system

Abstract

We provide the system. [Solution] A means for users to input schedule data, A means of sending the above scheduled data to the server, The above server receives the above scheduled data and stores it in the database, The above server has a means of calculating task priorities based on the above schedule data, A means for processing the dependencies of the above tasks and generating a time schedule, A system including means for notifying the user of the generated schedule.

Description

Technical Field

[0001] The technology of this 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, and includes steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In modern society, many people need to efficiently manage multiple tasks and schedules, but the current situation is that the effort and time required are increasing. In particular, it is complicated to create an optimal schedule while considering the priority and dependency of tasks, and time and labor are required to address this problem. To solve this problem, a system that is easy for users to use and can perform efficient task management is needed.

Means for Solving the Problems

[0005] To solve this problem, the present invention provides the following means: a system including means for a user to input schedule data, means for transmitting the schedule data to a server, means for the server to receive the schedule data and store it in a database, means for the server to calculate task priorities based on the schedule data, means for processing the dependencies of the tasks and generating a time schedule, and means for notifying the user of the generated schedule. This reduces the burden of task management for the user and enables efficient and effective execution of schedules. Furthermore, by further including means for the user's terminal to visually display the schedule, the user can easily check the schedule visually. In addition, by further including means for sorting tasks based on task priorities, resolving dependencies, and generating a time schedule, an optimal schedule is automatically generated.

[0006] Understood. Below are definitions for each of the important words.

[0007] A "user" is an individual or group that uses the system to input schedule data and manage tasks.

[0008] "Schedule data" refers to task information entered by the user, including the task name, priority, duration, and dependencies.

[0009] A "task" refers to a series of actions that a user must manage within a system, with a specific purpose.

[0010] A "terminal" is a device used by a user to operate a system, and includes personal computers and smartphones.

[0011] A "server" is a computer system that receives and stores scheduled data, and then performs the process of calculating task priorities and schedules.

[0012] A "database" is a management system used to store scheduled data on a server, and it maintains the integrity and completeness of the data.

[0013] "Priority" refers to the order in which a task should be given priority over other tasks, based on its importance and urgency.

[0014] A "dependency" refers to a situation where one task must be initiated only after another specific task has been completed.

[0015] A "schedule" is a time plan that includes the start and end times of tasks, and it indicates the optimal sequence of tasks that the system generates.

[0016] "Notification" refers to the process of informing the user of a generated schedule, and is the act of the system providing the schedule to the user.

[0017] "Visual display" refers to the process of displaying schedules in a way that allows users to visually confirm them on their devices, and includes calendar displays and list displays. [Brief explanation of the drawing]

[0018] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6]It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which multiple emotions are mapped. [Figure 10] It shows an emotion map to which multiple emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

Embodiments for Carrying Out the Invention

[0019] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0020] First, the language used in the following description will be explained.

[0021] 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).

[0022] 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.

[0023] 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.

[0024] 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).

[0025] 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."

[0026] [First Embodiment]

[0027] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0028] 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.

[0029] 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).

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0035] 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.

[0036] 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.

[0037] 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.

[0038] 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".

[0039] The invention described herein is a system that efficiently manages multiple tasks and appointments, allowing users to easily generate an optimal schedule. This system enables the user to input task data, which is then received, stored, and processed by a server, thereby generating an optimal schedule for the user.

[0040] 1. The user enters the task.

[0041] Users input task data, such as task name, priority, duration, and dependencies, into the system using a device (e.g., a smartphone or computer). This data is entered through the user interface and transmitted to the server in real time.

[0042] 2. Sending and receiving task data

[0043] The terminal sends task data to the server. Task data is typically sent over the internet, and the server receives it.

[0044] 3. The server saves the task data.

[0045] The server saves the received task data to a database. The database is managed to maintain data integrity and completeness. This saving process ensures that the data necessary for subsequent processing is retained.

[0046] 4. Calculating Priority

[0047] The server calculates task priorities based on stored task data. This calculation is based on the importance and urgency of each task. Furthermore, it considers task dependencies to determine which tasks should be executed before others.

[0048] 5. Handling dependencies and generating schedules

[0049] The server resolves task dependencies and generates an optimal time schedule. This includes checking the completion of other tasks on which a task depends and setting appropriate start and end times. The schedule is generated to ensure that tasks are completed efficiently, taking priorities and dependencies into consideration.

[0050] 6. Schedule notifications

[0051] The server generates a schedule and notifies the user. Possible notification methods include push notifications to the device and email notifications. This allows the user to receive the latest schedule in real time.

[0052] 7. Visual display of the schedule

[0053] The terminal visually displays the schedule received from the server. The visual display is in calendar or list format to allow users to easily understand and manage their schedule. Task details and progress are also displayed as needed.

[0054] Specific example

[0055] For example, suppose a user enters the following task into the system:

[0056] Task 1: Check emails (Priority 1, Estimated time: 0.5 hours, No dependencies)

[0057] Task 2: Meeting (Priority 3, Duration 1 hour, No dependencies)

[0058] Task 3: Report creation (Priority 2, Estimated time 2 hours, Dependent tasks 2)

[0059] The user enters these tasks from their terminal. The terminal then sends the task data to the server, which receives and stores it.

[0060] Next, the server calculates the task priorities and determines that Task 2 (meeting) has the highest priority. The server considers dependencies and creates a schedule so that report creation begins after the meeting ends. The final schedule will be "Task 1: Check email -> Task 2: Meeting -> Task 3: Report creation".

[0061] The generated schedule is sent to the user's terminal, which displays it visually. The user can easily check the order and start time of the tasks. In this way, the system of the present invention significantly improves the efficiency of the user's task management.

[0062] The following describes the processing flow.

[0063] Step 1:

[0064] The user uses a terminal to enter the task name, priority, duration, and dependencies. This task data is entered through the user interface.

[0065] Step 2:

[0066] The terminal sends the entered task data to the server. The task data is sent to the server as a POST request via the internet.

[0067] Step 3:

[0068] The server checks the received task data and saves it to the database. First, the server checks the integrity and completeness of the data, and if there are no problems, it saves it to the database.

[0069] Step 4:

[0070] The server calculates task priorities based on stored task data. The importance and urgency of tasks are then evaluated based on the priority calculation algorithm.

[0071] Step 5:

[0072] The server handles task dependencies. After confirming that all dependent tasks are complete, it adjusts the schedule so that the next task can start.

[0073] Step 6:

[0074] The server generates an optimal schedule. Task start and end times are set, taking priorities and dependencies into consideration. The generated schedule is saved to the database.

[0075] Step 7:

[0076] The server generates a schedule and notifies the user's device. Push notifications and email are used as notification methods. This notification process allows the user to receive the latest schedule in real time.

[0077] Step 8:

[0078] The user's device visually displays the schedule received from the server. The schedule is displayed on the device screen in calendar or list format, allowing the user to easily check the order and start time of tasks. Detailed information and progress are also displayed as needed.

[0079] Through the steps described above, the present invention significantly improves the efficiency of user task management and provides an optimal schedule.

[0080] (Example 1)

[0081] 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."

[0082] Traditional scheduling systems often resulted in inefficient schedules because users were unable to properly handle task priorities and dependencies when managing numerous tasks. Furthermore, the way generated schedules were communicated to users and their visual representation were unclear, making it difficult for users to easily understand and manage their schedules. This led to users having to expend a significant amount of time and effort on schedule management.

[0083] 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.

[0084] In this invention, the server includes means for the user to input schedule data, means for sending the schedule data to the server, means for the server to receive the schedule data and store it in a database, means for calculating task priorities based on the schedule data, means for processing task dependencies and generating a time schedule, and means for notifying the user terminal of the generated schedule. This enables the user to manage their schedule efficiently and appropriately and to easily visually confirm the generated schedule.

[0085] A "user" is a person who uses a system to input data for the purpose of managing tasks and schedules.

[0086] "Schedule data" refers to data that includes information such as task name, priority, duration, and dependencies entered by the user.

[0087] A "server" is a computer system that receives schedule data sent by users, stores it in a database, processes the data, and generates an optimal schedule.

[0088] A "database" is a collection of data managed by a server that stores received schedule data and retrieves or updates it as needed.

[0089] "Priority" refers to the order in which tasks should be performed before others, based on their importance and urgency.

[0090] A "dependency" is a relationship in which one task must be executed before another, and it is a factor that determines the order in which tasks are performed.

[0091] A "time schedule" is a timetable that shows the planned execution of tasks, specifying the start and end times of each task.

[0092] "Notification" refers to a means of communicating information to inform users of a generated schedule, and includes, for example, push notifications and email notifications.

[0093] "Visual display" refers to displaying schedules in an easy-to-read format, such as a calendar or list, on the user's device.

[0094] "Organizing" refers to rearranging tasks based on their priorities and dependencies, and determining the order in which they should be executed.

[0095] This invention relates to a system for enabling users to efficiently manage multiple tasks and appointments and generate an optimal schedule. In this system, a server processes task data entered by the user, generates an optimal schedule based on that data, and notifies the user.

[0096] First, users input task data using a smartphone or computer through the user interface (UI) of a web or mobile application. This includes the task name, priority, duration, dependencies, and so on.

[0097] Next, the task data entered by the user is sent to the server via the internet. The server receives this data and stores it in a database. The database can be a relational database such as MySQL® or PostgreSQL. This storage process ensures the integrity and completeness of the data.

[0098] The server calculates task priorities based on stored task data. Priority calculations are based on task importance and urgency, and also consider task dependencies. This allows the server to determine which tasks should be executed before others.

[0099] Next, the server analyzes the task dependencies and generates an optimal time schedule. In this step, it checks for the completion of other tasks on which the task depends and sets the start and end times for the task. Taking priorities and dependencies into consideration, the schedule is generated to ensure that the task is completed efficiently.

[0100] The generated schedule is notified from the server to the user's device. Notifications are sent using methods such as push notifications and email notifications. Users receive the notification and can check the latest schedule in real time.

[0101] Finally, the user's device visually displays the received schedule. Display formats include calendar and list, and task details and progress are shown as needed. This allows the user to easily understand and manage their schedule.

[0102] Specific example

[0103] For example, if a user enters the following task:

[0104] Task 1: Check emails (Priority 1, Estimated time: 0.5 hours, No dependencies)

[0105] Task 2: Meeting (Priority 3, Duration 1 hour, No dependencies)

[0106] Task 3: Report creation (Priority 2, Estimated time 2 hours, Dependent tasks 2)

[0107] The user enters these tasks from their terminal, and the terminal sends the task data to the server. The server receives this data and stores it in a database. The server then calculates the task priorities and determines that Task 2 (meeting) has the highest priority. Considering dependencies, the server creates a schedule so that report creation begins after the meeting ends. As a result, the final schedule will look like this:

[0108] Task 1: Check email

[0109] Task 2: Meeting

[0110] Task 3: Report creation

[0111] The generated schedule is sent to the user's device, where it is displayed visually. The user can easily check the order and start time of tasks, enabling efficient task management.

[0112] Example of a prompt

[0113] The following is an example of a prompt message that instructs the system to generate the optimal schedule:

[0114] "I have entered three tasks with priorities and dependencies. Please generate the optimal schedule for these tasks."

[0115] Task 1: Check emails (Priority 1, Estimated time: 0.5 hours, No dependencies)

[0116] Task 2: Meeting (Priority 3, Duration 1 hour, No dependencies)

[0117] Task 3: Report creation (Priority 2, Estimated time 2 hours, Dependent tasks 2)

[0118] In this way, the system of the present invention significantly improves the efficiency of user task management.

[0119] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0120] Step 1:

[0121] The user enters the task data.

[0122] Specifically, users use their devices to input data such as task name, priority, duration, and dependencies, and then send this data to the system. The input format is provided through forms in web and mobile applications. The input data here might be something like "Check email (priority 1, duration 0.5 hours, no dependencies)."

[0123] Step 2:

[0124] The terminal sends task data to the server.

[0125] The entered task data is sent to the server via the internet. This transmission is performed using an HTTP POST request, and the data is packaged in JSON format. For example, the task data "Email Confirmation" is sent in the following format:

[0126] json

[0127] {

[0128] "task_name": "Email confirmation",

[0129] "priority": 1,

[0130] "duration": 0.5,

[0131] "dependency": null

[0132] }

[0133] Step 3:

[0134] The server receives task data and saves it to the database.

[0135] The server receives task data sent from the terminal, verifies data integrity, and then saves it to the database. When saving, the server executes an SQL query similar to the following:

[0136] SQL

[0137] INSERT INTO tasks (task_name, priority, duration, dependency) VALUES ("Email confirmation", 1, 0.5, NULL);

[0138] The input here is task data, and the output is the completion of saving to the database.

[0139] Step 4:

[0140] The server calculates task priorities based on the stored task data.

[0141] The server retrieves task data stored in the database and calculates task priority based on priority levels. This calculation compares priority values, ensuring that tasks with higher values ​​are processed first. The input is task data retrieved from the database, and the output is a task list with assigned priorities.

[0142] Step 5:

[0143] The server analyzes task dependencies and generates an optimal time schedule.

[0144] The server analyzes the dependencies between tasks and generates a schedule to place dependent tasks in the appropriate order. For example, if task A depends on task B, task A will start after task B is completed. The input is a prioritized list of tasks, and the output is the optimal time schedule.

[0145] Step 6:

[0146] The server generates a schedule which is then sent to the user's device.

[0147] The generated schedule is notified from the server to the user's device. This notification can be a push notification or an email notification. The input is the generated schedule, and the output is the notification to the user. For example, in the case of an email notification, the notification content would be "Your new schedule."

[0148] Step 7:

[0149] The device visually displays the schedule it has received.

[0150] The system visually displays the schedule received by the user's device in calendar or list format. This allows the user to easily check the order and start time of tasks. The input is the notified schedule, and the output is the visually displayed schedule. The user interface is implemented using frameworks such as JavaScript® and React.

[0151] (Application Example 1)

[0152] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0153] Within factories, a wide variety of tasks are handled by robots, and there is a need to efficiently manage these tasks. Conventional systems have difficulty properly managing task priorities and dependencies, resulting in decreased production efficiency. Furthermore, there has been a lack of means to notify managers and robots of task schedules in real time, hindering smooth work progress. The objective of this invention is to solve these problems and streamline task management for robots within factories.

[0154] 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.

[0155] In this invention, the server includes means for a user to input schedule data, means for transmitting the schedule data to the server, means for the server to receive the schedule data and store it in a database, means for the server to calculate task priorities based on the schedule data, means for processing the dependencies of the tasks and generating a time schedule, means for notifying the user of the generated schedule, means for inputting robot work tasks from a management device and generating an optimized schedule based on priorities and dependencies in order to efficiently manage robot tasks in a factory, means for notifying factory managers and robots of the generated schedule, and visual display means for visually displaying the generated schedule.

[0156] This streamlines task management for robots within the factory, enabling real-time notifications of optimal schedules that take priorities and dependencies into consideration.

[0157] "User" refers to the person who manages the tasks of the robots within the factory.

[0158] "Schedule data" refers to data entered by the user, including information such as task name, priority, duration, and dependencies.

[0159] A "server" refers to a device that receives schedule data sent from a user's terminal, stores and processes it, and generates and notifies users of their schedule.

[0160] A "database" refers to an information storage system used to store and manage scheduled data received by a server.

[0161] "Priority" refers to the criteria used to determine the order in which each task is processed, taking into account its importance and urgency.

[0162] A "dependency" refers to a relationship where a particular task can only begin if another task is completed.

[0163] A "time schedule" refers to a plan that includes the start and end times of tasks, generated by taking priorities and dependencies into consideration.

[0164] "Management equipment" refers to devices used to input work tasks for robots in a factory.

[0165] "Notification" refers to a means of informing users and robots of the generated schedule.

[0166] "Visual display means" refers to a device or method for visually displaying a generated schedule so that it can be easily understood by the user.

[0167] The following describes a specific system configuration and its operation procedure for carrying out this invention.

[0168] First, the user uses factory management equipment (e.g., a dedicated tablet or PC) to input scheduled data for the tasks they want the robots to perform. This scheduled data includes the task name, priority, duration, and dependencies. This data is entered through the user interface and transmitted to the server in real time.

[0169] Next, the server receives the schedule data sent from the user terminal via the internet and stores it in the database. Commonly used database management systems such as SQLite or PostgreSQL are used as the database.

[0170] The server calculates the priority of each task based on the stored schedule data. Specifically, the priority is determined based on the importance and urgency of each task. It also considers the dependencies between tasks to determine which tasks should be executed before others. Considering task priorities and dependencies, it generates an optimal time schedule. This schedule is calculated with high accuracy using machine learning and optimization algorithms.

[0171] The generated schedule is notified to management equipment and robots within the factory. Notification methods include push notifications, email, or real-time notifications via a dedicated application. The schedule notified by the server is visually displayed on the management equipment's interface. Display formats such as Gantt charts and list formats are possible, designed to allow users to easily understand and manage the schedule.

[0172] As a concrete example, a factory manager enters the following task into the system:

[0173] Task 1: Inspection (Priority 2, Estimated time: 1 hour, No dependencies)

[0174] Task 2: Parts Delivery (Priority 1, Estimated Time 0.5 hours, No Dependencies)

[0175] Task 3: Component assembly (Priority 3, Estimated time 2 hours, Dependent tasks 2)

[0176] Users input these tasks through a dedicated interface, which are then sent to the server. The server receives and stores them, and, considering priority and dependencies, generates a schedule as follows: "Task 2 -> Task 1 -> Task 3". The schedule is communicated to administrators and robots and is displayed visually.

[0177] As an example of a prompt statement:

[0178] "Task name: Inspection, Priority: 2, Estimated time: 1 hour, Dependencies: None"

[0179] Task management can be performed efficiently using prompt statements like these.

[0180] This system streamlines robot operations within the factory and provides real-time notifications of optimal schedules that appropriately consider priorities and dependencies. This results in improved production efficiency and smoother workflow.

[0181] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0182] Step 1:

[0183] The user uses a management device to input scheduled data for the task they want the robot to perform (task name, priority, duration, dependencies, etc.). The entered data is sent to the server via the user interface. The input data is in the format of, for example, "Task name: Inspection, Priority: 2, Duration: 1 hour, Dependencies: None".

[0184] Step 2:

[0185] The terminal sends the entered schedule data to the server, which receives it via the internet. The server verifies the received data and saves it to a database. Databases such as SQLite and PostgreSQL are used. This saving process ensures that the data necessary for subsequent processing is reliably retained.

[0186] Step 3:

[0187] The server calculates task priorities based on the stored schedule data. This calculation is based on the importance and urgency of each task. Specifically, it retrieves the value of the "priority" field from the received data and determines the processing order of each task based on that value.

[0188] Step 4:

[0189] The server processes task dependencies and generates a time schedule. This process checks the "dependencies" field of each task and sets the time so that the next task starts only after its dependent tasks have completed. For example, if "Task 3" depends on "Task 2," the schedule will be set so that Task 3 starts only after Task 2 has finished.

[0190] Step 5:

[0191] The server notifies management equipment and robots within the factory of the generated schedule. Possible notification methods include push notifications, email, and real-time notifications via a dedicated application. At this point, the notified schedule is in an optimized order based on the task data entered by the user.

[0192] Step 6:

[0193] The management device terminal visually displays the schedule received from the server. The visual display format can be a Gantt chart or a list. This visual display allows users to easily check and manage the start and end times of each task.

[0194] Step 7:

[0195] As a concrete example, a user inputs the following tasks, the server receives and saves them, and, considering priority and dependencies, generates a schedule of "Task 2 -> Task 1 -> Task 3". This schedule is notified to the administrator and the robot and is visually displayed on the management device.

