System

Abstract

To provide a system.SOLUTION: A system includes: means for converting an abstract task into concrete actions and a time limit; means for managing the converted actions; means for presenting an action list including the actions periodically to a user; means for automatically executing the actions in a case where a predetermined condition is satisfied; means for detecting an emotional state of the user; means for controlling the automatic execution of the task corresponding to the emotional state; and means for confirming an incomplete task at a predetermined time and executing or temporarily stopping the incomplete task on the basis of the emotional state.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Generally, the key to task management is breaking down abstract tasks into concrete actions and deadlines that are easy to execute, but many people struggle with this. There is also a need for an efficient method for completing the entire process of specifying, managing, and executing tasks. [Means for solving the problem]

[0005] This invention provides a means for converting abstract tasks into specific actions and deadlines, a means for managing the converted actions, a means for periodically presenting an action list to the user, and a means for automatically executing simple actions. This allows the user to efficiently complete a series of steps from specifying a task to executing it. Furthermore, by providing a means for providing feedback to the user on the execution status of the specified actions and a means for updating the action list based on the user's actions, the efficiency and effectiveness of task management are improved. [Brief explanation of the drawings]

[0006] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 2 is a sequence diagram showing a flow of processing in the data processing system according to the first embodiment of the first form example. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1 of Embodiment 1. [Figure 13] FIG. 10 is a sequence diagram showing a processing flow of a data processing system in a second embodiment of the second form example. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 of Embodiment Example 2. [Figure 15] FIG. 10 is a sequence diagram showing the flow of processing in a data processing system according to a third embodiment of the third embodiment. [Figure 16] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 3 of Embodiment 3. [Figure 17] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the first embodiment of the first form example when an emotion engine is combined. [Figure 18] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1 of Form Example 1 when an emotion engine is combined. [Figure 19] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the second embodiment of the second form example when an emotion engine is combined. [Figure 20] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 of Form Example 2 when an emotion engine is combined. [Figure 21] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the third embodiment of the third form example when an emotion engine is combined. [Figure 22] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 3 of Form Example 3 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0007] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0008] First, the terms used in the following description will be explained.

[0009] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, the processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), or a TPU (TENSOR PROCESSING UNIT (registered trademark)).

[0010] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0011] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0012] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0013] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0014] [First embodiment]

[0015] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0016] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0017] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0018] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0019] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0020] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0021] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0022] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0023] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0024] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0025] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0026] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0027] "Example 1"

[0028] As one embodiment of the present invention, a task management application is provided. This application has a function of converting abstract tasks input by a user into specific actions and deadlines. Specifically, when a user inputs an abstract task such as "manage the progress of a project," the application converts this into a specific action such as "list each task of the project and set a deadline for each."

[0029] "Example 2"

[0030] Additionally, one embodiment of the present invention provides the ability to manage the converted actions. Specifically, the application sorts the actions according to the due date set by the user, displaying them in order of the nearest due date. When the user completes an action, it is removed from the list and the remaining incomplete actions are displayed.

[0031] "Example 3"

[0032] In addition, one embodiment of the present invention provides a function for periodically presenting an action list to the user. Specifically, the application notifies the user of incomplete action lists at a set time (e.g., 9:00 a.m. every morning). This allows the user to always keep track of their tasks and progress them efficiently.

[0033] "Example 4"

[0034] Furthermore, one embodiment of the present invention provides a function for automatically executing simple actions. Specifically, an application automatically executes simple actions such as "send an email" or "set a reminder." This allows the user to progress with tasks without any effort.

[0035] The processing flow of each embodiment will be described below.

[0036] "Example 1"

[0037] Step 1: The user inputs an abstract task into the application: "Manage the progress of a project."

[0038] Step 2: The application analyzes the input task and converts it into a specific action: "List each task in the project and set a due date for each one." Step 3: The converted specific action is added to the task list in the application.

[0039] "Example 2"

[0040] Step 1: The application reads the due date set for each action in the task list.

[0041] Step 2: Sort the actions by their due date and view the sorted task list.

[0042] Step 3: If the user completes an action, it is removed from the list and the incomplete actions are displayed.

[0043] "Example 3"

[0044] Step 1: The user sets the time (for example, 9:00 every morning) for presenting the action list on the application's settings screen.

[0045] Step 2: When the set time is up, the application will notify the user of the incomplete action list.

[0046] "Example 4"

[0047] Step 1: The user adds simple actions such as "send an email" or "set a reminder" to the task list.

[0048] Step 2: The application will automatically perform these simple actions.

[0049] Example 1

[0050] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0051] Conventional task management systems have the drawback of making efficient task management difficult because users have to convert abstract tasks into concrete actions, which is time-consuming. Furthermore, they lack the functionality to properly manage tasks entered by users and provide regular feedback, making it difficult to grasp the progress of tasks.

[0052] The identification process by the identification processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means. In this invention, the server includes means for converting abstract tasks into specific actions and due dates, means for managing the converted actions, means for periodically presenting an action list to the user, means for automatically executing simple actions, means for converting abstract tasks into specific actions using a generative AI model, means for transmitting tasks input from a user terminal to the server, means for transmitting specific actions generated from the server to the user terminal, and means for displaying the specific actions on the user terminal. This allows the user to simply input an abstract task, which is converted into specific actions and due dates, enabling efficient task management.

[0053] An "abstract task" is a general goal or objective without clearly defined specific actions or deadlines.

[0054] "Concrete actions" refer to the clear, concrete tasks or steps required to accomplish an abstract task.

[0055] A "deadline" refers to the deadline by which a particular task or action should be completed.

[0056] A "generative AI model" refers to an algorithm or system that uses artificial intelligence technology to analyze input data and generate appropriate output.

[0057] "User terminal" refers to a device such as a computer or smartphone that can be directly operated by a user.

[0058] A "server" refers to a computer system that communicates with user terminals via a network and processes and stores data.

[0059] A "prompt" is a piece of text containing instructions or questions to a generative AI model to perform a specific task.

[0060] An "action list" refers to a list of specific actions organized in a list format.

[0061] "Feedback" refers to information provided to a user about the progress or results of a task or action.

[0062] This invention is a system that realizes efficient task management by converting abstract tasks input by a user into specific actions and deadlines using a generative AI model. Specific embodiments of this system are described below.

[0063] Hardware and software used

[0064] Hardware: Server, user terminal (PC, smartphone)

[0065] Software: Task management applications, generative AI models (e.g., GPT-4®)

[0066] System Overview

[0067] 1. A user launches a task management application and enters an abstract task, for example, "Manage the progress of a project."

[0068] 2. The device receives this input and sends it to the server.

[0069] 3. The server passes the received abstract task to a generative AI model, which generates prompts to translate the abstract task into concrete actions and deadlines.

[0070] 4. The generative AI model analyzes the abstract tasks input and converts them into specific actions and deadlines, such as "list each task in a project and set a deadline for each one."

[0071] 5. The server receives the generated specific actions and deadlines and sends them to the user's terminal.

[0072] 6. The device displays the specific actions and deadlines received to the user.

[0073] Specific examples

[0074] A user enters "Manage project progress" into a task management application.

[0075] The terminal sends this input to the server.

[0076] The server sends the prompt "Manage the progress of the project" to the generative AI model.

[0077] The generative AI model analyzes this prompt and converts it into a specific action: "List each task in the project and set a due date for each."

[0078] The server transmits the generated specific action to the user terminal.

[0079] The device displays specific actions to the user, such as "List each task in the project and set a due date for each."

[0080] Prompt Sentence Examples

[0081] Convert the abstract task of "managing the progress of a project" into concrete action.

[0082] Break down the task of "managing the progress of a project" into specific steps.

[0083] This system allows users to simply input abstract tasks, which are then converted into specific actions and deadlines, enabling efficient task management. Furthermore, by using a generative AI model, task specificity is automated, reducing the burden on users.

[0084] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0085] Step 1:

[0086] A user launches a task management application and inputs an abstract task. The user opens the application on a PC or smartphone and inputs an abstract task, such as "manage the progress of a project," into the input field. The input data is in text format and is saved on the user's device.

[0087] Step 2:

[0088] The terminal sends the input task to the server. The terminal receives the task data entered by the user and sends it to the server using an HTTP POST request. The input data is task data in text format and is sent to the server.

[0089] Step 3:

[0090] The server passes the received task to the generative AI model. The server analyzes the received task data and generates a prompt to be passed to the generative AI model. For example, the task "Manage the progress of a project" is converted into a prompt such as "Please convert this task into a specific action." The input data is the task data in text format, and the output data is the prompt.

[0091] Step 4:

[0092] A generative AI model converts abstract tasks into specific actions and deadlines. A generative AI model receives a prompt and converts abstract tasks into specific actions and deadlines. For example, it converts them into specific actions such as "List each task in the project and set a deadline for each." The input data is the prompt, and the output data is specific actions and deadlines.

[0093] Step 5:

[0094] The server sends the generated specific actions and deadlines to the terminal. The server sends the specific actions and deadlines received from the generative AI model to the terminal as an HTTP response. The input data are the specific actions and deadlines, and the output data is the HTTP response.

[0095] Step 6:

[0096] The terminal displays specific actions and deadlines to the user. The terminal displays specific actions and deadlines received from the server to the user. For example, a specific action such as "List each task in the project and set a deadline for each" is displayed on the application screen. The input data are specific actions and deadlines, and the output data is the information displayed to the user.

[0097] In this way, abstract tasks entered by the user are converted into concrete actions and deadlines, enabling efficient task management.

[0098] (Application example 1)

[0099] Next, a description will be given of Application Example 1 of Embodiment Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0100] With conventional task management systems, it is difficult to convert abstract tasks into concrete actions and deadlines, and efficient operation is required, especially in task management within factories. Furthermore, converting abstract tasks entered by users into concrete actions requires a lot of manual work, which takes time and effort. Furthermore, there are no task management systems that utilize generative AI models, making it difficult to automate task management within factories.

[0101] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0102] In this invention, the server includes means for converting abstract tasks into specific actions and deadlines, means for managing the converted actions, means for periodically presenting an action list to the user, means for automatically executing simple actions, means for converting abstract tasks into specific actions using a generative AI model, and means for automating task management within the factory. This makes it possible to efficiently convert abstract tasks entered by the user into specific actions and automate task management within the factory.

[0103] An "abstract task" is a general goal or objective without clearly defined specific actions or deadlines.

[0104] "Specific actions" refer to the concrete steps or tasks required to accomplish an abstract task.

[0105] A "deadline" refers to the deadline by which a particular task or action should be completed.

[0106] A "generative AI model" refers to an algorithm or system that uses artificial intelligence technology to generate new information or results from input data.

[0107] "Factory task management" refers to the efficient planning, execution, and monitoring of various tasks and processes that take place within a factory.

[0108] "Automation" refers to minimizing human intervention and enabling machines and systems to operate autonomously.

[0109] A "server" refers to a computer system that provides services to other computers on a network.

[0110] "User" refers to an individual or organization that uses a system or application.

[0111] An "action list" is a list of specific actions needed to accomplish a particular task or goal.

[0112] "Feedback" refers to information that provides information about the performance and results of a system or process, allowing for improvements and adjustments.

[0113] As an embodiment of the present invention, a system for automating task management within a factory is constructed. A specific embodiment of the system is shown below.

[0114] System configuration

[0115] This system consists of a server, factory robots, and user terminals. The server uses a generative AI model to convert abstract tasks into specific actions and deadlines. The factory robots execute the specific actions received from the server. The user terminal provides an interface for users to input abstract tasks and receive feedback.

[0116] Program processing

[0117] The server receives abstract tasks input by users and uses a generative AI model to convert them into specific actions and deadlines. The specific actions are sent to robots in the factory, which then execute them. The server monitors the robots' execution and provides feedback to the user.

[0118] Hardware and software used

[0119] Hardware: Factory robots, user devices (PCs, tablets, smartphones)

[0120] Software: Python, OpenAI® API, generative AI models

[0121] Data processing and calculation

[0122] The server receives abstract tasks entered by the user in text format and inputs them into a generative AI model. The generative AI model converts the abstract tasks into specific actions and deadlines and returns the results to the server. The server then sends the converted specific actions to robots in the factory, which then execute them. The server monitors the robots' execution status and provides feedback to the user.

[0123] Specific examples

[0124] For example, if a user inputs an abstract task such as "improving production line efficiency," the generative AI model will output a specific task such as the following:

[0125] Specific examples

[0126] Identify bottlenecks on each production line

[0127] Propose improvements to eliminate bottlenecks

[0128] Create an implementation plan for improvement measures

[0129] Monitor the progress of each improvement measure

[0130] Prompt Sentence Examples

[0131] Convert the following abstract tasks into concrete actions and deadlines: Increase the efficiency of the production line

[0132] In this way, task management within the factory can be efficiently automated.

[0133] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0134] Step 1:

[0135] A user inputs an abstract task using a terminal.

[0136] Input: Abstract task (e.g., "Improve the efficiency of the production line")

[0137] Output: Abstract tasks are sent to the server

[0138] Specific operation: The user inputs the task through the terminal interface and presses the submit button.

[0139] Step 2:

[0140] The server receives the abstract task and sends a prompt to the generative AI model.

[0141] Input: Abstract task

[0142] Output: The prompt sent to the generative AI model

[0143] Specific operation: The server receives the abstract task, generates a prompt sentence, and sends it to the generative AI model.

[0144] Example prompt: "Translate the following abstract task into concrete actions and due dates: Increase the efficiency of the production line."

[0145] Step 3:

[0146] A generative AI model parses prompts and converts them into specific actions and deadlines.

[0147] Input: prompt statement

[0148] Output: Specific actions and due dates

[0149] Concrete Actions: The generative AI model parses the prompt and converts the abstract task into concrete actions and deadlines.

[0150] Examples: "Identify bottlenecks on each production line," "Propose improvements to eliminate bottlenecks," "Draw an implementation plan for the improvements," and "Monitor the progress of each improvement."

[0151] Step 4:

[0152] The server receives the output from the generative AI model and sends specific actions to the robots in the factory.

[0153] Input: Specific actions and due dates

[0154] Output: Specific actions sent to robots in the factory

[0155] Specific actions: The server sends the specific actions and deadlines received from the generative AI model to the robots in the factory.

[0156] Step 5:

[0157] Robots in factories perform specific actions.

[0158] Input: Specific action

[0159] Output: Action execution result

[0160] Specific action: The robot in the factory executes the specific action received and performs the work.

[0161] Step 6:

[0162] The server monitors the robot's performance and provides feedback to the user.

[0163] Input: Robot execution status

[0164] Output: Feedback provided to the user

[0165] Specific operation: The server monitors the robot's execution status and provides feedback to the user on progress and problems.

[0166] Example 2

[0167] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0168] Conventional task management systems lack the ability to sort actions based on user-set due dates or automatically remove completed actions from the list, making it difficult for users to efficiently manage their tasks. Furthermore, they lack the ability to display only incomplete actions, making it difficult for users to distinguish between completed and incomplete tasks.

[0169] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0170] In this invention, the server includes means for converting abstract tasks into specific actions and deadlines, means for managing the converted actions, means for periodically presenting a list of actions to the user, means for automatically executing simple actions, means for sorting actions based on deadlines set by the user, means for deleting an action from the list when the user completes it, and means for displaying only incomplete actions, thereby enabling the user to efficiently manage tasks and easily distinguish between completed and incomplete tasks.

[0171] An "abstract task" is a general task or goal without specific actions or deadlines.

[0172] A "specific action" refers to a specific task or procedure that a user needs to perform.

[0173] "Deadline" refers to the deadline set by the user for completing an action.

[0174] "Means for conversion" refers to a method or device for converting abstract tasks into concrete actions and deadlines.

[0175] "Means for managing" refers to a method or device for storing, tracking, and updating the translated actions.

[0176] "Presenting means" refers to a method or device for displaying the action list to the user.

[0177] "Automatic execution means" refers to a method or device for performing a simple action without user intervention.

[0178] "Means for sorting" refers to a method or device for ordering actions based on user-set deadlines.

[0179] "Means for deleting" refers to a method or device that allows a user to remove a completed action from the list.

[0180] "Means for displaying" refers to a method or device for showing only the incomplete actions to the user.

[0181] MODE FOR CARRYING OUT THE INVENTION

[0182] The present invention is a system for managing actions based on deadlines set by a user and for efficiently completing tasks. A specific embodiment of this system is described below.

[0183] Hardware and software used

[0184] Hardware: The server uses a high-performance cloud server (e.g., a virtual server from a cloud service provider).

[0185] Software: The application is developed in Python and uses MySQL® for database management. The front end is built with JavaScript libraries and the back end uses a web application framework.

[0186] System Overview

[0187] The system converts abstract tasks entered by users into concrete actions and due dates, and manages them. The server sorts the actions based on the due dates set by the user, displaying them in order of the nearest due date. When the user completes an action, it removes it from the list, and only uncompleted actions are displayed.

[0188] Data processing and calculation

[0189] 1. Data entry: The user enters an action and its due date.

[0190] 2. Data storage: The server stores the entered data in a MySQL (registered trademark) database.

[0191] 3. Data sorting: The server retrieves the actions from the database and sorts them based on their due date.

[0192] 4. Data display: Send the sorted actions to the front end and display them to the user.

[0193] 5. Data Update: When the user completes an action, the server removes it from the database and re-sorts and displays the incomplete actions.

[0194] Specific examples

[0195] Example 1: Adding and displaying an action

[0196] A user adds an action called "Submit a Report" with a due date of "2023-10-15". The server stores this information in a database and displays it along with other actions, sorted by due date.

[0197] Example 2: Completing an action

[0198] When the user completes the "report submission," the server removes this action from the database and re-sorts and displays the incomplete actions.

[0199] Prompt Sentence Examples

[0200] "Your application should sort actions based on the due date set by the user, displaying them in order of closest due date. When the user completes an action, you should also add the ability to remove it from the list and display only the incomplete actions."

[0201] By inputting this prompt sentence into a generative AI model, a program that outlines the above system can be generated.

[0202] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0203] Step 1:

[0204] The user enters the action

[0205] The user uses the terminal to input an action and its due date into the input form of the application. The input data is the content and due date of the action.

[0206] Step 2:

[0207] The device sends the action to the server

[0208] The terminal sends the entered action and due date to the server as an HTTP request. This request includes the action content and due date. The input is the action and due date entered by the user, and the output is the HTTP request sent to the server.

[0209] Step 3:

[0210] The server saves the action to the database

[0211] The server stores the received action and due date in a MySQL database. Specifically, it adds a new record to the database using an INSERT statement. The input is the HTTP request and the output is the record stored in the database.

[0212] Step 4:

[0213] The server sorts the actions by due date

[0214] The server retrieves all actions from the database using a SELECT statement and sorts them by due date using the SQL ORDER BY clause. The input is the action list retrieved from the database, and the output is the sorted action list.

[0215] Step 5:

[0216] The server sends the sorted actions to the terminal.

[0217] The server sends the sorted action list to the terminal in JSON format, so that the terminal can receive the latest action list. The input is the sorted action list, and the output is the JSON data sent to the terminal.

[0218] Step 6:

[0219] The device displays the action

[0220] The terminal displays the received action list in the user interface. The actions are listed in order of their due date. The input is JSON data received from the server, and the output is the action list displayed in the user interface.

[0221] Step 7:

[0222] The user completes the action

[0223] When the user completes an action, they mark it as complete in the application's interface. The input is the user's action, and the output is the action marked as complete.

[0224] Step 8:

[0225] The device notifies the server of the completed action

[0226] The device sends information about the completed action to the server as an HTTP request, which includes the ID of the completed action. The input is the action marked as completed, and the output is the HTTP request sent to the server.

[0227] Step 9:

[0228] The server removes completed actions from the database

[0229] The server uses the received action ID to delete the corresponding action from the database using a DELETE statement. The input is the HTTP request, and the output is the record deleted from the database.

[0230] Step 10:

[0231] The server resorts the outstanding actions

[0232] The server retrieves the pending actions from the database again using the SELECT statement and sorts them by due date. The input is the list of pending actions retrieved from the database, and the output is the sorted list of pending actions.

[0233] Step 11:

[0234] The server sends the updated action list to the device.

[0235] The server sends the updated list of pending actions to the terminal in JSON format. The input is the sorted list of pending actions, and the output is the JSON data sent to the terminal.

[0236] Step 12:

[0237] The device displays the updated action list

[0238] The terminal receives the updated action list and displays it again in the user interface, allowing the user to see the latest pending actions. The input is the JSON data received from the server, and the output is the updated action list displayed in the user interface.

[0239] (Application example 2)

[0240] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0241] Task management in logistics centers is difficult because multiple tasks occur simultaneously and each has a different deadline. Furthermore, if the information is not reflected immediately after a worker completes a task, there is a risk of unnecessary work being done. Furthermore, if task priorities are not clearly defined, there is a risk that important tasks will be put off.

[0242] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0243] In this invention, the server includes means for converting abstract tasks into specific actions and deadlines, means for managing the converted actions, means for periodically presenting a list of actions to the user, means for automatically executing simple actions, means for sorting the actions based on deadlines and displaying them in order of the nearest deadline, and means for deleting an action from the list when the user completes it and displaying uncompleted actions. This improves the efficiency of task management in the logistics center and enables important tasks to be appropriately prioritized.

[0244] An "abstract task" is a general task or goal without clearly defined specific actions or deadlines.

[0245] "Specific actions" are the concrete steps or tasks required to accomplish an abstract task.

[0246] A "deadline" is the date by which a particular task or action should be completed.

[0247] A "conversion means" is a method or device for converting abstract tasks into concrete actions and deadlines.

[0248] "Means for managing" refers to the methods and devices for tracking the converted actions and monitoring their progress.

[0249] A "presentation means" refers to a method or device for displaying the action list to the user.

[0250] An "automatic execution means" is a method or device for automatically executing a particular action without user intervention.

[0251] A "means for sorting" is a method or device for sorting actions based on due date.

[0252] "Means for displaying" refers to a method or device for visually indicating the sorted actions to the user.

[0253] "Means for removing the action from the list when completed" refers to a method or device for removing an action from the list when the user completes the action.

