219] The device sends the responder information to the server.

[2220] The server saves the contact person information to the database.

[2221] The server uses AI to analyze the schedules and skill sets of potential respondents and suggests the most suitable person for the task.

[2222] Specific example: The user selects "Tanaka" as the person responsible for the "Document Creation" task and presses the "Assign" button.

[2223] Output: Responder information is saved in the database, and the most suitable responder is suggested.

[2224] Step 7: Generate reminder notifications

[2225] Input: Task information (deadline, progress) from the database.

[2226] Operation:

[2227] The server periodically checks the task database.

[2228] The server checks the deadlines and progress of each task.

[2229] The server generates reminder notifications for tasks with approaching deadlines or those that are behind schedule.

[2230] Specific example: The server detects that the deadline for the "Create Document" task is 3 days away and generates a reminder notification.

[2231] Output: A reminder notification is generated.

[2232] Step 8: Sending a reminder notification

[2233] Input: Generated reminder notification data.

[2234] Operation:

[2235] The server sends a reminder notification to the user.

[2236] Specific example: Send reminder notifications to the user's device using email or in-app notifications. For example, notify the user that the deadline for the "Create Document" task is in 3 days.

[2237] Output: A reminder notification is sent to the user.

[2238] The above describes the system's program processing steps and the specific actions performed at each step. This system enables efficient management of the entire process, from task registration and prioritization to progress management, assignment of personnel, and generation and sending of reminder notifications.

[2239] (Application Example 1)

[2240] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[2241] In modern factories, there is a demand for increased efficiency through the use of robots. However, manual task management often leads to cumbersome prioritization and progress tracking. Furthermore, the lack of appropriate personnel assignment and timely reminder notifications can cause work delays. To address these challenges, a system is needed that automates task prioritization, progress tracking, personnel assignment, and reminder notifications.

[2242] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[2243] In this invention, the server includes an information input means for registering tasks, an intelligent algorithm means for evaluating and determining the priority of tasks, a status management means for managing the progress of tasks, a personnel allocation means for assigning personnel to handle tasks, an information notification means for generating and sending reminder notifications, a means for calculating task priority using AI, and an intelligent allocation means for proposing the optimal allocation of personnel. This enables automation of tasks in factories, optimization of priorities, effective management of progress, appropriate personnel allocation, and timely reminder notifications.

[2244] An "information input device" is a device that provides an interface for users to register tasks.

[2245] An "intelligent algorithmic means" is a device that executes an artificial intelligence algorithm to evaluate the priority of tasks and determine those priorities.

[2246] A "status management device" is a device used to track and manage the progress of a task.

[2247] A "personnel assignment tool" is a device that assigns the appropriate person to handle a task.

[2248] An "information notification means" is a device that generates and sends reminder notifications to users.

[2249] "Methods for calculation using AI" refers to devices that allow artificial intelligence to calculate the priority of tasks.

[2250] An "intelligent deployment system" is a device that uses AI to propose the optimal deployment of personnel.

[2251] As an embodiment for carrying out this invention, the configuration of a task management system for a factory robot is shown below.

[2252] composition

[2253] 1. Information input means:

[2254] Users input task information via devices such as smartphones and tablets. Specifically, they enter information such as the task title, details, deadline, priority, and assigned person. This registers the task on the server.

[2255] 2. Intelligent algorithmic means:

[2256] The server evaluates the priority of tasks and uses artificial intelligence algorithms to determine the priority. Examples of AI algorithms used include Scikit-learn and TensorFlow.

[2257] 3. Situation management measures:

[2258] Users update task progress via their devices. The server receives this progress information and stores it in a database. Based on the progress, the system sends reminder notifications and re-evaluates task priorities.

[2259] 4. Personnel allocation methods:

[2260] The user selects or accepts system suggestions to assign the most suitable person to a task. The server analyzes the responders' schedules and skill sets and runs an artificial intelligence algorithm to suggest the best person.

[2261] 5. Information Notification Means:

[2262] The server periodically checks task deadlines and progress, generates reminder notifications, and sends them to users. Firebase or SendGrid can be used as notification services.

[2263] Specific example

[2264] 1. Task registration:

[2265] The user registers a task on their smartphone with the title "Assemble Part A," setting the details to "Complete assembly by the end of the month," the deadline to "2023-10-31," and the priority to "High."