[0196] In this way, the server processes data entered by the user, generates an optimal schedule, and notifies and displays it, thus streamlining task management for robots within the factory.

[0197] 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.

[0198] This invention incorporates an emotion engine that recognizes, analyzes, and considers user emotions into a system aimed at improving the efficiency of task management. This system can analyze user emotions in real time and adjust task priorities and schedules based on that information. It also includes a task suggestion function to reduce user stress and fatigue.

[0199] 1. The user enters the schedule data.

[0200] Users input task names, priorities, estimated time, dependencies, and sentiment data into the system using their devices (smartphones or PCs). Sentiment data is either manually entered by the user or automatically acquired by sensors or cameras installed on the device.

[0201] 2. Sending and receiving task data and sentiment data

[0202] The device sends task data and emotion data to the server. The data is transmitted over the internet and received by the server. Emotion recognition technology is implemented using facial expression recognition, voice analysis, text analysis, etc.

[0203] 3. The server stores and processes the data.

[0204] The server reviews the received task and sentiment data and saves it to the database. The database contains the information necessary for schedule generation.

[0205] 4. Calculating Priority

[0206] The server calculates task priorities. In this process, in addition to task importance and urgency, user sentiment data is also considered. For example, if a user is stressed, the task order may be adjusted to alleviate that stress.

[0207] 5. Utilizing the Emotional Engine

[0208] An emotion engine within the server analyzes the user's emotions in real time. Based on the user's emotional state, it dynamically adjusts task priorities and schedules. The emotion engine also suggests refreshing tasks to reduce the user's stress and fatigue.

[0209] 6. Generating an optimal schedule

[0210] The server resolves task dependencies and generates an optimal schedule that takes sentiment data into account. Task start and end times are set based on a comprehensive evaluation of priorities, dependencies, and user sentiment states.

[0211] 7. Schedule notifications

[0212] The server generates a schedule and notifies the user's device. Notifications are sent via methods such as push notifications, email, and alerts, allowing the user to receive the latest schedule in real time.

[0213] 8. Visual representation of the schedule

[0214] The user's device visually displays the schedule received from the server. The visual display is presented in calendar or list format, designed for easy user understanding. Refreshment tasks and reminders based on emotional state are also displayed.

[0215] Specific example

[0216] For example, suppose a user enters the following task into the system:

[0217] Task 1: Check emails (Priority 1, Estimated time: 0.5 hours, No dependencies)

[0218] Task 2: Meeting (Priority 3, Duration 1 hour, No dependencies)

[0219] Task 3: Report creation (Priority 2, Estimated time 2 hours, Dependent tasks 2)

[0220] If the system determines that the user is experiencing stress, it can add a short break (refreshment task) before the meeting.

[0221] The specific processing flow is as follows: the user inputs the task data via their device, and the device sends this data to the server. The server receives and stores the task data and sentiment data, and generates a schedule based on priorities, dependencies, and sentiment data. Finally, the generated schedule is notified to the user's device and displayed visually.

[0222] As a result, the system of the present invention not only manages tasks but also provides an optimal schedule that takes into account the user's emotional state, thereby supporting the reduction of user stress and efficient task execution.

[0223] The following describes the processing flow.

[0224] Modes for carrying out the invention

[0225] This invention incorporates an emotion engine that recognizes, analyzes, and considers user emotions into a system aimed at improving the efficiency of task management. This system can analyze user emotions in real time and adjust task priorities and schedules based on that information. It also includes a task suggestion function to reduce user stress and fatigue.

[0226] System processing flow

[0227] Step 1:

[0228] The user uses the device to input the task name, priority, duration, and dependencies. This task data is entered through the device's user interface. User sentiment data is also collected. Sentiment data is either entered by the user or automatically acquired by sensors and cameras installed on the device.

[0229] Step 2:

[0230] The terminal sends the entered task data and sentiment data to the server. The data is sent to the server via the internet as a POST request.

[0231] Step 3:

[0232] The server verifies the received task and sentiment data and saves it to the database. First, the server checks the integrity and completeness of the data, and if there are no problems, it saves it to the database.

[0233] Step 4:

[0234] The server calculates task priorities based on stored task data. The importance and urgency of tasks are evaluated based on a priority calculation algorithm. Sentimental data is also considered in the calculation; for example, if a user is experiencing stress, task reordering is performed to reduce stress.

[0235] Step 5:

[0236] The emotion engine on the server analyzes the user's emotions in real time. The emotion engine uses emotion recognition technologies such as facial expression recognition, voice analysis, and text analysis to determine the user's emotional state.

[0237] Step 6:

[0238] The server dynamically adjusts task priorities and schedules based on the analysis results of the emotion engine. The order and start times of tasks may change based on the user's emotional state. The emotion engine also suggests refreshing tasks to reduce the user's stress and fatigue.

[0239] Step 7:

[0240] The server resolves task dependencies and generates an optimal schedule that takes sentiment data into account. Task start and end times are set based on a comprehensive evaluation of priorities, dependencies, and user sentiment states.

[0241] Step 8:

[0242] The server generates a schedule and notifies the user's device. Push notifications and email are used as notification methods. This notification process allows the user to receive the latest schedule in real time.

[0243] Step 9:

[0244] The user's device visually displays the schedule received from the server. The schedule is displayed on the device screen in calendar or list format, allowing the user to easily check the order and start times of tasks. Refreshment tasks and reminders based on emotional state are also displayed.

[0245] Specific example

[0246] For example, suppose a user enters the following task into the system:

[0247] Task 1: Check emails (Priority 1, Estimated time: 0.5 hours, No dependencies)

[0248] Task 2: Meeting (Priority 3, Duration 1 hour, No dependencies)

[0249] Task 3: Report creation (Priority 2, Estimated time 2 hours, Dependent tasks 2)

[0250] If the emotion engine determines that the user is experiencing stress, the system can add a short break (refreshment task) before the meeting. The specific process involves the user inputting the task data via their device, which then sends it to the server. The server receives and stores the task data and emotion data, and generates a schedule based on priorities, dependencies, and emotion data. Finally, the generated schedule is notified to the user's device and displayed visually.

[0251] As a result, the system of the present invention not only manages tasks but also provides an optimal schedule that takes into account the user's emotional state, thereby supporting the reduction of user stress and efficient task execution.

[0252] (Example 2)

[0253] 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".

[0254] Traditional task management systems only provided standardized schedules without considering the user's emotional state. This failed to alleviate user stress and fatigue, hindering efficient task completion. Furthermore, the lack of real-time analysis and reflection of emotional data made dynamic schedule adjustments difficult.

[0255] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0256] In this invention, the server includes means for the user to input schedule data, means for transmitting the schedule data and emotional data to the server, means for the server to receive the schedule data and emotional data and store it in a database, means for the server to calculate task priorities based on the schedule data and emotional data, means for analyzing the user's emotional state in real time using an emotional engine and dynamically adjusting task priorities and schedules, means for processing the dependencies of the tasks and generating a time schedule considering the emotional data, and means for notifying the user of the generated schedule. This makes it possible to provide an optimal task schedule that takes the user's emotional state into consideration.

[0257] A "user" refers to an individual who uses the system to manage tasks and adjust schedules.

[0258] "Schedule data" refers to information necessary for task management and schedule generation, such as the task name, priority, duration, and dependencies entered by the user.

[0259] "Emotional data" refers to information that indicates the user's emotional state, and is acquired either through manual input or by sensors or cameras installed on the device.

[0260] A "server" refers to a computer system that receives, stores, and processes data sent by users.

[0261] A "database" refers to a system that stores task data and sentiment data received by a server, and stores necessary information.

[0262] An "emotion engine" refers to a software component that analyzes a user's emotional state in real time and reflects the results in task prioritization and scheduling.

[0263] "Priority" refers to the order in which tasks are executed, determined based on their importance, urgency, and sentiment data.

[0264] "Dependency" refers to the dependencies that each task has on other tasks, and the order of tasks is determined based on these dependencies.

[0265] A "time schedule" refers to a plan that includes the start and end times of tasks, generated based on priorities and dependencies.

[0266] "Notification methods" refer to methods such as push notifications, emails, and alerts used to inform users of generated schedules.

[0267] "Visual display" refers to the function of displaying the generated schedule on the device in a calendar or list format so that users can easily check it.

[0268] This invention relates to a task management system that takes user emotions into consideration. This system provides a function in which a server generates an optimal task schedule based on the planned data and emotion data entered by the user, and notifies the user's terminal.

[0269] Hardware and software usage

[0270] This system uses the following hardware and software:

[0271] Devices: Smartphones (e.g., iPhone®, Android®), PCs (e.g., Windows, Mac)

[0272] Emotion recognition technologies: OpenCV (facial expression recognition), speech analysis software, natural language processing software (e.g., Google® Cloud Natural Language API)

[0273] Server: A high-performance computer system

[0274] Database: MySQL, PostgreSQL

[0275] Notification System: Firebase Cloud Messaging, Email Sending Service

[0276] Specific Processing of the System

[0277] Data Input

[0278] The user uses their own terminal to input the detailed information of the task (task name, priority, required time, dependencies). In addition, emotional data can also be input. This emotional data can be input by the user themselves or automatically acquired by sensors or cameras installed on the terminal.

[0279] Data Transmission and Reception

[0280] The input task data and emotional data are transmitted from the terminal to the server via the Internet. The server receives these data and saves them in the database after verification.

[0281] Data Analysis and Processing

[0282] The server calculates the priority of the task based on the received data. At this time, the emotional engine is used to analyze the user's emotional state in real time, and the order and schedule of the task are dynamically adjusted. In addition, the dependencies of the task are processed, and a time schedule considering emotional data is generated.

[0283] Schedule Generation and Notification

[0284] The schedule generated by the server is notified to the user's terminal and conveyed to the user by means such as push notifications, emails, and alerts. The terminal receives the notification and visually displays the schedule. The display format is in calendar format or list format, and refresh tasks and precautions are also displayed.

[0285] Examples of Specific Examples and Prompt Sentences

[0286] For example, assume that the user inputs the following tasks into the system:

[0287] Task 1: Email check (Priority 1, Duration 0.5 hours, No dependencies)

[0288] Task 2: Meeting (Priority 3, Duration 1 hour, No dependencies)

[0289] Task 3: Report creation (Priority 2, Duration 2 hours, Dependent on Task 2)

[0290] In this case, when the user inputs emotion data such as "I'm a bit tired today", the system can add a refresh task of "10 - minute stretch" before the meeting.

[0291] As a specific example when the user inputs a prompt sentence into the generative AI model, the following prompts can be considered:

[0292] Prompt example: "There is an important meeting at 3 pm. Please propose a short task that can refresh me before that."

[0293] The system of the present invention not only manages tasks simply, but also provides an optimal schedule considering the user's emotional state, and supports stress reduction and efficient task execution for the user.

[0294] The flow of the specific process in Example 2 will be described using FIG. 13.

[0295] The processing flow of the program of this system

[0296] Step 1: The user inputs schedule data

[0297] Users use their devices (smartphones or PCs) to input task details and sentiment data into the system. The input data includes task name, priority, duration, dependencies, and sentiment data. Sentiment data can be entered manually by the user or automatically acquired using sensors or cameras installed on the device.

[0298] Input: Task information (task name, priority, duration, dependencies), sentiment data

[0299] Output: Temporary data storage within the terminal

[0300] Specific actions: The user opens a smartphone app, enters "Task name: Report creation, Priority: 2, Estimated time: 2 hours, Dependency: Meeting," and describes their emotional state as "I'm a little tired today."

[0301] Step 2: Sending and receiving task data and sentiment data

[0302] The terminal sends the entered task data and sentiment data to the server. The transmission takes place over the internet, and the data is encrypted before transmission. The server receives the data and verifies its integrity.

[0303] Input: Task data and sentiment data entered into the terminal.

[0304] Output: Data sent to the server

[0305] Specific operation: The smartphone uses Wi-Fi or mobile data communication to encrypt the entered data and send it to the server.

[0306] Step 3: The server stores and processes the data.

[0307] The server reviews the received task and sentiment data and saves it to a database. This database is used to store the information necessary for schedule generation.

[0308] Input: Task data and sentiment data received by the server

[0309] Output: Data stored in the database

[0310] Specific operation: The server checks the received data in JSON format and checks for any missing information, and then inserts it into a database such as MySQL or PostgreSQL.

[0311] Step 4: Calculation of priority

[0312] The server calculates the priority of the task. In this calculation, in addition to the importance and urgency of the task, sentiment data is also considered. For example, when the user is feeling high stress, a refresh task may be inserted.

[0313] Input: Task data and sentiment data stored in the database

[0314] Output: Task data with calculated priority

[0315] Specific operation: The server uses the sentiment engine to analyze sentiment data such as "feeling a little tired today" and recalculates the priority based on the urgency and importance of the task.

[0316] Step 5: Utilization of the sentiment engine

[0317] The sentiment engine in the server analyzes sentiment data in real time. Based on the analysis results, the priority and schedule of the task are dynamically adjusted. Also, proposals for refresh tasks are made.

[0318] Input: Task data with calculated priority and sentiment data

[0319] Output: Adjusted priority and schedule

[0320] Specific action: The emotional engine detects a state of "fatigue" and suggests "10 minutes of stretching" as a way to refresh.

[0321] Step 6: Generate the optimal schedule

[0322] The server considers task dependencies and generates an optimal schedule that reflects sentiment data. It sets the start and end times for tasks and proposes the most efficient schedule.

[0323] Input: Adjusted priority and task data

[0324] Output: Generated time schedule

[0325] Specific operation: The server inserts a "10-minute stretch" between the meeting and report creation and generates it as a schedule.

[0326] Step 7: Schedule Notification

[0327] The server generates a schedule and notifies the user's device. Notification methods include push notifications, email, and alerts.

[0328] Input: Generated time schedule

[0329] Output: Schedule notified to the user's device

[0330] Specific action: The smartphone displays a schedule via push notification, such as "10:00-11:00 Meeting, 11:00-11:10 Refresh, 11:10-13:10 Report writing."

[0331] Step 8: Visualizing the Schedule

[0332] The user's device visually displays the schedule received from the server. The display is in calendar or list format, and refresh tasks and notes are also shown.

[0333] Input: Schedule notified to the user's device

[0334] Output: Visually displayed schedule

[0335] Specific action: The smartphone's calendar app displays the daily schedule and highlights stretching time as a refresh task on the screen.

[0336] (Application Example 2)

[0337] 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".

[0338] Traditional task management systems fail to consider the emotional state of users, making it difficult to maximize work efficiency and performance. Furthermore, they cannot detect and respond immediately to user stress or fatigue in real time. As a result, work efficiency decreases, potentially negatively impacting user health. This problem is particularly pronounced in factories and production lines where high precision and efficiency are required.

[0339] 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.

[0340] In this invention, the server includes means for receiving user schedule data and emotional data and storing it in a database, means for analyzing the user's emotional state in real time and calculating task priorities based on that analysis, and means for suggesting refreshing tasks to reduce the user's stress and fatigue. This makes it possible to dynamically adjust task priorities and schedules based on the user's emotional state, thereby improving the efficiency and accuracy of the steel production line.

[0341] "Schedule data" refers to information about the tasks and time schedules entered by the user.

[0342] "Emotional data" refers to data that represents the emotional state of a user and is collected in real time.

[0343] A "server" is a device that receives scheduled data and sentiment data sent by users, and processes and stores them.

[0344] A "database" is a data storage system for saving received schedule data and sentiment data.

[0345] The method for calculating "priority" is an algorithm that evaluates the importance and urgency of tasks based on scheduled data and sentiment data, and then determines the order in which they will be processed.

[0346] "Dependency" refers to a situation where one task is related to another task, and the schedule is adjusted based on that relationship.

[0347] The means of generating a "time schedule" is the process of determining the start and end times of each task, taking into account priorities and dependencies.

[0348] The means of notifying the "user" refers to a communication method for informing the user of the generated schedule in real time.

[0349] "Means of visual display" refers to an interface that clearly displays the generated schedule to the user.

[0350] An "emotion engine" is a system that analyzes a user's emotional state in real time and dynamically adjusts task priorities and schedules based on that information.

[0351] A "refreshment task" refers to a suggestion for a break or light work to reduce user stress and fatigue.

[0352] This invention incorporates an emotion engine into a factory work management system aimed at improving the efficiency of task management. This engine recognizes, analyzes, and considers the emotions of users and workers. The system analyzes user emotions in real time and uses this information to adjust task priorities and schedules. It also includes a function to suggest refreshing tasks to reduce user stress and fatigue.

[0353] The elements necessary to realize this system are as follows:

[0354] hardware

[0355] 1. Sensors: Cameras and microphones for collecting emotional data.

[0356] 2. Terminal: A user interface used for data entry and receiving notifications, such as a PC or smartphone.

[0357] 3. Server: A central computing device for processing data and storing and distributing results.

[0358] software

[0359] 1. Emotion Recognition API: A tool for analyzing user emotions in real time (e.g., Emotion API).

[0360] 2. Task Management API: A program for managing task data and generating schedules (e.g., Factory Tasks API).

[0361] 3. Data analysis libraries: Libraries used for data processing and analysis, such as Pandas and NumPy.

[0362] 4. Scheduling algorithm: A program for calculating task priorities and resolving dependencies.

[0363] This system processes information in the following steps:

[0364] Specific example

[0365] For example, suppose a factory worker inputs tasks such as "assembly," "quality control," and "packaging" into the system. Furthermore, if the system detects that the worker is experiencing a high stress level through emotion recognition, it automatically inserts break times to reduce the worker's stress. At this time, an optimal task schedule is generated and notified to the worker's device, and also displayed visually.

[0366] Example of a prompt

[0367] The following are possible input prompt formats:

[0368] "Enter tasks such as assembly, quality control, and packaging. Sensors will analyze your emotions in real time, suggesting refreshing tasks if stress levels are high. It will then generate and visually display an optimal schedule."

[0369] The system of this invention thus achieves optimal task management and scheduling based on the user's emotional state, improving work efficiency and reducing user stress. This makes it possible to balance factory productivity with employee health.

[0370] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0371] Step 1:

[0372] The user enters the schedule data.

[0373] The user uses a terminal to input task name, priority, duration, dependencies, and sentiment data into the system. The input data takes the form of task name, priority, and duration, while sentiment data is either entered by the user or automatically acquired by sensors or cameras installed on the terminal.

[0374] Step 2:

[0375] Sending and receiving task data and sentiment data

[0376] The terminal sends the entered task data and sentiment data to the server. The data is sent to the server via the internet using a secure communication protocol, and the server receives it.

[0377] Step 3:

[0378] The server stores and processes the data.

[0379] The server stores received task data and emotion data in a database. The data is stored in an organized format and used for subsequent processing and analysis. For example, emotion data is used for facial expression recognition, voice analysis, and text analysis to quantify the user's emotional state.

[0380] Step 4:

[0381] Priority calculation

[0382] The server calculates the priority of each task, taking into account its importance, urgency, and emotional data. For example, if a user is experiencing stress, the server adjusts the order of tasks to alleviate that stress. The calculated priority is then used to determine the order in which tasks are processed.

[0383] Step 5:

[0384] Utilizing the Emotion Engine

[0385] An emotion engine on the server analyzes the user's emotions in real time. The emotion engine uses facial expression recognition APIs and voice analysis APIs to analyze emotional data and dynamically adjust task priorities and schedules based on the emotional state. It also suggests refreshing tasks necessary to reduce the user's stress and fatigue.