[0254] The "means for displaying incomplete actions" refers to a method or device for displaying to the user only the actions that are not completed.

[0255] A system for carrying out the present invention is intended to improve the efficiency of task management in a logistics center. A specific embodiment of this system will be described below.

[0256] System configuration

[0257] The system consists of a server, worker devices (smartphones or smart glasses), and a user interface. The server plays a central role in task management, while the device is used by workers to check tasks and report their completion.

[0258] Program processing

[0259] The server manages tasks using the following means:

[0260] 1. A way to translate abstract tasks into concrete actions and deadlines

[0261] The server converts abstract tasks entered by the logistics center manager into specific actions and deadlines. For example, it converts an abstract task such as "check inventory" into a specific action such as "check inventory by October 10th."

[0262] 2. A way to manage the converted actions

[0263] The server stores the converted actions in a database and tracks the progress of each action, including information such as the action's due date, who is responsible for it, and its status.

[0264] 3. A way to periodically present the user with a list of actions

[0265] The server periodically sends the action list to the worker's device and displays it through a user interface, allowing the worker to see the current tasks and their due dates.

[0266] 4. Automating simple actions

[0267] The server automatically executes simple actions when certain conditions are met, such as automatically issuing a replenishment command when inventory falls below a certain level.

[0268] 5. A way to sort actions based on due date, with the most recent due first

[0269] The server sorts the action list based on due date and displays it on the worker's terminal in order of the nearest due date, allowing the worker to process the highest priority tasks first.

[0270] 6. When a user completes an action, a way to remove it from the list and display incomplete actions.

[0271] When a worker reports completion of an action via a terminal, the server removes that action from the list and displays only incomplete actions.

[0272] Hardware and software used

[0273] Hardware: Servers, smartphones, smart glasses

[0274] Software: Python (programming language), database management system (e.g., MySQL), user interface (e.g., React Native)

[0275] Specific examples

[0276] A logistics center worker puts on smart glasses and launches a task management application. The application sorts today's tasks by due date and displays those that need to be completed earliest. When the worker completes the "stock shelves" task, it disappears from the smart glasses display and the next task, "prepare for shipment," appears.

[0277] Prompt Sentence Examples

[0278] Develop an application that uses smart glasses to help logistics center workers efficiently manage their daily tasks. Tasks are sorted by due date and displayed in order of closest due date. When a worker completes a task, it is automatically removed from the list, and incomplete tasks continue to be displayed. Write the program using Python.

[0279] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0280] Step 1:

[0281] The server receives abstract tasks from the logistics center manager. The input is the task outline entered by the manager, and the output is the task converted into specific actions and due dates. The server analyzes the task content and generates specific actions and due dates.

[0282] Step 2:

[0283] The server saves the converted actions in a database. The input is the specific action and due date, and the output is the task information saved in the database. The server records information such as the action details, due date, and responsible person in the database.

[0284] Step 3:

[0285] The server periodically sends an action list to the worker's terminal. The input is task information stored in the database, and the output is an action list displayed on the worker's terminal. The server acquires the task information and presents it to the worker through a user interface.

[0286] Step 4:

[0287] The server automatically executes simple actions when certain conditions are met. The input is task information that meets the conditions, and the output is the result of the automatically executed action. For example, the server may automatically instruct replenishment when inventory falls below a certain level.

[0288] Step 5:

[0289] The server sorts the action list based on the due date and displays it on the worker's terminal in order of the nearest due date. The input is the task information stored in the database, and the output is the sorted action list. The server sorts the list based on the task due date and displays high-priority tasks at the top.

[0290] Step 6:

[0291] When a user completes an action, the information is sent to the server via the terminal. The input is the reported task information, and the output is an updated action list. The server then removes the completed task from the list and displays only the incomplete tasks.

[0292] Step 7:

[0293] The server updates the action list based on the user's actions. The input is the user's action data, and the output is the latest action list. The server monitors the user's progress and updates the task priority and content as needed.

[0294] Example 3

[0295] Next, a third embodiment of the third embodiment will be described. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0296] Conventional task management systems require users to manually manage tasks and check their progress, making efficient task management difficult. They also lack the functionality to automatically execute simple actions, which increases the workload for users. Furthermore, they lack sufficient notification functions to periodically check task progress, which increases the risk of users forgetting to complete tasks.

[0297] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[0298] In this invention, the server includes means for converting abstract tasks into specific actions and deadlines, means for managing the converted actions, means for periodically presenting an action list to the user, means for automatically executing simple actions, means for the user to input tasks, means for the server to save the tasks in a database, means for the server to periodically check the tasks, means for the server to notify the user of incomplete tasks, and means for the server to automatically execute simple actions. This allows the user to efficiently manage tasks and progress them without hassle.

[0299] An "abstract task" is a general task or goal without specific actions or deadlines.

[0300] "Specific actions" refer to concrete tasks or procedures that transform abstract tasks into executable forms.

[0301] A "deadline" refers to the date and time when a task or action should be completed.

[0302] An "action list" is a list of specific actions that a user should perform.

[0303] "User" refers to an individual or organization that uses the system to manage tasks.

[0304] A "server" is a computer system that serves as the core of a task management system and stores and processes data.

[0305] A "database" refers to a system for organizing and storing information about tasks and actions.

[0306] "Notification" refers to a message sent by the server to inform the user of the progress of a task or an uncompleted task.

[0307] "Simple actions" refer to tasks that can be automated relatively easily, such as sending emails or setting reminders.

[0308] A "reminder" refers to a notification that reminds a user to perform a specific task or action.

[0309] MODE FOR CARRYING OUT THE INVENTION

[0310] The present invention is a system for improving the efficiency of task management for users, which is realized through the interaction between a server, a terminal, and a user. A specific embodiment of this system will be described below.

[0311] Hardware and software used

[0312] Hardware: Servers, user devices (PCs, smartphones, etc.)

[0313] Software: Task management applications, notification systems, email sending systems, reminder setting systems

[0314] Data processing and calculation

[0315] 1. The user enters a task

[0316] The user uses the terminal to open a task management application.

[0317] The user enters a new task and enters the required information (task name, due date, reminder settings, etc.).

[0318] Example: A user enters a task "Prepare for a meeting" and sets the due date to "Tomorrow at 10:00 AM."

[0319] 2. The server saves the task in the database

[0320] After the user inputs the task, the terminal sends the information to the server.

[0321] The server stores the received task information in a database.

[0322] Example: The server saves the task "Prepare for meeting" in the database.

[0323] 3. The server periodically checks for tasks

[0324] The server checks the database at a set time (for example, 9:00 every morning) and retrieves any uncompleted tasks.

[0325] The server lists the acquired incomplete tasks.

[0326] Example: Every morning at 9am the server checks the database and lists all outstanding tasks.

[0327] 4. The server notifies the user of outstanding tasks

[0328] The server notifies the user's terminal of the list of uncompleted tasks.

[0329] The user receives a notification on the device and checks the incomplete tasks.

[0330] Example: The server sends a notification to the user's smartphone saying, "Good morning. You have uncompleted tasks. Please check them."

[0331] 5. The server automatically executes simple actions

[0332] The server periodically checks simple actions set by the user (e.g., "send email" or "set reminder").

[0333] When the conditions are met, the server automatically calls an email sending system or a reminder setting system to perform an action.

[0334] Example: If a user sets a task to "set a reminder every Monday," the server will call the reminder setting system every Monday and automatically set the reminder.

[0335] Specific examples

[0336] Presenting an action list

[0337] Every morning at 9:00, the server retrieves the user's uncompleted tasks from the database and notifies the user's smartphone.

[0338] For example: "Good morning. You have some uncompleted tasks. Please take a look."

[0339] Automatic execution of simple actions

[0340] If a user sets a task to "set a reminder every Monday," the server will call the reminder setting system every Monday and automatically set the reminder.

[0341] For example: "I've set a reminder. Our next meeting is on Monday at 10am."

[0342] Example prompts for generative AI models

[0343] "Please create a program that notifies the user of their incomplete tasks every morning at 9am."

[0344] "Create a program that automatically executes simple actions set by the user."

[0345] In this way, the user can efficiently manage his or her tasks and progress the tasks without any hassle. The flow of the specific processing in the third embodiment will be described with reference to FIG.

[0346] Step 1:

[0347] The user enters a task

[0348] Input: The user uses a device to open a task management application and enter a new task.

[0349] Data processing: The application receives information entered by the user, such as task name, deadline, and reminder settings.

[0350] Output: The terminal sends the input task information to the server.

[0351] Specific behavior: The user clicks the "Add new task" button, enters the task name "Prepare for meeting", sets the due date to "Tomorrow at 10:00 AM", and clicks the "Save" button.

[0352] Step 2:

[0353] The server saves the task in a database

[0354] Input: Task information sent from the terminal.

[0355] Data processing: The server analyzes the task information received and converts it into a format suitable for saving in the database.

[0356] Output: The server saves the task information to the database and sends a confirmation message to the terminal.

[0357] Specific operation: The server saves the task "Prepare for meeting" to the database and sends a confirmation message "Task saved successfully" to the terminal.

[0358] Step 3:

[0359] The server periodically checks for tasks

[0360] Input: Task information stored in the database.

[0361] Data processing: The server queries the database at a set time (for example, every morning at 9:00) to retrieve incomplete tasks.

[0362] Output: List of open tasks retrieved by the server.

[0363] What it does: Every morning at 9am, the server checks the database and lists all uncompleted tasks.

[0364] Step 4:

[0365] The server notifies the user of outstanding tasks

[0366] Input: Open tasks listed.

[0367] Data processing: The server converts the list of incomplete tasks into a format that can be sent to the user's device.

[0368] Output: The server notifies the user of the list of uncompleted tasks on their device.

[0369] Specific behavior: The server sends a notification to the user's smartphone saying, "Good morning. You have uncompleted tasks. Please check them."

[0370] Step 5:

[0371] The server automatically executes simple actions

[0372] Input: A simple action set by the user (e.g., "send email" or "set reminder").

[0373] Data processing: When the conditions are met, the server automatically calls an email sending system or reminder setting system to execute an action.

[0374] Output: The server performs a simple action and notifies the user of the result.

[0375] Specific behavior: If a user sets a task to "set a reminder every Monday," the server will call the reminder setting system every Monday and automatically set the reminder.

[0376] (Application example 3)

[0377] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0378] Robot maintenance and task management in factories is often done manually, which is inefficient. Even simple actions like ordering necessary parts and setting maintenance reminders must be done manually, placing a heavy burden on workers. This can lead to missed or delayed tasks, reducing the efficiency of factory operations.

[0379] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[0380] In this invention, the server includes means for converting abstract tasks into specific actions and deadlines, means for managing the converted actions, means for periodically presenting a list of actions to a user, means for automatically executing simple actions, means for periodically presenting a list of maintenance and work tasks for a factory robot, means for automatically setting maintenance reminders, means for automatically sending an order email for necessary parts, and means for automatically notifying an administrator of the results of the robot's self-diagnosis. This automates the management of factory robot maintenance and work tasks, reduces the burden on workers, prevents omissions and delays in tasks, and improves factory operation efficiency.

[0381] An "abstract task" is a general goal or objective without clear specific actions or steps.

[0382] A "specific action" refers to a specific task or operation that involves specific steps or actions.

[0383] A "deadline" refers to the deadline by which a particular task or action should be completed.

[0384] "Means for conversion" refers to a method or device for converting abstract tasks into concrete actions and deadlines.

[0385] "Means for managing" refers to a method or apparatus for tracking the translated actions and monitoring progress.

[0386] "Means for periodically presenting a list of actions to a user" refers to a method or device for notifying a user of uncompleted tasks or actions at set time intervals.

[0387] "Means for automatically performing simple actions" refers to a method or device for automatically performing specific simple tasks or operations to save the user time.

[0388] A "factory robot" refers to an automated mechanical device designed to perform work or maintenance in a factory.

[0389] The "means for presenting a list of maintenance and work tasks" refers to a method or device for displaying to a factory robot the maintenance and work tasks that need to be performed periodically.

[0390] "Means for automatically setting maintenance reminders" refers to a method or device for automatically setting notifications when factory robots require maintenance.

[0391] "Means for automatically sending an order email for necessary parts" refers to a method or device for automatically sending an order email when necessary parts are in short supply.

[0392] "Means for automatically notifying the manager of the results of a robot's self-diagnosis" refers to a method or device for a factory robot to perform a self-diagnosis and automatically notify the manager of the results.

[0393] As an embodiment of the present invention, we will explain an example of a "Factory Robot Task Manager" system installed on a factory robot. This system automates the maintenance and task management of factory robots, reduces the burden on workers, and improves factory operation efficiency.

[0394] System Program

[0395] The system is implemented using Python, specifically using the following libraries:

[0396] schedule library: periodic task execution

[0397] smtplib library: Sending email

[0398] Program processing explanation

[0399] The server processes and calculates data using the following hardware and software.

[0400] Hardware: Factory robot displays, internet connectivity

[0401] Software: Python, schedule library, smtplib library

[0402] The server displays a list of uncompleted maintenance and work tasks on the factory robot's display every morning at 9:00, making it easier for users to understand the tasks for the day. In addition, at 9:05, an order email for necessary parts is automatically sent, preventing work delays due to a parts shortage.

[0403] Specific examples

[0404] For example, every morning at 9:00, the tasks "Replace part A" and "Cleaning" are displayed on the robot's display. The user can check these and proceed with the tasks in order of priority. In addition, an order email for part A is automatically sent at 9:05, so the user does not have to manually place the order.

[0405] Prompt Sentence Examples

[0406] "Using the Factory Robot Task Manager, please create a program that displays a list of uncompleted tasks every morning at 9:00 and automatically sends an email to order the necessary parts at 9:05."

[0407] In this way, maintenance of factory robots and management of work tasks can be automated, reducing the burden on workers and improving factory operating efficiency.

[0408] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[0409] Step 1:

[0410] The server sets a trigger for task notification every morning at 9:00 using the schedule library. The input is a task list and the current time, and the output is an instruction to display the task list. Specifically, the server retrieves the task list and confirms that the current time is 9:00.

[0411] Step 2:

[0412] The server displays the task list on the display of the factory robot. The input is the task list, and the output is the task list that is displayed on the display. Specifically, the server formats the contents of the task list and sends it to the display.

[0413] Step 3:

[0414] The server uses the schedule library to set a trigger for the automatic execution of a simple action every morning at 9:05. The input is the current time, and the output is an instruction to execute the simple action. Specifically, the server checks that the current time is 9:05.

[0415] Step 4:

[0416] The server automatically sets maintenance reminders. The input is the maintenance schedule, and the output is the generated reminder settings. Specifically, the server checks the maintenance schedule and sets the reminder.

[0417] Step 5:

[0418] The server automatically sends an order email for the required parts. The input is the parts inventory information and the supplier's email address, and the output is an order email. Specifically, the server checks the inventory information, and if the required parts are in short supply, it generates and sends an order email.

[0419] Step 6:

[0420] The server automatically notifies the administrator of the robot's self-diagnosis results. The inputs are the self-diagnosis results and the administrator's contact information, and the output is a notification message. Specifically, the server obtains the self-diagnosis results and sends a notification message to the administrator.

[0421] In this way, maintenance of factory robots and management of work tasks are automated, reducing the burden on workers and improving factory operating efficiency.

[0422] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0423] "Example 1"

[0424] One embodiment of the present invention is a system incorporating an emotion engine. This system recognizes a user's emotion and adjusts task priorities according to that emotion. Specifically, if the system recognizes that the user's emotion is "stress," it increases the priority of tasks related to relaxation. Similarly, if the system recognizes that the user's emotion is "joy," it increases the priority of tasks related to enjoyable activities. In this way, dynamically adjusting task priorities according to the user's emotion allows for task management that takes the user's psychological state into account.

[0425] "Example 2"

[0426] The emotion engine also analyzes the user's facial expressions, tone of voice, and social media posts to recognize the user's emotions. Specifically, it uses a camera and microphone to capture the user's facial expressions and tone of voice and inputs this data into the emotion recognition algorithm. If the user allows it, the content of social media posts can also be used as data for emotion recognition. Based on this data, the emotion engine recognizes the user's current emotional state and adjusts task priorities accordingly.

[0427] "Example 3"

[0428] Furthermore, the emotion engine controls the automatic execution of tasks according to the user's emotional state. Specifically, if it recognizes that the user's emotion is "anger," it temporarily suspends tasks that may further anger the user (for example, automatic replies to emails from a specific person). If it recognizes that the user's emotion is "joy," it executes a task to share the user's joy (for example, automatic posting to social media). In this way, the emotion engine enables the automatic execution of tasks that take the user's emotional state into consideration.

[0429] The processing flow of each embodiment will be described below.

[0430] "Example 1"

[0431] Step 1: The system captures the user's facial expressions and tone of voice using a camera and microphone.

[0432] Step 2: The emotion engine then inputs the captured data into an emotion recognition algorithm to recognize the user's current emotional state.

[0433] Step 3: The emotion engine adjusts the priority of tasks according to the emotion it recognizes. For example, if it recognizes the emotion as "stress," it will increase the priority of tasks related to relaxation.

[0434] "Example 2"

[0435] Step 1: If the user allows it, the system uses the content of social media posts as data for emotion recognition.

[0436] Step 2: The emotion engine inputs the content of the social media post into the emotion recognition algorithm to recognize the user's current emotional state.

[0437] Step 3: The emotion engine adjusts the priority of tasks according to the recognized emotion. For example, if the emotion is recognized as "joy," it increases the priority of tasks related to enjoyable activities. "Example 3"

[0438] Step 1: The emotion engine recognizes the user's emotional state.

[0439] Step 2: The emotion engine controls the automatic execution of tasks according to the recognized emotion. For example, if the emotion is recognized as "anger," it temporarily stops tasks that may further anger the user.

[0440] Step 3: If the emotion is recognized as "joy," a task is performed to share the user's joy.

[0441] Example 1

[0442] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0443] Conventional task management systems have difficulty converting abstract tasks entered by users into concrete actions and deadlines, and lack the functionality to dynamically adjust task priorities based on the user's emotions. This poses a challenge in achieving efficient task management that takes the user's psychological state into account.

[0444] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0445] In this invention, the server includes means for converting abstract tasks into specific actions and deadlines, means for managing the converted actions, means for periodically presenting an action list to the user, means for automatically executing simple actions, means for recognizing the user's emotions and adjusting task priorities in accordance with the emotions, and means for dynamically adjusting task priorities based on the emotions, thereby enabling efficient task management that takes the user's psychological state into consideration.

[0446] An "abstract task" is a general goal or objective without clearly defined specific actions or deadlines.

[0447] "Specific actions" refer to the concrete procedures or steps required to accomplish an abstract task.

[0448] A "deadline" refers to the date and time by which a particular task or action should be completed.

[0449] "Translation means" refers to methods and techniques for converting abstract tasks into concrete actions and deadlines.

[0450] "Management tools" refers to the methods and techniques used to organize and track the specific actions and deadlines that are translated.

[0451] "Presentation means" refers to the method or technique for displaying the action list to the user.

[0452] "Automatic execution means" refers to a method or technology for automatically executing a specific action without user intervention.

[0453] "Means for recognizing emotions" refers to methods and techniques for detecting and identifying a user's emotions.

[0454] "Means for adjusting priority" refers to methods and techniques for changing the importance or urgency of a task.

[0455] "Dynamic adjustment means" refers to methods and techniques for changing task priorities in real time.

[0456] MODE FOR CARRYING OUT THE INVENTION

[0457] This system converts abstract tasks entered by users into concrete actions and deadlines, and dynamically adjusts task priorities according to the user's emotions. This system operates in cooperation with a server, a terminal, and a user.

[0458] Hardware and software used

[0459] Server: Use a server with high-performance computing capabilities. Specifically, use a cloud-based server (e.g., Microsoft® Azure®).

[0460] Terminal: A device that is operated by a user. Examples include smartphones, tablets, and PCs.

[0461] Software: We use "spaCy" and "NLTK" as natural language processing (NLP) engines, and "IBM Watson (registered trademark)" and "Microsoft Azure Text Analytics" as sentiment analysis algorithms.

[0462] Program processing

[0463] 1. The user enters a task

[0464] The user inputs an abstract task into an input field on the terminal, for example, "Manage the progress of a project."

[0465] 2. The device sends the input to the server

[0466] The terminal sends the task input by the user to the server using an HTTP request.

[0467] 3. The server analyzes the task

[0468] The server passes the received task to a natural language processing (NLP) engine to analyze the task, for example, using "spaCy" or "NLTK" to break down the abstract task into concrete steps.

[0469] 4. The server generates a specific action

[0470] The server generates specific actions based on the analysis results, such as "listing each task in the project and setting a due date for each."

[0471] 5. The server sends the generated results to the terminal.

[0472] The server sends the generated specific action to the terminal using an HTTP response.

[0473] 6. The device displays feedback to the user

[0474] The device displays the specific actions received to the user, for example, "Task 1: Proposal writing (Deadline: October 10, 2023), Task 2: Team meeting (Deadline: October 12, 2023)."

[0475] 7. User inputs emotion

[0476] A user inputs their emotion into an input field of the system that incorporates the emotion engine, for example, by inputting "stress."

[0477] 8. The device sends input to the server

[0478] The terminal transmits the emotion input by the user to the server using an HTTP request.

[0479] 9. Server-based emotion recognition

[0480] The server then passes the received emotions to a sentiment analysis algorithm, such as IBM Watson or Microsoft Azure Text Analytics, to recognize the emotion.

[0481] 10. The server adjusts task priorities

[0482] The server dynamically adjusts task priorities based on the perceived emotion, for example, if you are feeling "stressed," it will prioritize tasks related to relaxation.

[0483] 11. The server sends the adjustment results to the device

[0484] The server transmits the adjusted task priority to the terminal using an HTTP response.

[0485] 12. The device displays feedback to the user

[0486] The device displays the received adjustment results to the user, for example, "Task 1: Yoga session (priority: high), Task 2: Walk (priority: medium)."