[2266] 2. Progress update:

[2267] The user updates the progress of the "Assemble Part A" task to 50% and presses the submit button. The new progress information is saved to the server.

[2268] 3. Assigning a person to handle the issue:

[2269] The user selects Mr. Tanaka as the person responsible for the task and saves this information to the database.

[2270] 4. Reminder notifications:

[2271] The server detects that the deadline for the "assemble part A" task is approaching in 3 days and generates a reminder notification.

[2272] Example of a prompt

[2273] Task registration prompt message:

[2274] Title: Assembly of Part A, Details: Assembly to be completed by the end of the month, Deadline: 2023-10-31, Priority: High, Person in Charge: Tanaka

[2275] Progress update prompt message:

[2276] Task ID: 123, Progress: 50%

[2277] Respondent assignment prompt message:

[2278] Task ID: 123, Responsible Person: Tanaka

[2279] Thus, by using appropriate hardware and software as the means of implementing the invention, it is possible to improve the efficiency of task management in factories.

[2280] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[2281] Step 1:

[2282] The user enters and registers task information using a terminal. The entered task information includes title, details, due date, priority, and assigned person. This information is sent to the server and stored in the database. As output, a new task record with a unique identifier is generated.

[2283] Step 2:

[2284] The server periodically scans registered tasks and uses intelligent algorithms to calculate task priorities. The input is task information retrieved from a database, and attributes such as task due dates and importance are considered when calculating priorities. The output is the determined priority for each task, which is then updated in the database.

[2285] Step 3:

[2286] The user updates the task progress via their device. The user sends the progress data entered on the device (e.g., 50% complete), and the server receives it. The server stores the progress data in a database and sends reminder notifications or re-evaluates priorities as needed.

[2287] Step 4:

[2288] The server uses intelligent assignment mechanisms to suggest the most suitable responder to the task, proposing the optimal responder to the user. The input is data on the responder's schedule and skills, and the output is a suggestion of the most suitable responder. The user reviews this, selects the most suitable responder, and assigns them.

[2289] Step 5:

[2290] The server checks task deadlines and progress and generates reminder notifications. The input is task information stored in the database, targeting tasks with approaching deadlines or insufficient progress. The output is a generated reminder notification, which is sent to the corresponding user.

[2291] In this way, a task management system for factory robots is realized through specific actions at each step.

[2292] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[2293] This invention combines an emotion engine with a task management system to optimize task prioritization and reminder notifications. It is implemented in the following specific way:

[2294] 1. Register the task

[2295] User

[2296] The user launches the task management application on their device and registers a new task. When registering a task, they enter detailed information such as the title, description, due date, priority, and assigned person. This information is entered through the user interface.

[2297] server

[2298] The server receives task information from users and stores it in the database. At this time, a unique identifier for each task is generated and stored in the database. This allows tasks to be identified later.

[2299] Specific example:

[2300] "If a user creates a task titled 'Prepare Documents,' sets the details to 'Materials for next week', the due date to '2023-10-10', and the priority to 'High', the server will receive this and save it to the database."

[2301] 2. Prioritizing tasks

[2302] server

[2303] The server periodically scans the database to analyze the priority, due date, and progress of registered tasks. An artificial intelligence (AI) algorithm determines task priorities based on these attributes. Priorities are updated in the database, ensuring users always have access to the latest information.

[2304] Emotional Engine

[2305] The emotion engine recognizes the user's emotions and sends that information to the server. The server's AI adjusts task priorities based on the user's emotions.

[2306] Specific example:

[2307] "The server scans the task database and sets a high priority for the 'Document Creation' task because its deadline is approaching. Furthermore, if the emotion engine detects user stress, its priority is increased even further."

[2308] 3. Progress Management

[2309] User

[2310] The user selects a task from the application on their device and updates its progress. After updating, the user presses the "Update" button, which sends the progress information to the server.

[2311] server

[2312] The server stores received progress information in a database and manages the progress of tasks. Based on the progress, reminder notifications and re-evaluation of priorities are performed.

[2313] Specific example:

[2314] "When a user updates the progress of a 'Document Creation' task to 50% and presses the submit button, the server saves the new progress information."