[0386] Step 6:

[0387] Generating an optimal schedule

[0388] The server resolves task dependencies and generates an optimal schedule that takes sentiment data into account. It comprehensively evaluates priorities, dependencies, and the user's emotional state to set the start and end times for each task. The generated schedule reduces user stress levels while enabling efficient task processing.

[0389] Step 7:

[0390] Schedule notification

[0391] The server notifies the user's device of the generated schedule. Notifications are sent via methods such as push notifications, email, and alerts, allowing the user to receive the latest schedule in real time. The notified schedule is displayed in the device's notification center or in specific applications.

[0392] Step 8:

[0393] Visual display of schedule

[0394] The user's device visually displays the schedule received from the server. The visual display is presented in calendar or list format, designed for easy user understanding. Furthermore, refresh tasks and reminders are also displayed, providing intuitive feedback on the user's emotional state.

[0395] Through these steps, task prioritization and scheduling are optimized based on the user's emotional state, reducing user stress and enabling efficient task completion.

[0396] 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.

[0397] 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.

[0398] 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.

[0399] [Second Embodiment]

[0400] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0401] 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.

[0402] 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).

[0403] 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.

[0404] 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.

[0405] 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).

[0406] 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.

[0407] 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.

[0408] 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.

[0409] 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.

[0410] 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.

[0411] 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".

[0412] The invention described herein is a system that efficiently manages multiple tasks and appointments, allowing users to easily generate an optimal schedule. This system enables the user to input task data, which is then received, stored, and processed by a server, thereby generating an optimal schedule for the user.

[0413] 1. The user enters the task.

[0414] Users input task data, such as task name, priority, duration, and dependencies, into the system using a device (e.g., a smartphone or computer). This data is entered through the user interface and transmitted to the server in real time.

[0415] 2. Sending and receiving task data

[0416] The terminal sends task data to the server. Task data is typically sent over the internet, and the server receives it.

[0417] 3. The server saves the task data.

[0418] The server saves the received task data to a database. The database is managed to maintain data integrity and completeness. This saving process ensures that the data necessary for subsequent processing is retained.

[0419] 4. Calculating Priority

[0420] The server calculates task priorities based on stored task data. This calculation is based on the importance and urgency of each task. Furthermore, it considers task dependencies to determine which tasks should be executed before others.

[0421] 5. Handling dependencies and generating schedules

[0422] The server resolves task dependencies and generates an optimal time schedule. This includes checking the completion of other tasks on which a task depends and setting appropriate start and end times. The schedule is generated to ensure that tasks are completed efficiently, taking priorities and dependencies into consideration.

[0423] 6. Schedule notifications

[0424] The server generates a schedule and notifies the user. Possible notification methods include push notifications to the device and email notifications. This allows the user to receive the latest schedule in real time.

[0425] 7. Visual display of the schedule

[0426] The terminal visually displays the schedule received from the server. The visual display is in calendar or list format to allow users to easily understand and manage their schedule. Task details and progress are also displayed as needed.

[0427] Specific example

[0428] For example, suppose a user enters the following task into the system:

[0429] Task 1: Check emails (Priority 1, Estimated time: 0.5 hours, No dependencies)

[0430] Task 2: Meeting (Priority 3, Duration 1 hour, No dependencies)

[0431] Task 3: Report creation (Priority 2, Estimated time 2 hours, Dependent tasks 2)

[0432] The user enters these tasks from their terminal. The terminal then sends the task data to the server, which receives and stores it.

[0433] Next, the server calculates the task priorities and determines that Task 2 (meeting) has the highest priority. The server considers dependencies and creates a schedule so that report creation begins after the meeting ends. The final schedule will be "Task 1: Check email -> Task 2: Meeting -> Task 3: Report creation".

[0434] The generated schedule is sent to the user's terminal, which displays it visually. The user can easily check the order and start time of the tasks. In this way, the system of the present invention significantly improves the efficiency of the user's task management.

[0435] The following describes the processing flow.

[0436] Step 1:

[0437] The user uses a terminal to enter the task name, priority, duration, and dependencies. This task data is entered through the user interface.

[0438] Step 2:

[0439] The terminal sends the entered task data to the server. The task data is sent to the server as a POST request via the internet.

[0440] Step 3:

[0441] The server checks the received task data and saves it to the database. First, the server checks the integrity and completeness of the data, and if there are no problems, it saves it to the database.

[0442] Step 4:

[0443] The server calculates task priorities based on stored task data. The importance and urgency of tasks are then evaluated based on the priority calculation algorithm.

[0444] Step 5:

[0445] The server handles task dependencies. After confirming that all dependent tasks are complete, it adjusts the schedule so that the next task can start.

[0446] Step 6:

[0447] The server generates an optimal schedule. Task start and end times are set, taking priorities and dependencies into consideration. The generated schedule is saved to the database.

[0448] Step 7:

[0449] The server generates a schedule and notifies the user's device. Push notifications and email are used as notification methods. This notification process allows the user to receive the latest schedule in real time.

[0450] Step 8:

[0451] The user's device visually displays the schedule received from the server. The schedule is displayed on the device screen in calendar or list format, allowing the user to easily check the order and start time of tasks. Detailed information and progress are also displayed as needed.

[0452] Through the steps described above, the present invention significantly improves the efficiency of user task management and provides an optimal schedule.

[0453] (Example 1)

[0454] 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."

[0455] Traditional scheduling systems often resulted in inefficient schedules because users were unable to properly handle task priorities and dependencies when managing numerous tasks. Furthermore, the way generated schedules were communicated to users and their visual representation were unclear, making it difficult for users to easily understand and manage their schedules. This led to users having to expend a significant amount of time and effort on schedule management.

[0456] 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.

[0457] In this invention, the server includes means for the user to input schedule data, means for sending the schedule data to the server, means for the server to receive the schedule data and store it in a database, means for calculating task priorities based on the schedule data, means for processing task dependencies and generating a time schedule, and means for notifying the user terminal of the generated schedule. This enables the user to manage their schedule efficiently and appropriately and to easily visually confirm the generated schedule.

[0458] A "user" is a person who uses a system to input data for the purpose of managing tasks and schedules.

[0459] "Schedule data" refers to data that includes information such as task name, priority, duration, and dependencies entered by the user.

[0460] A "server" is a computer system that receives schedule data sent by users, stores it in a database, processes the data, and generates an optimal schedule.

[0461] A "database" is a collection of data managed by a server that stores received schedule data and retrieves or updates it as needed.

[0462] "Priority" refers to the order in which tasks should be performed before others, based on their importance and urgency.

[0463] A "dependency" is a relationship in which one task must be executed before another, and it is a factor that determines the order in which tasks are performed.

[0464] A "time schedule" is a timetable that shows the planned execution of tasks, specifying the start and end times of each task.

[0465] "Notification" refers to a means of communicating information to inform users of a generated schedule, and includes, for example, push notifications and email notifications.

[0466] "Visual display" refers to displaying schedules in an easy-to-read format, such as a calendar or list, on the user's device.

[0467] "Organizing" refers to rearranging tasks based on their priorities and dependencies, and determining the order in which they should be executed.

[0468] This invention relates to a system for enabling users to efficiently manage multiple tasks and appointments and generate an optimal schedule. In this system, a server processes task data entered by the user, generates an optimal schedule based on that data, and notifies the user.

[0469] First, users input task data using a smartphone or computer through the user interface (UI) of a web or mobile application. This includes the task name, priority, duration, dependencies, and so on.

[0470] Next, the task data entered by the user is sent to the server via the internet. The server receives this data and stores it in a database. The database can be a relational database such as MySQL or PostgreSQL. This storage process ensures the integrity and completeness of the data.

[0471] The server calculates task priorities based on stored task data. Priority calculations are based on task importance and urgency, and also consider task dependencies. This allows the server to determine which tasks should be executed before others.

[0472] Next, the server analyzes the task dependencies and generates an optimal time schedule. In this step, it checks for the completion of other tasks on which the task depends and sets the start and end times for the task. Taking priorities and dependencies into consideration, the schedule is generated to ensure that the task is completed efficiently.

[0473] The generated schedule is notified from the server to the user's device. Notifications are sent using methods such as push notifications and email notifications. Users receive the notification and can check the latest schedule in real time.

[0474] Finally, the user's device visually displays the received schedule. Display formats include calendar and list, and task details and progress are shown as needed. This allows the user to easily understand and manage their schedule.

[0475] Specific example

[0476] For example, if a user enters the following task:

[0477] Task 1: Check emails (Priority 1, Estimated time: 0.5 hours, No dependencies)

[0478] Task 2: Meeting (Priority 3, Duration 1 hour, No dependencies)

[0479] Task 3: Report creation (Priority 2, Estimated time 2 hours, Dependent tasks 2)

[0480] The user enters these tasks from their terminal, and the terminal sends the task data to the server. The server receives this data and stores it in a database. The server then calculates the task priorities and determines that Task 2 (meeting) has the highest priority. Considering dependencies, the server creates a schedule so that report creation begins after the meeting ends. As a result, the final schedule will look like this:

[0481] Task 1: Check email

[0482] Task 2: Meeting

[0483] Task 3: Report creation

[0484] The generated schedule is sent to the user's device, where it is displayed visually. The user can easily check the order and start time of tasks, enabling efficient task management.

[0485] Example of a prompt

[0486] The following is an example of a prompt message that instructs the system to generate the optimal schedule:

[0487] "I have entered three tasks with priorities and dependencies. Please generate the optimal schedule for these tasks."

[0488] Task 1: Check emails (Priority 1, Estimated time: 0.5 hours, No dependencies)

[0489] Task 2: Meeting (Priority 3, Duration 1 hour, No dependencies)

[0490] Task 3: Report creation (Priority 2, Estimated time 2 hours, Dependent tasks 2)

[0491] In this way, the system of the present invention significantly improves the efficiency of user task management.

[0492] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0493] Step 1:

[0494] The user enters the task data.

[0495] Specifically, users use their devices to input data such as task name, priority, duration, and dependencies, and then send this data to the system. The input format is provided through forms in web and mobile applications. The input data here might be something like "Check email (priority 1, duration 0.5 hours, no dependencies)."

[0496] Step 2:

[0497] The terminal sends task data to the server.

[0498] The entered task data is sent to the server via the internet. This transmission is performed using an HTTP POST request, and the data is packaged in JSON format. For example, the task data "Email Confirmation" is sent in the following format:

[0499] json

[0500] {

[0501] "task_name": "Email confirmation",

[0502] "priority": 1,

[0503] "duration": 0.5,

[0504] "dependency": null

[0505] }

[0506] Step 3:

[0507] The server receives task data and saves it to the database.

[0508] The server receives task data sent from the terminal, verifies data integrity, and then saves it to the database. When saving, the server executes an SQL query similar to the following:

[0509] SQL

[0510] INSERT INTO tasks (task_name, priority, duration, dependency) VALUES ("Email confirmation", 1, 0.5, NULL);

[0511] The input here is task data, and the output is the completion of saving to the database.

[0512] Step 4:

[0513] The server calculates task priorities based on the stored task data.

[0514] The server retrieves task data stored in the database and calculates task priority based on priority levels. This calculation compares priority values, ensuring that tasks with higher values ​​are processed first. The input is task data retrieved from the database, and the output is a task list with assigned priorities.

[0515] Step 5:

[0516] The server analyzes task dependencies and generates an optimal time schedule.

[0517] The server analyzes the dependencies between tasks and generates a schedule to place dependent tasks in the appropriate order. For example, if task A depends on task B, task A will start after task B is completed. The input is a prioritized list of tasks, and the output is the optimal time schedule.

[0518] Step 6:

[0519] The server generates a schedule which is then sent to the user's device.

[0520] The generated schedule is notified from the server to the user's device. This notification can be a push notification or an email notification. The input is the generated schedule, and the output is the notification to the user. For example, in the case of an email notification, the notification content would be "Your new schedule."

[0521] Step 7:

[0522] The device visually displays the schedule it has received.

[0523] The system visually displays the schedule received by the user's device in calendar or list format. This allows the user to easily check the order and start time of tasks. The input is the notified schedule, and the output is the visually displayed schedule. The user interface is implemented using frameworks such as JavaScript or React.

[0524] (Application Example 1)

[0525] 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."

[0526] Within factories, a wide variety of tasks are handled by robots, and there is a need to efficiently manage these tasks. Conventional systems have difficulty properly managing task priorities and dependencies, resulting in decreased production efficiency. Furthermore, there has been a lack of means to notify managers and robots of task schedules in real time, hindering smooth work progress. The objective of this invention is to solve these problems and streamline task management for robots within factories.

[0527] 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.

[0528] In this invention, the server includes means for a user to input schedule data, means for transmitting the schedule data to the server, means for the server to receive the schedule data and store it in a database, means for the server to calculate task priorities based on the schedule data, means for processing the dependencies of the tasks and generating a time schedule, means for notifying the user of the generated schedule, means for inputting robot work tasks from a management device and generating an optimized schedule based on priorities and dependencies in order to efficiently manage robot tasks in a factory, means for notifying factory managers and robots of the generated schedule, and visual display means for visually displaying the generated schedule.

[0529] This streamlines task management for robots within the factory, enabling real-time notifications of optimal schedules that take priorities and dependencies into consideration.

[0530] "User" refers to the person who manages the tasks of the robots within the factory.

[0531] "Schedule data" refers to data entered by the user, including information such as task name, priority, duration, and dependencies.

[0532] A "server" refers to a device that receives schedule data sent from a user's terminal, stores and processes it, and generates and notifies users of their schedule.

[0533] A "database" refers to an information storage system used to store and manage scheduled data received by a server.

[0534] "Priority" refers to the criteria used to determine the order in which each task is processed, taking into account its importance and urgency.

[0535] A "dependency" refers to a relationship where a particular task can only begin if another task is completed.

[0536] A "time schedule" refers to a plan that includes the start and end times of tasks, generated by taking priorities and dependencies into consideration.

[0537] "Management equipment" refers to devices used to input work tasks for robots in a factory.

[0538] "Notification" refers to a means of informing users and robots of the generated schedule.

[0539] "Visual display means" refers to a device or method for visually displaying a generated schedule so that it can be easily understood by the user.

[0540] The following describes a specific system configuration and its operation procedure for carrying out this invention.

[0541] First, the user uses factory management equipment (e.g., a dedicated tablet or PC) to input scheduled data for the tasks they want the robots to perform. This scheduled data includes the task name, priority, duration, and dependencies. This data is entered through the user interface and transmitted to the server in real time.

[0542] Next, the server receives the schedule data sent from the user terminal via the internet and stores it in the database. Commonly used database management systems such as SQLite or PostgreSQL are used as the database.

[0543] The server calculates the priority of each task based on the stored schedule data. Specifically, the priority is determined based on the importance and urgency of each task. It also considers the dependencies between tasks to determine which tasks should be executed before others. Considering task priorities and dependencies, it generates an optimal time schedule. This schedule is calculated with high accuracy using machine learning and optimization algorithms.

[0544] The generated schedule is notified to management equipment and robots within the factory. Notification methods include push notifications, email, or real-time notifications via a dedicated application. The schedule notified by the server is visually displayed on the management equipment's interface. Display formats such as Gantt charts and list formats are possible, designed to allow users to easily understand and manage the schedule.

[0545] As a concrete example, a factory manager enters the following task into the system:

[0546] Task 1: Inspection (Priority 2, Estimated time: 1 hour, No dependencies)

[0547] Task 2: Parts Delivery (Priority 1, Estimated Time 0.5 hours, No Dependencies)

[0548] Task 3: Component assembly (Priority 3, Estimated time 2 hours, Dependent tasks 2)

[0549] Users input these tasks through a dedicated interface, which are then sent to the server. The server receives and stores them, and, considering priority and dependencies, generates a schedule as follows: "Task 2 -> Task 1 -> Task 3". The schedule is communicated to administrators and robots and is displayed visually.

[0550] As an example of a prompt statement:

[0551] "Task name: Inspection, Priority: 2, Estimated time: 1 hour, Dependencies: None"

[0552] Task management can be performed efficiently using prompt statements like these.

[0553] This system streamlines robot operations within the factory and provides real-time notifications of optimal schedules that appropriately consider priorities and dependencies. This results in improved production efficiency and smoother workflow.

[0554] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0555] Step 1:

[0556] The user uses a management device to input scheduled data for the task they want the robot to perform (task name, priority, duration, dependencies, etc.). The entered data is sent to the server via the user interface. The input data is in the format of, for example, "Task name: Inspection, Priority: 2, Duration: 1 hour, Dependencies: None".

[0557] Step 2:

[0558] The terminal sends the entered schedule data to the server, which receives it via the internet. The server verifies the received data and saves it to a database. Databases such as SQLite and PostgreSQL are used. This saving process ensures that the data necessary for subsequent processing is reliably retained.

[0559] Step 3:

[0560] The server calculates task priorities based on the stored schedule data. This calculation is based on the importance and urgency of each task. Specifically, it retrieves the value of the "priority" field from the received data and determines the processing order of each task based on that value.

[0561] Step 4:

[0562] The server processes task dependencies and generates a time schedule. This process checks the "dependencies" field of each task and sets the time so that the next task starts only after its dependent tasks have completed. For example, if "Task 3" depends on "Task 2," the schedule will be set so that Task 3 starts only after Task 2 has finished.

[0563] Step 5:

[0564] The server notifies management equipment and robots within the factory of the generated schedule. Possible notification methods include push notifications, email, and real-time notifications via a dedicated application. At this point, the notified schedule is in an optimized order based on the task data entered by the user.

[0565] Step 6:

[0566] The management device terminal visually displays the schedule received from the server. The visual display format can be a Gantt chart or a list. This visual display allows users to easily check and manage the start and end times of each task.

[0567] Step 7:

[0568] As a concrete example, a user inputs the following tasks, the server receives and saves them, and, considering priority and dependencies, generates a schedule of "Task 2 -> Task 1 -> Task 3". This schedule is notified to the administrator and the robot and is visually displayed on the management device.

[0569] In this way, the server processes data entered by the user, generates an optimal schedule, and notifies and displays it, thus streamlining task management for robots within the factory.

[0570] 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.

[0571] This invention incorporates an emotion engine that recognizes, analyzes, and considers user emotions into a system aimed at improving the efficiency of task management. This system can analyze user emotions in real time and adjust task priorities and schedules based on that information. It also includes a task suggestion function to reduce user stress and fatigue.

[0572] 1. The user enters the schedule data.

[0573] Users input task names, priorities, estimated time, dependencies, and sentiment data into the system using their devices (smartphones or PCs). Sentiment data is either manually entered by the user or automatically acquired by sensors or cameras installed on the device.

[0574] 2. Sending and receiving task data and sentiment data

[0575] The device sends task data and emotion data to the server. The data is transmitted over the internet and received by the server. Emotion recognition technology is implemented using facial expression recognition, voice analysis, text analysis, etc.

[0576] 3. The server stores and processes the data.

[0577] The server reviews the received task and sentiment data and saves it to the database. The database contains the information necessary for schedule generation.

[0578] 4. Calculating Priority

[0579] The server calculates task priorities. In this process, in addition to task importance and urgency, user sentiment data is also considered. For example, if a user is stressed, the task order may be adjusted to alleviate that stress.

[0580] 5. Utilizing the Emotional Engine

[0581] An emotion engine within the server analyzes the user's emotions in real time. Based on the user's emotional state, it dynamically adjusts task priorities and schedules. The emotion engine also suggests refreshing tasks to reduce the user's stress and fatigue.

[0582] 6. Generating an optimal schedule

[0583] The server resolves task dependencies and generates an optimal schedule that takes sentiment data into account. Task start and end times are set based on a comprehensive evaluation of priorities, dependencies, and user sentiment states.