[0487] Specific examples

[0488] User input: "Manage the progress of the project."

[0489] Sending from the device: Send an HTTP request to the server to "Manage the progress of the project"

[0490] Server analysis: Analyze "Manage project progress" using an NLP engine (e.g., spaCy)

[0491] Server generation: Generate a specific action such as "List each task in the project and set a due date for each one."

[0492] Server transmission: Sends the generated results to the terminal via HTTP response

[0493] Display on device: "Task 1: Proposal writing (Due: October 10, 2023), Task 2: Team meeting (Due: October 12, 2023)"

[0494] User input: "Stress"

[0495] Sending the terminal: Send "stress" to the server via HTTP request

[0496] Server recognition: Recognizing "stress" using a sentiment analysis algorithm (e.g., IBM Watson)

[0497] Server tuning: Increase the priority of relaxation-related tasks

[0498] Server transmission: Sends the adjustment results to the device via HTTP response

[0499] Device display: "Task 1: Yoga session (high priority), Task 2: Walk (medium priority)"

[0500] Prompt Sentence Examples

[0501] Prompt: "When the user enters 'Manage project progress,' generate specific actions and due dates."

[0502] Prompt: "If the user types 'stress', how can I increase the priority of relaxation-related tasks?"

[0503] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0504] Program processing flow

[0505] Task management application

[0506] Step 1:

[0507] The user enters a task.

[0508] Input: The user types "Manage project progress" into the input field on the device.

[0509] Specific behavior: The user enters text into the input field and presses the submit button.

[0510] Output: The input task is saved on the device.

[0511] Step 2:

[0512] The device sends input to the server.

[0513] Input: Task data entered by the user.

[0514] Specific operation: The terminal generates an HTTP request and sends the input task data to the server.

[0515] Output: The server receives the task data.

[0516] Step 3:

[0517] The server analyzes the task.

[0518] Input: The received task data.

[0519] What happens: The server uses a natural language processing (NLP) engine (e.g., spaCy) to parse the task data.

[0520] Data processing: Breaking down abstract tasks into concrete steps.

[0521] Output: A concrete action list is generated as a result of the analysis.

[0522] Step 4:

[0523] The server generates the specific action.

[0524] Input: Analysis result data.

[0525] Specific behavior: The server generates specific actions based on the analysis results.

[0526] Data processing: Set deadlines for specific actions.

[0527] Output: The generated concrete action list.

[0528] Step 5:

[0529] The server transmits the generated results to the terminal.

[0530] Input: The generated concrete action list.

[0531] Specific operation: The server generates an HTTP response and sends a specific action list to the terminal.

[0532] Output: The device receives a list of specific actions.

[0533] Step 6:

[0534] The device displays feedback to the user.

[0535] Input: The received concrete action list.

[0536] Specific operation: The terminal displays the received action list on the user interface.

[0537] Output: User can see a list of specific actions.

[0538] A system incorporating an emotion engine

[0539] Step 1:

[0540] The user inputs the emotion.

[0541] Input: The user enters "stress" into the input field of the system incorporating the emotion engine.

[0542] Specific behavior: The user enters an emotion into the input field and presses the send button.

[0543] Output: The input emotion data is saved on the device.

[0544] Step 2:

[0545] The device sends input to the server.

[0546] Input: Emotion data entered by the user.

[0547] Specific operation: The device generates an HTTP request and sends the input emotion data to the server.

[0548] Output: The server receives the emotion data.

[0549] Step 3:

[0550] The server recognizes emotions.

[0551] Input: Received emotion data.

[0552] Specific operation: The server analyzes the sentiment data using a sentiment analysis algorithm (e.g., IBM Watson).

[0553] Data processing: Classifying emotion data into specific emotions such as "stress."

[0554] Output: Recognized emotion data.

[0555] Step 4:

[0556] The server adjusts the priority of the tasks.

[0557] Input: Recognized emotion data and an existing task list.

[0558] Specific behavior: The server dynamically adjusts task priorities based on the recognized emotions.

[0559] Data manipulation: Increase the priority of relaxation-related tasks.

[0560] Output: The adjusted task list.

[0561] Step 5:

[0562] The server sends the adjustment results to the terminal.

[0563] Input: The adjusted task list.

[0564] Specific operation: The server generates an HTTP response and sends the adjusted task list to the device.

[0565] Output: The device receives the adjusted task list.

[0566] Step 6:

[0567] The device displays feedback to the user.

[0568] Input: The received reconciled task list.

[0569] Specific operation: The terminal displays the received task list on the user interface.

[0570] Output: User can see the adjusted task list.

[0571] (Application example 1)

[0572] Next, a description will be given of Application Example 1 of Embodiment Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0573] Conventional task management systems lack the ability to convert abstract tasks into concrete actions or adjust task priorities based on the user's emotions, making it difficult to efficiently manage tasks while taking into account the user's psychological state. Furthermore, they lack specific tools for efficiently managing production tasks within factories, making it difficult to identify bottlenecks on the production line and adjust the workload based on the emotions of workers.

[0574] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. In this invention, the server includes means for converting abstract tasks into specific actions and deadlines, means for managing the converted actions, means for periodically presenting an action list to the user, means for automatically executing simple actions, means for recognizing the user's emotions and adjusting task priorities in accordance with the emotions, means for efficiently managing production tasks in the factory, means for measuring the time for each production step in the factory and identifying bottlenecks, and means for adjusting workloads based on the emotions of workers. This enables efficient task management that takes into account the psychological state of the user, and enables efficient management of production tasks in the factory and adjustment of workloads based on the emotions of workers.

[0575] An "abstract task" is a general goal or objective without clear specific actions or steps.

[0576] "Specific actions" refer to the concrete actions or steps required to accomplish an abstract task.

[0577] A "deadline" refers to the deadline by which a particular task or action should be completed.

[0578] "Means for conversion" refers to a method or device for converting abstract tasks into concrete actions and deadlines.

[0579] "Means for managing" refers to a method or apparatus for efficiently organizing and tracking transformed actions.

[0580] "Presenting means" refers to a method or device for visually or audibly presenting the action list to the user.

[0581] "Automatic execution means" refers to a method or device for automatically executing a particular action without user intervention.

[0582] "Means for recognizing emotions" refers to a method or apparatus for detecting and identifying a user's emotional state.

[0583] "Means for adjusting priority" refers to a method or device for changing the importance or urgency of a task.

[0584] "Production tasks" refer to specific production activities and work carried out within a factory.

[0585] "Efficient management means" refers to methods and devices for optimizing and efficiently performing production tasks.

[0586] "Production step" refers to an individual task or process in the manufacturing process of a product.

[0587] A "bottleneck" refers to a delay or obstacle in a production process that reduces overall efficiency.

[0588] "Means for adjusting workload" refers to methods and devices for appropriately allocating and adjusting the workload of workers.

[0589] A system for carrying out this invention has the following configuration: A server includes means for converting abstract tasks into specific actions and deadlines, means for managing the converted actions, means for periodically presenting an action list to the user, means for automatically executing simple actions, means for recognizing the user's emotions and adjusting task priorities in accordance with those emotions, means for efficiently managing production tasks in a factory, means for measuring the time for each production step in the factory and identifying bottlenecks, and means for adjusting the workload based on the emotions of workers.

[0590] Hardware and software used

[0591] Hardware: Factory robots, emotion-recognition cameras

[0592] Software: EmotionEngine (emotion recognition library), TaskManager (task management library)

[0593] Program processing explanation

[0594] The server first initializes the EmotionEngine to prepare for emotion recognition. Next, it initializes the TaskManager to prepare for task management. When the user inputs an abstract task, the server converts it into a specific action and adds it to the TaskManager. A deadline is set for the specific action, and it is periodically presented to the user.

[0595] The server uses the Emotion Engine to recognize the emotions of workers in the factory and adjust task priorities based on those emotions. For example, if a worker is feeling stressed, it will increase the priority of relaxation-related tasks. To efficiently manage production tasks in the factory, the server also measures the time required for each production step and identifies bottlenecks. This makes it possible to adjust the workload based on the emotions of workers.

[0596] Specific examples

[0597] For example, if a factory manager inputs the task of "improving the efficiency of the production line," the server converts this into specific actions such as "measuring the time for each production step" and "identifying bottlenecks." Additionally, if a worker is feeling stressed, the server can increase the priority of relaxation-related tasks to reduce the worker's psychological burden.

[0598] Prompt Sentence Examples

[0599] If a factory manager inputs a task like "Increase production line efficiency," translate it into a concrete action. If a worker is feeling stressed, prioritize relaxation-related tasks.

[0600] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0601] Step 1:

[0602] The server initializes the EmotionEngine and prepares it for emotion recognition. The EmotionEngine receives video data from the emotion recognition camera as input and analyzes emotions from the user's facial expressions and voice. The output is the user's emotional state (e.g., stress, joy).

[0603] Step 2:

[0604] The server initializes TaskManager and prepares for task management. TaskManager creates a database to manage task data entered by the user. It receives information such as task lists and due dates as input, and provides the managed task list as output.

[0605] Step 3:

[0606] A user inputs an abstract task into the server. For example, the server inputs a task such as "Improve the efficiency of the production line." The server converts this abstract task into specific actions. Specific actions generated include "Measure the time required for each production step" and "Identify bottlenecks." The input is an abstract task, and the output is a list of specific actions.

[0607] Step 4:

[0608] The server adds specific actions to the TaskManager and sets a due date for each action. The TaskManager stores and manages these actions in a database. The input is a list of specific actions and their due dates, and the output is an updated task list.

[0609] Step 5:

[0610] The server periodically presents the action list to the user, and sends a notification to the user's terminal to display the action list. The input is the updated task list, and the output is the action list presented to the user.

[0611] Step 6:

[0612] The server uses EmotionEngine to recognize the emotions of workers in the factory. It receives video data from the emotion recognition camera as input and analyzes the emotional state of the workers. As an output, it obtains the emotional state of the workers (e.g., stress, joy).

[0613] Step 7:

[0614] The server adjusts task priorities based on the worker's emotions. For example, if a worker is feeling stressed, it increases the priority of relaxation-related tasks. The input is the worker's emotional state, and the output is the adjusted task priorities.

[0615] Step 8:

[0616] The server measures the time for each production step and identifies bottlenecks in order to efficiently manage production tasks within the factory. It receives sensor data from the production line as input, analyzes the time for each step, and outputs the results of identifying bottlenecks.

[0617] Step 9:

[0618] The server adjusts the workload based on the worker's emotions. For example, if a worker is feeling stressed, it adjusts the workload to reduce it. The input is the worker's emotional state and production task data, and the output is the adjusted workload.

[0619] Example 2

[0620] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0621] Conventional task management systems have difficulty converting abstract tasks into concrete actions and deadlines, making it difficult to effectively manage actions according to deadlines set by users. Furthermore, task prioritization does not take into account the user's emotional state, which can lead to user stress and reduced efficiency. Furthermore, there is insufficient data collection for updating lists when users complete actions and for emotion recognition.

[0622] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for converting abstract tasks into specific actions and deadlines, means for managing the converted actions, means for periodically presenting an action list to the user, means for automatically executing simple actions, means for sorting actions according to deadlines set by the user and displaying those with the closest deadline first, means for deleting an action from the list when the user completes it and displaying uncompleted actions, means for capturing the user's facial expressions and tone of voice using a camera or microphone and inputting them into an emotion recognition algorithm, means for using the content of posts on SNS as data for emotion recognition if the user allows it, and means for adjusting task priorities according to the user's emotional state. This allows for efficient task management for the user and enables flexible adjustment of task priorities according to the user's emotional state.

[0623] An "abstract task" is a general goal or objective without clearly defined specific actions or deadlines.

[0624] "Concrete actions" refer to specific actions or tasks that transform abstract tasks into executable forms.

[0625] A "deadline" is the date by which a particular action or task should be completed.

[0626] "Means of management" refers to the methods or systems used to track the status of actions or tasks and make updates or changes as needed.

[0627] "Presentation means" refers to a method or system for displaying information to a user.

[0628] "Automatic execution means" refers to a method or system for automatically performing a particular action or task without user intervention.

[0629] A "means for sorting" refers to a method or system for ordering data based on specific criteria.

[0630] "Capturing means" refers to a method or system for capturing a user's facial expressions and tone of voice using a camera or microphone.

[0631] "Emotion recognition algorithm" refers to a computational method or program that analyzes collected data to identify a user's emotional state.

[0632] "Means for adjusting priority" refers to a method or system for changing the importance or execution order of tasks depending on the emotional state of the user.

[0633] The present invention provides a system that enables efficient task management for a user and flexible adjustment of task priorities according to the user's emotional state. Specific embodiments of this system are described below.

[0634] Hardware and software used

[0635] server:

[0636] Database: A database system (e.g., MySQL, PostgreSQL) for storing action information and user data.

[0637] Emotion recognition algorithms: Algorithms for analyzing the user's facial expressions and tone of voice (e.g., OpenCV, TENSORFLOW®)

[0638] Sorting algorithm: The algorithm used to sort actions by due date.

[0639] Device:

[0640] Camera: A device for capturing the user's facial expressions.

[0641] Microphone: A device for capturing the tone of a user's voice.

[0642] Application: Software that allows users to input and manage actions (e.g., mobile app, web app)

[0643] Program processing

[0644] The server converts abstract tasks entered by users into concrete actions and due dates. The converted actions are stored in a database and sorted according to the due dates set by the user. The sorted action list is periodically sent to the user's device and displayed.

[0645] The device uses a camera and microphone to capture the user's facial expressions and tone of voice. This data is sent to a server in real time and input into an emotion recognition algorithm. If the user allows it, social media posts can also be used as data for emotion recognition.

[0646] The server uses emotion recognition algorithms to understand the user's emotional state and adjust task priorities accordingly—for example, if the user is feeling stressed, it will postpone less important tasks.

[0647] Specific examples

[0648] If a user sets an action to "Submit a report by October 10, 2023," the following processing will occur:

[0649] 1. The user enters the action into the terminal application and presses the registration button.

[0650] 2. The terminal sends the input action information to the server.

[0651] 3. The server stores the received action information in a database, sorting it along with other actions by due date.

[0652] 4. As the deadline approaches, the server will prioritize displaying this action on the user's device.

[0653] 5. Once the user submits the report and marks the action as completed on the device, the server removes this action from the database and sends an updated action list to the device.

[0654] Prompt Sentence Examples

[0655] Input prompt for the generative AI model:

[0656] Your program should sort the actions by the due date set by the user, displaying them in order of the nearest due date, and also remove the action from the list when the user completes it, displaying the remaining incomplete actions.

[0657] Furthermore, to recognize the user's emotions, add a function to capture facial expressions and tone of voice using a camera or microphone and input them into the emotion recognition algorithm. If the user allows it, use social media posts as data for emotion recognition. Based on this data, implement a function to recognize the user's current emotional state and adjust task priority accordingly.

[0658] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0659] Step 1:

[0660] The user uses the application on the device to register an action. The user enters the action content and due date and presses the register button. The input data is the action content and due date. The device sends this data to the server. Specifically, the user enters the action "Submit a report by October 10, 2023" and presses the register button.

[0661] Step 2:

[0662] The server saves the received action information in a database. The input data is the action information sent from the terminal. The server stores this data in a database. Specifically, the server saves the action "Submit a report" and its due date in the database.

[0663] Step 3:

[0664] The server retrieves the action information stored in the database and applies a sorting algorithm based on the due date. The input data is the action information retrieved from the database. The server uses the sorting algorithm to sort the actions in order of due date. Specifically, the server sorts multiple actions in order of due date.

[0665] Step 4:

[0666] The server sends the sorted action list to the user's terminal. The input data is the sorted action list. The server sends this list to the terminal. In concrete operations, the server sends the sorted action list to the terminal, and the terminal displays it to the user.

[0667] Step 5:

[0668] When a user completes an action, the user marks the action as completed in the terminal application. The input data is the action information marked as completed. The terminal sends this information to the server. As a specific operation, the user marks the action as completed, indicating that "the report has been submitted."

[0669] Step 6:

[0670] The server deletes the action from the database and sends an updated list of incomplete actions to the user's device again. The input data is the action information marked as completed. The server deletes the action from the database and generates an incomplete action list. Specifically, the server deletes the action "Submit a report" from the database and sends an updated action list to the device.

[0671] Step 7:

[0672] The device uses a camera and microphone to capture the user's facial expressions and tone of voice. The input data is the user's facial expressions and tone of voice. The device transmits this data in real time to the server. Specifically, the device captures the user's facial expressions and tone of voice and transmits them to the server.

[0673] Step 8:

[0674] The server analyzes the captured data using an emotion recognition algorithm to recognize the user's current emotional state. The input data is the captured facial expression and tone of voice. The server applies the emotion recognition algorithm to identify the user's emotional state. Specifically, the server determines that the user is tired.

[0675] Step 9:

[0676] If the user allows it, the server also acquires the content of posts on social media and uses it as additional data for emotion recognition. The input data is the content of posts on social media. The server inputs this data into the emotion recognition algorithm. Specifically, the server analyzes the user's social media posts and uses them for emotion recognition.

[0677] Step 10:

[0678] The server adjusts task priorities according to the user's emotional state. The input data is the recognized emotional state. The server reevaluates task priorities and generates an adjusted task list. Specifically, the server determines that the user is tired and postpones less important tasks.

[0679] Step 11:

[0680] The server sends the adjusted task list to the user's terminal. The input data is the adjusted task list. The server sends this list to the terminal. In specific operations, the server sends the adjusted task list to the terminal, and the terminal displays it to the user.

[0681] (Application example 2)

[0682] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0683] Conventional task management systems prioritize tasks without considering the user's emotional state, which can lead to stress and reduced efficiency. Furthermore, in factory work task management, tasks are assigned without considering the emotional state of workers, which can lead to problems with work efficiency and safety. To solve these issues, a system is needed that recognizes the emotional state of users and workers and adjusts task priorities based on that information.

[0684] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0685] In this invention, the server includes: means for converting abstract tasks into specific actions and deadlines; means for managing the converted actions; means for periodically presenting a list of actions to the user; means for automatically executing simple actions; means for recognizing the user's emotional state; means for adjusting task priorities based on the recognized emotional state; means for capturing the user's facial expressions and tone of voice using a camera and a microphone; means for analyzing the user's emotions using an emotion recognition algorithm; means for using social media posts as data for emotion recognition if the user allows it; means for managing work tasks within a factory; and means for adjusting task priorities based on the emotional states of workers. This enables task management that takes into account the emotional states of users and workers, thereby reducing stress, improving work efficiency, and ensuring safety.

[0686] An "abstract task" is a general task or goal without clearly defined specific actions or deadlines.

[0687] A "specific action" is a task or work that involves clearly defined specific actions and procedures.

[0688] A "deadline" is the date or time when a particular task or action should be completed.

[0689] A "conversion means" is a method or device for converting abstract tasks into concrete actions and deadlines.

[0690] A "managing means" is a method or device for organizing, tracking, and, if necessary, updating the translated actions.

[0691] The "means for periodically presenting" refers to a method or device for displaying the action list to the user at regular intervals.

[0692] An "automatic execution means" is a method or device for performing a particular action without user intervention.

[0693] "Emotional state" refers to the current psychological state or mood of a user or worker.

[0694] "Means for recognizing" refers to a method or device for detecting and identifying the emotional state of a user or worker.

[0695] A "means for adjusting priorities" is a method or device for changing the importance or execution order of tasks based on a perceived emotional state.

[0696] A "camera" is a device for capturing images or video.

[0697] A "microphone" is a device for capturing sound.

[0698] "Facial expression" refers to the facial movements and expressions of the user or worker.

[0699] "Vocal tone" refers to characteristics such as pitch, intensity, and texture of the voice.

[0700] An "emotion recognition algorithm" is a computational method or program that analyzes captured data to identify emotional states.

[0701] "SNS posting content" refers to content such as text, images, and videos posted by users on social networking services.

[0702] "Work tasks within a factory" refers to the specific work and tasks performed within a factory.

[0703] "Workers" are people who perform work in a factory.

[0704] The following system configuration will be described as an embodiment of the present invention.

[0705] System Configuration

[0706] The system consists of the following main components:

[0707] 1. Server:

[0708] A way to translate abstract tasks into concrete actions and deadlines

[0709] A way to manage the converted actions

[0710] A means of periodically presenting a list of actions to the user

[0711] A means of automatically executing simple actions

[0712] A means of recognizing a user's emotional state

[0713] A means of adjusting task priorities based on perceived emotional states

[0714] A means of capturing a user's facial expressions and tone of voice using a camera or microphone

[0715] A means of analyzing user emotions using emotion recognition algorithms

[0716] A method for using social media posts as data for emotion recognition if the user allows it

[0717] A means of managing work tasks within a factory

[0718] A means of adjusting task priorities based on workers' emotional states

[0719] Program processing

[0720] The server performs data processing and calculation using the following hardware and software:

[0721] Hardware:

[0722] Camera: Used to capture the facial expressions of users and workers.

[0723] Microphone: Used to capture the tone of the user's or worker's voice.

[0724] software:

[0725] OpenCV: Used for capturing and analyzing facial expressions.

[0726] EmotionRecognizer: Used as an emotion recognition algorithm.

[0727] TaskManager: Used for task management.

[0728] Processing flow

[0729] 1. Capturing emotions:

[0730] Cameras and microphones are used to capture the facial expressions and tone of voice of users and workers.

[0731] The captured data is fed into an emotion recognition algorithm.

[0732] 2. Emotion Recognition:

[0733] An emotion recognition algorithm (EmotionRecognizer) is used to analyze the emotional state of users and workers from the captured data.

[0734] If necessary, and if the user gives permission, the content of social media posts will also be used as data for emotion recognition.

[0735] 3. Adjusting task priorities:

[0736] Based on the perceived emotional state, the TaskManager adjusts the priority of tasks.

[0737] The adjusted tasks are sorted by due date and presented to the user or worker.

[0738] Specific examples

[0739] For example, if a worker in a factory feels stressed, the emotion recognition algorithm will recognize that emotion and adjust the task manager to reduce high-priority tasks to reduce stress. In this way, worker stress can be reduced and work efficiency can be improved.