[2315] 4. Assignment of a person to handle the situation.

[2316] User

[2317] The user selects and assigns a suitable person to the task. The selection of a suitable person can be done by the user themselves or by receiving suggestions from the system.

[2318] server

[2319] The server stores the contact person information selected by the user in a database. It also has a function where AI analyzes the contact person's schedule and skill set to suggest the most suitable contact person to the user.

[2320] Specific example:

[2321] "When a user selects 'Tanaka' as the person responsible for the 'Document Creation' task and presses the assign button, the server saves the person's information."

[2322] 5. Reminder notifications

[2323] server

[2324] The server periodically checks the task database to monitor the deadlines and progress of each task. For tasks with approaching deadlines or those behind schedule, it generates and sends reminder notifications to the user.

[2325] Emotional Engine

[2326] The emotion engine optimizes the content and timing of reminder notifications based on the user's emotions. For example, if the user is feeling stressed, it will soften the content of the reminder notification or adjust the frequency of notifications.

[2327] Specific example:

[2328] "The server detects that the 'Document Creation' task is due in three days and generates and sends a reminder notification to the user. If the emotion engine detects user stress, it changes the content of the reminder notification to an encouraging message."

[2329] This system allows users to efficiently register, prioritize, manage progress, assign tasks, and manage reminder notifications. Furthermore, the emotion engine enables task management that takes the user's emotional state into account, more effectively preventing project delays and unattended important tasks.

[2330] The following describes the processing flow.

[2331] Task registration

[2332] Processing steps

[2333] Step 1:

[2334] User

[2335] The user opens a task management application on their device.

[2336] Step 2:

[2337] User

[2338] The user clicks the "Add New Task" button.

[2339] Step 3:

[2340] User

[2341] The user enters the task title, details, due date, priority, and responsible party.

[2342] Step 4:

[2343] User

[2344] The user clicks the "Save" button.

[2345] Step 5:

[2346] server

[2347] The server saves the received task information to the database.

[2348] Step 6:

[2349] server

[2350] The server generates a unique identifier (ID) for each task and stores it in the database.

[2351] Task prioritization

[2352] Processing steps

[2353] Step 1:

[2354] server

[2355] The server periodically scans the task database.

[2356] Step 2:

[2357] server

[2358] The server analyzes the priority, deadline, and progress of each task.

[2359] Step 3:

[2360] server

[2361] The AI ​​algorithm uses this information to calculate the priority of tasks.

[2362] Step 4:

[2363] server

[2364] The server updates the database with the new priority.

[2365] Step 5:

[2366] Emotional Engine

[2367] The emotion engine recognizes the user's emotions.

[2368] Step 6:

[2369] server

[2370] The server's AI adjusts task priorities based on emotional data received from the emotion engine.

[2371] Progress management

[2372] Processing steps

[2373] Step 1:

[2374] User

[2375] The user opens a task management application on their device.

[2376] Step 2:

[2377] User

[2378] The user selects a task and enters its progress.

[2379] Step 3:

[2380] User

[2381] The user clicks the "Update" button.

[2382] Step 4:

[2383] server

[2384] The server saves the received progress information to the database.

[2385] Step 5:

[2386] server

[2387] The server will send appropriate notifications and change priorities based on the progress of the tasks.

[2388] Assignment of responders

[2389] Processing steps

[2390] Step 1:

[2391] User

[2392] The user opens a task management application on their device.

[2393] Step 2:

[2394] User

[2395] The user selects a task and then selects a person to handle it.

[2396] Step 3:

[2397] User

[2398] The user clicks the "Assign" button.

[2399] Step 4:

[2400] server

[2401] The server saves the contact information it receives to the database.

[2402] Step 5:

[2403] server

[2404] The server's AI analyzes the schedules and skill sets of the responders and suggests the most suitable responder.

[2405] Reminder notification

[2406] Processing steps

[2407] Step 1:

[2408] server

[2409] The server periodically checks the task database.

[2410] Step 2:

[2411] server

[2412] The server checks the deadline and progress of each task.

[2413] Step 3:

[2414] server

[2415] Identify tasks that are nearing their deadline or are behind schedule.

[2416] Step 4:

[2417] server

[2418] The server generates a reminder notification.