[0584] 7. Schedule notifications

[0585] The server generates a schedule and notifies the user's device. Notifications are sent via methods such as push notifications, email, and alerts, allowing the user to receive the latest schedule in real time.

[0586] 8. Visual representation of the schedule

[0587] The user's device visually displays the schedule received from the server. The visual display is presented in calendar or list format, designed for easy user understanding. Refreshment tasks and reminders based on emotional state are also displayed.

[0588] Specific example

[0589] For example, suppose a user enters the following task into the system:

[0590] Task 1: Check emails (Priority 1, Estimated time: 0.5 hours, No dependencies)

[0591] Task 2: Meeting (Priority 3, Duration 1 hour, No dependencies)

[0592] Task 3: Report creation (Priority 2, Estimated time 2 hours, Dependent tasks 2)

[0593] If the system determines that the user is experiencing stress, it can add a short break (refreshment task) before the meeting.

[0594] The specific processing flow is as follows: the user inputs the task data via their device, and the device sends this data to the server. The server receives and stores the task data and sentiment data, and generates a schedule based on priorities, dependencies, and sentiment data. Finally, the generated schedule is notified to the user's device and displayed visually.

[0595] As a result, the system of the present invention not only manages tasks but also provides an optimal schedule that takes into account the user's emotional state, thereby supporting the reduction of user stress and efficient task execution.

[0596] The following describes the processing flow.

[0597] Modes for carrying out the invention

[0598] This invention incorporates an emotion engine that recognizes, analyzes, and considers user emotions into a system aimed at improving the efficiency of task management. This system can analyze user emotions in real time and adjust task priorities and schedules based on that information. It also includes a task suggestion function to reduce user stress and fatigue.

[0599] System processing flow

[0600] Step 1:

[0601] The user uses the device to input the task name, priority, duration, and dependencies. This task data is entered through the device's user interface. User sentiment data is also collected. Sentiment data is either entered by the user or automatically acquired by sensors and cameras installed on the device.

[0602] Step 2:

[0603] The terminal sends the entered task data and sentiment data to the server. The data is sent to the server via the internet as a POST request.

[0604] Step 3:

[0605] The server verifies the received task and sentiment data and saves it to the database. First, the server checks the integrity and completeness of the data, and if there are no problems, it saves it to the database.

[0606] Step 4:

[0607] The server calculates task priorities based on stored task data. The importance and urgency of tasks are evaluated based on a priority calculation algorithm. Sentimental data is also considered in the calculation; for example, if a user is experiencing stress, task reordering is performed to reduce stress.

[0608] Step 5:

[0609] The emotion engine on the server analyzes the user's emotions in real time. The emotion engine uses emotion recognition technologies such as facial expression recognition, voice analysis, and text analysis to determine the user's emotional state.

[0610] Step 6:

[0611] The server dynamically adjusts task priorities and schedules based on the analysis results of the emotion engine. The order and start times of tasks may change based on the user's emotional state. The emotion engine also suggests refreshing tasks to reduce the user's stress and fatigue.

[0612] Step 7:

[0613] The server resolves task dependencies and generates an optimal schedule that takes sentiment data into account. Task start and end times are set based on a comprehensive evaluation of priorities, dependencies, and user sentiment states.

[0614] Step 8:

[0615] The server generates a schedule and notifies the user's device. Push notifications and email are used as notification methods. This notification process allows the user to receive the latest schedule in real time.

[0616] Step 9:

[0617] The user's device visually displays the schedule received from the server. The schedule is displayed on the device screen in calendar or list format, allowing the user to easily check the order and start times of tasks. Refreshment tasks and reminders based on emotional state are also displayed.

[0618] Specific example

[0619] For example, suppose a user enters the following task into the system:

[0620] Task 1: Check emails (Priority 1, Estimated time: 0.5 hours, No dependencies)

[0621] Task 2: Meeting (Priority 3, Duration 1 hour, No dependencies)

[0622] Task 3: Report creation (Priority 2, Estimated time 2 hours, Dependent tasks 2)

[0623] If the emotion engine determines that the user is experiencing stress, the system can add a short break (refreshment task) before the meeting. The specific process involves the user inputting the task data via their device, which then sends it to the server. The server receives and stores the task data and emotion data, and generates a schedule based on priorities, dependencies, and emotion data. Finally, the generated schedule is notified to the user's device and displayed visually.

[0624] As a result, the system of the present invention not only manages tasks but also provides an optimal schedule that takes into account the user's emotional state, thereby supporting the reduction of user stress and efficient task execution.

[0625] (Example 2)

[0626] 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".

[0627] Traditional task management systems only provided standardized schedules without considering the user's emotional state. This failed to alleviate user stress and fatigue, hindering efficient task completion. Furthermore, the lack of real-time analysis and reflection of emotional data made dynamic schedule adjustments difficult.

[0628] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0629] In this invention, the server includes means for the user to input schedule data, means for transmitting the schedule data and emotional data to the server, means for the server to receive the schedule data and emotional data and store it in a database, means for the server to calculate task priorities based on the schedule data and emotional data, means for analyzing the user's emotional state in real time using an emotional engine and dynamically adjusting task priorities and schedules, means for processing the dependencies of the tasks and generating a time schedule considering the emotional data, and means for notifying the user of the generated schedule. This makes it possible to provide an optimal task schedule that takes the user's emotional state into consideration.

[0630] A "user" refers to an individual who uses the system to manage tasks and adjust schedules.

[0631] "Schedule data" refers to information necessary for task management and schedule generation, such as the task name, priority, duration, and dependencies entered by the user.

[0632] "Emotional data" refers to information that indicates the user's emotional state, and is acquired either through manual input or by sensors or cameras installed on the device.

[0633] A "server" refers to a computer system that receives, stores, and processes data sent by users.

[0634] A "database" refers to a system that stores task data and sentiment data received by a server, and stores necessary information.

[0635] An "emotion engine" refers to a software component that analyzes a user's emotional state in real time and reflects the results in task prioritization and scheduling.

[0636] "Priority" refers to the order in which tasks are executed, determined based on their importance, urgency, and sentiment data.

[0637] "Dependency" refers to the dependencies that each task has on other tasks, and the order of tasks is determined based on these dependencies.

[0638] A "time schedule" refers to a plan that includes the start and end times of tasks, generated based on priorities and dependencies.

[0639] "Notification methods" refer to methods such as push notifications, emails, and alerts used to inform users of generated schedules.

[0640] "Visual display" refers to the function of displaying the generated schedule on the device in a calendar or list format so that users can easily check it.

[0641] This invention relates to a task management system that takes user emotions into consideration. This system provides a function in which a server generates an optimal task schedule based on the planned data and emotion data entered by the user, and notifies the user's terminal.

[0642] Hardware and software usage

[0643] This system uses the following hardware and software:

[0644] Devices: Smartphones (e.g., iPhone, Android), PCs (e.g., Windows, Mac)

[0645] Emotion recognition technology: OpenCV (facial expression recognition), speech analysis software, natural language processing software (e.g., Google Cloud Natural Language API)

[0646] Server: A high-performance computer system

[0647] Database: MySQL, PostgreSQL

[0648] Notification system: Firebase Cloud Messaging, email sending service

[0649] Specific processing of the system

[0650] Data entry

[0651] Users input task details (task name, priority, duration, dependencies) using their own devices. In addition, they can input sentiment data. This sentiment data can be entered manually by the user or automatically acquired by sensors and cameras installed on the device.

[0652] Data transmission and reception

[0653] The entered task data and sentiment data are transmitted from the terminal to the server via the internet. The server receives this data, verifies it, and then stores it in a database.

[0654] Data analysis and processing

[0655] The server calculates task priorities based on the received data. During this process, it uses an emotion engine to analyze the user's emotional state in real time, dynamically adjusting the task order and schedule. It also processes task dependencies and generates a time schedule that takes emotional data into account.

[0656] Schedule generation and notification

[0657] The schedule generated by the server is notified to the user's device and communicated to the user through means such as push notifications, email, and alerts. The device receives the notification and displays the schedule visually. The display format can be calendar or list, and refresh tasks and notes are also displayed.

[0658] Examples of specific cases and prompt statements

[0659] For example, suppose a user enters the following task into the system:

[0660] Task 1: Check emails (Priority 1, Estimated time: 0.5 hours, No dependencies)

[0661] Task 2: Meeting (Priority 3, Duration 1 hour, No dependencies)

[0662] Task 3: Report creation (Priority 2, Estimated time 2 hours, Dependent tasks 2)

[0663] In this case, if the user enters emotional data such as "I'm a little tired today," the system can add a refreshing task such as "10 minutes of stretching" before the meeting.

[0664] The following are some examples of prompts that users might input into a generated AI model:

[0665] Example prompt: "I have an important meeting at 3 PM. Please suggest a short task to refresh myself before then."

[0666] The system of this invention not only manages tasks but also provides an optimal schedule that takes into account the user's emotional state, thereby supporting user stress reduction and efficient task execution.

[0667] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0668] Processing flow of this system's program

[0669] Step 1: The user enters the schedule data.

[0670] Users use their devices (smartphones or PCs) to input task details and sentiment data into the system. The input data includes task name, priority, duration, dependencies, and sentiment data. Sentiment data can be entered manually by the user or automatically acquired using sensors or cameras installed on the device.

[0671] Input: Task information (task name, priority, duration, dependencies), sentiment data

[0672] Output: Temporary data storage within the terminal

[0673] Specific actions: The user opens a smartphone app, enters "Task name: Report creation, Priority: 2, Estimated time: 2 hours, Dependency: Meeting," and describes their emotional state as "I'm a little tired today."

[0674] Step 2: Sending and receiving task data and sentiment data

[0675] The terminal sends the entered task data and sentiment data to the server. The transmission takes place over the internet, and the data is encrypted before transmission. The server receives the data and verifies its integrity.

[0676] Input: Task data and sentiment data entered into the terminal.

[0677] Output: Data sent to the server

[0678] Specific operation: The smartphone uses Wi-Fi or mobile data communication to encrypt the entered data and send it to the server.

[0679] Step 3: The server stores and processes the data.

[0680] The server reviews the received task and sentiment data and saves it to a database. This database is used to store the information necessary for schedule generation.

[0681] Input: Task data and sentiment data received by the server

[0682] Output: Data stored in the database

[0683] Specific operation: The server checks the received data in JSON format, verifies that there is no missing information, and then inserts it into a database such as MySQL or PostgreSQL.

[0684] Step 4: Calculating Priorities

[0685] The server calculates task priorities. This calculation considers not only the importance and urgency of tasks, but also emotional data. For example, if a user is experiencing high stress levels, a refresh task may be inserted.

[0686] Input: Task data and sentiment data stored in the database

[0687] Output: Task data with calculated priorities

[0688] Specific operation: The server uses an emotion engine to analyze emotion data such as "I'm a little tired today," and recalculates the priority based on the urgency and importance of the task.

[0689] Step 5: Utilizing the Emotional Engine

[0690] The emotion engine on the server analyzes emotion data in real time. Based on the analysis results, task priorities and schedules are dynamically adjusted. It also suggests refresh tasks.

[0691] Input: Task data with calculated priorities and sentiment data

[0692] Output: Adjusted priorities and schedules

[0693] Specific action: The emotional engine detects a state of "fatigue" and suggests "10 minutes of stretching" as a way to refresh.

[0694] Step 6: Generate the optimal schedule

[0695] The server considers task dependencies and generates an optimal schedule that reflects sentiment data. It sets the start and end times for tasks and proposes the most efficient schedule.

[0696] Input: Adjusted priority and task data

[0697] Output: Generated time schedule

[0698] Specific operation: The server inserts a "10-minute stretch" between the meeting and report creation and generates it as a schedule.

[0699] Step 7: Schedule Notification

[0700] The server generates a schedule and notifies the user's device. Notification methods include push notifications, email, and alerts.

[0701] Input: Generated time schedule

[0702] Output: Schedule notified to the user's device

[0703] Specific action: The smartphone displays a schedule via push notification, such as "10:00-11:00 Meeting, 11:00-11:10 Refresh, 11:10-13:10 Report writing."

[0704] Step 8: Visualizing the Schedule

[0705] The user's device visually displays the schedule received from the server. The display is in calendar or list format, and refresh tasks and notes are also shown.

[0706] Input: Schedule notified to the user's device

[0707] Output: Visually displayed schedule

[0708] Specific action: The smartphone's calendar app displays the daily schedule and highlights stretching time as a refresh task on the screen.

[0709] (Application Example 2)

[0710] 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."

[0711] Traditional task management systems fail to consider the emotional state of users, making it difficult to maximize work efficiency and performance. Furthermore, they cannot detect and respond immediately to user stress or fatigue in real time. As a result, work efficiency decreases, potentially negatively impacting user health. This problem is particularly pronounced in factories and production lines where high precision and efficiency are required.

[0712] 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.

[0713] In this invention, the server includes means for receiving user schedule data and emotional data and storing it in a database, means for analyzing the user's emotional state in real time and calculating task priorities based on that analysis, and means for suggesting refreshing tasks to reduce the user's stress and fatigue. This makes it possible to dynamically adjust task priorities and schedules based on the user's emotional state, thereby improving the efficiency and accuracy of the steel production line.

[0714] "Schedule data" refers to information about the tasks and time schedules entered by the user.

[0715] "Emotional data" refers to data that represents the emotional state of a user and is collected in real time.

[0716] A "server" is a device that receives scheduled data and sentiment data sent by users, and processes and stores them.

[0717] A "database" is a data storage system for saving received schedule data and sentiment data.

[0718] The method for calculating "priority" is an algorithm that evaluates the importance and urgency of tasks based on scheduled data and sentiment data, and then determines the order in which they will be processed.

[0719] "Dependency" refers to a situation where one task is related to another task, and the schedule is adjusted based on that relationship.

[0720] The means of generating a "time schedule" is the process of determining the start and end times of each task, taking into account priorities and dependencies.

[0721] The means of notifying the "user" refers to a communication method for informing the user of the generated schedule in real time.

[0722] "Means of visual display" refers to an interface that clearly displays the generated schedule to the user.

[0723] An "emotion engine" is a system that analyzes a user's emotional state in real time and dynamically adjusts task priorities and schedules based on that information.

[0724] A "refreshment task" refers to a suggestion for a break or light work to reduce user stress and fatigue.

[0725] This invention incorporates an emotion engine into a factory work management system aimed at improving the efficiency of task management. This engine recognizes, analyzes, and considers the emotions of users and workers. The system analyzes user emotions in real time and uses this information to adjust task priorities and schedules. It also includes a function to suggest refreshing tasks to reduce user stress and fatigue.

[0726] The elements necessary to realize this system are as follows:

[0727] hardware

[0728] 1. Sensors: Cameras and microphones for collecting emotional data.

[0729] 2. Terminal: A user interface used for data entry and receiving notifications, such as a PC or smartphone.

[0730] 3. Server: A central computing device for processing data and storing and distributing results.

[0731] software

[0732] 1. Emotion Recognition API: A tool for analyzing user emotions in real time (e.g., Emotion API).

[0733] 2. Task Management API: A program for managing task data and generating schedules (e.g., Factory Tasks API).

[0734] 3. Data analysis libraries: Libraries used for data processing and analysis, such as Pandas and NumPy.

[0735] 4. Scheduling algorithm: A program for calculating task priorities and resolving dependencies.

[0736] This system processes information in the following steps:

[0737] Specific example

[0738] For example, suppose a factory worker inputs tasks such as "assembly," "quality control," and "packaging" into the system. Furthermore, if the system detects that the worker is experiencing a high stress level through emotion recognition, it automatically inserts break times to reduce the worker's stress. At this time, an optimal task schedule is generated and notified to the worker's device, and also displayed visually.

[0739] Example of a prompt

[0740] The following are possible input prompt formats:

[0741] "Enter tasks such as assembly, quality control, and packaging. Sensors will analyze your emotions in real time, suggesting refreshing tasks if stress levels are high. It will then generate and visually display an optimal schedule."

[0742] The system of this invention thus achieves optimal task management and scheduling based on the user's emotional state, improving work efficiency and reducing user stress. This makes it possible to balance factory productivity with employee health.

[0743] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0744] Step 1:

[0745] The user enters the schedule data.

[0746] The user uses a terminal to input task name, priority, duration, dependencies, and sentiment data into the system. The input data takes the form of task name, priority, and duration, while sentiment data is either entered by the user or automatically acquired by sensors or cameras installed on the terminal.

[0747] Step 2:

[0748] Sending and receiving task data and sentiment data

[0749] The terminal sends the entered task data and sentiment data to the server. The data is sent to the server via the internet using a secure communication protocol, and the server receives it.

[0750] Step 3:

[0751] The server stores and processes the data.

[0752] The server stores received task data and emotion data in a database. The data is stored in an organized format and used for subsequent processing and analysis. For example, emotion data is used for facial expression recognition, voice analysis, and text analysis to quantify the user's emotional state.

[0753] Step 4:

[0754] Priority calculation

[0755] The server calculates the priority of each task, taking into account its importance, urgency, and emotional data. For example, if a user is experiencing stress, the server adjusts the order of tasks to alleviate that stress. The calculated priority is then used to determine the order in which tasks are processed.

[0756] Step 5:

[0757] Utilizing the Emotion Engine

[0758] An emotion engine on the server analyzes the user's emotions in real time. The emotion engine uses facial expression recognition APIs and voice analysis APIs to analyze emotional data and dynamically adjust task priorities and schedules based on the emotional state. It also suggests refreshing tasks necessary to reduce the user's stress and fatigue.

[0759] Step 6:

[0760] Generating an optimal schedule

[0761] The server resolves task dependencies and generates an optimal schedule that takes sentiment data into account. It comprehensively evaluates priorities, dependencies, and the user's emotional state to set the start and end times for each task. The generated schedule reduces user stress levels while enabling efficient task processing.

[0762] Step 7:

[0763] Schedule notification

[0764] The server notifies the user's device of the generated schedule. Notifications are sent via methods such as push notifications, email, and alerts, allowing the user to receive the latest schedule in real time. The notified schedule is displayed in the device's notification center or in specific applications.

[0765] Step 8:

[0766] Visual display of schedule

[0767] The user's device visually displays the schedule received from the server. The visual display is presented in calendar or list format, designed for easy user understanding. Furthermore, refresh tasks and reminders are also displayed, providing intuitive feedback on the user's emotional state.

[0768] Through these steps, task prioritization and scheduling are optimized based on the user's emotional state, reducing user stress and enabling efficient task completion.

[0769] 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.

[0770] The data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of the data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">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.

[0771] 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.

[0772] [Third Embodiment]

[0773] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0774] 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.

[0775] 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).

[0776] 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.

[0777] 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.

[0778] 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).

[0779] 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.

[0780] 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.

[0781] 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.

[0782] 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.

[0783] 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.

[0784] 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".

[0785] The invention described herein is a system that efficiently manages multiple tasks and appointments, allowing users to easily generate an optimal schedule. This system enables the user to input task data, which is then received, stored, and processed by a server, thereby generating an optimal schedule for the user.

[0786] 1. The user enters the task.

[0787] Users input task data, such as task name, priority, duration, and dependencies, into the system using a device (e.g., a smartphone or computer). This data is entered through the user interface and transmitted to the server in real time.

[0788] 2. Sending and receiving task data

[0789] The terminal sends task data to the server. Task data is typically sent over the internet, and the server receives it.

[0790] 3. The server saves the task data.

[0791] The server saves the received task data to a database. The database is managed to maintain data integrity and completeness. This saving process ensures that the data necessary for subsequent processing is retained.

[0792] 4. Calculating Priority

[0793] The server calculates task priorities based on stored task data. This calculation is based on the importance and urgency of each task. Furthermore, it considers task dependencies to determine which tasks should be executed before others.