[0740] Prompt Sentence Examples

[0741] "Develop an application that manages work tasks in a factory and adjusts task priorities by recognizing the emotional state of workers. Use a camera and microphone to capture facial expressions and tone of voice, and analyze emotions using emotion recognition algorithms. Adjust task priorities based on the recognized emotions and display them in order of due date."

[0742] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0743] Step 1:

[0744] The server uses a camera and microphone to capture the facial expressions and tone of voice of users and workers.

[0745] Input: Video data from the camera, audio data from the microphone

[0746] Output: Captured facial expression data, tone of voice data

[0747] How it works: The camera captures the face of the user or worker, and the microphone records their voice. This data is sent to the server in real time.

[0748] Step 2:

[0749] The server inputs the captured facial expression data and tone of voice data into an emotion recognition algorithm.

[0750] Input: Facial expression data, voice tone data

[0751] Output: Emotional state of the user or worker

[0752] Specific operation: The server analyzes facial expression data using OpenCV and recognizes emotions using EmotionRecognizer. Voice tone data is also analyzed in the same way to identify emotional states.

[0753] Step 3:

[0754] If the user gives permission, the server retrieves the content of the SNS post and inputs it into an emotion recognition algorithm.

[0755] Input: Social media post content

[0756] Output: Additional emotion data

[0757] Specific operation: The server retrieves posts from the user's authorized social media accounts and performs text analysis to identify the user's emotional state, enabling more accurate emotion recognition.

[0758] Step 4:

[0759] The server instructs the task manager to adjust task priorities based on the perceived emotional state.

[0760] Input: Emotional state data

[0761] Output: Adjusted task priorities

[0762] Specific behavior: The server sends emotional state data to the task manager and recalculates task priorities. For example, if the user is feeling stressed, the server adjusts the priority of high-priority tasks to be reduced.

[0763] Step 5:

[0764] The server sorts the adjusted tasks by due date and presents them to the user or worker.

[0765] Input: Adjusted task priority

[0766] Output: Sorted task list

[0767] Specific operation: The server sorts the task list based on the due date and priority of the task and displays it on the user's or worker's device, allowing the user or worker to view the task that best suits their current situation.

[0768] Step 6:

[0769] When a user or worker completes a task, the server removes it from the list and displays only incomplete tasks.

[0770] Input: Task completion information

[0771] Output: Updated task list

[0772] Specific behavior: When a user or worker reports that a task is complete, the server receives the information and removes the task from the task list. Only incomplete tasks are displayed again.

[0773] Example 3

[0774] Next, a description will be given of a third embodiment of the third embodiment. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0775] Conventional task management systems provide insufficient support for users to efficiently manage tasks, and in particular, they do not automatically control task execution according to the user's emotional state, making it difficult to manage tasks that take the user's emotions into consideration. Furthermore, because they do not automatically execute simple actions or provide periodic action lists, the burden on the user increases and task progress can be delayed.

[0776] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[0777] In this invention, the server includes means for converting abstract tasks into specific actions and deadlines, means for managing the converted actions, means for periodically presenting an action list to the user, means for automatically executing simple actions, means for recognizing the user's emotional state, and means for controlling the automatic execution of tasks based on the recognized emotional state. This enables task management that takes the user's emotional state into consideration, and by automatically executing simple actions and periodically presenting an action list, the burden on the user is reduced and tasks can be progressed efficiently.

[0778] An "abstract task" is one that does not have clearly defined specific actions or deadlines.

[0779] A "specific action" is a specific task or action that the user must perform.

[0780] A "deadline" is a specific date and time by which a task should be completed.

[0781] A "conversion means" is a method or device for converting abstract tasks into concrete actions and deadlines.

[0782] A "managing means" is a method or device for tracking the translated actions and monitoring their progress.

[0783] The "means for periodically presenting the action list to the user" refers to a method or device for notifying the user of an incomplete action list at a set time interval.

[0784] A "simple action" is a simple task or activity that can be completed in a relatively short amount of time.

[0785] An "automatic execution means" is a method or device for performing a simple action without user intervention.

[0786] The term "means for recognizing an emotional state" refers to a method or device for analyzing emotions from a user's facial expressions, voice, etc., and identifying a specific emotional state.

[0787] A "means for controlling the automatic performance of a task" is a method or device for starting, stopping, or modifying the performance of a particular task based on a recognized emotional state.

[0788] MODE FOR CARRYING OUT THE INVENTION

[0789] The present invention provides a system that improves the efficiency of task management for a user and enables automatic task execution control according to the user's emotional state. Specific embodiments of this system will be described below.

[0790] Server Roles

[0791] The server extracts incomplete tasks from the user's task list and periodically presents the action list to the user. Specifically, the server retrieves the user's task information from the database and lists tasks with a status of "incomplete." For example, the server retrieves task information from the database every morning at 8:00 and lists incomplete tasks. Next, it uses a Cron job or scheduler to schedule a notification of the incomplete action list to the user every morning at 9:00. Notifications are sent via email or push notification.

[0792] Application Roles

[0793] The application extracts simple actions from the user's task list and executes them automatically. Specifically, the application analyzes the content of the task and lists simple actions such as "send an email" or "set a reminder." It then calls the email sending API or reminder setting API to automatically execute these tasks. For example, if there is a "send an email" task, it sends an email to the specified recipient.

[0794] The role of the emotional engine

[0795] The emotion engine recognizes the user's emotional state and controls the automatic execution of tasks based on the recognized emotional state. Specifically, the emotion engine analyzes the user's facial and voice data and classifies emotions into categories such as "anger" and "joy." For example, if the emotion engine analyzes the user's facial data and recognizes the emotion "anger," it temporarily stops automatic replies to emails from specific people. Also, if the user is in a "joy" state, it automatically posts to social media.

[0796] Examples and prompts

[0797] Example 1: Periodic action list notifications

[0798] Hardware: Server

[0799] Software: Task management application

[0800] Data processing: Extraction and notification of incomplete task list

[0801] Example prompt sentence:

[0802] Write a program that notifies the user of their incomplete task list every morning at 9am.

[0803] Example 2: Automatic execution of simple actions

[0804] Hardware: User's device (smartphone, PC, etc.)

[0805] Software: Task management application

[0806] Data Calculation: Extract simple actions from the user's task list and execute them automatically

[0807] Example prompt sentence:

[0808] Create a program that automatically performs simple actions such as "send email" or "set reminders" from a user's task list.

[0809] Example 3: Automatic task execution control using an emotion engine

[0810] Hardware: User's device, server

[0811] Software: Emotion recognition engine, task management application

[0812] Data Computation: Recognizing User Emotional States and Automatic Task Control

[0813] Example prompt sentence:

[0814] Create a program that controls the automatic execution of tasks according to the user's emotional state. For example, stop a specific task if the user is in an "anger" state, or automatically post to social media if the user is in a "joy" state.

[0815] In this way, the server, application, and emotion engine each play their respective roles to build a system that improves the efficiency of task management for users. The flow of the specific processing in the third embodiment will be described with reference to FIG.

[0816] Step 1:

[0817] The server retrieves user task information from the database every morning at 8:00. The input is the user's task information, and the output is a list of incomplete tasks. Specifically, it uses an SQL query to extract tasks with a status of "incomplete."

[0818] Step 2:

[0819] The server sets up a schedule to send notifications to users every morning at 9:00 based on the extracted list of incomplete tasks. The input is the list of incomplete tasks, and the output is the notification schedule. Specifically, a Cron job or scheduler is set up to trigger notifications at the specified time.

[0820] Step 3:

[0821] The server notifies the user of the list of uncompleted actions at the set time. The input is the notification schedule and the list of uncompleted tasks, and the output is the notification to the user. Specifically, the notification is sent to the user's device using email or push notification.

[0822] Step 4:

[0823] The application extracts simple actions from the user's task list. The input is the user's task list, and the output is a list of simple actions. Specifically, it analyzes the content of the task and lists simple actions such as "send an email" or "set a reminder."

[0824] Step 5:

[0825] The application automatically executes the extracted simple actions. The input is a list of simple actions, and the output is the executed actions. Specifically, it calls the email sending API and reminder setting API to execute the tasks.

[0826] Step 6:

[0827] The emotion engine recognizes the user's emotional state. The input is the user's facial expression and voice data, and the output is the recognized emotional state. Specifically, it uses facial expression recognition algorithms and voice analysis algorithms to classify emotions into categories such as "anger" and "joy."

[0828] Step 7:

[0829] The emotion engine controls the automatic execution of tasks based on the recognized emotional state. The input is the recognized emotional state and a task list, and the output is the controlled execution of the tasks. Specifically, if the user is in an "anger" state, it stops a specific task (for example, automatically replying to an email from a specific person), and if the user is in a "joy" state, it executes an automatic post to a social networking site.

[0830] (Application example 3)

[0831] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0832] Conventional task management systems require users to manually check and execute tasks, making efficient task management difficult. Furthermore, tasks are executed without taking into account the user's emotional state, which can cause stress and dissatisfaction. Furthermore, there is a problem of reduced work efficiency when robots in factories execute tasks without considering the emotional state of workers.

[0833] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[0834] In this invention, the server includes means for converting abstract tasks into specific actions and deadlines, means for managing the converted actions, means for periodically presenting an action list to the user, means for automatically executing simple actions, means for detecting the user's emotional state, means for controlling the automatic execution of tasks according to the emotional state, and means for checking uncompleted tasks at a specific time and executing or pausing the tasks based on the emotional state, thereby enabling efficient task management and execution while taking the user's emotional state into consideration.

[0835] An "abstract task" is one that does not have clearly defined specific actions or deadlines.

[0836] A "specific action" is a clear action that involves specific steps or operations.

[0837] A "deadline" is the date or time by which a particular task should be completed.

[0838] A "conversion means" is a method or device for converting abstract tasks into concrete actions and deadlines.

[0839] "Means for managing" refers to the methods and devices for tracking the transformed actions and monitoring their progress.

[0840] The "means for periodically presenting an action list to a user" refers to a method or device for notifying a user of an incomplete task list at a set time interval.

[0841] A "means for automatically performing simple actions" is a method or device for automatically performing a specific task without user intervention.

[0842] "Means for detecting a user's emotional state" refers to a method or device for identifying a user's emotional state and determining that state.

[0843] "Means for controlling the automatic performance of a task in response to an emotional state" refers to a method or apparatus for adjusting the performance of a task based on a detected emotional state.

[0844] "Means for checking for incomplete tasks at a specific time" refers to a method or device for checking for incomplete tasks at a set time.

[0845] A "means for executing or pausing a task based on emotional state" refers to a method or device for starting or pausing the execution of a task depending on the emotional state of a user.

[0846] As an embodiment of the present invention, a system is provided in which a robot in a factory efficiently manages and executes tasks while taking into account the emotional state of a user. A specific embodiment of this system is described below.

[0847] System Configuration

[0848] The system consists of the following main components:

[0849] 1. Server: Plays a central role in task management and emotional state detection.

[0850] 2. Robots: These actually perform tasks in the factory.

[0851] 3. User terminal: A device used by the worker to input emotional state and task feedback.

[0852] Program processing

[0853] The server does the following:

[0854] Task transformation: Transform abstract tasks into concrete actions and deadlines. For example, transform an abstract task like "check inventory" into a concrete action like "check the inventory list every morning at 9am."

[0855] Task Management: Manage converted actions and monitor progress. This includes the ability to track task status and list incomplete tasks.

[0856] Periodic notifications: Present the action list to the user periodically. For example, notify the user of uncompleted tasks at 9:00 every morning.

[0857] Auto-execute: Automatically execute simple actions, such as setting a reminder or sending an email.

[0858] Emotion detection: Detecting the user's emotional state using inputs and sensors from the user's device.

[0859] Emotion control: Controlling the automatic execution of tasks according to the user's emotional state. For example, if the user is in an "anger" state, pausing a specific task (e.g., sending an email) will be suspended.

[0860] Task confirmation: Check for uncompleted tasks at a specific time and execute or pause the tasks based on the user's emotional state. For example, check for uncompleted tasks at 9:00 every morning and decide whether to execute them based on the user's emotional state.

[0861] Hardware and software used

[0862] Hardware: Server, user device (smartphone, tablet, etc.), robot, emotion detection sensors (camera, microphone, etc.).

[0863] Software: Task management systems, emotion detection algorithms, notification systems, generative AI models.

[0864] Specific examples

[0865] For example, consider the following scenario in a factory:

[0866] Every morning at 9:00, the server checks for uncompleted tasks and notifies the user's device.

[0867] If the user is in the "Anger" state, the server suspends the "Send Mail" task.

[0868] When the user is in the "joy" state, the server automatically executes the "post to SNS" task.

[0869] Prompt Sentence Examples

[0870] The following prompts can be fed into the generative AI model to provide useful information for detailed system design and implementation:

[0871] Develop an application in which a robot in a factory checks the uncompleted tasks every morning at 9:00 and automatically executes or pauses the tasks depending on the worker's emotional state. The emotional states can be "Happy," "Anger," "Sadness," "Surprise," or "Calm," and the robot should have the ability to pause certain tasks (e.g., sending emails) depending on the worker's emotional state.

[0872] In this way, tasks can be managed and performed efficiently while taking into account the user's emotional state.

[0873] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[0874] Step 1:

[0875] The server translates abstract tasks into concrete actions and deadlines.

[0876] Input: Abstract task (e.g., "Check inventory")

[0877] Data transformation: Convert tasks into specific actions (e.g., "Check the inventory list every morning at 9am").

[0878] Output: Specific actions and due dates

[0879] Step 2:

[0880] The server manages the translated actions and monitors their progress.

[0881] Input: Specific actions and due dates

[0882] Data processing: Track the status of actions and list incomplete tasks.

[0883] Output: A list of open tasks

[0884] Step 3:

[0885] The server periodically presents the action list to the user.

[0886] Input: List of open tasks

[0887] Data processing: Notify the user's device of the list of uncompleted tasks at a set time (e.g., 9:00 every morning).

[0888] Output: Notification to user terminal

[0889] Step 4:

[0890] The server automatically executes simple actions.

[0891] Input: A specific action (e.g., "Set a reminder")

[0892] Data manipulation: Performing actions automatically.

[0893] Output: Execution results

[0894] Step 5:

[0895] The server detects the emotional state of the user.

[0896] Input: Emotion data from the user's device (e.g., camera footage, audio data)

[0897] Data processing: Emotion detection algorithms are used to identify emotional states.

[0898] Output: Emotional state (e.g., "joy", "anger")

[0899] Step 6:

[0900] The server controls the automatic execution of tasks according to the emotional state.

[0901] Input: Emotional state and unfinished task list

[0902] Data manipulation: Adjusting task execution based on emotional state (e.g., pausing email sending if "angry").

[0903] Output: Reconciled task list

[0904] Step 7:

[0905] The server checks for outstanding tasks at specific times and executes or pauses the tasks based on the emotional state.

[0906] Input: Unfinished task list and emotional state

[0907] Data processing: At a set time (e.g., every morning at 9:00), review your outstanding tasks and execute or pause them based on your emotional state.

[0908] Output: Status of the task being run or paused

[0909] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0910] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0911] Another example of generative AI is Gemini (registered trademark) (Internet search engine). <url: https: gemini.google.com ?hl="ja">) are mentioned.

[0912] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0913] [Second embodiment]

[0914] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0915] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0916] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0917] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0918] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0919] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0920] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0921] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0922] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0923] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0924] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0925] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0926] "Example 1"

[0927] As one embodiment of the present invention, a task management application is provided. This application has a function of converting abstract tasks input by a user into specific actions and deadlines. Specifically, when a user inputs an abstract task such as "manage the progress of a project," the application converts this into a specific action such as "list each task of the project and set a deadline for each."

[0928] "Example 2"

[0929] Additionally, one embodiment of the present invention provides the ability to manage the converted actions. Specifically, the application sorts the actions according to the due date set by the user, displaying them in order of the nearest due date. When the user completes an action, it is removed from the list and the remaining incomplete actions are displayed.

[0930] "Example 3"

[0931] In addition, one embodiment of the present invention provides a function for periodically presenting an action list to the user. Specifically, the application notifies the user of incomplete action lists at a set time (e.g., 9:00 a.m. every morning). This allows the user to always keep track of their tasks and progress them efficiently.

[0932] "Example 4"

[0933] Furthermore, one embodiment of the present invention provides a function for automatically executing simple actions. Specifically, an application automatically executes simple actions such as "send an email" or "set a reminder." This allows the user to progress with tasks without any effort.

[0934] The processing flow of each embodiment will be described below.

[0935] "Example 1"

[0936] Step 1: The user inputs an abstract task into the application: "Manage the progress of a project."

[0937] Step 2: The application analyzes the input task and converts it into a specific action: "List each task in the project and set a due date for each one." Step 3: The converted specific action is added to the task list in the application.

[0938] "Example 2"

[0939] Step 1: The application reads the due date set for each action in the task list.

[0940] Step 2: Sort the actions by their due date and view the sorted task list.

[0941] Step 3: If the user completes an action, it is removed from the list and the incomplete actions are displayed.

[0942] "Example 3"

[0943] Step 1: The user sets the time (for example, 9:00 every morning) for presenting the action list on the application's settings screen.

[0944] Step 2: When the set time is up, the application will notify the user of the incomplete action list.

[0945] "Example 4"

[0946] Step 1: The user adds simple actions such as "send an email" or "set a reminder" to the task list.

[0947] Step 2: The application will perform these simple actions automatically.

[0948] Example 1

[0949] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0950] Conventional task management systems have the drawback of making efficient task management difficult because users have to convert abstract tasks into concrete actions, which is time-consuming. Furthermore, they lack the functionality to properly manage tasks entered by users and provide regular feedback, making it difficult to grasp the progress of tasks.

[0951] The identification process by the identification processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means. In this invention, the server includes means for converting abstract tasks into specific actions and due dates, means for managing the converted actions, means for periodically presenting an action list to the user, means for automatically executing simple actions, means for converting abstract tasks into specific actions using a generative AI model, means for transmitting tasks input from a user terminal to the server, means for transmitting specific actions generated from the server to the user terminal, and means for displaying the specific actions on the user terminal. This allows the user to simply input an abstract task, which is converted into specific actions and due dates, enabling efficient task management.

[0952] An "abstract task" is a general goal or objective without clearly defined specific actions or deadlines.

[0953] "Concrete actions" refer to the clear, concrete tasks or steps required to accomplish an abstract task.

[0954] A "deadline" refers to the deadline by which a particular task or action should be completed.

[0955] A "generative AI model" refers to an algorithm or system that uses artificial intelligence technology to analyze input data and generate appropriate output.

[0956] "User terminal" refers to a device such as a computer or smartphone that can be directly operated by a user.

[0957] A "server" refers to a computer system that communicates with user terminals via a network and processes and stores data.

[0958] A "prompt" is a piece of text containing instructions or questions to a generative AI model to perform a specific task.

[0959] An "action list" refers to a list of specific actions organized in a list format.

[0960] "Feedback" refers to information provided to a user about the progress or results of a task or action.

[0961] This invention is a system that realizes efficient task management by converting abstract tasks input by a user into specific actions and deadlines using a generative AI model. Specific embodiments of this system are described below.

[0962] Hardware and software used

[0963] Hardware: Server, user terminal (PC, smartphone)

[0964] Software: Task management applications, generative AI models (e.g., GPT-4)

[0965] System Overview

[0966] 1. A user launches a task management application and enters an abstract task, for example, "Manage the progress of a project."

[0967] 2. The device receives this input and sends it to the server.

[0968] 3. The server passes the received abstract task to a generative AI model, which generates prompts to convert the abstract task into concrete actions and deadlines.

[0969] 4. The generative AI model analyzes the abstract tasks input and converts them into specific actions and deadlines, such as "list each task in a project and set a deadline for each one."

[0970] 5. The server receives the generated specific actions and deadlines and sends them to the user's terminal.

[0971] 6. The device displays the specific actions and deadlines received to the user.

[0972] Specific examples

[0973] A user enters "Manage project progress" into a task management application.

[0974] The terminal sends this input to the server.

[0975] The server sends the prompt "Manage the progress of the project" to the generative AI model.

[0976] The generative AI model analyzes this prompt and converts it into a specific action: "List each task in the project and set a due date for each."

[0977] The server transmits the generated specific action to the user terminal.

[0978] The device displays specific actions to the user, such as "List each task in the project and set a due date for each."

[0979] Prompt Sentence Examples

[0980] Convert the abstract task of "managing the progress of a project" into concrete action.

[0981] Break down the task of "managing the progress of a project" into specific steps.

[0982] This system allows users to simply input abstract tasks, which are then converted into specific actions and deadlines, enabling efficient task management. Furthermore, by using a generative AI model, task specificity is automated, reducing the burden on users.

[0983] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0984] Step 1:

[0985] A user launches a task management application and inputs an abstract task. The user opens the application on a PC or smartphone and inputs an abstract task, such as "manage the progress of a project," into the input field. The input data is in text format and is saved on the user's device.

[0986] Step 2:

[0987] The terminal sends the input task to the server. The terminal receives the task data entered by the user and sends it to the server using an HTTP POST request. The input data is task data in text format and is sent to the server.

[0988] Step 3:

[0989] The server passes the received task to the generative AI model. The server analyzes the received task data and generates a prompt to be passed to the generative AI model. For example, the task "Manage the progress of a project" is converted into a prompt such as "Please convert this task into a specific action." The input data is the task data in text format, and the output data is the prompt.

[0990] Step 4:

[0991] A generative AI model converts abstract tasks into specific actions and deadlines. A generative AI model receives a prompt and converts abstract tasks into specific actions and deadlines. For example, it converts them into specific actions such as "List each task in the project and set a deadline for each." The input data is the prompt, and the output data is specific actions and deadlines.

[0992] Step 5:

[0993] The server sends the generated specific actions and deadlines to the terminal. The server sends the specific actions and deadlines received from the generative AI model to the terminal as an HTTP response. The input data are the specific actions and deadlines, and the output data is the HTTP response.