[2419] Step 5:

[2420] server

[2421] The server sends reminder notifications to users via email or push notifications.

[2422] Step 6:

[2423] Emotional Engine

[2424] The emotion engine recognizes the user's emotions.

[2425] Step 7:

[2426] server

[2427] The server adjusts the content and timing of reminder notifications based on the emotional data received from the emotion engine.

[2428] (Example 2)

[2429] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[2430] Traditional task management systems often struggle to accurately prioritize tasks and lack the flexibility to manage tasks based on users' emotional states. Furthermore, task assignment and reminder notifications are frequently not adequately optimized. This can lead to project delays, unattended important tasks, and decreased work efficiency.

[2431] In Example 2, the identification processing by the identification processing unit 290 of the data processing device 12 is realized by the following means. In this invention, the server includes a user input means for registering tasks, an artificial intelligence means for evaluating the priority of tasks and determining the priority, an emotion analysis means for analyzing the user's emotional state and adjusting the task priority, a means for managing the progress of tasks, a means for assigning a person to handle the task, and a means for generating and sending reminder notifications. This makes it possible to manage tasks while taking into account the user's emotional state, and by optimizing the task priority and the content of reminder notifications, it becomes possible to effectively prevent project delays and unattended important tasks.

[2432] A "user input means for registering tasks" is an interface for users to input task information and register it in the system.

[2433] "An artificial intelligence means for evaluating and determining task priority" refers to artificial intelligence technology that analyzes registered task information and determines task priority based on its importance and urgency.

[2434] "An emotion analysis method that analyzes a user's emotional state and adjusts task priorities" refers to a technology that analyzes a user's emotional data and dynamically adjusts task priorities based on the results.

[2435] "Means for managing task progress" refers to a system for tracking the progress of a task and updating that progress as needed.

[2436] "A means of assigning a person to a task" refers to a function for selecting a person suitable for a task and saving that information linked to the task.

[2437] "Means for generating and sending reminder notifications" refers to a system for creating and sending reminder notifications to users based on the progress and deadline of a task.

[2438] This invention relates to a system for users to efficiently manage tasks. This system includes user input means, artificial intelligence means, sentiment analysis means, progress management means, person assignment means, and reminder notification generation means to achieve task prioritization and optimization of reminder notifications.

[2439] This system consists of the following components:

[2440] User input method:

[2441] Users enter task information through a task management application on their device. This information includes title, details, due date, priority, and assigned person. This information is entered using a user interface (e.g., React, Vue.js). For example, a user might register a task called "Document Creation," setting the details to "Documents for next week's meeting," the due date to "2023-10-10," and the priority to "High." This information is then sent from the device to the server.

[2442] Artificial intelligence tools:

[2443] The server stores the received task information in a database (e.g., MySQL, PostgreSQL). The server scans the database for tasks at regular intervals and uses artificial intelligence algorithms (e.g., TensorFlow, PyTorch) to determine task priorities. For example, if the server detects that the deadline for a "document creation" task is approaching, it sets a higher priority.

[2444] Emotion analysis means:

[2445] The emotion engine analyzes the user's emotional state in real time and sends that information to the server. The emotion analysis uses an emotion analysis API (e.g., Microsoft Azure Cognitive Services). For example, if the emotion engine detects user stress, the server uses that information to further prioritize tasks.

[2446] Progress management methods:

[2447] Users update task progress through an application on their device. After entering the progress and pressing the submit button, the information is sent to the server. The server saves the new progress information to its database. For example, if a user sets the progress of the "Document Creation" task to 50% and presses the submit button, the server saves the new progress information.

[2448] Method for assigning a responder:

[2449] The user selects a suitable person to handle a task and sends the person's information to the server. The server stores this information in a database. The server's AI also analyzes the person's schedule and skill set and suggests the most suitable person to the user. For example, if the user selects "Tanaka" as the person to handle the "document creation" task, the server will save that information.

[2450] Reminder notification generation method:

[2451] The server periodically scans the task database to identify tasks with approaching deadlines or those behind schedule. It generates and sends reminder notifications using a reminder notification system (e.g., Twilio API). Furthermore, an emotion engine analyzes the user's emotional state before sending notifications, optimizing the content and timing. For example, if the server detects that the "Create Document" task is due in three days, it generates a reminder notification and sends it to the user. If the emotion engine detects user stress, it changes the notification content to an encouraging message.