[0794] 5. Handling dependencies and generating schedules

[0795] The server resolves task dependencies and generates an optimal time schedule. This includes checking the completion of other tasks on which a task depends and setting appropriate start and end times. The schedule is generated to ensure that tasks are completed efficiently, taking priorities and dependencies into consideration.

[0796] 6. Schedule notifications

[0797] The server generates a schedule and notifies the user. Possible notification methods include push notifications to the device and email notifications. This allows the user to receive the latest schedule in real time.

[0798] 7. Visual display of the schedule

[0799] The terminal visually displays the schedule received from the server. The visual display is in calendar or list format to allow users to easily understand and manage their schedule. Task details and progress are also displayed as needed.

[0800] Specific example

[0801] For example, suppose a user enters the following task into the system:

[0802] Task 1: Check emails (Priority 1, Estimated time: 0.5 hours, No dependencies)

[0803] Task 2: Meeting (Priority 3, Duration 1 hour, No dependencies)

[0804] Task 3: Report creation (Priority 2, Estimated time 2 hours, Dependent tasks 2)

[0805] The user enters these tasks from their terminal. The terminal then sends the task data to the server, which receives and stores it.

[0806] Next, the server calculates the task priorities and determines that Task 2 (meeting) has the highest priority. The server considers dependencies and creates a schedule so that report creation begins after the meeting ends. The final schedule will be "Task 1: Check email -> Task 2: Meeting -> Task 3: Report creation".

[0807] The generated schedule is sent to the user's terminal, which displays it visually. The user can easily check the order and start time of the tasks. In this way, the system of the present invention significantly improves the efficiency of the user's task management.

[0808] The following describes the processing flow.

[0809] Step 1:

[0810] The user uses a terminal to enter the task name, priority, duration, and dependencies. This task data is entered through the user interface.

[0811] Step 2:

[0812] The terminal sends the entered task data to the server. The task data is sent to the server as a POST request via the internet.

[0813] Step 3:

[0814] The server checks the received task data and saves it to the database. First, the server checks the integrity and completeness of the data, and if there are no problems, it saves it to the database.

[0815] Step 4:

[0816] The server calculates task priorities based on stored task data. The importance and urgency of tasks are then evaluated based on the priority calculation algorithm.

[0817] Step 5:

[0818] The server handles task dependencies. After confirming that all dependent tasks are complete, it adjusts the schedule so that the next task can start.

[0819] Step 6:

[0820] The server generates an optimal schedule. Task start and end times are set, taking priorities and dependencies into consideration. The generated schedule is saved to the database.

[0821] Step 7:

[0822] The server generates a schedule and notifies the user's device. Push notifications and email are used as notification methods. This notification process allows the user to receive the latest schedule in real time.

[0823] Step 8:

[0824] The user's device visually displays the schedule received from the server. The schedule is displayed on the device screen in calendar or list format, allowing the user to easily check the order and start time of tasks. Detailed information and progress are also displayed as needed.

[0825] Through the steps described above, the present invention significantly improves the efficiency of user task management and provides an optimal schedule.

[0826] (Example 1)

[0827] 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."

[0828] Traditional scheduling systems often resulted in inefficient schedules because users were unable to properly handle task priorities and dependencies when managing numerous tasks. Furthermore, the way generated schedules were communicated to users and their visual representation were unclear, making it difficult for users to easily understand and manage their schedules. This led to users having to expend a significant amount of time and effort on schedule management.

[0829] 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.

[0830] In this invention, the server includes means for the user to input schedule data, means for sending the schedule data to the server, means for the server to receive the schedule data and store it in a database, means for calculating task priorities based on the schedule data, means for processing task dependencies and generating a time schedule, and means for notifying the user terminal of the generated schedule. This enables the user to manage their schedule efficiently and appropriately and to easily visually confirm the generated schedule.

[0831] A "user" is a person who uses a system to input data for the purpose of managing tasks and schedules.

[0832] "Schedule data" refers to data that includes information such as task name, priority, duration, and dependencies entered by the user.

[0833] A "server" is a computer system that receives schedule data sent by users, stores it in a database, processes the data, and generates an optimal schedule.

[0834] A "database" is a collection of data managed by a server that stores received schedule data and retrieves or updates it as needed.

[0835] "Priority" refers to the order in which tasks should be performed before others, based on their importance and urgency.

[0836] A "dependency" is a relationship in which one task must be executed before another, and it is a factor that determines the order in which tasks are performed.

[0837] A "time schedule" is a timetable that shows the planned execution of tasks, specifying the start and end times of each task.

[0838] "Notification" refers to a means of communicating information to inform users of a generated schedule, and includes, for example, push notifications and email notifications.

[0839] "Visual display" refers to displaying schedules in an easy-to-read format, such as a calendar or list, on the user's device.

[0840] "Organizing" refers to rearranging tasks based on their priorities and dependencies, and determining the order in which they should be executed.

[0841] This invention relates to a system for enabling users to efficiently manage multiple tasks and appointments and generate an optimal schedule. In this system, a server processes task data entered by the user, generates an optimal schedule based on that data, and notifies the user.

[0842] First, users input task data using a smartphone or computer through the user interface (UI) of a web or mobile application. This includes the task name, priority, duration, dependencies, and so on.

[0843] Next, the task data entered by the user is sent to the server via the internet. The server receives this data and stores it in a database. The database can be a relational database such as MySQL or PostgreSQL. This storage process ensures the integrity and completeness of the data.

[0844] The server calculates task priorities based on stored task data. Priority calculations are based on task importance and urgency, and also consider task dependencies. This allows the server to determine which tasks should be executed before others.

[0845] Next, the server analyzes the task dependencies and generates an optimal time schedule. In this step, it checks for the completion of other tasks on which the task depends and sets the start and end times for the task. Taking priorities and dependencies into consideration, the schedule is generated to ensure that the task is completed efficiently.

[0846] The generated schedule is notified from the server to the user's device. Notifications are sent using methods such as push notifications and email notifications. Users receive the notification and can check the latest schedule in real time.

[0847] Finally, the user's device visually displays the received schedule. Display formats include calendar and list, and task details and progress are shown as needed. This allows the user to easily understand and manage their schedule.

[0848] Specific example

[0849] For example, if a user enters the following task:

[0850] Task 1: Check emails (Priority 1, Estimated time: 0.5 hours, No dependencies)

[0851] Task 2: Meeting (Priority 3, Duration 1 hour, No dependencies)

[0852] Task 3: Report creation (Priority 2, Estimated time 2 hours, Dependent tasks 2)

[0853] The user enters these tasks from their terminal, and the terminal sends the task data to the server. The server receives this data and stores it in a database. The server then calculates the task priorities and determines that Task 2 (meeting) has the highest priority. Considering dependencies, the server creates a schedule so that report creation begins after the meeting ends. As a result, the final schedule will look like this:

[0854] Task 1: Check email

[0855] Task 2: Meeting

[0856] Task 3: Report creation

[0857] The generated schedule is sent to the user's device, where it is displayed visually. The user can easily check the order and start time of tasks, enabling efficient task management.

[0858] Example of a prompt

[0859] The following is an example of a prompt message that instructs the system to generate the optimal schedule:

[0860] "I have entered three tasks with priorities and dependencies. Please generate the optimal schedule for these tasks."

[0861] Task 1: Check emails (Priority 1, Estimated time: 0.5 hours, No dependencies)

[0862] Task 2: Meeting (Priority 3, Duration 1 hour, No dependencies)

[0863] Task 3: Report creation (Priority 2, Estimated time 2 hours, Dependent tasks 2)

[0864] In this way, the system of the present invention significantly improves the efficiency of user task management.

[0865] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0866] Step 1:

[0867] The user enters the task data.

[0868] Specifically, users use their devices to input data such as task name, priority, duration, and dependencies, and then send this data to the system. The input format is provided through forms in web and mobile applications. The input data here might be something like "Check email (priority 1, duration 0.5 hours, no dependencies)."

[0869] Step 2:

[0870] The terminal sends task data to the server.

[0871] The entered task data is sent to the server via the internet. This transmission is performed using an HTTP POST request, and the data is packaged in JSON format. For example, the task data "Email Confirmation" is sent in the following format:

[0872] json

[0873] {

[0874] "task_name": "Email confirmation",

[0875] "priority": 1,

[0876] "duration": 0.5,

[0877] "dependency": null

[0878] }

[0879] Step 3:

[0880] The server receives task data and saves it to the database.

[0881] The server receives task data sent from the terminal, verifies data integrity, and then saves it to the database. When saving, the server executes an SQL query similar to the following:

[0882] SQL

[0883] INSERT INTO tasks (task_name, priority, duration, dependency) VALUES ("Email confirmation", 1, 0.5, NULL);

[0884] The input here is task data, and the output is the completion of saving to the database.

[0885] Step 4:

[0886] The server calculates task priorities based on the stored task data.

[0887] The server retrieves task data stored in the database and calculates task priority based on priority levels. This calculation compares priority values, ensuring that tasks with higher values ​​are processed first. The input is task data retrieved from the database, and the output is a task list with assigned priorities.

[0888] Step 5:

[0889] The server analyzes task dependencies and generates an optimal time schedule.

[0890] The server analyzes the dependencies between tasks and generates a schedule to place dependent tasks in the appropriate order. For example, if task A depends on task B, task A will start after task B is completed. The input is a prioritized list of tasks, and the output is the optimal time schedule.

[0891] Step 6:

[0892] The server generates a schedule which is then sent to the user's device.

[0893] The generated schedule is notified from the server to the user's device. This notification can be a push notification or an email notification. The input is the generated schedule, and the output is the notification to the user. For example, in the case of an email notification, the notification content would be "Your new schedule."

[0894] Step 7:

[0895] The device visually displays the schedule it has received.

[0896] The system visually displays the schedule received by the user's device in calendar or list format. This allows the user to easily check the order and start time of tasks. The input is the notified schedule, and the output is the visually displayed schedule. The user interface is implemented using frameworks such as JavaScript or React.

[0897] (Application Example 1)

[0898] 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."

[0899] Within factories, a wide variety of tasks are handled by robots, and there is a need to efficiently manage these tasks. Conventional systems have difficulty properly managing task priorities and dependencies, resulting in decreased production efficiency. Furthermore, there has been a lack of means to notify managers and robots of task schedules in real time, hindering smooth work progress. The objective of this invention is to solve these problems and streamline task management for robots within factories.

[0900] 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.

[0901] In this invention, the server includes means for a user to input schedule data, means for transmitting the schedule data to the server, means for the server to receive the schedule data and store it in a database, means for the server to calculate task priorities based on the schedule data, means for processing the dependencies of the tasks and generating a time schedule, means for notifying the user of the generated schedule, means for inputting robot work tasks from a management device and generating an optimized schedule based on priorities and dependencies in order to efficiently manage robot tasks in a factory, means for notifying factory managers and robots of the generated schedule, and visual display means for visually displaying the generated schedule.

[0902] This streamlines task management for robots within the factory, enabling real-time notifications of optimal schedules that take priorities and dependencies into consideration.

[0903] "User" refers to the person who manages the tasks of the robots within the factory.

[0904] "Schedule data" refers to data entered by the user, including information such as task name, priority, duration, and dependencies.

[0905] A "server" refers to a device that receives schedule data sent from a user's terminal, stores and processes it, and generates and notifies users of their schedule.

[0906] A "database" refers to an information storage system used to store and manage scheduled data received by a server.

[0907] "Priority" refers to the criteria used to determine the order in which each task is processed, taking into account its importance and urgency.

[0908] A "dependency" refers to a relationship where a particular task can only begin if another task is completed.

[0909] A "time schedule" refers to a plan that includes the start and end times of tasks, generated by taking priorities and dependencies into consideration.

[0910] "Management equipment" refers to devices used to input work tasks for robots in a factory.

[0911] "Notification" refers to a means of informing users and robots of the generated schedule.

[0912] "Visual display means" refers to a device or method for visually displaying a generated schedule so that it can be easily understood by the user.

[0913] The following describes a specific system configuration and its operation procedure for carrying out this invention.

[0914] First, the user uses factory management equipment (e.g., a dedicated tablet or PC) to input scheduled data for the tasks they want the robots to perform. This scheduled data includes the task name, priority, duration, and dependencies. This data is entered through the user interface and transmitted to the server in real time.

[0915] Next, the server receives the schedule data sent from the user terminal via the internet and stores it in the database. Commonly used database management systems such as SQLite or PostgreSQL are used as the database.

[0916] The server calculates the priority of each task based on the stored schedule data. Specifically, the priority is determined based on the importance and urgency of each task. It also considers the dependencies between tasks to determine which tasks should be executed before others. Considering task priorities and dependencies, it generates an optimal time schedule. This schedule is calculated with high accuracy using machine learning and optimization algorithms.

[0917] The generated schedule is notified to management equipment and robots within the factory. Notification methods include push notifications, email, or real-time notifications via a dedicated application. The schedule notified by the server is visually displayed on the management equipment's interface. Display formats such as Gantt charts and list formats are possible, designed to allow users to easily understand and manage the schedule.

[0918] As a concrete example, a factory manager enters the following task into the system:

[0919] Task 1: Inspection (Priority 2, Estimated time: 1 hour, No dependencies)

[0920] Task 2: Parts Delivery (Priority 1, Estimated Time 0.5 hours, No Dependencies)

[0921] Task 3: Component assembly (Priority 3, Estimated time 2 hours, Dependent tasks 2)

[0922] Users input these tasks through a dedicated interface, which are then sent to the server. The server receives and stores them, and, considering priority and dependencies, generates a schedule as follows: "Task 2 -> Task 1 -> Task 3". The schedule is communicated to administrators and robots and is displayed visually.

[0923] As an example of a prompt statement:

[0924] "Task name: Inspection, Priority: 2, Estimated time: 1 hour, Dependencies: None"

[0925] Task management can be performed efficiently using prompt statements like these.

[0926] This system streamlines robot operations within the factory and provides real-time notifications of optimal schedules that appropriately consider priorities and dependencies. This results in improved production efficiency and smoother workflow.

[0927] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0928] Step 1:

[0929] The user uses a management device to input scheduled data for the task they want the robot to perform (task name, priority, duration, dependencies, etc.). The entered data is sent to the server via the user interface. The input data is in the format of, for example, "Task name: Inspection, Priority: 2, Duration: 1 hour, Dependencies: None".

[0930] Step 2:

[0931] The terminal sends the entered schedule data to the server, which receives it via the internet. The server verifies the received data and saves it to a database. Databases such as SQLite and PostgreSQL are used. This saving process ensures that the data necessary for subsequent processing is reliably retained.

[0932] Step 3:

[0933] The server calculates task priorities based on the stored schedule data. This calculation is based on the importance and urgency of each task. Specifically, it retrieves the value of the "priority" field from the received data and determines the processing order of each task based on that value.

[0934] Step 4:

[0935] The server processes task dependencies and generates a time schedule. This process checks the "dependencies" field of each task and sets the time so that the next task starts only after its dependent tasks have completed. For example, if "Task 3" depends on "Task 2," the schedule will be set so that Task 3 starts only after Task 2 has finished.

[0936] Step 5:

[0937] The server notifies management equipment and robots within the factory of the generated schedule. Possible notification methods include push notifications, email, and real-time notifications via a dedicated application. At this point, the notified schedule is in an optimized order based on the task data entered by the user.

[0938] Step 6:

[0939] The management device terminal visually displays the schedule received from the server. The visual display format can be a Gantt chart or a list. This visual display allows users to easily check and manage the start and end times of each task.

[0940] Step 7:

[0941] As a concrete example, a user inputs the following tasks, the server receives and saves them, and, considering priority and dependencies, generates a schedule of "Task 2 -> Task 1 -> Task 3". This schedule is notified to the administrator and the robot and is visually displayed on the management device.

[0942] In this way, the server processes data entered by the user, generates an optimal schedule, and notifies and displays it, thus streamlining task management for robots within the factory.

[0943] 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.

[0944] This invention incorporates an emotion engine that recognizes, analyzes, and considers user emotions into a system aimed at improving the efficiency of task management. This system can analyze user emotions in real time and adjust task priorities and schedules based on that information. It also includes a task suggestion function to reduce user stress and fatigue.

[0945] 1. The user enters the schedule data.

[0946] Users input task names, priorities, estimated time, dependencies, and sentiment data into the system using their devices (smartphones or PCs). Sentiment data is either manually entered by the user or automatically acquired by sensors or cameras installed on the device.

[0947] 2. Sending and receiving task data and sentiment data

[0948] The device sends task data and emotion data to the server. The data is transmitted over the internet and received by the server. Emotion recognition technology is implemented using facial expression recognition, voice analysis, text analysis, etc.

[0949] 3. The server stores and processes the data.

[0950] The server reviews the received task and sentiment data and saves it to the database. The database contains the information necessary for schedule generation.

[0951] 4. Calculating Priority

[0952] The server calculates task priorities. In this process, in addition to task importance and urgency, user sentiment data is also considered. For example, if a user is stressed, the task order may be adjusted to alleviate that stress.

[0953] 5. Utilizing the Emotional Engine

[0954] An emotion engine within the server analyzes the user's emotions in real time. Based on the user's emotional state, it dynamically adjusts task priorities and schedules. The emotion engine also suggests refreshing tasks to reduce the user's stress and fatigue.

[0955] 6. Generating an optimal schedule

[0956] The server resolves task dependencies and generates an optimal schedule that takes sentiment data into account. Task start and end times are set based on a comprehensive evaluation of priorities, dependencies, and user sentiment states.

[0957] 7. Schedule notifications

[0958] The server generates a schedule and notifies the user's device. Notifications are sent via methods such as push notifications, email, and alerts, allowing the user to receive the latest schedule in real time.

[0959] 8. Visual representation of the schedule

[0960] The user's device visually displays the schedule received from the server. The visual display is presented in calendar or list format, designed for easy user understanding. Refreshment tasks and reminders based on emotional state are also displayed.

[0961] Specific example

[0962] For example, suppose a user enters the following task into the system:

[0963] Task 1: Check emails (Priority 1, Estimated time: 0.5 hours, No dependencies)

[0964] Task 2: Meeting (Priority 3, Duration 1 hour, No dependencies)

[0965] Task 3: Report creation (Priority 2, Estimated time 2 hours, Dependent tasks 2)

[0966] If the system determines that the user is experiencing stress, it can add a short break (refreshment task) before the meeting.

[0967] The specific processing flow is as follows: the user inputs the task data via their device, and the device sends this data to the server. The server receives and stores the task data and sentiment data, and generates a schedule based on priorities, dependencies, and sentiment data. Finally, the generated schedule is notified to the user's device and displayed visually.

[0968] As a result, the system of the present invention not only manages tasks but also provides an optimal schedule that takes into account the user's emotional state, thereby supporting the reduction of user stress and efficient task execution.

[0969] The following describes the processing flow.

[0970] Modes for carrying out the invention

[0971] This invention incorporates an emotion engine that recognizes, analyzes, and considers user emotions into a system aimed at improving the efficiency of task management. This system can analyze user emotions in real time and adjust task priorities and schedules based on that information. It also includes a task suggestion function to reduce user stress and fatigue.

[0972] System processing flow

[0973] Step 1:

[0974] The user uses the device to input the task name, priority, duration, and dependencies. This task data is entered through the device's user interface. User sentiment data is also collected. Sentiment data is either entered by the user or automatically acquired by sensors and cameras installed on the device.

[0975] Step 2:

[0976] The terminal sends the entered task data and sentiment data to the server. The data is sent to the server via the internet as a POST request.