[0994] Step 6:

[0995] The terminal displays specific actions and deadlines to the user. The terminal displays specific actions and deadlines received from the server to the user. For example, a specific action such as "List each task in the project and set a deadline for each" is displayed on the application screen. The input data are specific actions and deadlines, and the output data is the information displayed to the user.

[0996] In this way, abstract tasks entered by the user are converted into concrete actions and deadlines, enabling efficient task management.

[0997] (Application example 1)

[0998] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0999] With conventional task management systems, it is difficult to convert abstract tasks into concrete actions and deadlines, and efficient operation is required, especially in task management within factories. Furthermore, converting abstract tasks entered by users into concrete actions requires a lot of manual work, which takes time and effort. Furthermore, there are no task management systems that utilize generative AI models, making it difficult to automate task management within factories.

[1000] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1001] In this invention, the server includes means for converting abstract tasks into specific actions and deadlines, means for managing the converted actions, means for periodically presenting an action list to the user, means for automatically executing simple actions, means for converting abstract tasks into specific actions using a generative AI model, and means for automating task management within the factory. This makes it possible to efficiently convert abstract tasks entered by the user into specific actions and automate task management within the factory.

[1002] An "abstract task" is a general goal or objective without clearly defined specific actions or deadlines.

[1003] "Specific actions" refer to the concrete steps or tasks required to accomplish an abstract task.

[1004] A "deadline" refers to the deadline by which a particular task or action should be completed.

[1005] A "generative AI model" refers to an algorithm or system that uses artificial intelligence technology to generate new information or results from input data.

[1006] "Factory task management" refers to the efficient planning, execution, and monitoring of various tasks and processes that take place within a factory.

[1007] "Automation" refers to minimizing human intervention and enabling machines and systems to operate autonomously.

[1008] A "server" refers to a computer system that provides services to other computers on a network.

[1009] "User" refers to an individual or organization that uses a system or application.

[1010] An "action list" is a list of specific actions needed to accomplish a particular task or goal.

[1011] "Feedback" refers to information that provides information about the performance and results of a system or process, allowing for improvements and adjustments.

[1012] As an embodiment of the present invention, a system for automating task management within a factory is constructed. A specific embodiment of the system is shown below.

[1013] System configuration

[1014] This system consists of a server, factory robots, and user terminals. The server uses a generative AI model to convert abstract tasks into specific actions and deadlines. The factory robots execute the specific actions received from the server. The user terminal provides an interface for users to input abstract tasks and receive feedback.

[1015] Program processing

[1016] The server receives abstract tasks input by users and uses a generative AI model to convert them into specific actions and deadlines. The specific actions are sent to robots in the factory, which then execute them. The server monitors the robots' execution and provides feedback to the user.

[1017] Hardware and software used

[1018] Hardware: Factory robots, user devices (PCs, tablets, smartphones)

[1019] Software: Python, OpenAI API, generative AI models

[1020] Data processing and calculation

[1021] The server receives abstract tasks entered by the user in text format and inputs them into a generative AI model. The generative AI model converts the abstract tasks into specific actions and deadlines and returns the results to the server. The server then sends the converted specific actions to robots in the factory, which then execute them. The server monitors the robots' execution status and provides feedback to the user.

[1022] Specific examples

[1023] For example, if a user inputs an abstract task such as "improving production line efficiency," the generative AI model will output a specific task such as the following:

[1024] Specific examples

[1025] Identify bottlenecks on each production line

[1026] Propose improvements to eliminate bottlenecks

[1027] Create an implementation plan for improvements

[1028] Monitor the progress of each improvement measure

[1029] Prompt Sentence Examples

[1030] Convert the following abstract tasks into concrete actions and deadlines: Increase the efficiency of the production line

[1031] In this way, task management within the factory can be efficiently automated.

[1032] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1033] Step 1:

[1034] A user inputs an abstract task using a terminal.

[1035] Input: Abstract task (e.g., "Improve the efficiency of the production line")

[1036] Output: Abstract tasks are sent to the server

[1037] Specific operation: The user inputs the task through the terminal interface and presses the send button.

[1038] Step 2:

[1039] The server receives the abstract task and sends a prompt to the generative AI model.

[1040] Input: Abstract task

[1041] Output: The prompt sent to the generative AI model

[1042] Specific operation: The server receives the abstract task, generates a prompt sentence, and sends it to the generative AI model.

[1043] Example prompt: "Translate the following abstract task into concrete actions and due dates: Increase the efficiency of the production line."

[1044] Step 3:

[1045] A generative AI model parses prompts and converts them into specific actions and deadlines.

[1046] Input: prompt statement

[1047] Output: Specific actions and due dates

[1048] Concrete Actions: The generative AI model parses the prompt and converts the abstract task into concrete actions and deadlines.

[1049] Examples: "Identify bottlenecks on each production line," "Propose improvements to eliminate bottlenecks," "Draw an implementation plan for the improvements," and "Monitor the progress of each improvement."

[1050] Step 4:

[1051] The server receives the output from the generative AI model and sends specific actions to the robots in the factory.

[1052] Input: Specific actions and due dates

[1053] Output: Specific actions sent to robots in the factory

[1054] Specific actions: The server sends the specific actions and deadlines received from the generative AI model to the robots in the factory.

[1055] Step 5:

[1056] Robots in factories perform specific actions.

[1057] Input: Specific action

[1058] Output: Action execution result

[1059] Specific action: The robot in the factory executes the specific action received and performs the work.

[1060] Step 6:

[1061] The server monitors the robot's performance and provides feedback to the user.

[1062] Input: Robot execution status

[1063] Output: Feedback provided to the user

[1064] Specific operation: The server monitors the robot's execution status and provides feedback to the user on progress and problems.

[1065] Example 2

[1066] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1067] Conventional task management systems lack the ability to sort actions based on user-set due dates or automatically remove completed actions from the list, making it difficult for users to efficiently manage their tasks. Furthermore, they lack the ability to display only incomplete actions, making it difficult for users to distinguish between completed and incomplete tasks.

[1068] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1069] In this invention, the server includes means for converting abstract tasks into specific actions and deadlines, means for managing the converted actions, means for periodically presenting a list of actions to the user, means for automatically executing simple actions, means for sorting actions based on deadlines set by the user, means for deleting an action from the list when the user completes it, and means for displaying only incomplete actions, thereby enabling the user to efficiently manage tasks and easily distinguish between completed and incomplete tasks.

[1070] An "abstract task" is a general task or goal without specific actions or deadlines.

[1071] A "specific action" refers to a specific task or procedure that a user needs to perform.

[1072] "Deadline" refers to the deadline set by the user for completing an action.

[1073] "Means for conversion" refers to a method or device for converting abstract tasks into concrete actions and deadlines.

[1074] "Means for managing" refers to a method or device for storing, tracking, and updating the translated actions.

[1075] "Presenting means" refers to a method or device for displaying the action list to the user.

[1076] "Automatic execution means" refers to a method or device for performing a simple action without user intervention.

[1077] "Means for sorting" refers to a method or device for ordering actions based on user-set deadlines.

[1078] "Means for deleting" refers to a method or device that allows a user to remove a completed action from the list.

[1079] "Means for displaying" refers to a method or device for showing only the incomplete actions to the user.

[1080] MODE FOR CARRYING OUT THE INVENTION

[1081] The present invention is a system for managing actions based on deadlines set by a user and for efficiently completing tasks. A specific embodiment of this system is described below.

[1082] Hardware and software used

[1083] Hardware: The server uses a high-performance cloud server (e.g., a virtual server from a cloud service provider).

[1084] Software: The application is developed in Python and uses MySQL for database management. The front-end is built with JavaScript libraries and the back-end uses a web application framework.

[1085] System Overview

[1086] The system converts abstract tasks entered by users into concrete actions and due dates, and manages them. The server sorts the actions based on the due dates set by the user, displaying them in order of the nearest due date. When the user completes an action, it removes it from the list, and only uncompleted actions are displayed.

[1087] Data processing and calculation

[1088] 1. Data entry: The user enters an action and its due date.

[1089] 2. Data storage: The server stores the entered data in a MySQL database.

[1090] 3. Data sorting: The server retrieves the actions from the database and sorts them based on their due date.

[1091] 4. Data display: Send the sorted actions to the front end and display them to the user.

[1092] 5. Data Update: When the user completes an action, the server removes it from the database and re-sorts and displays the incomplete actions.

[1093] Specific examples

[1094] Example 1: Adding and displaying an action

[1095] A user adds an action called "Submit a Report" with a due date of "2023-10-15". The server stores this information in a database and displays it along with other actions, sorted by due date.

[1096] Example 2: Completing an action

[1097] When the user completes the "report submission," the server removes this action from the database and re-sorts and displays the incomplete actions.

[1098] Prompt Sentence Examples

[1099] "Your application should sort actions based on the due date set by the user, displaying them in order of closest due date. When the user completes an action, you should also add the ability to remove it from the list and display only the incomplete actions."

[1100] By inputting this prompt sentence into a generative AI model, a program that outlines the above system can be generated.

[1101] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1102] Step 1:

[1103] The user enters the action

[1104] The user uses the terminal to input an action and its due date into the input form of the application. The input data is the content and due date of the action.

[1105] Step 2:

[1106] The device sends the action to the server

[1107] The terminal sends the entered action and due date to the server as an HTTP request. This request includes the action content and due date. The input is the action and due date entered by the user, and the output is the HTTP request sent to the server.

[1108] Step 3:

[1109] The server saves the action to the database

[1110] The server stores the received action and due date in a MySQL database. Specifically, it adds a new record to the database using an INSERT statement. The input is the HTTP request and the output is the record stored in the database.

[1111] Step 4:

[1112] The server sorts the actions by due date

[1113] The server retrieves all actions from the database using a SELECT statement and sorts them by due date using the SQL ORDER BY clause. The input is the action list retrieved from the database, and the output is the sorted action list.

[1114] Step 5:

[1115] The server sends the sorted actions to the terminal.

[1116] The server sends the sorted action list to the terminal in JSON format, so that the terminal can receive the latest action list. The input is the sorted action list, and the output is the JSON data sent to the terminal.

[1117] Step 6:

[1118] The device displays the action

[1119] The terminal displays the received action list in the user interface. The actions are listed in order of their due date. The input is JSON data received from the server, and the output is the action list displayed in the user interface.

[1120] Step 7:

[1121] The user completes the action

[1122] When the user completes an action, they mark it as complete in the application's interface. The input is the user's action, and the output is the action marked as complete.

[1123] Step 8:

[1124] The device notifies the server of the completed action

[1125] The device sends information about the completed action to the server as an HTTP request, which includes the ID of the completed action. The input is the action marked as completed, and the output is the HTTP request sent to the server.

[1126] Step 9:

[1127] The server removes completed actions from the database

[1128] The server uses the received action ID to delete the corresponding action from the database using a DELETE statement. The input is the HTTP request, and the output is the record deleted from the database.

[1129] Step 10:

[1130] The server resorts the outstanding actions

[1131] The server retrieves the incomplete actions from the database again using the SELECT statement and sorts them by due date. The input is the list of incomplete actions retrieved from the database, and the output is the sorted list of incomplete actions.

[1132] Step 11:

[1133] The server sends the updated action list to the device.

[1134] The server sends the updated list of pending actions to the terminal in JSON format. The input is the sorted list of pending actions, and the output is the JSON data sent to the terminal.

[1135] Step 12:

[1136] The device displays the updated action list

[1137] The terminal receives the updated action list and displays it again in the user interface, allowing the user to see the latest pending actions. The input is the JSON data received from the server, and the output is the updated action list displayed in the user interface.

[1138] (Application example 2)

[1139] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1140] Task management in logistics centers is difficult because multiple tasks occur simultaneously and each has a different deadline. Furthermore, if the information is not reflected immediately after a worker completes a task, there is a risk of unnecessary work being done. Furthermore, if task priorities are not clearly defined, there is a risk that important tasks will be put off.

[1141] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1142] In this invention, the server includes means for converting abstract tasks into specific actions and deadlines, means for managing the converted actions, means for periodically presenting a list of actions to the user, means for automatically executing simple actions, means for sorting the actions based on deadlines and displaying them in order of the nearest deadline, and means for deleting an action from the list when the user completes it and displaying uncompleted actions. This improves the efficiency of task management in the logistics center and enables important tasks to be appropriately prioritized.

[1143] An "abstract task" is a general task or goal without clearly defined specific actions or deadlines.

[1144] "Specific actions" are the concrete steps or tasks required to accomplish an abstract task.

[1145] A "deadline" is the date by which a particular task or action should be completed.

[1146] A "conversion means" is a method or device for converting abstract tasks into concrete actions and deadlines.

[1147] "Means for managing" refers to the methods and devices for tracking the converted actions and monitoring their progress.

[1148] A "presentation means" refers to a method or device for displaying the action list to the user.

[1149] An "automatic execution means" is a method or device for automatically executing a particular action without user intervention.

[1150] A "means for sorting" is a method or device for sorting actions based on due date.

[1151] "Means for displaying" refers to a method or device for visually indicating the sorted actions to the user.

[1152] "Means for removing the action from the list when completed" refers to a method or device for removing an action from the list when the user completes the action.

[1153] The "means for displaying incomplete actions" refers to a method or device for displaying to the user only the actions that are not completed.

[1154] A system for carrying out the present invention is intended to improve the efficiency of task management in a logistics center. A specific embodiment of this system will be described below.

[1155] System configuration

[1156] The system consists of a server, worker devices (smartphones or smart glasses), and a user interface. The server plays a central role in task management, while the device is used by workers to check tasks and report their completion.

[1157] Program processing

[1158] The server manages tasks using the following means:

[1159] 1. A way to translate abstract tasks into concrete actions and deadlines

[1160] The server converts abstract tasks entered by the logistics center manager into specific actions and deadlines. For example, it converts an abstract task such as "check inventory" into a specific action such as "check inventory by October 10th."

[1161] 2. A way to manage the converted actions

[1162] The server stores the converted actions in a database and tracks the progress of each action, including information such as the action's due date, who is responsible for it, and its status.

[1163] 3. A way to periodically present the user with a list of actions

[1164] The server periodically sends the action list to the worker's device and displays it through a user interface, allowing the worker to see the current tasks and their due dates.

[1165] 4. Automating simple actions

[1166] The server automatically executes simple actions when certain conditions are met, such as automatically issuing a replenishment command when inventory falls below a certain level.

[1167] 5. A way to sort actions based on due date, with the most recent due first

[1168] The server sorts the action list based on due date and displays it on the worker's terminal in order of the nearest due date, allowing the worker to process the highest priority tasks first.

[1169] 6. When a user completes an action, a way to remove it from the list and display incomplete actions.

[1170] When a worker reports completion of an action via a terminal, the server removes that action from the list and displays only incomplete actions.

[1171] Hardware and software used

[1172] Hardware: Servers, smartphones, smart glasses

[1173] Software: Python (programming language), database management system (e.g., MySQL), user interface (e.g., React Native)

[1174] Specific examples

[1175] A logistics center worker puts on smart glasses and launches a task management application. The application sorts today's tasks by due date and displays those that need to be completed earliest. When the worker completes the "stock shelves" task, it disappears from the smart glasses display and the next task, "prepare for shipment," appears.

[1176] Prompt Sentence Examples

[1177] Develop an application that uses smart glasses to help logistics center workers efficiently manage their daily tasks. Tasks are sorted by due date and displayed in order of closest due date. When a worker completes a task, it is automatically removed from the list, and incomplete tasks continue to be displayed. Write the program using Python.

[1178] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1179] Step 1:

[1180] The server receives abstract tasks from the logistics center manager. The input is the task outline entered by the manager, and the output is the task converted into specific actions and due dates. The server analyzes the task content and generates specific actions and due dates.

[1181] Step 2:

[1182] The server saves the converted actions in a database. The input is the specific action and due date, and the output is the task information saved in the database. The server records information such as the action details, due date, and responsible person in the database.

[1183] Step 3:

[1184] The server periodically sends an action list to the worker's terminal. The input is task information stored in the database, and the output is an action list displayed on the worker's terminal. The server acquires the task information and presents it to the worker through a user interface.

[1185] Step 4:

[1186] The server automatically executes simple actions when certain conditions are met. The input is task information that meets the conditions, and the output is the result of the automatically executed action. For example, the server may automatically instruct replenishment when inventory falls below a certain level.

[1187] Step 5:

[1188] The server sorts the action list based on the due date and displays it on the worker's terminal in order of the nearest due date. The input is the task information stored in the database, and the output is the sorted action list. The server sorts the list based on the due date of the task, displaying the highest priority tasks at the top.

[1189] Step 6:

[1190] When a user completes an action, the information is sent to the server via the terminal. The input is the reported task information, and the output is an updated action list. The server then removes the completed task from the list and displays only the incomplete tasks.

[1191] Step 7:

[1192] The server updates the action list based on the user's actions. The input is the user's action data, and the output is the latest action list. The server monitors the user's progress and updates the task priority and content as needed.

[1193] Example 3

[1194] Next, a description will be given of Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1195] Conventional task management systems require users to manually manage tasks and check their progress, making efficient task management difficult. They also lack the functionality to automatically execute simple actions, which increases the workload for users. Furthermore, they lack sufficient notification functions to periodically check task progress, which increases the risk of users forgetting to complete tasks.

[1196] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[1197] In this invention, the server includes means for converting abstract tasks into specific actions and deadlines, means for managing the converted actions, means for periodically presenting an action list to the user, means for automatically executing simple actions, means for the user to input tasks, means for the server to save the tasks in a database, means for the server to periodically check the tasks, means for the server to notify the user of incomplete tasks, and means for the server to automatically execute simple actions. This allows the user to efficiently manage tasks and progress them without hassle.

[1198] An "abstract task" is a general task or goal without specific actions or deadlines.

[1199] "Specific actions" refer to concrete tasks or procedures that transform abstract tasks into executable forms.

[1200] A "deadline" refers to the date and time when a task or action should be completed.

[1201] An "action list" is a list of specific actions that a user should perform.

[1202] "User" refers to an individual or organization that uses the system to manage tasks.

[1203] A "server" is a computer system that serves as the core of a task management system and stores and processes data.

[1204] A "database" refers to a system for organizing and storing information about tasks and actions.

[1205] "Notification" refers to a message sent by the server to inform the user of the progress of a task or an uncompleted task.

[1206] "Simple actions" refer to tasks that can be automated relatively easily, such as sending emails or setting reminders.

[1207] A "reminder" refers to a notification that reminds a user to perform a specific task or action.

[1208] MODE FOR CARRYING OUT THE INVENTION

[1209] The present invention is a system for improving the efficiency of task management for users, which is realized through the interaction between a server, a terminal, and a user. A specific embodiment of this system will be described below.

[1210] Hardware and software used

[1211] Hardware: Servers, user devices (PCs, smartphones, etc.)

[1212] Software: Task management applications, notification systems, email sending systems, reminder setting systems

[1213] Data processing and calculation

[1214] 1. The user enters a task

[1215] The user uses the terminal to open a task management application.

[1216] The user enters a new task and enters the required information (task name, due date, reminder settings, etc.).

[1217] Example: A user enters a task "Prepare for a meeting" and sets the due date to "Tomorrow at 10:00 AM."

[1218] 2. The server saves the task in the database

[1219] After the user inputs the task, the terminal sends the information to the server.

[1220] The server stores the received task information in a database.

[1221] Example: The server saves the task "Prepare for meeting" in the database.

[1222] 3. The server periodically checks for tasks

[1223] The server checks the database at a set time (for example, 9:00 every morning) and retrieves any uncompleted tasks.

[1224] The server lists the acquired incomplete tasks.

[1225] Example: Every morning at 9am the server checks the database and lists all outstanding tasks.

[1226] 4. The server notifies the user of outstanding tasks

[1227] The server notifies the user's terminal of the list of uncompleted tasks.

[1228] The user receives a notification on the device and checks the incomplete tasks.

[1229] Example: The server sends a notification to the user's smartphone saying, "Good morning. You have uncompleted tasks. Please check them."

[1230] 5. The server automatically executes simple actions

[1231] The server periodically checks simple actions set by the user (e.g., "send email" or "set reminder").

[1232] When the conditions are met, the server automatically calls an email sending system or a reminder setting system to perform an action.

[1233] Example: If a user sets a task to "set a reminder every Monday," the server will call the reminder setting system every Monday and automatically set the reminder.

[1234] Specific examples

[1235] Presenting an action list

[1236] Every morning at 9:00, the server retrieves the user's uncompleted tasks from the database and notifies the user's smartphone.

[1237] For example: "Good morning. You have some uncompleted tasks. Please take a look."

[1238] Automatic execution of simple actions

[1239] If a user sets a task to "set a reminder every Monday," the server will call the reminder setting system every Monday and automatically set the reminder.

[1240] For example: "I've set a reminder. Our next meeting is on Monday at 10am."

[1241] Example prompts for generative AI models

[1242] "Please create a program that notifies the user of their incomplete tasks every morning at 9am."

[1243] "Create a program that automatically executes simple actions set by the user."

[1244] In this way, the user can efficiently manage his or her tasks and progress the tasks without any hassle. The flow of the specific processing in the third embodiment will be described with reference to FIG.

[1245] Step 1:

[1246] The user enters a task

[1247] Input: The user uses a device to open a task management application and enter a new task.

[1248] Data processing: The application receives information entered by the user, such as task name, deadline, and reminder settings.

[1249] Output: The terminal sends the input task information to the server.

[1250] Specific behavior: The user clicks the "Add new task" button, enters the task name "Prepare for meeting", sets the due date to "Tomorrow at 10:00 AM", and clicks the "Save" button.

[1251] Step 2:

[1252] The server saves the task in a database

[1253] Input: Task information sent from the terminal.

[1254] Data processing: The server analyzes the task information received and converts it into a format suitable for saving in the database.

[1255] Output: The server saves the task information to the database and sends a confirmation message to the terminal.

[1256] Specific operation: The server saves the task "Prepare for meeting" to the database and sends a confirmation message "Task saved successfully" to the terminal.

[1257] Step 3:

[1258] The server periodically checks for tasks

[1259] Input: Task information stored in the database.