[2452] Example of a prompt

[2453] "Explain how a system that assists users with task management uses an emotion engine to optimize task priorities and notification content."

[2454] The flow of the specific processing in Example 2 will be explained using Figure 13.

[2455] Step 1: Enter task information

[2456] User:

[2457] The user launches a task management application on their device and enters task information. Specifically, they enter the task title, details, due date, priority, and assigned person.

[2458] Input: Task title, details, deadline, priority, responsible party, and other relevant information.

[2459] Output: Input task information

[2460] Specific action: The user registers a task with the title "Create Documents," sets the details to "Materials for next week's meeting," the deadline to "2023-10-10," and the priority to "High."

[2461] Step 2: Submit task information

[2462] Terminal:

[2463] The terminal sends the entered task information to the server. This is done using an API endpoint (e.g., a POST request).

[2464] Input: Task information entered by the user

[2465] Output: Request to send to server

[2466] Specific action: The terminal sends the user's input information to the server.

[2467] Step 3: Save task information

[2468] server:

[2469] The server saves the received task information to the database. During this process, a unique identifier is generated and assigned to each task.

[2470] Input: Task information sent from the device

[2471] Output: Task information and unique identifier stored in the database

[2472] Specific operation: The server saves the "Create Document" task to the database and generates a unique identifier.

[2473] Step 4: Scan the database and determine task priorities.

[2474] server:

[2475] The server scans the database at regular intervals to analyze task deadlines, priorities, and progress. An artificial intelligence algorithm is used to determine task priorities.

[2476] Input: Task information in the database

[2477] Output: Prioritized task information

[2478] Specific action: The server detects that the deadline for the "Document Creation" task is approaching and sets it to a higher priority.

[2479] Step 5: Analyze user sentiment and readjust priorities

[2480] Emotional engine:

[2481] The emotion engine analyzes the user's emotional state in real time and sends that information to the server.

[2482] Input: User sentiment data

[2483] Output: Sentiment data including analysis results

[2484] Specific operation: The emotion engine detects the user's stress level and sends that information to the server.

[2485] server:

[2486] The server readjusts task priorities based on information received from the emotion engine.

[2487] Input: Sentiment data and existing task information

[2488] Output: Re-adjusted priority

[2489] Specific action: The server further increases the priority of the task.

[2490] Step 6: Update progress

[2491] User:

[2492] The user updates the task progress by entering progress information in the application on their device.

[2493] Input: Latest progress of the task

[2494] Output: Update Request

[2495] Specific action: The user sets the progress of the "Create Document" task to 50%.

[2496] Terminal:

[2497] The device sends progress information to the server.

[2498] Input: Updated progress information

[2499] Output: Request to send to server

[2500] Specific action: The device sends progress information to the server.

[2501] server:

[2502] The server saves the new progress information to the database.

[2503] Input: Progress information sent from the device

[2504] Output: Latest progress information stored in the database

[2505] Specific action: The server saves the new progress information.

[2506] Step 7: Assigning a responder

[2507] User:

[2508] The user selects the appropriate person to handle the task and enters the assignment information.

[2509] Input: Information of the person in charge

[2510] Output: Assignment Request

[2511] Specific action: The user selects "Tanaka" as the person responsible for the "Document Creation" task.

[2512] Terminal:

[2513] The device sends the responder information to the server.

[2514] Input: Person in charge information

[2515] Output: Request to send to server

[2516] Specific action: The device sends the responder's information to the server.

[2517] server:

[2518] The server stores contact information in a database, and the AI ​​suggests the most suitable contact person.

[2519] Input: Respondent information sent from the device

[2520] Output: Responder information stored in the database, suggested best responder

[2521] Specific operation: The server stores contact information, and the AI ​​suggests the most suitable contact person.

[2522] Step 8: Generate and send reminder notifications

[2523] server:

[2524] The server periodically scans the task database to identify tasks that are nearing their deadline or are behind schedule.

[2525] Input: Task information in the database

[2526] Output: Verification result

[2527] Specific action: The server detects that the deadline for the "Document Creation" task is approaching.