[0977] Step 3:

[0978] The server verifies the received task and sentiment data and saves it to the database. First, the server checks the integrity and completeness of the data, and if there are no problems, it saves it to the database.

[0979] Step 4:

[0980] The server calculates task priorities based on stored task data. The importance and urgency of tasks are evaluated based on a priority calculation algorithm. Sentimental data is also considered in the calculation; for example, if a user is experiencing stress, task reordering is performed to reduce stress.

[0981] Step 5:

[0982] The emotion engine on the server analyzes the user's emotions in real time. The emotion engine uses emotion recognition technologies such as facial expression recognition, voice analysis, and text analysis to determine the user's emotional state.

[0983] Step 6:

[0984] The server dynamically adjusts task priorities and schedules based on the analysis results of the emotion engine. The order and start times of tasks may change based on the user's emotional state. The emotion engine also suggests refreshing tasks to reduce the user's stress and fatigue.

[0985] Step 7:

[0986] The server resolves task dependencies and generates an optimal schedule that takes sentiment data into account. Task start and end times are set based on a comprehensive evaluation of priorities, dependencies, and user sentiment states.

[0987] Step 8:

[0988] The server generates a schedule and notifies the user's device. Push notifications and email are used as notification methods. This notification process allows the user to receive the latest schedule in real time.

[0989] Step 9:

[0990] The user's device visually displays the schedule received from the server. The schedule is displayed on the device screen in calendar or list format, allowing the user to easily check the order and start times of tasks. Refreshment tasks and reminders based on emotional state are also displayed.

[0991] Specific example

[0992] For example, suppose a user enters the following task into the system:

[0993] Task 1: Check emails (Priority 1, Estimated time: 0.5 hours, No dependencies)

[0994] Task 2: Meeting (Priority 3, Duration 1 hour, No dependencies)

[0995] Task 3: Report creation (Priority 2, Estimated time 2 hours, Dependent tasks 2)

[0996] If the emotion engine determines that the user is experiencing stress, the system can add a short break (refreshment task) before the meeting. The specific process involves the user inputting the task data via their device, which then sends it to the server. The server receives and stores the task data and emotion data, and generates a schedule based on priorities, dependencies, and emotion data. Finally, the generated schedule is notified to the user's device and displayed visually.

[0997] As a result, the system of the present invention not only manages tasks but also provides an optimal schedule that takes into account the user's emotional state, thereby supporting the reduction of user stress and efficient task execution.

[0998] (Example 2)

[0999] 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."

[1000] Traditional task management systems only provided standardized schedules without considering the user's emotional state. This failed to alleviate user stress and fatigue, hindering efficient task completion. Furthermore, the lack of real-time analysis and reflection of emotional data made dynamic schedule adjustments difficult.

[1001] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1002] In this invention, the server includes means for the user to input schedule data, means for transmitting the schedule data and emotional data to the server, means for the server to receive the schedule data and emotional data and store it in a database, means for the server to calculate task priorities based on the schedule data and emotional data, means for analyzing the user's emotional state in real time using an emotional engine and dynamically adjusting task priorities and schedules, means for processing the dependencies of the tasks and generating a time schedule considering the emotional data, and means for notifying the user of the generated schedule. This makes it possible to provide an optimal task schedule that takes the user's emotional state into consideration.

[1003] A "user" refers to an individual who uses the system to manage tasks and adjust schedules.

[1004] "Schedule data" refers to information necessary for task management and schedule generation, such as the task name, priority, duration, and dependencies entered by the user.

[1005] "Emotional data" refers to information that indicates the user's emotional state, and is acquired either through manual input or by sensors or cameras installed on the device.

[1006] A "server" refers to a computer system that receives, stores, and processes data sent by users.

[1007] A "database" refers to a system that stores task data and sentiment data received by a server, and stores necessary information.

[1008] An "emotion engine" refers to a software component that analyzes a user's emotional state in real time and reflects the results in task prioritization and scheduling.

[1009] "Priority" refers to the order in which tasks are executed, determined based on their importance, urgency, and sentiment data.

[1010] "Dependency" refers to the dependencies that each task has on other tasks, and the order of tasks is determined based on these dependencies.

[1011] A "time schedule" refers to a plan that includes the start and end times of tasks, generated based on priorities and dependencies.

[1012] "Notification methods" refer to methods such as push notifications, emails, and alerts used to inform users of generated schedules.

[1013] "Visual display" refers to the function of displaying the generated schedule on the device in a calendar or list format so that users can easily check it.

[1014] This invention relates to a task management system that takes user emotions into consideration. This system provides a function in which a server generates an optimal task schedule based on the planned data and emotion data entered by the user, and notifies the user's terminal.

[1015] Hardware and software usage

[1016] This system uses the following hardware and software:

[1017] Devices: Smartphones (e.g., iPhone, Android), PCs (e.g., Windows, Mac)

[1018] Emotion recognition technology: OpenCV (facial expression recognition), speech analysis software, natural language processing software (e.g., Google Cloud Natural Language API)

[1019] Server: A high-performance computer system

[1020] Database: MySQL, PostgreSQL

[1021] Notification system: Firebase Cloud Messaging, email sending service

[1022] Specific processing of the system

[1023] Data entry

[1024] Users input task details (task name, priority, duration, dependencies) using their own devices. In addition, they can input sentiment data. This sentiment data can be entered manually by the user or automatically acquired by sensors and cameras installed on the device.

[1025] Data transmission and reception

[1026] The entered task data and sentiment data are transmitted from the terminal to the server via the internet. The server receives this data, verifies it, and then stores it in a database.

[1027] Data analysis and processing

[1028] The server calculates task priorities based on the received data. During this process, it uses an emotion engine to analyze the user's emotional state in real time, dynamically adjusting the task order and schedule. It also processes task dependencies and generates a time schedule that takes emotional data into account.

[1029] Schedule generation and notification

[1030] The schedule generated by the server is notified to the user's device and communicated to the user through means such as push notifications, email, and alerts. The device receives the notification and displays the schedule visually. The display format can be calendar or list, and refresh tasks and notes are also displayed.

[1031] Examples of specific cases and prompt statements

[1032] For example, suppose a user enters the following task into the system:

[1033] Task 1: Check emails (Priority 1, Estimated time: 0.5 hours, No dependencies)

[1034] Task 2: Meeting (Priority 3, Duration 1 hour, No dependencies)

[1035] Task 3: Report creation (Priority 2, Estimated time 2 hours, Dependent tasks 2)

[1036] In this case, if the user enters emotional data such as "I'm a little tired today," the system can add a refreshing task such as "10 minutes of stretching" before the meeting.

[1037] The following are some examples of prompts that users might input into a generated AI model:

[1038] Example prompt: "I have an important meeting at 3 PM. Please suggest a short task to refresh myself before then."

[1039] The system of this invention not only manages tasks but also provides an optimal schedule that takes into account the user's emotional state, thereby supporting user stress reduction and efficient task execution.

[1040] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1041] Processing flow of this system's program

[1042] Step 1: The user enters the schedule data.

[1043] Users use their devices (smartphones or PCs) to input task details and sentiment data into the system. The input data includes task name, priority, duration, dependencies, and sentiment data. Sentiment data can be entered manually by the user or automatically acquired using sensors or cameras installed on the device.

[1044] Input: Task information (task name, priority, duration, dependencies), sentiment data

[1045] Output: Temporary data storage within the terminal

[1046] Specific actions: The user opens a smartphone app, enters "Task name: Report creation, Priority: 2, Estimated time: 2 hours, Dependency: Meeting," and describes their emotional state as "I'm a little tired today."

[1047] Step 2: Sending and receiving task data and sentiment data

[1048] The terminal sends the entered task data and sentiment data to the server. The transmission takes place over the internet, and the data is encrypted before transmission. The server receives the data and verifies its integrity.

[1049] Input: Task data and sentiment data entered into the terminal.

[1050] Output: Data sent to the server

[1051] Specific operation: The smartphone uses Wi-Fi or mobile data communication to encrypt the entered data and send it to the server.

[1052] Step 3: The server stores and processes the data.

[1053] The server reviews the received task and sentiment data and saves it to a database. This database is used to store the information necessary for schedule generation.

[1054] Input: Task data and sentiment data received by the server

[1055] Output: Data stored in the database

[1056] Specific operation: The server checks the received data in JSON format, verifies that there is no missing information, and then inserts it into a database such as MySQL or PostgreSQL.

[1057] Step 4: Calculating Priorities

[1058] The server calculates task priorities. This calculation considers not only the importance and urgency of tasks, but also emotional data. For example, if a user is experiencing high stress levels, a refresh task may be inserted.

[1059] Input: Task data and sentiment data stored in the database

[1060] Output: Task data with calculated priorities

[1061] Specific operation: The server uses an emotion engine to analyze emotion data such as "I'm a little tired today," and recalculates the priority based on the urgency and importance of the task.

[1062] Step 5: Utilizing the Emotional Engine

[1063] The emotion engine on the server analyzes emotion data in real time. Based on the analysis results, task priorities and schedules are dynamically adjusted. It also suggests refresh tasks.

[1064] Input: Task data with calculated priorities and sentiment data

[1065] Output: Adjusted priorities and schedules

[1066] Specific action: The emotional engine detects a state of "fatigue" and suggests "10 minutes of stretching" as a way to refresh.

[1067] Step 6: Generate the optimal schedule

[1068] The server considers task dependencies and generates an optimal schedule that reflects sentiment data. It sets the start and end times for tasks and proposes the most efficient schedule.

[1069] Input: Adjusted priority and task data

[1070] Output: Generated time schedule

[1071] Specific operation: The server inserts a "10-minute stretch" between the meeting and report creation and generates it as a schedule.

[1072] Step 7: Schedule Notification

[1073] The server generates a schedule and notifies the user's device. Notification methods include push notifications, email, and alerts.

[1074] Input: Generated time schedule

[1075] Output: Schedule notified to the user's device

[1076] Specific action: The smartphone displays a schedule via push notification, such as "10:00-11:00 Meeting, 11:00-11:10 Refresh, 11:10-13:10 Report writing."

[1077] Step 8: Visualizing the Schedule

[1078] The user's device visually displays the schedule received from the server. The display is in calendar or list format, and refresh tasks and notes are also shown.

[1079] Input: Schedule notified to the user's device

[1080] Output: Visually displayed schedule

[1081] Specific action: The smartphone's calendar app displays the daily schedule and highlights stretching time as a refresh task on the screen.

[1082] (Application Example 2)

[1083] 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."

[1084] Traditional task management systems fail to consider the emotional state of users, making it difficult to maximize work efficiency and performance. Furthermore, they cannot detect and respond immediately to user stress or fatigue in real time. As a result, work efficiency decreases, potentially negatively impacting user health. This problem is particularly pronounced in factories and production lines where high precision and efficiency are required.

[1085] 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.

[1086] In this invention, the server includes means for receiving user schedule data and emotional data and storing it in a database, means for analyzing the user's emotional state in real time and calculating task priorities based on that analysis, and means for suggesting refreshing tasks to reduce the user's stress and fatigue. This makes it possible to dynamically adjust task priorities and schedules based on the user's emotional state, thereby improving the efficiency and accuracy of the steel production line.

[1087] "Schedule data" refers to information about the tasks and time schedules entered by the user.

[1088] "Emotional data" refers to data that represents the emotional state of a user and is collected in real time.

[1089] A "server" is a device that receives scheduled data and sentiment data sent by users, and processes and stores them.

[1090] A "database" is a data storage system for saving received schedule data and sentiment data.

[1091] The method for calculating "priority" is an algorithm that evaluates the importance and urgency of tasks based on scheduled data and sentiment data, and then determines the order in which they will be processed.

[1092] "Dependency" refers to a situation where one task is related to another task, and the schedule is adjusted based on that relationship.

[1093] The means of generating a "time schedule" is the process of determining the start and end times of each task, taking into account priorities and dependencies.

[1094] The means of notifying the "user" refers to a communication method for informing the user of the generated schedule in real time.

[1095] "Means of visual display" refers to an interface that clearly displays the generated schedule to the user.

[1096] An "emotion engine" is a system that analyzes a user's emotional state in real time and dynamically adjusts task priorities and schedules based on that information.

[1097] A "refreshment task" refers to a suggestion for a break or light work to reduce user stress and fatigue.

[1098] This invention incorporates an emotion engine into a factory work management system aimed at improving the efficiency of task management. This engine recognizes, analyzes, and considers the emotions of users and workers. The system analyzes user emotions in real time and uses this information to adjust task priorities and schedules. It also includes a function to suggest refreshing tasks to reduce user stress and fatigue.

[1099] The elements necessary to realize this system are as follows:

[1100] hardware

[1101] 1. Sensors: Cameras and microphones for collecting emotional data.

[1102] 2. Terminal: A user interface used for data entry and receiving notifications, such as a PC or smartphone.

[1103] 3. Server: A central computing device for processing data and storing and distributing results.

[1104] software

[1105] 1. Emotion Recognition API: A tool for analyzing user emotions in real time (e.g., Emotion API).

[1106] 2. Task Management API: A program for managing task data and generating schedules (e.g., Factory Tasks API).

[1107] 3. Data analysis libraries: Libraries used for data processing and analysis, such as Pandas and NumPy.

[1108] 4. Scheduling algorithm: A program for calculating task priorities and resolving dependencies.

[1109] This system processes information in the following steps:

[1110] Specific example

[1111] For example, suppose a factory worker inputs tasks such as "assembly," "quality control," and "packaging" into the system. Furthermore, if the system detects that the worker is experiencing a high stress level through emotion recognition, it automatically inserts break times to reduce the worker's stress. At this time, an optimal task schedule is generated and notified to the worker's device, and also displayed visually.

[1112] Example of a prompt

[1113] The following are possible input prompt formats:

[1114] "Enter tasks such as assembly, quality control, and packaging. Sensors will analyze your emotions in real time, suggesting refreshing tasks if stress levels are high. It will then generate and visually display an optimal schedule."

[1115] The system of this invention thus achieves optimal task management and scheduling based on the user's emotional state, improving work efficiency and reducing user stress. This makes it possible to balance factory productivity with employee health.

[1116] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1117] Step 1:

[1118] The user enters the schedule data.

[1119] The user uses a terminal to input task name, priority, duration, dependencies, and sentiment data into the system. The input data takes the form of task name, priority, and duration, while sentiment data is either entered by the user or automatically acquired by sensors or cameras installed on the terminal.

[1120] Step 2:

[1121] Sending and receiving task data and sentiment data

[1122] The terminal sends the entered task data and sentiment data to the server. The data is sent to the server via the internet using a secure communication protocol, and the server receives it.

[1123] Step 3:

[1124] The server stores and processes the data.

[1125] The server stores received task data and emotion data in a database. The data is stored in an organized format and used for subsequent processing and analysis. For example, emotion data is used for facial expression recognition, voice analysis, and text analysis to quantify the user's emotional state.

[1126] Step 4:

[1127] Priority calculation

[1128] The server calculates the priority of each task, taking into account its importance, urgency, and emotional data. For example, if a user is experiencing stress, the server adjusts the order of tasks to alleviate that stress. The calculated priority is then used to determine the order in which tasks are processed.

[1129] Step 5:

[1130] Utilizing the Emotion Engine

[1131] An emotion engine on the server analyzes the user's emotions in real time. The emotion engine uses facial expression recognition APIs and voice analysis APIs to analyze emotional data and dynamically adjust task priorities and schedules based on the emotional state. It also suggests refreshing tasks necessary to reduce the user's stress and fatigue.

[1132] Step 6:

[1133] Generating an optimal schedule

[1134] The server resolves task dependencies and generates an optimal schedule that takes sentiment data into account. It comprehensively evaluates priorities, dependencies, and the user's emotional state to set the start and end times for each task. The generated schedule reduces user stress levels while enabling efficient task processing.

[1135] Step 7:

[1136] Schedule notification

[1137] The server notifies the user's device of the generated schedule. Notifications are sent via methods such as push notifications, email, and alerts, allowing the user to receive the latest schedule in real time. The notified schedule is displayed in the device's notification center or in specific applications.

[1138] Step 8:

[1139] Visual display of schedule

[1140] The user's device visually displays the schedule received from the server. The visual display is presented in calendar or list format, designed for easy user understanding. Furthermore, refresh tasks and reminders are also displayed, providing intuitive feedback on the user's emotional state.

[1141] Through these steps, task prioritization and scheduling are optimized based on the user's emotional state, reducing user stress and enabling efficient task completion.

[1142] 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.

[1143] The data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of the data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">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.

[1144] 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.

[1145] [Fourth Embodiment]

[1146] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1147] 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.

[1148] 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).

[1149] 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.

[1150] 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.

[1151] 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).

[1152] 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.

[1153] 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.

[1154] 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.

[1155] 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.

[1156] 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.

[1157] 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.

[1158] 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".

[1159] The invention described herein is a system that efficiently manages multiple tasks and appointments, allowing users to easily generate an optimal schedule. This system enables the user to input task data, which is then received, stored, and processed by a server, thereby generating an optimal schedule for the user.

[1160] 1. The user enters the task.

[1161] Users input task data, such as task name, priority, duration, and dependencies, into the system using a device (e.g., a smartphone or computer). This data is entered through the user interface and transmitted to the server in real time.

[1162] 2. Sending and receiving task data

[1163] The terminal sends task data to the server. Task data is typically sent over the internet, and the server receives it.

[1164] 3. The server saves the task data.

[1165] The server saves the received task data to a database. The database is managed to maintain data integrity and completeness. This saving process ensures that the data necessary for subsequent processing is retained.

[1166] 4. Calculating Priority

[1167] The server calculates task priorities based on stored task data. This calculation is based on the importance and urgency of each task. Furthermore, it considers task dependencies to determine which tasks should be executed before others.

[1168] 5. Handling dependencies and generating schedules

[1169] The server resolves task dependencies and generates an optimal time schedule. This includes checking the completion of other tasks on which a task depends and setting appropriate start and end times. The schedule is generated to ensure that tasks are completed efficiently, taking priorities and dependencies into consideration.

[1170] 6. Schedule notifications

[1171] The server generates a schedule and notifies the user. Possible notification methods include push notifications to the device and email notifications. This allows the user to receive the latest schedule in real time.

[1172] 7. Visual display of the schedule

[1173] The terminal visually displays the schedule received from the server. The visual display is in calendar or list format to allow users to easily understand and manage their schedule. Task details and progress are also displayed as needed.

[1174] Specific example

[1175] For example, suppose a user enters the following task into the system:

[1176] Task 1: Check emails (Priority 1, Estimated time: 0.5 hours, No dependencies)

[1177] Task 2: Meeting (Priority 3, Duration 1 hour, No dependencies)

[1178] Task 3: Report creation (Priority 2, Estimated time 2 hours, Dependent tasks 2)

[1179] The user enters these tasks from their terminal. The terminal then sends the task data to the server, which receives and stores it.

[1180] Next, the server calculates the task priorities and determines that Task 2 (meeting) has the highest priority. The server considers dependencies and creates a schedule so that report creation begins after the meeting ends. The final schedule will be "Task 1: Check email -> Task 2: Meeting -> Task 3: Report creation".

[1181] The generated schedule is sent to the user's terminal, which displays it visually. The user can easily check the order and start time of the tasks. In this way, the system of the present invention significantly improves the efficiency of the user's task management.

[1182] The following describes the processing flow.

[1183] Step 1:

[1184] The user uses a terminal to enter the task name, priority, duration, and dependencies. This task data is entered through the user interface.

[1185] Step 2:

[1186] The terminal sends the entered task data to the server. The task data is sent to the server as a POST request via the internet.