[1260] Data processing: The server queries the database at a set time (for example, every morning at 9:00) to retrieve incomplete tasks.

[1261] Output: List of open tasks retrieved by the server.

[1262] What it does: Every morning at 9am, the server checks the database and lists all uncompleted tasks.

[1263] Step 4:

[1264] The server notifies the user of outstanding tasks

[1265] Input: A list of open tasks.

[1266] Data processing: The server converts the list of incomplete tasks into a format that can be sent to the user's device.

[1267] Output: The server notifies the user of the list of uncompleted tasks on their device.

[1268] Specific behavior: The server sends a notification to the user's smartphone saying, "Good morning. You have uncompleted tasks. Please check them."

[1269] Step 5:

[1270] The server automatically executes simple actions

[1271] Input: A simple action set by the user (e.g., "send email" or "set reminder").

[1272] Data processing: When the conditions are met, the server automatically calls an email sending system or reminder setting system to execute an action.

[1273] Output: The server performs a simple action and notifies the user of the result.

[1274] Specific behavior: If a user sets a task to "set a reminder every Monday," the server will call the reminder setting system every Monday and automatically set the reminder.

[1275] (Application example 3)

[1276] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1277] Robot maintenance and task management in factories is often done manually, which is inefficient. Even simple actions like ordering necessary parts and setting maintenance reminders must be done manually, placing a heavy burden on workers. This can lead to missed or delayed tasks, reducing the efficiency of factory operations.

[1278] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[1279] In this invention, the server includes means for converting abstract tasks into specific actions and deadlines, means for managing the converted actions, means for periodically presenting a list of actions to a user, means for automatically executing simple actions, means for periodically presenting a list of maintenance and work tasks for a factory robot, means for automatically setting maintenance reminders, means for automatically sending an order email for necessary parts, and means for automatically notifying an administrator of the results of the robot's self-diagnosis. This automates the management of factory robot maintenance and work tasks, reduces the burden on workers, prevents omissions and delays in tasks, and improves factory operation efficiency.

[1280] An "abstract task" is a general goal or objective without clear specific actions or steps.

[1281] A "specific action" refers to a specific task or operation that involves specific steps or actions.

[1282] A "deadline" refers to the deadline by which a particular task or action should be completed.

[1283] "Means for conversion" refers to a method or device for converting abstract tasks into concrete actions and deadlines.

[1284] "Means for managing" refers to a method or apparatus for tracking the translated actions and monitoring progress.

[1285] "Means for periodically presenting a list of actions to a user" refers to a method or device for notifying a user of uncompleted tasks or actions at set time intervals.

[1286] "Means for automatically performing simple actions" refers to a method or device for automatically performing specific simple tasks or operations to save the user time.

[1287] A "factory robot" refers to an automated mechanical device designed to perform work or maintenance in a factory.

[1288] The "means for presenting a list of maintenance and work tasks" refers to a method or device for displaying to a factory robot the maintenance and work tasks that need to be performed periodically.

[1289] "Means for automatically setting maintenance reminders" refers to a method or device for automatically setting notifications when factory robots require maintenance.

[1290] "Means for automatically sending an order email for necessary parts" refers to a method or device for automatically sending an order email when necessary parts are in short supply.

[1291] "Means for automatically notifying the manager of the results of a robot's self-diagnosis" refers to a method or device for a factory robot to perform a self-diagnosis and automatically notify the manager of the results.

[1292] As an embodiment of the present invention, we will explain an example of a "Factory Robot Task Manager" system installed on a factory robot. This system automates the maintenance and task management of factory robots, reduces the burden on workers, and improves factory operation efficiency.

[1293] System Program

[1294] The system is implemented using Python, specifically using the following libraries:

[1295] schedule library: periodic task execution

[1296] smtplib library: Sending email

[1297] Program processing explanation

[1298] The server processes and calculates data using the following hardware and software.

[1299] Hardware: Factory robot displays, internet connectivity

[1300] Software: Python, schedule library, smtplib library

[1301] The server displays a list of uncompleted maintenance and work tasks on the factory robot's display every morning at 9:00, making it easier for users to understand the tasks for the day. In addition, at 9:05, an order email for necessary parts is automatically sent, preventing work delays due to a parts shortage.

[1302] Specific examples

[1303] For example, every morning at 9:00, the tasks "Replace part A" and "Cleaning" are displayed on the robot's display. The user can check these and proceed with the tasks in order of priority. In addition, an order email for part A is automatically sent at 9:05, so the user does not have to manually place the order.

[1304] Prompt Sentence Examples

[1305] "Using the Factory Robot Task Manager, please create a program that displays a list of uncompleted tasks every morning at 9:00 and automatically sends an email to order the necessary parts at 9:05."

[1306] In this way, maintenance of factory robots and management of work tasks can be automated, reducing the burden on workers and improving factory operating efficiency.

[1307] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1308] Step 1:

[1309] The server sets a trigger for task notification every morning at 9:00 using the schedule library. The input is a task list and the current time, and the output is an instruction to display the task list. Specifically, the server retrieves the task list and confirms that the current time is 9:00.

[1310] Step 2:

[1311] The server displays the task list on the display of the factory robot. The input is the task list, and the output is the task list that is displayed on the display. Specifically, the server formats the contents of the task list and sends it to the display.

[1312] Step 3:

[1313] The server uses the schedule library to set a trigger for the automatic execution of a simple action every morning at 9:05. The input is the current time, and the output is an instruction to execute the simple action. Specifically, the server checks that the current time is 9:05.

[1314] Step 4:

[1315] The server automatically sets maintenance reminders. The input is the maintenance schedule, and the output is the generated reminder settings. Specifically, the server checks the maintenance schedule and sets the reminder.

[1316] Step 5:

[1317] The server automatically sends an order email for the required parts. The input is the parts inventory information and the supplier's email address, and the output is an order email. Specifically, the server checks the inventory information, and if the required parts are in short supply, it generates and sends an order email.

[1318] Step 6:

[1319] The server automatically notifies the administrator of the robot's self-diagnosis results. The inputs are the self-diagnosis results and the administrator's contact information, and the output is a notification message. Specifically, the server obtains the self-diagnosis results and sends a notification message to the administrator.

[1320] In this way, maintenance of factory robots and management of work tasks are automated, reducing the burden on workers and improving factory operating efficiency.

[1321] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1322] "Example 1"

[1323] One embodiment of the present invention is a system incorporating an emotion engine. This system recognizes a user's emotion and adjusts task priorities according to that emotion. Specifically, if the system recognizes that the user's emotion is "stress," it increases the priority of tasks related to relaxation. Similarly, if the system recognizes that the user's emotion is "joy," it increases the priority of tasks related to enjoyable activities. In this way, dynamically adjusting task priorities according to the user's emotion allows for task management that takes the user's psychological state into account.

[1324] "Example 2"

[1325] The emotion engine also analyzes the user's facial expressions, tone of voice, and social media posts to recognize the user's emotions. Specifically, it uses a camera and microphone to capture the user's facial expressions and tone of voice and inputs this data into the emotion recognition algorithm. If the user allows it, the content of social media posts can also be used as data for emotion recognition. Based on this data, the emotion engine recognizes the user's current emotional state and adjusts task priorities accordingly.

[1326] "Example 3"

[1327] Furthermore, the emotion engine controls the automatic execution of tasks according to the user's emotional state. Specifically, if it recognizes that the user's emotion is "anger," it temporarily suspends tasks that may further anger the user (for example, automatic replies to emails from a specific person). If it recognizes that the user's emotion is "joy," it executes a task to share the user's joy (for example, automatic posting to social media). In this way, the emotion engine enables the automatic execution of tasks that take the user's emotional state into consideration.

[1328] The processing flow of each embodiment will be described below.

[1329] "Example 1"

[1330] Step 1: The system captures the user's facial expressions and tone of voice using a camera and microphone.

[1331] Step 2: The emotion engine then inputs the captured data into an emotion recognition algorithm to recognize the user's current emotional state.

[1332] Step 3: The emotion engine adjusts the priority of tasks according to the emotion it recognizes. For example, if it recognizes the emotion as "stress," it will increase the priority of tasks related to relaxation.

[1333] "Example 2"

[1334] Step 1: If the user allows it, the system uses the content of social media posts as data for emotion recognition.

[1335] Step 2: The emotion engine inputs the content of the social media post into the emotion recognition algorithm to recognize the user's current emotional state.

[1336] Step 3: The emotion engine adjusts the priority of tasks according to the recognized emotion. For example, if the emotion is recognized as "joy," it increases the priority of tasks related to enjoyable activities. "Example 3"

[1337] Step 1: The emotion engine recognizes the user's emotional state.

[1338] Step 2: The emotion engine controls the automatic execution of tasks according to the recognized emotion. For example, if the emotion is recognized as "anger," it temporarily stops tasks that may further anger the user.

[1339] Step 3: If the emotion is recognized as "joy," a task is performed to share the user's joy.

[1340] Example 1

[1341] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1342] Conventional task management systems have difficulty converting abstract tasks entered by users into concrete actions and deadlines, and lack the functionality to dynamically adjust task priorities based on the user's emotions. This poses a challenge in achieving efficient task management that takes the user's psychological state into account.

[1343] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1344] In this invention, the server includes means for converting abstract tasks into specific actions and deadlines, means for managing the converted actions, means for periodically presenting an action list to the user, means for automatically executing simple actions, means for recognizing the user's emotions and adjusting task priorities in accordance with the emotions, and means for dynamically adjusting task priorities based on the emotions, thereby enabling efficient task management that takes the user's psychological state into consideration.

[1345] An "abstract task" is a general goal or objective without clearly defined specific actions or deadlines.

[1346] "Specific actions" refer to the concrete procedures or steps required to accomplish an abstract task.

[1347] A "deadline" refers to the date and time by which a particular task or action should be completed.

[1348] "Translation means" refers to methods and techniques for converting abstract tasks into concrete actions and deadlines.

[1349] "Management tools" refers to the methods and techniques used to organize and track the specific actions and deadlines that are translated.

[1350] "Presentation means" refers to the method or technique for displaying the action list to the user.

[1351] "Automatic execution means" refers to a method or technology for automatically executing a specific action without user intervention.

[1352] "Means for recognizing emotions" refers to methods and techniques for detecting and identifying a user's emotions.

[1353] "Means for adjusting priority" refers to methods and techniques for changing the importance or urgency of a task.

[1354] "Dynamic adjustment means" refers to methods and techniques for changing task priorities in real time.

[1355] MODE FOR CARRYING OUT THE INVENTION

[1356] This system converts abstract tasks entered by users into concrete actions and deadlines, and dynamically adjusts task priorities according to the user's emotions. This system operates in cooperation with a server, a terminal, and a user.

[1357] Hardware and software used

[1358] Server: Use a server with high-performance computing power, specifically a cloud-based server (e.g., Amazon Web Services, Microsoft Azure).

[1359] Terminal: A device that is operated by a user. Examples include smartphones, tablets, and PCs.

[1360] Software: We use "spaCy" and "NLTK" as natural language processing (NLP) engines, and "IBM Watson" and "Microsoft Azure Text Analytics" as sentiment analysis algorithms.

[1361] Program processing

[1362] 1. The user enters a task

[1363] The user inputs an abstract task into an input field on the terminal, for example, "Manage the progress of a project."

[1364] 2. The device sends the input to the server

[1365] The terminal sends the task input by the user to the server using an HTTP request.

[1366] 3. The server analyzes the task

[1367] The server passes the received task to a natural language processing (NLP) engine to analyze the task, for example, using "spaCy" or "NLTK" to break down the abstract task into concrete steps.

[1368] 4. The server generates a specific action

[1369] The server generates specific actions based on the analysis results, such as "listing each task in the project and setting a due date for each."

[1370] 5. The server sends the generated results to the terminal.

[1371] The server sends the generated specific action to the terminal using an HTTP response.

[1372] 6. The device displays feedback to the user

[1373] The device displays the specific actions received to the user, for example, "Task 1: Proposal writing (Deadline: October 10, 2023), Task 2: Team meeting (Deadline: October 12, 2023)."

[1374] 7. User inputs emotion

[1375] A user inputs their emotion into an input field of the system that incorporates the emotion engine, for example, by inputting "stress."

[1376] 8. The device sends input to the server

[1377] The terminal transmits the emotion input by the user to the server using an HTTP request.

[1378] 9. Server-based emotion recognition

[1379] The server then passes the received emotions to a sentiment analysis algorithm, such as IBM Watson or Microsoft Azure Text Analytics, to recognize the emotion.

[1380] 10. The server adjusts task priorities

[1381] The server dynamically adjusts task priorities based on the perceived emotion, for example, if you are feeling "stressed," it will prioritize tasks related to relaxation.

[1382] 11. The server sends the adjustment results to the device

[1383] The server transmits the adjusted task priority to the terminal using an HTTP response.

[1384] 12. The device displays feedback to the user

[1385] The device displays the received adjustment results to the user, for example, "Task 1: Yoga session (priority: high), Task 2: Walk (priority: medium)."

[1386] Specific examples

[1387] User input: "Manage the progress of the project."

[1388] Sending from the device: Send an HTTP request to the server to "Manage the progress of the project"

[1389] Server analysis: Analyze "Manage project progress" using an NLP engine (e.g., spaCy)

[1390] Server generation: Generate a specific action such as "List each task in the project and set a due date for each one."

[1391] Server transmission: Sends the generated results to the terminal via HTTP response

[1392] Display on device: "Task 1: Proposal writing (Due: October 10, 2023), Task 2: Team meeting (Due: October 12, 2023)"

[1393] User input: "Stress"

[1394] Sending the terminal: Send "stress" to the server via HTTP request

[1395] Server recognition: Recognizing "stress" using a sentiment analysis algorithm (e.g., IBM Watson)

[1396] Server tuning: Increase the priority of relaxation-related tasks

[1397] Server transmission: Sends the adjustment results to the device via HTTP response

[1398] Device display: "Task 1: Yoga session (high priority), Task 2: Walk (medium priority)"

[1399] Prompt Sentence Examples

[1400] Prompt: "When the user enters 'Manage project progress,' generate specific actions and due dates."

[1401] Prompt: "If the user types 'stress', how can I increase the priority of relaxation-related tasks?"

[1402] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1403] Program processing flow

[1404] Task management application

[1405] Step 1:

[1406] The user enters a task.

[1407] Input: The user types "Manage project progress" into the input field on the device.

[1408] Specific behavior: The user enters text into the input field and presses the submit button.

[1409] Output: The input task is saved on the device.

[1410] Step 2:

[1411] The device sends input to the server.

[1412] Input: Task data entered by the user.

[1413] Specific operation: The terminal generates an HTTP request and sends the input task data to the server.

[1414] Output: The server receives the task data.

[1415] Step 3:

[1416] The server analyzes the task.

[1417] Input: The received task data.

[1418] What happens: The server uses a natural language processing (NLP) engine (e.g., spaCy) to parse the task data.

[1419] Data processing: Breaking down abstract tasks into concrete steps.

[1420] Output: A concrete action list is generated as a result of the analysis.

[1421] Step 4:

[1422] The server generates the specific action.

[1423] Input: Analysis result data.

[1424] Specific behavior: The server generates specific actions based on the analysis results.

[1425] Data processing: Set deadlines for specific actions.

[1426] Output: The generated concrete action list.

[1427] Step 5:

[1428] The server transmits the generated results to the terminal.

[1429] Input: The generated concrete action list.

[1430] Specific operation: The server generates an HTTP response and sends a specific action list to the terminal.

[1431] Output: The device receives a list of specific actions.

[1432] Step 6:

[1433] The device displays feedback to the user.

[1434] Input: The received concrete action list.

[1435] Specific operation: The terminal displays the received action list on the user interface.

[1436] Output: User can see a list of specific actions.

[1437] A system incorporating an emotion engine

[1438] Step 1:

[1439] The user inputs the emotion.

[1440] Input: The user enters "stress" into the input field of the system incorporating the emotion engine.

[1441] Specific behavior: The user enters an emotion into the input field and presses the send button.

[1442] Output: The input emotion data is saved on the device.

[1443] Step 2:

[1444] The device sends input to the server.

[1445] Input: Emotion data entered by the user.

[1446] Specific operation: The device generates an HTTP request and sends the input emotion data to the server.

[1447] Output: The server receives the emotion data.

[1448] Step 3:

[1449] The server recognizes emotions.

[1450] Input: Received emotion data.

[1451] Specific operation: The server analyzes the sentiment data using a sentiment analysis algorithm (e.g., IBM Watson).

[1452] Data processing: Classifying emotion data into specific emotions such as "stress."

[1453] Output: Recognized emotion data.

[1454] Step 4:

[1455] The server adjusts the priority of the tasks.

[1456] Input: Recognized emotion data and an existing task list.

[1457] Specific behavior: The server dynamically adjusts task priorities based on the recognized emotions.

[1458] Data manipulation: Increase the priority of relaxation-related tasks.

[1459] Output: The adjusted task list.

[1460] Step 5:

[1461] The server sends the adjustment results to the terminal.

[1462] Input: The adjusted task list.

[1463] Specific operation: The server generates an HTTP response and sends the adjusted task list to the device.

[1464] Output: The device receives the adjusted task list.

[1465] Step 6:

[1466] The device displays feedback to the user.

[1467] Input: The received reconciled task list.

[1468] Specific operation: The terminal displays the received task list on the user interface.

[1469] Output: User can see the adjusted task list.

[1470] (Application example 1)

[1471] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1472] Conventional task management systems lack the ability to convert abstract tasks into concrete actions or adjust task priorities based on the user's emotions, making it difficult to efficiently manage tasks while taking into account the user's psychological state. Furthermore, they lack specific tools for efficiently managing production tasks within factories, making it difficult to identify bottlenecks on the production line and adjust the workload based on the emotions of workers.

[1473] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. In this invention, the server includes means for converting abstract tasks into specific actions and deadlines, means for managing the converted actions, means for periodically presenting an action list to the user, means for automatically executing simple actions, means for recognizing the user's emotions and adjusting task priorities in accordance with the emotions, means for efficiently managing production tasks in the factory, means for measuring the time for each production step in the factory and identifying bottlenecks, and means for adjusting workloads based on the emotions of workers. This enables efficient task management that takes into account the psychological state of the user, and enables efficient management of production tasks in the factory and adjustment of workloads based on the emotions of workers.

[1474] An "abstract task" is a general goal or objective without clear specific actions or steps.

[1475] "Specific actions" refer to the concrete actions or steps required to accomplish an abstract task.

[1476] A "deadline" refers to the deadline by which a particular task or action should be completed.

[1477] "Means for conversion" refers to a method or device for converting abstract tasks into concrete actions and deadlines.

[1478] "Means for managing" refers to a method or apparatus for efficiently organizing and tracking transformed actions.

[1479] "Presenting means" refers to a method or device for visually or audibly presenting the action list to the user.

[1480] "Automatic execution means" refers to a method or device for automatically executing a particular action without user intervention.

[1481] "Means for recognizing emotions" refers to a method or apparatus for detecting and identifying a user's emotional state.

[1482] "Means for adjusting priority" refers to a method or device for changing the importance or urgency of a task.

[1483] "Production tasks" refer to specific production activities and work carried out within a factory.

[1484] "Efficient management means" refers to methods and devices for optimizing and efficiently performing production tasks.

[1485] "Production step" refers to an individual task or process in the manufacturing process of a product.

[1486] A "bottleneck" refers to a delay or obstacle in a production process that reduces overall efficiency.

[1487] "Means for adjusting workload" refers to methods and devices for appropriately allocating and adjusting the workload of workers.

[1488] A system for carrying out this invention has the following configuration: A server includes means for converting abstract tasks into specific actions and deadlines, means for managing the converted actions, means for periodically presenting an action list to the user, means for automatically executing simple actions, means for recognizing the user's emotions and adjusting task priorities in accordance with those emotions, means for efficiently managing production tasks in a factory, means for measuring the time for each production step in the factory and identifying bottlenecks, and means for adjusting the workload based on the emotions of workers.

[1489] Hardware and software used

[1490] Hardware: Factory robots, emotion-recognition cameras

[1491] Software: EmotionEngine (emotion recognition library), TaskManager (task management library)

[1492] Program processing explanation

[1493] The server first initializes the EmotionEngine to prepare for emotion recognition. Next, it initializes the TaskManager to prepare for task management. When the user inputs an abstract task, the server converts it into a specific action and adds it to the TaskManager. A deadline is set for the specific action, and it is periodically presented to the user.

[1494] The server uses the Emotion Engine to recognize the emotions of workers in the factory and adjust task priorities based on those emotions. For example, if a worker is feeling stressed, it will increase the priority of relaxation-related tasks. To efficiently manage production tasks in the factory, the server also measures the time required for each production step and identifies bottlenecks. This makes it possible to adjust the workload based on the emotions of workers.

[1495] Specific examples

[1496] For example, if a factory manager inputs the task of "improving the efficiency of the production line," the server converts this into specific actions such as "measuring the time for each production step" and "identifying bottlenecks." Additionally, if a worker is feeling stressed, the server can increase the priority of relaxation-related tasks to reduce the worker's psychological burden.

[1497] Prompt Sentence Examples

[1498] If a factory manager inputs a task like "Increase production line efficiency," translate it into a concrete action. If a worker is feeling stressed, prioritize relaxation-related tasks.

[1499] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1500] Step 1:

[1501] The server initializes the EmotionEngine and prepares it for emotion recognition. The EmotionEngine receives video data from the emotion recognition camera as input and analyzes emotions from the user's facial expressions and voice. The output is the user's emotional state (e.g., stress, joy).

[1502] Step 2:

[1503] The server initializes TaskManager and prepares for task management. TaskManager creates a database to manage task data entered by the user. It receives information such as task lists and due dates as input, and provides the managed task list as output.

[1504] Step 3:

[1505] A user inputs an abstract task into the server. For example, the server inputs a task such as "Improve the efficiency of the production line." The server converts this abstract task into specific actions. Specific actions generated include "Measure the time required for each production step" and "Identify bottlenecks." The input is an abstract task, and the output is a list of specific actions.