[2528] server:

[2529] Based on the confirmation results, a reminder notification is generated and sent to the user.

[2530] Input: Confirmation result

[2531] Output: Reminder notification

[2532] Specific operation: The server generates a reminder notification and sends it to the user.

[2533] Emotional engine:

[2534] Before sending a reminder notification, the emotion engine analyzes the user's emotional state and adjusts the timing and content to the optimal level.

[2535] Input: User sentiment data

[2536] Output: Adjustment of notification content based on analysis results.

[2537] Specific operation: The emotion engine detects the user's stress level and changes the notification content to an encouraging message.

[2538] (Application Example 2)

[2539] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[2540] In modern industrial settings, managing complex tasks and setting appropriate priorities are critical challenges. In particular, the lack of task management that considers workers' emotions and stress levels can lead to decreased productivity. Furthermore, when multiple robots work together, inefficient communication and task redistribution between robots can result in task delays and the neglect of critical tasks. To solve this problem, a system is needed that allows numerous robots to efficiently perform tasks in industrial applications while also considering user emotions.

[2541] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a user input means for registering tasks, an artificial intelligence means for evaluating the priority of tasks and determining the priority, an emotion engine means for recognizing emotions and adjusting the priority using that information, a means for managing the progress of tasks, a means for assigning a person to handle a task, a communication means for realizing cooperation with multiple work robots in industrial applications, and a means for generating and transmitting reminder notifications. This enables effective task management that takes into account the user's emotional state and realizes efficient coordinated work of multiple work robots in industrial applications.

[2542] A "user input device" is an interface device used by a user to input information in order to register a task.

[2543] "Artificial intelligence tools" refer to algorithms and systems that analyze input task information, evaluate task priority and progress, and provide the optimal response.

[2544] An "emotional engine" is a technology that recognizes a user's emotions and adjusts task priorities based on that information.

[2545] "Means for managing task progress" refers to systems or devices for checking the progress status of registered tasks and recording and monitoring their progress.

[2546] "A means of assigning a person to a task" refers to a function that selects the most suitable person to handle a registered task and assigns that task to them.

[2547] "Means for generating and sending reminder notifications" refers to a system that creates reminder notifications based on task deadlines and progress, and notifies users or responsible parties at the appropriate time.

[2548] "Communication methods" refer to protocols and hardware used to exchange information necessary for multiple work robots to cooperate and perform tasks.

[2549] In this invention, the following systems and processes are introduced in a task management system for a factory, in order to achieve effective task management that takes into account the emotional states of multiple work robots and users.

[2550] Hardware and software used

[2551] Hardware: Work robots, cloud servers, user terminals

[2552] Software: MySQL database, TensorFlow, Affectiva SDK, Twilio API

[2553] System components and their functions

[2554] 1. User input method for registering tasks:

[2555] The server provides an interface for users to register new tasks through a task management application. Users enter information such as the task title, details, due date, priority, and assigned person. This information is sent to the server and stored in the database.

[2556] Specific example:

[2557] The user registers a task titled "Equipment Maintenance," setting the details to "Maintenance work scheduled for the weekend," the deadline to "2023-12-01," and the priority to "High." This information is sent to the server.

[2558] 2. Artificial intelligence methods for evaluating task priority:

[2559] The server periodically scans the database and uses TensorFlow to evaluate the priority of registered tasks. An AI algorithm analyzes task deadlines, progress, and other factors to determine priority.

[2560] Specific example:

[2561] The server uses AI to detect when the deadline for "equipment maintenance" tasks is approaching and sets them to a higher priority.

[2562] 3. Means of managing task progress:

[2563] As the robot completes a task, it sends real-time progress information to the server. The server stores this information in a database and monitors the task's progress.

[2564] Specific example:

[2565] The robot updates the progress of the "equipment maintenance" task up to 50% and sends that information to the server.

[2566] 4. Methods for assigning task managers:

[2567] The server selects the most suitable robot and assigns it tasks. AI analyzes each robot's schedule and skill set to suggest the optimal assignment.

[2568] Specific example:

[2569] The server suggests the most suitable robot for the "equipment maintenance" task and assigns the task to that robot.