[1187] Step 3:

[1188] The server checks the received task data and saves it to the database. First, the server checks the integrity and completeness of the data, and if there are no problems, it saves it to the database.

[1189] Step 4:

[1190] The server calculates task priorities based on stored task data. The importance and urgency of tasks are then evaluated based on the priority calculation algorithm.

[1191] Step 5:

[1192] The server handles task dependencies. After confirming that all dependent tasks are complete, it adjusts the schedule so that the next task can start.

[1193] Step 6:

[1194] The server generates an optimal schedule. Task start and end times are set, taking priorities and dependencies into consideration. The generated schedule is saved to the database.

[1195] Step 7:

[1196] The server generates a schedule and notifies the user's device. Push notifications and email are used as notification methods. This notification process allows the user to receive the latest schedule in real time.

[1197] Step 8:

[1198] The user's device visually displays the schedule received from the server. The schedule is displayed on the device screen in calendar or list format, allowing the user to easily check the order and start time of tasks. Detailed information and progress are also displayed as needed.

[1199] Through the steps described above, the present invention significantly improves the efficiency of user task management and provides an optimal schedule.

[1200] (Example 1)

[1201] 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".

[1202] Traditional scheduling systems often resulted in inefficient schedules because users were unable to properly handle task priorities and dependencies when managing numerous tasks. Furthermore, the way generated schedules were communicated to users and their visual representation were unclear, making it difficult for users to easily understand and manage their schedules. This led to users having to expend a significant amount of time and effort on schedule management.

[1203] 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.

[1204] In this invention, the server includes means for the user to input schedule data, means for sending the schedule data to the server, means for the server to receive the schedule data and store it in a database, means for calculating task priorities based on the schedule data, means for processing task dependencies and generating a time schedule, and means for notifying the user terminal of the generated schedule. This enables the user to manage their schedule efficiently and appropriately and to easily visually confirm the generated schedule.

[1205] A "user" is a person who uses a system to input data for the purpose of managing tasks and schedules.

[1206] "Schedule data" refers to data that includes information such as task name, priority, duration, and dependencies entered by the user.

[1207] A "server" is a computer system that receives schedule data sent by users, stores it in a database, processes the data, and generates an optimal schedule.

[1208] A "database" is a collection of data managed by a server that stores received schedule data and retrieves or updates it as needed.

[1209] "Priority" refers to the order in which tasks should be performed before others, based on their importance and urgency.

[1210] A "dependency" is a relationship in which one task must be executed before another, and it is a factor that determines the order in which tasks are performed.

[1211] A "time schedule" is a timetable that shows the planned execution of tasks, specifying the start and end times of each task.

[1212] "Notification" refers to a means of communicating information to inform users of a generated schedule, and includes, for example, push notifications and email notifications.

[1213] "Visual display" refers to displaying schedules in an easy-to-read format, such as a calendar or list, on the user's device.

[1214] "Organizing" refers to rearranging tasks based on their priorities and dependencies, and determining the order in which they should be executed.

[1215] This invention relates to a system for enabling users to efficiently manage multiple tasks and appointments and generate an optimal schedule. In this system, a server processes task data entered by the user, generates an optimal schedule based on that data, and notifies the user.

[1216] First, users input task data using a smartphone or computer through the user interface (UI) of a web or mobile application. This includes the task name, priority, duration, dependencies, and so on.

[1217] Next, the task data entered by the user is sent to the server via the internet. The server receives this data and stores it in a database. The database can be a relational database such as MySQL or PostgreSQL. This storage process ensures the integrity and completeness of the data.

[1218] The server calculates task priorities based on stored task data. Priority calculations are based on task importance and urgency, and also consider task dependencies. This allows the server to determine which tasks should be executed before others.

[1219] Next, the server analyzes the task dependencies and generates an optimal time schedule. In this step, it checks for the completion of other tasks on which the task depends and sets the start and end times for the task. Taking priorities and dependencies into consideration, the schedule is generated to ensure that the task is completed efficiently.

[1220] The generated schedule is notified from the server to the user's device. Notifications are sent using methods such as push notifications and email notifications. Users receive the notification and can check the latest schedule in real time.

[1221] Finally, the user's device visually displays the received schedule. Display formats include calendar and list, and task details and progress are shown as needed. This allows the user to easily understand and manage their schedule.

[1222] Specific example

[1223] For example, if a user enters the following task:

[1224] Task 1: Check emails (Priority 1, Estimated time: 0.5 hours, No dependencies)

[1225] Task 2: Meeting (Priority 3, Duration 1 hour, No dependencies)

[1226] Task 3: Report creation (Priority 2, Estimated time 2 hours, Dependent tasks 2)

[1227] The user enters these tasks from their terminal, and the terminal sends the task data to the server. The server receives this data and stores it in a database. The server then calculates the task priorities and determines that Task 2 (meeting) has the highest priority. Considering dependencies, the server creates a schedule so that report creation begins after the meeting ends. As a result, the final schedule will look like this:

[1228] Task 1: Check email

[1229] Task 2: Meeting

[1230] Task 3: Report creation

[1231] The generated schedule is sent to the user's device, where it is displayed visually. The user can easily check the order and start time of tasks, enabling efficient task management.

[1232] Example of a prompt

[1233] The following is an example of a prompt message that instructs the system to generate the optimal schedule:

[1234] "I have entered three tasks with priorities and dependencies. Please generate the optimal schedule for these tasks."

[1235] Task 1: Check emails (Priority 1, Estimated time: 0.5 hours, No dependencies)

[1236] Task 2: Meeting (Priority 3, Duration 1 hour, No dependencies)

[1237] Task 3: Report creation (Priority 2, Estimated time 2 hours, Dependent tasks 2)

[1238] In this way, the system of the present invention significantly improves the efficiency of user task management.

[1239] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1240] Step 1:

[1241] The user enters the task data.

[1242] Specifically, users use their devices to input data such as task name, priority, duration, and dependencies, and then send this data to the system. The input format is provided through forms in web and mobile applications. The input data here might be something like "Check email (priority 1, duration 0.5 hours, no dependencies)."

[1243] Step 2:

[1244] The terminal sends task data to the server.

[1245] The entered task data is sent to the server via the internet. This transmission is performed using an HTTP POST request, and the data is packaged in JSON format. For example, the task data "Email Confirmation" is sent in the following format:

[1246] json

[1247] {

[1248] "task_name": "Email confirmation",

[1249] "priority": 1,

[1250] "duration": 0.5,

[1251] "dependency": null

[1252] }

[1253] Step 3:

[1254] The server receives task data and saves it to the database.

[1255] The server receives task data sent from the terminal, verifies data integrity, and then saves it to the database. When saving, the server executes an SQL query similar to the following:

[1256] SQL

[1257] INSERT INTO tasks (task_name, priority, duration, dependency) VALUES ("Email confirmation", 1, 0.5, NULL);

[1258] The input here is task data, and the output is the completion of saving to the database.

[1259] Step 4:

[1260] The server calculates task priorities based on the stored task data.

[1261] The server retrieves task data stored in the database and calculates task priority based on priority levels. This calculation compares priority values, ensuring that tasks with higher values ​​are processed first. The input is task data retrieved from the database, and the output is a task list with assigned priorities.

[1262] Step 5:

[1263] The server analyzes task dependencies and generates an optimal time schedule.

[1264] The server analyzes the dependencies between tasks and generates a schedule to place dependent tasks in the appropriate order. For example, if task A depends on task B, task A will start after task B is completed. The input is a prioritized list of tasks, and the output is the optimal time schedule.

[1265] Step 6:

[1266] The server generates a schedule which is then sent to the user's device.

[1267] The generated schedule is notified from the server to the user's device. This notification can be a push notification or an email notification. The input is the generated schedule, and the output is the notification to the user. For example, in the case of an email notification, the notification content would be "Your new schedule."

[1268] Step 7:

[1269] The device visually displays the schedule it has received.

[1270] The system visually displays the schedule received by the user's device in calendar or list format. This allows the user to easily check the order and start time of tasks. The input is the notified schedule, and the output is the visually displayed schedule. The user interface is implemented using frameworks such as JavaScript or React.

[1271] (Application Example 1)

[1272] 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".

[1273] Within factories, a wide variety of tasks are handled by robots, and there is a need to efficiently manage these tasks. Conventional systems have difficulty properly managing task priorities and dependencies, resulting in decreased production efficiency. Furthermore, there has been a lack of means to notify managers and robots of task schedules in real time, hindering smooth work progress. The objective of this invention is to solve these problems and streamline task management for robots within factories.

[1274] 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.

[1275] In this invention, the server includes means for a user to input schedule data, means for transmitting the schedule data to the server, means for the server to receive the schedule data and store it in a database, means for the server to calculate task priorities based on the schedule data, means for processing the dependencies of the tasks and generating a time schedule, means for notifying the user of the generated schedule, means for inputting robot work tasks from a management device and generating an optimized schedule based on priorities and dependencies in order to efficiently manage robot tasks in a factory, means for notifying factory managers and robots of the generated schedule, and visual display means for visually displaying the generated schedule.

[1276] This streamlines task management for robots within the factory, enabling real-time notifications of optimal schedules that take priorities and dependencies into consideration.

[1277] "User" refers to the person who manages the tasks of the robots within the factory.

[1278] "Schedule data" refers to data entered by the user, including information such as task name, priority, duration, and dependencies.

[1279] A "server" refers to a device that receives schedule data sent from a user's terminal, stores and processes it, and generates and notifies users of their schedule.

[1280] A "database" refers to an information storage system used to store and manage scheduled data received by a server.

[1281] "Priority" refers to the criteria used to determine the order in which each task is processed, taking into account its importance and urgency.

[1282] A "dependency" refers to a relationship where a particular task can only begin if another task is completed.

[1283] A "time schedule" refers to a plan that includes the start and end times of tasks, generated by taking priorities and dependencies into consideration.

[1284] "Management equipment" refers to devices used to input work tasks for robots in a factory.

[1285] "Notification" refers to a means of informing users and robots of the generated schedule.

[1286] "Visual display means" refers to a device or method for visually displaying a generated schedule so that it can be easily understood by the user.

[1287] The following describes a specific system configuration and its operation procedure for carrying out this invention.

[1288] First, the user uses factory management equipment (e.g., a dedicated tablet or PC) to input scheduled data for the tasks they want the robots to perform. This scheduled data includes the task name, priority, duration, and dependencies. This data is entered through the user interface and transmitted to the server in real time.

[1289] Next, the server receives the schedule data sent from the user terminal via the internet and stores it in the database. Commonly used database management systems such as SQLite or PostgreSQL are used as the database.

[1290] The server calculates the priority of each task based on the stored schedule data. Specifically, the priority is determined based on the importance and urgency of each task. It also considers the dependencies between tasks to determine which tasks should be executed before others. Considering task priorities and dependencies, it generates an optimal time schedule. This schedule is calculated with high accuracy using machine learning and optimization algorithms.

[1291] The generated schedule is notified to management equipment and robots within the factory. Notification methods include push notifications, email, or real-time notifications via a dedicated application. The schedule notified by the server is visually displayed on the management equipment's interface. Display formats such as Gantt charts and list formats are possible, designed to allow users to easily understand and manage the schedule.

[1292] As a concrete example, a factory manager enters the following task into the system:

[1293] Task 1: Inspection (Priority 2, Estimated time: 1 hour, No dependencies)

[1294] Task 2: Parts Delivery (Priority 1, Estimated Time 0.5 hours, No Dependencies)

[1295] Task 3: Component assembly (Priority 3, Estimated time 2 hours, Dependent tasks 2)

[1296] Users input these tasks through a dedicated interface, which are then sent to the server. The server receives and stores them, and, considering priority and dependencies, generates a schedule as follows: "Task 2 -> Task 1 -> Task 3". The schedule is communicated to administrators and robots and is displayed visually.

[1297] As an example of a prompt statement:

[1298] "Task name: Inspection, Priority: 2, Estimated time: 1 hour, Dependencies: None"

[1299] Task management can be performed efficiently using prompt statements like these.

[1300] This system streamlines robot operations within the factory and provides real-time notifications of optimal schedules that appropriately consider priorities and dependencies. This results in improved production efficiency and smoother workflow.

[1301] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1302] Step 1:

[1303] The user uses a management device to input scheduled data for the task they want the robot to perform (task name, priority, duration, dependencies, etc.). The entered data is sent to the server via the user interface. The input data is in the format of, for example, "Task name: Inspection, Priority: 2, Duration: 1 hour, Dependencies: None".

[1304] Step 2:

[1305] The terminal sends the entered schedule data to the server, which receives it via the internet. The server verifies the received data and saves it to a database. Databases such as SQLite and PostgreSQL are used. This saving process ensures that the data necessary for subsequent processing is reliably retained.

[1306] Step 3:

[1307] The server calculates task priorities based on the stored schedule data. This calculation is based on the importance and urgency of each task. Specifically, it retrieves the value of the "priority" field from the received data and determines the processing order of each task based on that value.

[1308] Step 4:

[1309] The server processes task dependencies and generates a time schedule. This process checks the "dependencies" field of each task and sets the time so that the next task starts only after its dependent tasks have completed. For example, if "Task 3" depends on "Task 2," the schedule will be set so that Task 3 starts only after Task 2 has finished.

[1310] Step 5:

[1311] The server notifies management equipment and robots within the factory of the generated schedule. Possible notification methods include push notifications, email, and real-time notifications via a dedicated application. At this point, the notified schedule is in an optimized order based on the task data entered by the user.

[1312] Step 6:

[1313] The management device terminal visually displays the schedule received from the server. The visual display format can be a Gantt chart or a list. This visual display allows users to easily check and manage the start and end times of each task.

[1314] Step 7:

[1315] As a concrete example, a user inputs the following tasks, the server receives and saves them, and, considering priority and dependencies, generates a schedule of "Task 2 -> Task 1 -> Task 3". This schedule is notified to the administrator and the robot and is visually displayed on the management device.

[1316] In this way, the server processes data entered by the user, generates an optimal schedule, and notifies and displays it, thus streamlining task management for robots within the factory.

[1317] 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.

[1318] This invention incorporates an emotion engine that recognizes, analyzes, and considers user emotions into a system aimed at improving the efficiency of task management. This system can analyze user emotions in real time and adjust task priorities and schedules based on that information. It also includes a task suggestion function to reduce user stress and fatigue.

[1319] 1. The user enters the schedule data.

[1320] Users input task names, priorities, estimated time, dependencies, and sentiment data into the system using their devices (smartphones or PCs). Sentiment data is either manually entered by the user or automatically acquired by sensors or cameras installed on the device.

[1321] 2. Sending and receiving task data and sentiment data

[1322] The device sends task data and emotion data to the server. The data is transmitted over the internet and received by the server. Emotion recognition technology is implemented using facial expression recognition, voice analysis, text analysis, etc.

[1323] 3. The server stores and processes the data.

[1324] The server reviews the received task and sentiment data and saves it to the database. The database contains the information necessary for schedule generation.

[1325] 4. Calculating Priority

[1326] The server calculates task priorities. In this process, in addition to task importance and urgency, user sentiment data is also considered. For example, if a user is stressed, the task order may be adjusted to alleviate that stress.

[1327] 5. Utilizing the Emotional Engine

[1328] An emotion engine within the server analyzes the user's emotions in real time. Based on the user's emotional state, it dynamically adjusts task priorities and schedules. The emotion engine also suggests refreshing tasks to reduce the user's stress and fatigue.

[1329] 6. Generating an optimal schedule

[1330] The server resolves task dependencies and generates an optimal schedule that takes sentiment data into account. Task start and end times are set based on a comprehensive evaluation of priorities, dependencies, and user sentiment states.

[1331] 7. Schedule notifications

[1332] The server generates a schedule and notifies the user's device. Notifications are sent via methods such as push notifications, email, and alerts, allowing the user to receive the latest schedule in real time.

[1333] 8. Visual representation of the schedule

[1334] The user's device visually displays the schedule received from the server. The visual display is presented in calendar or list format, designed for easy user understanding. Refreshment tasks and reminders based on emotional state are also displayed.

[1335] Specific example

[1336] For example, suppose a user enters the following task into the system:

[1337] Task 1: Check emails (Priority 1, Estimated time: 0.5 hours, No dependencies)

[1338] Task 2: Meeting (Priority 3, Duration 1 hour, No dependencies)

[1339] Task 3: Report creation (Priority 2, Estimated time 2 hours, Dependent tasks 2)

[1340] If the system determines that the user is experiencing stress, it can add a short break (refreshment task) before the meeting.

[1341] The specific processing flow is as follows: the user inputs the task data via their device, and the device sends this data to the server. The server receives and stores the task data and sentiment data, and generates a schedule based on priorities, dependencies, and sentiment data. Finally, the generated schedule is notified to the user's device and displayed visually.

[1342] As a result, the system of the present invention not only manages tasks but also provides an optimal schedule that takes into account the user's emotional state, thereby supporting the reduction of user stress and efficient task execution.

[1343] The following describes the processing flow.

[1344] Modes for carrying out the invention

[1345] This invention incorporates an emotion engine that recognizes, analyzes, and considers user emotions into a system aimed at improving the efficiency of task management. This system can analyze user emotions in real time and adjust task priorities and schedules based on that information. It also includes a task suggestion function to reduce user stress and fatigue.

[1346] System processing flow

[1347] Step 1:

[1348] The user uses the device to input the task name, priority, duration, and dependencies. This task data is entered through the device's user interface. User sentiment data is also collected. Sentiment data is either entered by the user or automatically acquired by sensors and cameras installed on the device.

[1349] Step 2:

[1350] The terminal sends the entered task data and sentiment data to the server. The data is sent to the server via the internet as a POST request.

[1351] Step 3:

[1352] The server verifies the received task and sentiment data and saves it to the database. First, the server checks the integrity and completeness of the data, and if there are no problems, it saves it to the database.

[1353] Step 4:

[1354] The server calculates task priorities based on stored task data. The importance and urgency of tasks are evaluated based on a priority calculation algorithm. Sentimental data is also considered in the calculation; for example, if a user is experiencing stress, task reordering is performed to reduce stress.

[1355] Step 5:

[1356] The emotion engine on the server analyzes the user's emotions in real time. The emotion engine uses emotion recognition technologies such as facial expression recognition, voice analysis, and text analysis to determine the user's emotional state.

[1357] Step 6:

[1358] The server dynamically adjusts task priorities and schedules based on the analysis results of the emotion engine. The order and start times of tasks may change based on the user's emotional state. The emotion engine also suggests refreshing tasks to reduce the user's stress and fatigue.

[1359] Step 7:

[1360] The server resolves task dependencies and generates an optimal schedule that takes sentiment data into account. Task start and end times are set based on a comprehensive evaluation of priorities, dependencies, and user sentiment states.

[1361] Step 8:

[1362] The server generates a schedule and notifies the user's device. Push notifications and email are used as notification methods. This notification process allows the user to receive the latest schedule in real time.

[1363] Step 9:

[1364] The user's device visually displays the schedule received from the server. The schedule is displayed on the device screen in calendar or list format, allowing the user to easily check the order and start times of tasks. Refreshment tasks and reminders based on emotional state are also displayed.

[1365] Specific example

[1366] For example, suppose a user enters the following task into the system:

[1367] Task 1: Check emails (Priority 1, Estimated time: 0.5 hours, No dependencies)

[1368] Task 2: Meeting (Priority 3, Duration 1 hour, No dependencies)

[1369] Task 3: Report creation (Priority 2, Estimated time 2 hours, Dependent tasks 2)

[1370] If the emotion engine determines that the user is experiencing stress, the system can add a short break (refreshment task) before the meeting. The specific process involves the user inputting the task data via their device, which then sends it to the server. The server receives and stores the task data and emotion data, and generates a schedule based on priorities, dependencies, and emotion data. Finally, the generated schedule is notified to the user's device and displayed visually.