[1506] Step 4:

[1507] The server adds specific actions to the TaskManager and sets a due date for each action. The TaskManager stores and manages these actions in a database. The input is a list of specific actions and their due dates, and the output is an updated task list.

[1508] Step 5:

[1509] The server periodically presents the action list to the user, and sends a notification to the user's terminal to display the action list. The input is the updated task list, and the output is the action list presented to the user.

[1510] Step 6:

[1511] The server uses EmotionEngine to recognize the emotions of workers in the factory. It receives video data from the emotion recognition camera as input and analyzes the emotional state of the workers. As an output, it obtains the emotional state of the workers (e.g., stress, joy).

[1512] Step 7:

[1513] The server adjusts task priorities based on the worker's emotions. For example, if a worker is feeling stressed, it increases the priority of relaxation-related tasks. The input is the worker's emotional state, and the output is the adjusted task priorities.

[1514] Step 8:

[1515] The server measures the time for each production step and identifies bottlenecks in order to efficiently manage production tasks within the factory. It receives sensor data from the production line as input, analyzes the time for each step, and outputs the results of identifying bottlenecks.

[1516] Step 9:

[1517] The server adjusts the workload based on the worker's emotions. For example, if a worker is feeling stressed, it adjusts the workload to reduce it. The input is the worker's emotional state and production task data, and the output is the adjusted workload.

[1518] Example 2

[1519] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1520] Conventional task management systems have difficulty converting abstract tasks into concrete actions and deadlines, making it difficult to effectively manage actions according to deadlines set by users. Furthermore, task prioritization does not take into account the user's emotional state, which can lead to user stress and reduced efficiency. Furthermore, there is insufficient data collection for updating lists when users complete actions and for emotion recognition.

[1521] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for converting abstract tasks into specific actions and deadlines, means for managing the converted actions, means for periodically presenting an action list to the user, means for automatically executing simple actions, means for sorting actions according to deadlines set by the user and displaying those with the closest deadline first, means for deleting an action from the list when the user completes it and displaying uncompleted actions, means for capturing the user's facial expressions and tone of voice using a camera or microphone and inputting them into an emotion recognition algorithm, means for using the content of posts on SNS as data for emotion recognition if the user allows it, and means for adjusting task priorities according to the user's emotional state. This allows for efficient task management for the user and enables flexible adjustment of task priorities according to the user's emotional state.

[1522] An "abstract task" is a general goal or objective without clearly defined specific actions or deadlines.

[1523] "Concrete actions" refer to specific actions or tasks that transform abstract tasks into executable forms.

[1524] A "deadline" is the date by which a particular action or task should be completed.

[1525] "Means of management" refers to the methods or systems used to track the status of actions or tasks and make updates or changes as needed.

[1526] "Presentation means" refers to a method or system for displaying information to a user.

[1527] "Automatic execution means" refers to a method or system for automatically performing a particular action or task without user intervention.

[1528] A "means for sorting" refers to a method or system for ordering data based on specific criteria.

[1529] "Capturing means" refers to a method or system for capturing a user's facial expressions and tone of voice using a camera or microphone.

[1530] "Emotion recognition algorithm" refers to a computational method or program that analyzes collected data to identify a user's emotional state.

[1531] "Means for adjusting priority" refers to a method or system for changing the importance or execution order of tasks depending on the emotional state of the user.

[1532] The present invention provides a system that enables efficient task management for a user and flexible adjustment of task priorities according to the user's emotional state. Specific embodiments of this system are described below.

[1533] Hardware and software used

[1534] server:

[1535] Database: A database system (e.g., MySQL, PostgreSQL) for storing action information and user data.

[1536] Emotion recognition algorithms: Algorithms for analyzing the user's facial expressions and tone of voice (e.g., OpenCV, TensorFlow)

[1537] Sorting algorithm: The algorithm used to sort actions by due date.

[1538] Device:

[1539] Camera: A device for capturing the user's facial expressions.

[1540] Microphone: A device for capturing the tone of a user's voice.

[1541] Application: Software that allows users to input and manage actions (e.g., mobile app, web app)

[1542] Program processing

[1543] The server converts abstract tasks entered by users into concrete actions and due dates. The converted actions are stored in a database and sorted according to the due dates set by the user. The sorted action list is periodically sent to the user's device and displayed.

[1544] The device uses a camera and microphone to capture the user's facial expressions and tone of voice. This data is sent to a server in real time and input into an emotion recognition algorithm. If the user allows it, social media posts can also be used as data for emotion recognition.

[1545] The server uses emotion recognition algorithms to understand the user's emotional state and adjust task priorities accordingly—for example, if the user is feeling stressed, it will postpone less important tasks.

[1546] Specific examples

[1547] If a user sets an action to "Submit a report by October 10, 2023," the following processing will occur:

[1548] 1. The user enters the action into the terminal application and presses the registration button.

[1549] 2. The terminal sends the input action information to the server.

[1550] 3. The server stores the received action information in a database, sorting it along with other actions by due date.

[1551] 4. As the deadline approaches, the server will prioritize displaying this action on the user's device.

[1552] 5. Once the user submits the report and marks the action as completed on the device, the server removes this action from the database and sends an updated action list to the device.

[1553] Prompt Sentence Examples

[1554] Input prompt for the generative AI model:

[1555] Your program should sort the actions by the due date set by the user, displaying them in order of the nearest due date, and also remove the action from the list when the user completes it, displaying the remaining incomplete actions.

[1556] Furthermore, to recognize the user's emotions, add a function to capture facial expressions and tone of voice using a camera or microphone and input them into the emotion recognition algorithm. If the user allows it, use social media posts as data for emotion recognition. Based on this data, implement a function to recognize the user's current emotional state and adjust task priority accordingly.

[1557] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1558] Step 1:

[1559] The user uses the application on the device to register an action. The user enters the action content and due date and presses the register button. The input data is the action content and due date. The device sends this data to the server. Specifically, the user enters the action "Submit a report by October 10, 2023" and presses the register button.

[1560] Step 2:

[1561] The server saves the received action information in a database. The input data is the action information sent from the terminal. The server stores this data in a database. Specifically, the server saves the action "Submit a report" and its due date in the database.

[1562] Step 3:

[1563] The server retrieves the action information stored in the database and applies a sorting algorithm based on the due date. The input data is the action information retrieved from the database. The server uses the sorting algorithm to sort the actions in order of due date. Specifically, the server sorts multiple actions in order of due date.

[1564] Step 4:

[1565] The server sends the sorted action list to the user's terminal. The input data is the sorted action list. The server sends this list to the terminal. In concrete operations, the server sends the sorted action list to the terminal, and the terminal displays it to the user.

[1566] Step 5:

[1567] When a user completes an action, the user marks the action as completed in the terminal application. The input data is the action information marked as completed. The terminal sends this information to the server. As a specific operation, the user marks the action as completed, indicating that "the report has been submitted."

[1568] Step 6:

[1569] The server deletes the action from the database and sends an updated list of incomplete actions to the user's device again. The input data is the action information marked as completed. The server deletes the action from the database and generates an incomplete action list. Specifically, the server deletes the action "Submit a report" from the database and sends an updated action list to the device.

[1570] Step 7:

[1571] The device uses a camera and microphone to capture the user's facial expressions and tone of voice. The input data is the user's facial expressions and tone of voice. The device transmits this data in real time to the server. Specifically, the device captures the user's facial expressions and tone of voice and transmits them to the server.

[1572] Step 8:

[1573] The server analyzes the captured data using an emotion recognition algorithm to recognize the user's current emotional state. The input data is the captured facial expression and tone of voice. The server applies the emotion recognition algorithm to identify the user's emotional state. Specifically, the server determines that the user is tired.

[1574] Step 9:

[1575] If the user allows it, the server also acquires the content of posts on social media and uses it as additional data for emotion recognition. The input data is the content of posts on social media. The server inputs this data into the emotion recognition algorithm. Specifically, the server analyzes the user's social media posts and uses them for emotion recognition.

[1576] Step 10:

[1577] The server adjusts task priorities according to the user's emotional state. The input data is the recognized emotional state. The server reevaluates task priorities and generates an adjusted task list. Specifically, the server determines that the user is tired and postpones less important tasks.

[1578] Step 11:

[1579] The server sends the adjusted task list to the user's terminal. The input data is the adjusted task list. The server sends this list to the terminal. In specific operations, the server sends the adjusted task list to the terminal, and the terminal displays it to the user.

[1580] (Application example 2)

[1581] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1582] Conventional task management systems prioritize tasks without considering the user's emotional state, which can lead to stress and reduced efficiency. Furthermore, in factory work task management, tasks are assigned without considering the emotional state of workers, which can lead to problems with work efficiency and safety. To solve these issues, a system is needed that recognizes the emotional state of users and workers and adjusts task priorities based on that information.

[1583] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1584] In this invention, the server includes: means for converting abstract tasks into specific actions and deadlines; means for managing the converted actions; means for periodically presenting a list of actions to the user; means for automatically executing simple actions; means for recognizing the user's emotional state; means for adjusting task priorities based on the recognized emotional state; means for capturing the user's facial expressions and tone of voice using a camera and a microphone; means for analyzing the user's emotions using an emotion recognition algorithm; means for using social media posts as data for emotion recognition if the user allows it; means for managing work tasks within a factory; and means for adjusting task priorities based on the emotional states of workers. This enables task management that takes into account the emotional states of users and workers, thereby reducing stress, improving work efficiency, and ensuring safety.

[1585] An "abstract task" is a general task or goal without clearly defined specific actions or deadlines.

[1586] A "specific action" is a task or work that involves clearly defined specific actions and procedures.

[1587] A "deadline" is the date or time when a particular task or action should be completed.

[1588] A "conversion means" is a method or device for converting abstract tasks into concrete actions and deadlines.

[1589] A "managing means" is a method or device for organizing, tracking, and, if necessary, updating the translated actions.

[1590] The "means for periodically presenting" refers to a method or device for displaying the action list to the user at regular intervals.

[1591] An "automatic execution means" is a method or device for performing a particular action without user intervention.

[1592] "Emotional state" refers to the current psychological state or mood of a user or worker.

[1593] "Means for recognizing" refers to a method or device for detecting and identifying the emotional state of a user or worker.

[1594] A "means for adjusting priorities" is a method or device for changing the importance or execution order of tasks based on a perceived emotional state.

[1595] A "camera" is a device for capturing images or video.

[1596] A "microphone" is a device for capturing sound.

[1597] "Facial expression" refers to the facial movements and expressions of the user or worker.

[1598] "Vocal tone" refers to characteristics such as pitch, intensity, and texture of the voice.

[1599] An "emotion recognition algorithm" is a computational method or program that analyzes captured data to identify emotional states.

[1600] "SNS posting content" refers to content such as text, images, and videos posted by users on social networking services.

[1601] "Work tasks within a factory" refers to the specific work and tasks performed within a factory.

[1602] "Workers" are people who perform work in a factory.

[1603] The following system configuration will be described as an embodiment of the present invention.

[1604] System Configuration

[1605] The system consists of the following main components:

[1606] 1. Server:

[1607] A way to translate abstract tasks into concrete actions and deadlines

[1608] A way to manage the converted actions

[1609] A means of periodically presenting a list of actions to the user

[1610] A means of automatically executing simple actions

[1611] A means of recognizing a user's emotional state

[1612] A means of adjusting task priorities based on perceived emotional states

[1613] A means of capturing a user's facial expressions and tone of voice using a camera or microphone

[1614] A means of analyzing user emotions using emotion recognition algorithms

[1615] A method for using social media posts as data for emotion recognition if the user allows it

[1616] A means of managing work tasks within a factory

[1617] A means of adjusting task priorities based on workers' emotional states

[1618] Program processing

[1619] The server performs data processing and calculation using the following hardware and software:

[1620] Hardware:

[1621] Camera: Used to capture the facial expressions of users and workers.

[1622] Microphone: Used to capture the tone of the user's or worker's voice.

[1623] software:

[1624] OpenCV: Used for capturing and analyzing facial expressions.

[1625] EmotionRecognizer: Used as an emotion recognition algorithm.

[1626] TaskManager: Used for task management.

[1627] Processing flow

[1628] 1. Capturing emotions:

[1629] Cameras and microphones are used to capture the facial expressions and tone of voice of users and workers.

[1630] The captured data is fed into an emotion recognition algorithm.

[1631] 2. Emotion Recognition:

[1632] An emotion recognition algorithm (EmotionRecognizer) is used to analyze the emotional state of users and workers from the captured data.

[1633] If necessary, and if the user gives permission, the content of social media posts will also be used as data for emotion recognition.

[1634] 3. Adjusting task priorities:

[1635] Based on the perceived emotional state, the TaskManager adjusts the priority of tasks.

[1636] The adjusted tasks are sorted by due date and presented to the user or worker.

[1637] Specific examples

[1638] For example, if a worker in a factory feels stressed, the emotion recognition algorithm will recognize that emotion and adjust the task manager to reduce high-priority tasks to reduce stress. In this way, worker stress can be reduced and work efficiency can be improved.

[1639] Prompt Sentence Examples

[1640] "Develop an application that manages work tasks in a factory and adjusts task priorities by recognizing the emotional state of workers. Use a camera and microphone to capture facial expressions and tone of voice, and analyze emotions using emotion recognition algorithms. Adjust task priorities based on the recognized emotions and display them in order of due date."

[1641] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1642] Step 1:

[1643] The server uses a camera and microphone to capture the facial expressions and tone of voice of users and workers.

[1644] Input: Video data from the camera, audio data from the microphone

[1645] Output: Captured facial expression data, tone of voice data

[1646] How it works: The camera captures the face of the user or worker, and the microphone records their voice. This data is sent to the server in real time.

[1647] Step 2:

[1648] The server inputs the captured facial expression data and tone of voice data into an emotion recognition algorithm.

[1649] Input: Facial expression data, voice tone data

[1650] Output: Emotional state of the user or worker

[1651] Specific operation: The server analyzes facial expression data using OpenCV and recognizes emotions using EmotionRecognizer. Voice tone data is also analyzed in the same way to identify emotional states.

[1652] Step 3:

[1653] If the user gives permission, the server retrieves the content of the SNS post and inputs it into an emotion recognition algorithm.

[1654] Input: Social media post content

[1655] Output: Additional emotion data

[1656] Specific operation: The server retrieves posts from the user's authorized social media accounts and performs text analysis to identify the user's emotional state, enabling more accurate emotion recognition.

[1657] Step 4:

[1658] The server instructs the task manager to adjust task priorities based on the perceived emotional state.

[1659] Input: Emotional state data

[1660] Output: Adjusted task priorities

[1661] Specific behavior: The server sends emotional state data to the task manager and recalculates task priorities. For example, if the user is feeling stressed, the server will adjust the priority of high-priority tasks to be reduced.

[1662] Step 5:

[1663] The server sorts the adjusted tasks by due date and presents them to the user or worker.

[1664] Input: Adjusted task priority

[1665] Output: Sorted task list

[1666] Specific operation: The server sorts the task list based on the due date and priority of the task and displays it on the user's or worker's device, allowing the user or worker to view the task that best suits their current situation.

[1667] Step 6:

[1668] When a user or worker completes a task, the server removes it from the list and displays only incomplete tasks.

[1669] Input: Task completion information

[1670] Output: Updated task list

[1671] Specific behavior: When a user or worker reports that a task is complete, the server receives the information and removes the task from the task list. Only incomplete tasks are displayed again.

[1672] Example 3

[1673] Next, a description will be given of Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1674] Conventional task management systems provide insufficient support for users to efficiently manage tasks, and in particular, they do not automatically control task execution according to the user's emotional state, making it difficult to manage tasks that take the user's emotions into consideration. Furthermore, because they do not automatically execute simple actions or provide periodic action lists, the burden on the user increases and task progress can be delayed.

[1675] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[1676] In this invention, the server includes means for converting abstract tasks into specific actions and deadlines, means for managing the converted actions, means for periodically presenting an action list to the user, means for automatically executing simple actions, means for recognizing the user's emotional state, and means for controlling the automatic execution of tasks based on the recognized emotional state. This enables task management that takes the user's emotional state into consideration, and by automatically executing simple actions and periodically presenting an action list, the burden on the user is reduced and tasks can be progressed efficiently.

[1677] An "abstract task" is one that does not have clearly defined specific actions or deadlines.

[1678] A "specific action" is a specific task or action that the user must perform.

[1679] A "deadline" is a specific date and time by which a task should be completed.

[1680] A "conversion means" is a method or device for converting abstract tasks into concrete actions and deadlines.

[1681] A "managing means" is a method or device for tracking the translated actions and monitoring their progress.

[1682] The "means for periodically presenting the action list to the user" refers to a method or device for notifying the user of an incomplete action list at a set time interval.

[1683] A "simple action" is a simple task or activity that can be completed in a relatively short amount of time.

[1684] An "automatic execution means" is a method or device for performing a simple action without user intervention.

[1685] The term "means for recognizing an emotional state" refers to a method or device for analyzing emotions from a user's facial expressions, voice, etc., and identifying a specific emotional state.

[1686] A "means for controlling the automatic performance of a task" is a method or device for starting, stopping, or modifying the performance of a particular task based on a recognized emotional state.

[1687] MODE FOR CARRYING OUT THE INVENTION

[1688] The present invention provides a system that improves the efficiency of task management for a user and enables automatic task execution control according to the user's emotional state. Specific embodiments of this system will be described below.

[1689] Server Roles

[1690] The server extracts incomplete tasks from the user's task list and periodically presents the action list to the user. Specifically, the server retrieves the user's task information from the database and lists tasks with a status of "incomplete." For example, the server retrieves task information from the database every morning at 8:00 and lists incomplete tasks. Next, it uses a Cron job or scheduler to schedule a notification of the incomplete action list to the user every morning at 9:00. Notifications are sent via email or push notification.

[1691] Application Roles

[1692] The application extracts simple actions from the user's task list and executes them automatically. Specifically, the application analyzes the content of the task and lists simple actions such as "send an email" or "set a reminder." It then calls the email sending API or reminder setting API to automatically execute these tasks. For example, if there is a "send an email" task, it sends an email to the specified recipient.

[1693] The role of the emotional engine

[1694] The emotion engine recognizes the user's emotional state and controls the automatic execution of tasks based on the recognized emotional state. Specifically, the emotion engine analyzes the user's facial and voice data and classifies emotions into categories such as "anger" and "joy." For example, if the emotion engine analyzes the user's facial data and recognizes the emotion "anger," it temporarily stops automatic replies to emails from specific people. Also, if the user is in a "joy" state, it automatically posts to social media.

[1695] Examples and prompts

[1696] Example 1: Periodic action list notifications

[1697] Hardware: Server

[1698] Software: Task management application

[1699] Data processing: Extraction and notification of incomplete task list

[1700] Example prompt sentence:

[1701] Write a program that notifies the user of their incomplete task list every morning at 9am.

[1702] Example 2: Automatic execution of simple actions

[1703] Hardware: User's device (smartphone, PC, etc.)

[1704] Software: Task management application

[1705] Data Calculation: Extract simple actions from the user's task list and execute them automatically

[1706] Example prompt sentence:

[1707] Create a program that automatically performs simple actions such as "send email" or "set reminders" from a user's task list.

[1708] Example 3: Automatic task execution control using an emotion engine

[1709] Hardware: User's device, server

[1710] Software: Emotion recognition engine, task management application

[1711] Data Computation: Recognizing User Emotional States and Automatic Task Control

[1712] Example prompt sentence:

[1713] Create a program that controls the automatic execution of tasks according to the user's emotional state. For example, stop a specific task if the user is in an "anger" state, or automatically post to social media if the user is in a "joy" state.

[1714] In this way, the server, application, and emotion engine each play their respective roles to build a system that improves the efficiency of task management for users. The flow of the specific processing in the third embodiment will be described with reference to FIG.

[1715] Step 1:

[1716] The server retrieves user task information from the database every morning at 8:00. The input is the user's task information, and the output is a list of incomplete tasks. Specifically, it uses an SQL query to extract tasks with a status of "incomplete."

[1717] Step 2:

[1718] The server sets up a schedule to send notifications to users every morning at 9:00 based on the extracted list of incomplete tasks. The input is the list of incomplete tasks, and the output is the notification schedule. Specifically, a Cron job or scheduler is set up to trigger notifications at the specified time.

[1719] Step 3:

[1720] The server notifies the user of the list of uncompleted actions at the set time. The input is the notification schedule and the list of uncompleted tasks, and the output is the notification to the user. Specifically, the notification is sent to the user's device using email or push notification.

[1721] Step 4:

[1722] The application extracts simple actions from the user's task list. The input is the user's task list, and the output is a list of simple actions. Specifically, it analyzes the content of the task and lists simple actions such as "send an email" or "set a reminder."

[1723] Step 5:

[1724] The application automatically executes the extracted simple actions. The input is a list of simple actions, and the output is the executed actions. Specifically, it calls the email sending API and reminder setting API to execute the tasks.

[1725] Step 6:

[1726] The emotion engine recognizes the user's emotional state. The input is the user's facial expression and voice data, and the output is the recognized emotional state. Specifically, it uses facial expression recognition algorithms and voice analysis algorithms to classify emotions into categories such as "anger" and "joy."

[1727] Step 7:

[1728] The emotion engine controls the automatic execution of tasks based on the recognized emotional state. The input is the recognized emotional state and a task list, and the output is the controlled execution of the tasks. Specifically, if the user is in an "anger" state, it stops a specific task (for example, automatically replying to an email from a specific person), and if the user is in a "joy" state, it executes an automatic post to a social networking site.

[1729] (Application example 3)

[1730] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1731] Conventional task management systems require users to manually check and execute tasks, making efficient task management difficult. Furthermore, tasks are executed without taking into account the user's emotional state, which can cause stress and dissatisfaction. Furthermore, there is a problem of reduced work efficiency when robots in factories execute tasks without considering the emotional state of workers.