[2570] 5. Means for generating and sending reminder notifications:

[2571] The server checks task deadlines and progress and generates reminder notifications. It uses the Twilio API to send notifications to administrators and robots. It uses the Affectiva SDK to detect the user's emotional state and adjust the content and timing of reminders accordingly.

[2572] Specific example:

[2573] The server detects that the deadline for the "equipment maintenance" task is approaching in three days and generates and sends a reminder notification to the user. If the emotion engine detects that the user is stressed, the content of the reminder notification is made gentler.

[2574] Program processing

[2575] The server integrates all of the above methods and runs the overall task management system. MySQL is used for the database, and TensorFlow is used for the AI ​​algorithm. Affectiva SDK is used for sentiment analysis, and the Twilio API is used for reminder notifications.

[2576] Example of a prompt:

[2577] "Please provide Python code that adjusts task priorities based on stress levels and sends appropriate reminder notifications."

[2578] The above describes the embodiments for carrying out the present invention. This enables task management that takes into account the user's emotional state, and allows for the effective and efficient operation of multiple work robots.

[2579] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[2580] Step 1:

[2581] The user launches the task management application on their device and registers a new task. The user enters information such as the task title, details, due date, priority, and assigned person. This information is sent to the server and stored in a MySQL database.

[2582] input:

[2583] Task information registered by the user (title, details, deadline, priority, responsible party)

[2584] output:

[2585] Task data stored on the server

[2586] Specific operation:

[2587] The user enters "Equipment maintenance," sets the details as "Maintenance work scheduled for the weekend," the deadline as "2023-12-01," and the priority as "High," and then submits the form.

[2588] Step 2:

[2589] The server periodically scans the database and evaluates the priority of registered tasks. It uses TensorFlow's AI algorithm to analyze task deadlines and progress to determine priorities. The results are updated in the database.

[2590] input:

[2591] Task information stored in the database

[2592] output:

[2593] Task data with re-evaluated priorities

[2594] Specific operation:

[2595] The server uses AI to analyze that the deadline for the "equipment maintenance" task is approaching and resets its priority to "highest."

[2596] Step 3:

[2597] Users update the progress of ongoing tasks using their terminals. Users enter the progress percentage and send it to the server. This progress information is stored in a database.

[2598] input:

[2599] User-updated progress information

[2600] output:

[2601] Progress data stored on the server

[2602] Specific operation:

[2603] The user updates the progress of "equipment maintenance" to 50% and presses the send button.

[2604] Step 4:

[2605] The server uses the emotion engine to recognize the user's emotion and adjusts the task priority based on that information. Perform emotion analysis using the Affectiva SDK and save the results in the database.

[2606] Input:

[2607] The user's emotion data

[2608] Output:

[2609] The task priority adjusted based on the emotion data

[2610] Specific operation:

[2611] If the emotion engine detects that the user's stress level is high, it further raises the task priority.

[2612] Step 5:

[2613] The server assigns the optimal robot based on the progress information and priority. The server uses AI to evaluate the schedule and skill set of each robot and assigns the task.

[2614] Input:

[2615] The task priority, the schedule and skill set information of each robot

[2616] Output:

[2617] The assignment information of the robot optimal for the task

[2618] Specific operation:

[2619] The server selects robot A, which is best suited for the "equipment maintenance" task, and sends a notification to that robot.

[2620] Step 6:

[2621] The server generates and sends reminder notifications to the user based on task deadlines and progress. It uses the Twilio API to send notifications and the Affectiva SDK to adjust the notification content based on the user's emotional state.

[2622] input:

[2623] Task deadlines, progress information, and user sentiment data

[2624] output:

[2625] Reminder notifications sent to users

[2626] Specific operation:

[2627] The server detects that the deadline for the "equipment maintenance" task is approaching in three days and, sensing the user's stress, sends a notification containing a kind and encouraging message.

[2628] Through each of the above steps, this system effectively manages tasks and integrates robots while taking into account the user's emotional state.

[2629] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[2630] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[2631] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[2632] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[2633] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[2634] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[2635] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[2636] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[2637] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[2638] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[2639] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[2640] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[2641] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[2642] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[2643] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[2644] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[2645] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[2646] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[2647] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[2648] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[2649] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[2650] The following is further disclosed regarding the embodiments described above.