[1371] As a result, the system of the present invention not only manages tasks but also provides an optimal schedule that takes into account the user's emotional state, thereby supporting the reduction of user stress and efficient task execution.

[1372] (Example 2)

[1373] 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".

[1374] Traditional task management systems only provided standardized schedules without considering the user's emotional state. This failed to alleviate user stress and fatigue, hindering efficient task completion. Furthermore, the lack of real-time analysis and reflection of emotional data made dynamic schedule adjustments difficult.

[1375] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1376] In this invention, the server includes means for the user to input schedule data, means for transmitting the schedule data and emotional data to the server, means for the server to receive the schedule data and emotional data and store it in a database, means for the server to calculate task priorities based on the schedule data and emotional data, means for analyzing the user's emotional state in real time using an emotional engine and dynamically adjusting task priorities and schedules, means for processing the dependencies of the tasks and generating a time schedule considering the emotional data, and means for notifying the user of the generated schedule. This makes it possible to provide an optimal task schedule that takes the user's emotional state into consideration.

[1377] A "user" refers to an individual who uses the system to manage tasks and adjust schedules.

[1378] "Schedule data" refers to information necessary for task management and schedule generation, such as the task name, priority, duration, and dependencies entered by the user.

[1379] "Emotional data" refers to information that indicates the user's emotional state, and is acquired either through manual input or by sensors or cameras installed on the device.

[1380] A "server" refers to a computer system that receives, stores, and processes data sent by users.

[1381] A "database" refers to a system that stores task data and sentiment data received by a server, and stores necessary information.

[1382] An "emotion engine" refers to a software component that analyzes a user's emotional state in real time and reflects the results in task prioritization and scheduling.

[1383] "Priority" refers to the order in which tasks are executed, determined based on their importance, urgency, and sentiment data.

[1384] "Dependency" refers to the dependencies that each task has on other tasks, and the order of tasks is determined based on these dependencies.

[1385] A "time schedule" refers to a plan that includes the start and end times of tasks, generated based on priorities and dependencies.

[1386] "Notification methods" refer to methods such as push notifications, emails, and alerts used to inform users of generated schedules.

[1387] "Visual display" refers to the function of displaying the generated schedule on the device in a calendar or list format so that users can easily check it.

[1388] This invention relates to a task management system that takes user emotions into consideration. This system provides a function in which a server generates an optimal task schedule based on the planned data and emotion data entered by the user, and notifies the user's terminal.

[1389] Hardware and software usage

[1390] This system uses the following hardware and software:

[1391] Devices: Smartphones (e.g., iPhone, Android), PCs (e.g., Windows, Mac)

[1392] Emotion recognition technology: OpenCV (facial expression recognition), speech analysis software, natural language processing software (e.g., Google Cloud Natural Language API)

[1393] Server: A high-performance computer system

[1394] Database: MySQL, PostgreSQL

[1395] Notification system: Firebase Cloud Messaging, email sending service

[1396] Specific processing of the system

[1397] Data entry

[1398] Users input task details (task name, priority, duration, dependencies) using their own devices. In addition, they can input sentiment data. This sentiment data can be entered manually by the user or automatically acquired by sensors and cameras installed on the device.

[1399] Data transmission and reception

[1400] The entered task data and sentiment data are transmitted from the terminal to the server via the internet. The server receives this data, verifies it, and then stores it in a database.

[1401] Data analysis and processing

[1402] The server calculates task priorities based on the received data. During this process, it uses an emotion engine to analyze the user's emotional state in real time, dynamically adjusting the task order and schedule. It also processes task dependencies and generates a time schedule that takes emotional data into account.

[1403] Schedule generation and notification

[1404] The schedule generated by the server is notified to the user's device and communicated to the user through means such as push notifications, email, and alerts. The device receives the notification and displays the schedule visually. The display format can be calendar or list, and refresh tasks and notes are also displayed.

[1405] Examples of specific cases and prompt statements

[1406] For example, suppose a user enters the following task into the system:

[1407] Task 1: Check emails (Priority 1, Estimated time: 0.5 hours, No dependencies)

[1408] Task 2: Meeting (Priority 3, Duration 1 hour, No dependencies)

[1409] Task 3: Report creation (Priority 2, Estimated time 2 hours, Dependent tasks 2)

[1410] In this case, if the user enters emotional data such as "I'm a little tired today," the system can add a refreshing task such as "10 minutes of stretching" before the meeting.

[1411] The following are some examples of prompts that users might input into a generated AI model:

[1412] Example prompt: "I have an important meeting at 3 PM. Please suggest a short task to refresh myself before then."

[1413] The system of this invention not only manages tasks but also provides an optimal schedule that takes into account the user's emotional state, thereby supporting user stress reduction and efficient task execution.

[1414] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1415] Processing flow of this system's program

[1416] Step 1: The user enters the schedule data.

[1417] Users use their devices (smartphones or PCs) to input task details and sentiment data into the system. The input data includes task name, priority, duration, dependencies, and sentiment data. Sentiment data can be entered manually by the user or automatically acquired using sensors or cameras installed on the device.

[1418] Input: Task information (task name, priority, duration, dependencies), sentiment data

[1419] Output: Temporary data storage within the terminal

[1420] Specific actions: The user opens a smartphone app, enters "Task name: Report creation, Priority: 2, Estimated time: 2 hours, Dependency: Meeting," and describes their emotional state as "I'm a little tired today."

[1421] Step 2: Sending and receiving task data and sentiment data

[1422] The terminal sends the entered task data and sentiment data to the server. The transmission takes place over the internet, and the data is encrypted before transmission. The server receives the data and verifies its integrity.

[1423] Input: Task data and sentiment data entered into the terminal.

[1424] Output: Data sent to the server

[1425] Specific operation: The smartphone uses Wi-Fi or mobile data communication to encrypt the entered data and send it to the server.

[1426] Step 3: The server stores and processes the data.

[1427] The server reviews the received task and sentiment data and saves it to a database. This database is used to store the information necessary for schedule generation.

[1428] Input: Task data and sentiment data received by the server

[1429] Output: Data stored in the database

[1430] Specific operation: The server checks the received data in JSON format, verifies that there is no missing information, and then inserts it into a database such as MySQL or PostgreSQL.

[1431] Step 4: Calculating Priorities

[1432] The server calculates task priorities. This calculation considers not only the importance and urgency of tasks, but also emotional data. For example, if a user is experiencing high stress levels, a refresh task may be inserted.

[1433] Input: Task data and sentiment data stored in the database

[1434] Output: Task data with calculated priorities

[1435] Specific operation: The server uses an emotion engine to analyze emotion data such as "I'm a little tired today," and recalculates the priority based on the urgency and importance of the task.

[1436] Step 5: Utilizing the Emotional Engine

[1437] The emotion engine on the server analyzes emotion data in real time. Based on the analysis results, task priorities and schedules are dynamically adjusted. It also suggests refresh tasks.

[1438] Input: Task data with calculated priorities and sentiment data

[1439] Output: Adjusted priorities and schedules

[1440] Specific action: The emotional engine detects a state of "fatigue" and suggests "10 minutes of stretching" as a way to refresh.

[1441] Step 6: Generate the optimal schedule

[1442] The server considers task dependencies and generates an optimal schedule that reflects sentiment data. It sets the start and end times for tasks and proposes the most efficient schedule.

[1443] Input: Adjusted priority and task data

[1444] Output: Generated time schedule

[1445] Specific operation: The server inserts a "10-minute stretch" between the meeting and report creation and generates it as a schedule.

[1446] Step 7: Schedule Notification

[1447] The server generates a schedule and notifies the user's device. Notification methods include push notifications, email, and alerts.

[1448] Input: Generated time schedule

[1449] Output: Schedule notified to the user's device

[1450] Specific action: The smartphone displays a schedule via push notification, such as "10:00-11:00 Meeting, 11:00-11:10 Refresh, 11:10-13:10 Report writing."

[1451] Step 8: Visualizing the Schedule

[1452] The user's device visually displays the schedule received from the server. The display is in calendar or list format, and refresh tasks and notes are also shown.

[1453] Input: Schedule notified to the user's device

[1454] Output: Visually displayed schedule

[1455] Specific action: The smartphone's calendar app displays the daily schedule and highlights stretching time as a refresh task on the screen.

[1456] (Application Example 2)

[1457] 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".

[1458] Traditional task management systems fail to consider the emotional state of users, making it difficult to maximize work efficiency and performance. Furthermore, they cannot detect and respond immediately to user stress or fatigue in real time. As a result, work efficiency decreases, potentially negatively impacting user health. This problem is particularly pronounced in factories and production lines where high precision and efficiency are required.

[1459] 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.

[1460] In this invention, the server includes means for receiving user schedule data and emotional data and storing it in a database, means for analyzing the user's emotional state in real time and calculating task priorities based on that analysis, and means for suggesting refreshing tasks to reduce the user's stress and fatigue. This makes it possible to dynamically adjust task priorities and schedules based on the user's emotional state, thereby improving the efficiency and accuracy of the steel production line.

[1461] "Schedule data" refers to information about the tasks and time schedules entered by the user.

[1462] "Emotional data" refers to data that represents the emotional state of a user and is collected in real time.

[1463] A "server" is a device that receives scheduled data and sentiment data sent by users, and processes and stores them.

[1464] A "database" is a data storage system for saving received schedule data and sentiment data.

[1465] The method for calculating "priority" is an algorithm that evaluates the importance and urgency of tasks based on scheduled data and sentiment data, and then determines the order in which they will be processed.

[1466] "Dependency" refers to a situation where one task is related to another task, and the schedule is adjusted based on that relationship.

[1467] The means of generating a "time schedule" is the process of determining the start and end times of each task, taking into account priorities and dependencies.

[1468] The means of notifying the "user" refers to a communication method for informing the user of the generated schedule in real time.

[1469] "Means of visual display" refers to an interface that clearly displays the generated schedule to the user.

[1470] An "emotion engine" is a system that analyzes a user's emotional state in real time and dynamically adjusts task priorities and schedules based on that information.

[1471] A "refreshment task" refers to a suggestion for a break or light work to reduce user stress and fatigue.

[1472] This invention incorporates an emotion engine into a factory work management system aimed at improving the efficiency of task management. This engine recognizes, analyzes, and considers the emotions of users and workers. The system analyzes user emotions in real time and uses this information to adjust task priorities and schedules. It also includes a function to suggest refreshing tasks to reduce user stress and fatigue.

[1473] The elements necessary to realize this system are as follows:

[1474] hardware

[1475] 1. Sensors: Cameras and microphones for collecting emotional data.

[1476] 2. Terminal: A user interface used for data entry and receiving notifications, such as a PC or smartphone.

[1477] 3. Server: A central computing device for processing data and storing and distributing results.

[1478] software

[1479] 1. Emotion Recognition API: A tool for analyzing user emotions in real time (e.g., Emotion API).

[1480] 2. Task Management API: A program for managing task data and generating schedules (e.g., Factory Tasks API).

[1481] 3. Data analysis libraries: Libraries used for data processing and analysis, such as Pandas and NumPy.

[1482] 4. Scheduling algorithm: A program for calculating task priorities and resolving dependencies.

[1483] This system processes information in the following steps:

[1484] Specific example

[1485] For example, suppose a factory worker inputs tasks such as "assembly," "quality control," and "packaging" into the system. Furthermore, if the system detects that the worker is experiencing a high stress level through emotion recognition, it automatically inserts break times to reduce the worker's stress. At this time, an optimal task schedule is generated and notified to the worker's device, and also displayed visually.

[1486] Example of a prompt

[1487] The following are possible input prompt formats:

[1488] "Enter tasks such as assembly, quality control, and packaging. Sensors will analyze your emotions in real time, suggesting refreshing tasks if stress levels are high. It will then generate and visually display an optimal schedule."

[1489] The system of this invention thus achieves optimal task management and scheduling based on the user's emotional state, improving work efficiency and reducing user stress. This makes it possible to balance factory productivity with employee health.

[1490] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1491] Step 1:

[1492] The user enters the schedule data.

[1493] The user uses a terminal to input task name, priority, duration, dependencies, and sentiment data into the system. The input data takes the form of task name, priority, and duration, while sentiment data is either entered by the user or automatically acquired by sensors or cameras installed on the terminal.

[1494] Step 2:

[1495] Sending and receiving task data and sentiment data

[1496] The terminal sends the entered task data and sentiment data to the server. The data is sent to the server via the internet using a secure communication protocol, and the server receives it.

[1497] Step 3:

[1498] The server stores and processes the data.

[1499] The server stores received task data and emotion data in a database. The data is stored in an organized format and used for subsequent processing and analysis. For example, emotion data is used for facial expression recognition, voice analysis, and text analysis to quantify the user's emotional state.

[1500] Step 4:

[1501] Priority calculation

[1502] The server calculates the priority of each task, taking into account its importance, urgency, and emotional data. For example, if a user is experiencing stress, the server adjusts the order of tasks to alleviate that stress. The calculated priority is then used to determine the order in which tasks are processed.

[1503] Step 5:

[1504] Utilizing the Emotion Engine

[1505] An emotion engine on the server analyzes the user's emotions in real time. The emotion engine uses facial expression recognition APIs and voice analysis APIs to analyze emotional data and dynamically adjust task priorities and schedules based on the emotional state. It also suggests refreshing tasks necessary to reduce the user's stress and fatigue.

[1506] Step 6:

[1507] Generating an optimal schedule

[1508] The server resolves task dependencies and generates an optimal schedule that takes sentiment data into account. It comprehensively evaluates priorities, dependencies, and the user's emotional state to set the start and end times for each task. The generated schedule reduces user stress levels while enabling efficient task processing.

[1509] Step 7:

[1510] Schedule notification

[1511] The server notifies the user's device of the generated schedule. Notifications are sent via methods such as push notifications, email, and alerts, allowing the user to receive the latest schedule in real time. The notified schedule is displayed in the device's notification center or in specific applications.

[1512] Step 8:

[1513] Visual display of schedule

[1514] The user's device visually displays the schedule received from the server. The visual display is presented in calendar or list format, designed for easy user understanding. Furthermore, refresh tasks and reminders are also displayed, providing intuitive feedback on the user's emotional state.

[1515] Through these steps, task prioritization and scheduling are optimized based on the user's emotional state, reducing user stress and enabling efficient task completion.

[1516] 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.

[1517] The data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of the data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">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.

[1518] 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.

[1519] 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.

[1520] 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.

[1521] 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.

[1522] 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.

[1523] 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.

[1524] 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."

[1525] 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.

[1526] 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.

[1527] 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.

[1528] 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.

[1529] 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.

[1530] 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.

[1531] 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.

[1532] 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.

[1533] 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.

[1534] 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.

[1535] 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.

[1536] 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.

[1537] The following is further disclosed regarding the embodiments described above.

[1538] Claims

[1539] (Claim 1)

[1540] A means for users to input schedule data,

[1541] A means of sending the above scheduled data to the server,

[1542] The above server receives the above scheduled data and stores it in the database,

[1543] The above server has a means of calculating task priorities based on the above schedule data,

[1544] A means for processing the dependencies of the above tasks and generating a time schedule,

[1545] A system including means for notifying the user of the generated schedule.

[1546] (Claim 2)

[1547] The system according to claim 1, further comprising means for the user's terminal to visually display the schedule.

[1548] (Claim 3)

[1549] The system according to claim 1, further comprising means for sorting tasks based on task priority, resolving dependencies, and generating a time schedule.

[1550] "Example 1"

[1551] (Claim 1)

[1552] A means for users to input schedule data,

[1553] A means of sending the above scheduled data to the server,

[1554] The above server receives the above scheduled data and stores it in the database,

[1555] The above server has a means of calculating task priorities based on the above schedule data,

[1556] A means for processing the dependencies of the above tasks and generating a time schedule,

[1557] A system including means for notifying the user terminal of the above schedule.

[1558] (Claim 2)

[1559] The system according to claim 1, further comprising means for visually displaying the schedule received by the user's terminal.

[1560] (Claim 3)

[1561] The system according to claim 1, further comprising means for organizing tasks based on task priorities, resolving dependencies, and generating a time schedule.

[1562] "Application Example 1"

[1563] (Claim 1)

[1564] A means for users to input schedule data,

[1565] A means of sending the above scheduled data to the server,

[1566] The above server receives the above scheduled data and stores it in the database,

[1567] The above server has a means of calculating task priorities based on the above schedule data,

[1568] A means for processing the dependencies of the above tasks and generating a time schedule,

[1569] A means of notifying the user of the generated schedule,

[1570] To efficiently manage robot tasks in a factory, a means is provided to input robot work tasks from a management device and generate an optimized schedule based on priorities and dependencies.

[1571] A means of notifying factory managers and robots of the generated schedule,

[1572] A visual display means for visually displaying the generated schedule,

[1573] A system that includes this.

[1574] (Claim 2)

[1575] The system according to claim 1, further comprising means for the user's terminal to visually display the schedule.

[1576] (Claim 3)

[1577] The system according to claim 1, further comprising means for sorting tasks based on task priority, resolving dependencies, and generating a time schedule.

[1578] "Example 2 of combining an emotion engine"

[1579] (Claim 1)

[1580] A means for users to input schedule data,

[1581] A means for sending the above-mentioned schedule data and sentiment data to the server,

[1582] The above server receives the above schedule data and sentiment data and stores it in a database,

[1583] The above server has a means for calculating task priorities based on the above schedule data and sentiment data,

[1584] A means of dynamically adjusting task priorities and schedules by using an emotion engine to analyze the user's emotional state in real time,

[1585] A means for processing the dependencies of the above tasks and generating a time schedule that takes sentiment data into consideration,

[1586] A system including means for notifying the user of the generated schedule.

[1587] (Claim 2)

[1588] The system according to claim 1, further comprising means for the user's terminal to visually display the schedule.

[1589] (Claim 3)

[1590] The system according to claim 1, further comprising means for sorting tasks based on task priority, resolving dependencies, and generating a time schedule that takes sentiment data into account.

[1591] "Application example 2 when combining with an emotional engine"

[1592] (Claim 1)

[1593] A means for users to input schedule data,

[1594] A means of sending the above scheduled data to the server,

[1595] The above server receives the above schedule data and sentiment data and stores it in a database,

[1596] The above server has a means for calculating task priorities based on the above schedule data and sentiment data,

[1597] A method for sorting tasks based on the above priority, resolving dependencies, and generating a time schedule,

[1598] A means of analyzing the user's emotional state in real time and dynamically adjusting the task schedule based on that analysis,

[1599] A means of suggesting refreshing tasks to reduce user stress and fatigue,

[1600] A means of notifying the user of the generated schedule,

[1601] A system including means for visually displaying the generated schedule.

[1602] (Claim 2)

[1603] The system according to claim 1, further comprising means for the user's terminal to visually display the schedule.

[1604] (Claim 3)

[1605] The system according to claim 1, further comprising an emotion engine that collects emotion data in real time and dynamically adjusts task priorities and schedules based on that data. [Explanation of symbols]

[1606] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for users to input schedule data, A means of sending the above scheduled data to the server, The above server receives the above scheduled data and stores it in the database, The above server has a means of calculating task priorities based on the above schedule data, A means for processing the dependencies of the above tasks and generating a time schedule, A system including means for notifying the user of the generated schedule.

2. The system according to claim 1, further comprising means for the user's terminal to visually display the schedule.

3. The system according to claim 1, further comprising means for sorting tasks based on task priority, resolving dependencies, and generating a time schedule.

Images