[2651] (Claim 1)

[2652] A user input method for registering tasks,

[2653] An artificial intelligence tool for evaluating and determining the priority of tasks,

[2654] A means of managing the progress of tasks,

[2655] Methods for assigning task managers,

[2656] A means of generating and sending reminder notifications,

[2657] A system that includes this.

[2658] (Claim 2)

[2659] The system according to claim 1, comprising artificial intelligence for re-evaluating the priority of tasks.

[2660] (Claim 3)

[2661] The system according to claim 1, comprising means for analyzing the schedule and skill set of the person responsible for a task.

[2662] "Example 1"

[2663] (Claim 1)

[2664] A user input method for registering tasks,

[2665] An artificial intelligence tool for evaluating and determining the priority of tasks,

[2666] A means of managing the progress of tasks,

[2667] A means of assigning a person to handle a task,

[2668] A means of generating and sending reminder notifications,

[2669] A means of sending task information from the user's terminal to the server,

[2670] A means for the server to receive task information and store it in a database,

[2671] A means for the server to periodically scan the database and update priorities,

[2672] Methods for receiving reminder notifications and priority requests,

[2673] A means of scanning a database and generating notifications based on progress,

[2674] A method to analyze the schedules and skill sets of responders and propose the most suitable responder,

[2675] A system that includes this.

[2676] (Claim 2)

[2677] The system according to claim 1, comprising artificial intelligence for re-evaluating the priority of tasks.

[2678] (Claim 3)

[2679] The system according to claim 1, comprising means for analyzing the schedule and skill set of the responder.

[2680] "Application Example 1"

[2681] (Claim 1)

[2682] A means of inputting information to register a task,

[2683] An intelligent algorithmic means for evaluating task priority and determining priority,

[2684] A status management tool for managing the progress of tasks,

[2685] A personnel allocation method for assigning people to handle tasks,

[2686] An information notification means for generating and sending reminder notifications,

[2687] Methods for calculating task priority using AI,

[2688] An intelligent deployment method that proposes the optimal placement of personnel,

[2689] A system that includes this.

[2690] (Claim 2)

[2691] The system according to claim 1, comprising an artificial intelligence algorithm for re-evaluating the priority of tasks.

[2692] (Claim 3)

[2693] The system according to claim 1, comprising an analysis means for analyzing the schedule and capability set of the person responsible for a task.

[2694] "Example 2 of combining an emotion engine"

[2695] (Claim 1)

[2696] A user input method for registering tasks,

[2697] An artificial intelligence tool for evaluating and determining the priority of tasks,

[2698] A sentiment analysis tool that analyzes the user's emotional state and adjusts task priorities,

[2699] A means of managing the progress of tasks,

[2700] Methods for assigning task managers,

[2701] A means of generating and sending reminder notifications,

[2702] A system that includes this.

[2703] (Claim 2)

[2704] The system according to claim 1, comprising artificial intelligence for re-evaluating the priority of tasks.

[2705] (Claim 3)

[2706] The system according to claim 1, comprising means for analyzing the schedule and skill set of the person responsible for a task.

[2707] "Application example 2 when combining with an emotional engine"

[2708] (Claim 1)

[2709] A user input method for registering tasks,

[2710] An artificial intelligence tool for evaluating and determining the priority of tasks,

[2711] A means of managing the progress of tasks,

[2712] Methods for assigning task managers,

[2713] A means of generating and sending reminder notifications,

[2714] An emotion engine means that recognizes emotions and uses that information to adjust priorities,

[2715] A communication method that enables coordination between multiple robots in industrial applications,

[2716] A system that includes this.

[2717] (Claim 2)

[2718] The system according to claim 1, comprising artificial intelligence for re-evaluating the priority of tasks.

[2719] (Claim 3)

[2720] The system according to claim 1, comprising means for analyzing the schedule and skill set of the person responsible for a task. [Explanation of symbols]

[2721] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A user input method for registering tasks, An artificial intelligence tool for evaluating and determining the priority of tasks, A means of managing the progress of tasks, Methods for assigning task managers, A means of generating and sending reminder notifications, A system that includes this.

2. The system according to claim 1, comprising artificial intelligence for re-evaluating the priority of tasks.

3. The system according to claim 1, comprising means for analyzing the schedule and skill set of the person responsible for a task.

Images