[1732] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[1733] In this invention, the server includes means for converting abstract tasks into specific actions and deadlines, means for managing the converted actions, means for periodically presenting an action list to the user, means for automatically executing simple actions, means for detecting the user's emotional state, means for controlling the automatic execution of tasks according to the emotional state, and means for checking uncompleted tasks at a specific time and executing or pausing the tasks based on the emotional state, thereby enabling efficient task management and execution while taking the user's emotional state into consideration.

[1734] An "abstract task" is one that does not have clearly defined specific actions or deadlines.

[1735] A "specific action" is a clear action that involves specific steps or operations.

[1736] A "deadline" is the date or time by which a particular task should be completed.

[1737] A "conversion means" is a method or device for converting abstract tasks into concrete actions and deadlines.

[1738] "Means for managing" refers to the methods and devices for tracking the transformed actions and monitoring their progress.

[1739] The "means for periodically presenting an action list to a user" refers to a method or device for notifying a user of an incomplete task list at a set time interval.

[1740] A "means for automatically performing simple actions" is a method or device for automatically performing a specific task without user intervention.

[1741] "Means for detecting a user's emotional state" refers to a method or device for identifying a user's emotional state and determining that state.

[1742] "Means for controlling the automatic performance of a task in response to an emotional state" refers to a method or apparatus for adjusting the performance of a task based on a detected emotional state.

[1743] "Means for checking for incomplete tasks at a specific time" refers to a method or device for checking for incomplete tasks at a set time.

[1744] A "means for executing or pausing a task based on emotional state" refers to a method or device for starting or pausing the execution of a task depending on the emotional state of a user.

[1745] As an embodiment of the present invention, a system is provided in which a robot in a factory efficiently manages and executes tasks while taking into account the emotional state of a user. A specific embodiment of this system is described below.

[1746] System Configuration

[1747] The system consists of the following main components:

[1748] 1. Server: Plays a central role in task management and emotional state detection.

[1749] 2. Robots: These actually perform tasks in the factory.

[1750] 3. User terminal: A device used by the worker to input emotional state and task feedback.

[1751] Program processing

[1752] The server does the following:

[1753] Task transformation: Transform abstract tasks into concrete actions and deadlines. For example, transform an abstract task like "check inventory" into a concrete action like "check the inventory list every morning at 9am."

[1754] Task Management: Manage converted actions and monitor progress. This includes the ability to track task status and list incomplete tasks.

[1755] Periodic notifications: Present the action list to the user periodically. For example, notify the user of uncompleted tasks at 9:00 every morning.

[1756] Auto-execute: Automatically execute simple actions, such as setting a reminder or sending an email.

[1757] Emotion detection: Detecting the user's emotional state using inputs and sensors from the user's device.

[1758] Emotion control: Controlling the automatic execution of tasks according to the user's emotional state. For example, if the user is in an "anger" state, pausing a specific task (e.g., sending an email) will be suspended.

[1759] Task confirmation: Check for uncompleted tasks at a specific time and execute or pause the tasks based on the user's emotional state. For example, check for uncompleted tasks at 9:00 every morning and decide whether to execute them based on the user's emotional state.

[1760] Hardware and software used

[1761] Hardware: Server, user device (smartphone, tablet, etc.), robot, emotion detection sensors (camera, microphone, etc.).

[1762] Software: Task management systems, emotion detection algorithms, notification systems, generative AI models.

[1763] Specific examples

[1764] For example, consider the following scenario in a factory:

[1765] Every morning at 9:00, the server checks for uncompleted tasks and notifies the user's device.

[1766] If the user is in the "Anger" state, the server suspends the "Send Mail" task.

[1767] When the user is in the "joy" state, the server automatically executes the "post to SNS" task.

[1768] Prompt Sentence Examples

[1769] The following prompts can be fed into the generative AI model to provide useful information for detailed system design and implementation:

[1770] Develop an application in which a robot in a factory checks the uncompleted tasks every morning at 9:00 and automatically executes or pauses the tasks depending on the worker's emotional state. The emotional states can be "Happy," "Anger," "Sadness," "Surprise," or "Calm," and the robot should have the ability to pause certain tasks (e.g., sending emails) depending on the worker's emotional state.

[1771] In this way, tasks can be managed and performed efficiently while taking into account the user's emotional state.

[1772] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1773] Step 1:

[1774] The server translates abstract tasks into concrete actions and deadlines.

[1775] Input: Abstract task (e.g., "Check inventory")

[1776] Data transformation: Convert tasks into specific actions (e.g., "Check the inventory list every morning at 9am").

[1777] Output: Specific actions and due dates

[1778] Step 2:

[1779] The server manages the translated actions and monitors their progress.

[1780] Input: Specific actions and due dates

[1781] Data processing: Track the status of actions and list incomplete tasks.

[1782] Output: A list of open tasks

[1783] Step 3:

[1784] The server periodically presents the action list to the user.

[1785] Input: List of open tasks

[1786] Data processing: Notify the user's device of the list of uncompleted tasks at a set time (e.g., 9:00 every morning).

[1787] Output: Notification to user terminal

[1788] Step 4:

[1789] The server automatically executes simple actions.

[1790] Input: A specific action (e.g., "Set a reminder")

[1791] Data manipulation: Performing actions automatically.

[1792] Output: Execution results

[1793] Step 5:

[1794] The server detects the emotional state of the user.

[1795] Input: Emotion data from the user device (e.g., camera footage, audio data)

[1796] Data processing: Emotion detection algorithms are used to identify emotional states.

[1797] Output: Emotional state (e.g., "joy", "anger")

[1798] Step 6:

[1799] The server controls the automatic execution of tasks according to the emotional state.

[1800] Input: Emotional state and unfinished task list

[1801] Data manipulation: Adjusting task execution based on emotional state (e.g., pausing email sending if "angry").

[1802] Output: Reconciled task list

[1803] Step 7:

[1804] The server checks for outstanding tasks at specific times and executes or pauses the tasks based on the emotional state.

[1805] Input: Unfinished task list and emotional state

[1806] Data processing: At a set time (e.g., every morning at 9:00), review your outstanding tasks and execute or pause them based on your emotional state.

[1807] Output: Status of the task being run or paused

[1808] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1809] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1810] Another example of generative AI is Gemini (internet search engine). <url: https: gemini.google.com ?hl="ja">) are mentioned.

[1811] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1812] [Third embodiment]

[1813] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1814] .

[1815] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1816] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1817] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1818] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1819] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1820] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1821] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1822] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1823] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1824] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1825] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[1826] "Example 1"

[1827] As one embodiment of the present invention, a task management application is provided. This application has a function of converting abstract tasks input by a user into specific actions and deadlines. Specifically, when a user inputs an abstract task such as "manage the progress of a project," the application converts this into a specific action such as "list each task of the project and set a deadline for each."

[1828] "Example 2"

[1829] Additionally, one embodiment of the present invention provides the ability to manage the converted actions. Specifically, the application sorts the actions according to the due date set by the user, displaying them in order of the nearest due date. When the user completes an action, it is removed from the list and the remaining incomplete actions are displayed.

[1830] "Example 3"

[1831] In addition, one embodiment of the present invention provides a function for periodically presenting an action list to the user. Specifically, the application notifies the user of incomplete action lists at a set time (e.g., 9:00 a.m. every morning). This allows the user to always keep track of their tasks and progress them efficiently.

[1832] "Example 4"

[1833] Furthermore, one embodiment of the present invention provides a function for automatically executing simple actions. Specifically, an application automatically executes simple actions such as "send an email" or "set a reminder." This allows the user to progress with tasks without any effort.

[1834] The processing flow of each embodiment will be described below.

[1835] "Example 1"

[1836] Step 1: The user inputs an abstract task into the application: "Manage the progress of a project."

[1837] Step 2: The application analyzes the input task and converts it into a specific action: "List each task in the project and set a due date for each one." Step 3: The converted specific action is added to the task list in the application.

[1838] "Example 2"

[1839] Step 1: The application reads the due date set for each action in the task list.

[1840] Step 2: Sort the actions by their due date and view the sorted task list.

[1841] Step 3: If the user completes an action, it is removed from the list and the incomplete actions are displayed.

[1842] "Example 3"

[1843] Step 1: The user presents the action list in the application settings screen.

[1844] (For example, every morning at 9:00).

[1845] Step 2: When the set time is up, the application will notify the user of the incomplete action list.

[1846] "Example 4"

[1847] Step 1: The user adds simple actions such as "send an email" or "set a reminder" to the task list.

[1848] Step 2: The application will perform these simple actions automatically.

[1849] Example 1

[1850] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1851] Conventional task management systems have the drawback of making efficient task management difficult because users have to convert abstract tasks into concrete actions, which is time-consuming. Furthermore, they lack the functionality to properly manage tasks entered by users and provide regular feedback, making it difficult to grasp the progress of tasks.

[1852] The identification process by the identification processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means. In this invention, the server includes means for converting abstract tasks into specific actions and due dates, means for managing the converted actions, means for periodically presenting an action list to the user, means for automatically executing simple actions, means for converting abstract tasks into specific actions using a generative AI model, means for transmitting tasks input from a user terminal to the server, means for transmitting specific actions generated from the server to the user terminal, and means for displaying the specific actions on the user terminal. This allows the user to simply input an abstract task, which is converted into specific actions and due dates, enabling efficient task management.

[1853] An "abstract task" is a general goal or objective without clearly defined specific actions or deadlines.

[1854] "Concrete actions" refer to the clear, concrete tasks or steps required to accomplish an abstract task.

[1855] A "deadline" refers to the deadline by which a particular task or action should be completed.

[1856] A "generative AI model" refers to an algorithm or system that uses artificial intelligence technology to analyze input data and generate appropriate output.

[1857] "User terminal" refers to a device such as a computer or smartphone that can be directly operated by a user.

[1858] A "server" refers to a computer system that communicates with user terminals via a network and processes and stores data.

[1859] A "prompt" is a piece of text containing instructions or questions to a generative AI model to perform a specific task.

[1860] An "action list" refers to a list of specific actions organized in a list format.

[1861] "Feedback" refers to information provided to a user about the progress or results of a task or action.

[1862] This invention is a system that realizes efficient task management by converting abstract tasks input by a user into specific actions and deadlines using a generative AI model. Specific embodiments of this system are described below.

[1863] Hardware and software used

[1864] Hardware: Server, user terminal (PC, smartphone)

[1865] Software: Task management applications, generative AI models (e.g., GPT-4)

[1866] System Overview

[1867] 1. A user launches a task management application and enters an abstract task, for example, "Manage the progress of a project."

[1868] 2. The device receives this input and sends it to the server.

[1869] 3. The server passes the received abstract task to a generative AI model, which generates prompts to convert the abstract task into concrete actions and deadlines.

[1870] 4. The generative AI model analyzes the abstract tasks input and converts them into specific actions and deadlines, such as "list each task in a project and set a deadline for each one."

[1871] 5. The server receives the generated specific actions and deadlines and sends them to the user's terminal.

[1872] 6. The device displays the specific actions and deadlines received to the user.

[1873] Specific examples

[1874] A user enters "Manage project progress" into a task management application.

[1875] The terminal sends this input to the server.

[1876] The server sends the prompt "Manage the progress of the project" to the generative AI model.

[1877] The generative AI model analyzes this prompt and converts it into a specific action: "List each task in the project and set a due date for each."

[1878] The server transmits the generated specific action to the user terminal.

[1879] The device displays specific actions to the user, such as "List each task in the project and set a due date for each."

[1880] Prompt Sentence Examples

[1881] Convert the abstract task of "managing the progress of a project" into concrete action.

[1882] Break down the task of "managing the progress of a project" into specific steps.

[1883] This system allows users to simply input abstract tasks, which are then converted into specific actions and deadlines, enabling efficient task management. Furthermore, by using a generative AI model, task specificity is automated, reducing the burden on users.

[1884] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1885] Step 1:

[1886] A user launches a task management application and inputs an abstract task. The user opens the application on a PC or smartphone and inputs an abstract task, such as "manage the progress of a project," into the input field. The input data is in text format and is saved on the user's device.

[1887] Step 2:

[1888] The terminal sends the input task to the server. The terminal receives the task data entered by the user and sends it to the server using an HTTP POST request. The input data is task data in text format and is sent to the server.

[1889] Step 3:

[1890] The server passes the received task to the generative AI model. The server analyzes the received task data and generates a prompt to be passed to the generative AI model. For example, the task "Manage the progress of a project" is converted into a prompt such as "Please convert this task into a specific action." The input data is the task data in text format, and the output data is the prompt.

[1891] Step 4:

[1892] A generative AI model converts abstract tasks into specific actions and deadlines. A generative AI model receives a prompt and converts abstract tasks into specific actions and deadlines. For example, it converts them into specific actions such as "List each task in the project and set a deadline for each." The input data is the prompt, and the output data is specific actions and deadlines.

[1893] Step 5:

[1894] The server sends the generated specific actions and deadlines to the terminal. The server sends the specific actions and deadlines received from the generative AI model to the terminal as an HTTP response. The input data are the specific actions and deadlines, and the output data is the HTTP response.

[1895] Step 6:

[1896] The terminal displays specific actions and deadlines to the user. The terminal displays specific actions and deadlines received from the server to the user. For example, a specific action such as "List each task in the project and set a deadline for each" is displayed on the application screen. The input data are specific actions and deadlines, and the output data is the information displayed to the user.

[1897] In this way, abstract tasks entered by the user are converted into concrete actions and deadlines, enabling efficient task management.

[1898] (Application example 1)

[1899] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1900] With conventional task management systems, it is difficult to convert abstract tasks into concrete actions and deadlines, and efficient operation is required, especially in task management within factories. Furthermore, converting abstract tasks entered by users into concrete actions requires a lot of manual work, which takes time and effort. Furthermore, there are no task management systems that utilize generative AI models, making it difficult to automate task management within factories.

[1901] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1902] In this invention, the server includes means for converting abstract tasks into specific actions and deadlines, means for managing the converted actions, means for periodically presenting an action list to the user, means for automatically executing simple actions, means for converting abstract tasks into specific actions using a generative AI model, and means for automating task management within the factory. This makes it possible to efficiently convert abstract tasks entered by the user into specific actions and automate task management within the factory.

[1903] An "abstract task" is a general goal or objective without clearly defined specific actions or deadlines.

[1904] "Specific actions" refer to the concrete steps or tasks required to accomplish an abstract task.

[1905] A "deadline" refers to the deadline by which a particular task or action should be completed.

[1906] A "generative AI model" refers to an algorithm or system that uses artificial intelligence technology to generate new information or results from input data.

[1907] "Factory task management" refers to the efficient planning, execution, and monitoring of various tasks and processes that take place within a factory.

[1908] "Automation" refers to minimizing human intervention and enabling machines and systems to operate autonomously.

[1909] A "server" refers to a computer system that provides services to other computers on a network.

[1910] "User" refers to an individual or organization that uses a system or application.

[1911] An "action list" is a list of specific actions needed to accomplish a particular task or goal.

[1912] "Feedback" refers to information that provides information about the performance and results of a system or process, allowing for improvements and adjustments.

[1913] As an embodiment of the present invention, a system for automating task management within a factory is constructed. A specific embodiment of the system is shown below.

[1914] System configuration

[1915] This system consists of a server, factory robots, and user terminals. The server uses a generative AI model to convert abstract tasks into specific actions and deadlines. The factory robots execute the specific actions received from the server. The user terminal provides an interface for users to input abstract tasks and receive feedback.

[1916] Program processing

[1917] The server receives abstract tasks input by users and uses a generative AI model to convert them into specific actions and deadlines. The specific actions are sent to robots in the factory, which then execute them. The server monitors the robots' execution and provides feedback to the user.

[1918] Hardware and software used

[1919] Hardware: Factory robots, user devices (PCs, tablets, smartphones)

[1920] Software: Python, OpenAI API, generative AI models

[1921] Data processing and calculation

[1922] The server receives abstract tasks entered by the user in text format and inputs them into a generative AI model. The generative AI model converts the abstract tasks into specific actions and deadlines and returns the results to the server. The server then sends the converted specific actions to robots in the factory, which then execute them. The server monitors the robots' execution status and provides feedback to the user.

[1923] Specific examples

[1924] For example, if a user inputs an abstract task such as "improving production line efficiency," the generative AI model will output a specific task such as the following:

[1925] Specific examples

[1926] Identify bottlenecks on each production line

[1927] Propose improvements to eliminate bottlenecks

[1928] Create an implementation plan for improvements

[1929] Monitor the progress of each improvement measure

[1930] Prompt Sentence Examples

[1931] Convert the following abstract tasks into concrete actions and deadlines: Increase the efficiency of the production line

[1932] In this way, task management within the factory can be efficiently automated.

[1933] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1934] Step 1:

[1935] A user inputs an abstract task using a terminal.

[1936] Input: Abstract task (e.g., "Improve the efficiency of the production line")

[1937] Output: Abstract tasks are sent to the server

[1938] Specific operation: The user inputs the task through the terminal interface and presses the send button.

[1939] Step 2:

[1940] The server receives the abstract task and sends a prompt to the generative AI model.

[1941] Input: Abstract task

[1942] Output: The prompt sent to the generative AI model

[1943] Specific operation: The server receives the abstract task, generates a prompt sentence, and sends it to the generative AI model.

[1944] Example prompt: "Translate the following abstract task into concrete actions and due dates: Increase the efficiency of the production line."

[1945] Step 3:

[1946] A generative AI model parses prompts and converts them into specific actions and deadlines.

[1947] Input: prompt statement

[1948] Output: Specific actions and due dates

[1949] Concrete Actions: The generative AI model parses the prompt and converts the abstract task into concrete actions and deadlines.

[1950] Examples: "Identify bottlenecks on each production line," "Propose improvements to eliminate bottlenecks," "Draw an implementation plan for the improvements," and "Monitor the progress of each improvement."

[1951] Step 4:

[1952] The server receives the output from the generative AI model and sends specific actions to the robots in the factory.

[1953] Input: Specific actions and due dates

[1954] Output: Specific actions sent to robots in the factory

[1955] Specific actions: The server sends the specific actions and deadlines received from the generative AI model to the robots in the factory.

[1956] Step 5:

[1957] Robots in factories perform specific actions.

[1958] Input: Specific action

[1959] Output: Action execution result

[1960] Specific action: The robot in the factory executes the specific action received and performs the work.

[1961] Step 6:

[1962] The server monitors the robot's performance and provides feedback to the user.

[1963] Input: Robot execution status

[1964] Output: Feedback provided to the user

[1965] Specific operation: The server monitors the robot's execution status and provides feedback to the user on progress and problems.

[1966] Example 2

[1967] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1968] Conventional task management systems lack the ability to sort actions based on user-set due dates or automatically remove completed actions from the list, making it difficult for users to efficiently manage their tasks. Furthermore, they lack the ability to display only incomplete actions, making it difficult for users to distinguish between completed and incomplete tasks.

[1969] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1970] In this invention, the server includes means for converting abstract tasks into specific actions and deadlines, means for managing the converted actions, means for periodically presenting a list of actions to the user, means for automatically executing simple actions, means for sorting actions based on deadlines set by the user, means for deleting an action from the list when the user completes it, and means for displaying only incomplete actions, thereby enabling the user to efficiently manage tasks and easily distinguish between completed and incomplete tasks.

[1971] An "abstract task" is a general task or goal without specific actions or deadlines.

[1972] A "specific action" refers to a specific task or procedure that a user needs to perform.

[1973] "Deadline" refers to the deadline set by the user for completing an action.

[1974] "Means for conversion" refers to a method or device for converting abstract tasks into concrete actions and deadlines.

[1975] "Means for managing" refers to a method or device for storing, tracking, and updating the translated actions.

[1976] "Presenting means" refers to a method or device for displaying the action list to the user.

[1977] "Automatic execution means" refers to a method or device for performing a simple action without user intervention.

[1978] "Means for sorting" refers to a method or device for ordering actions based on user-set deadlines.

[1979] "Means for deleting" refers to a method or device that allows a user to remove a completed action from the list.

[1980] "Means for displaying" refers to a method or device for showing only the incomplete actions to the user.

[1981] MODE FOR CARRYING OUT THE INVENTION

[1982] The present invention is a system for managing actions based on deadlines set by a user and for efficiently completing tasks. A specific embodiment of this system is described below.

[1983] Hardware and software used

[1984] Hardware: The server uses a high-performance cloud server (e.g., a virtual server from a cloud service provider).

[1985] Software: The application is developed in Python and uses MySQL for database management. The front-end is built with JavaScript libraries and the back-end uses a web application framework.

[1986] System Overview

[1987] The system converts abstract tasks entered by users into concrete actions and due dates, and manages them. The server sorts the actions based on the due dates set by the user, displaying them in order of the nearest due date. When the user completes an action, it removes it from the list, and only uncompleted actions are displayed.

[1988] Data processing and calculation

[1989] 1. Data entry: The user enters an action and its due date.

[1990] 2. Data storage: The server stores the entered data in a MySQL database.

[1991] 3. Data sorting: The server retrieves the actions from the database and sorts them based on their due date.

[1992] 4. Data display: Send the sorted actions to the front end and display them to the user.

[1993] 5. Data Update: When the user completes an action, the server removes it from the database and re-sorts and displays the incomplete actions.

[1994] Specific examples

[1995] Example 1: Adding and displaying an action

[1996] A user adds an action called "Submit a Report" with a due date of "2023-10-15". The server stores this information in a database and displays it along with other actions, sorted by due date.

[1997] Example 2: Completing an action

[1998] When the user completes the "report submission," the server removes this action from the database and re-sorts and displays the incomplete actions.

[1999] Prompt Sentence Examples

[2000] "Your application should sort actions based on the due date set by the user, displaying them in order of closest due date. When the user completes an action, you should also add the ability to remove it from the list and display only the incomplete actions."

[2001] By inputting this prompt sentence into a generative AI model, a program that outlines the above system can be generated.

[2002] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2003] Step 1:

[2004] The user enters the action

[2005] The user uses the terminal to input an action and its due date into the input form of the application. The input data is the content and due date of the action.

[2006] Step 2:

[2007] The device sends the action to the server

[2008] The terminal sends the entered action and due date to the server as an HTTP request. This request includes the action content and due date. The input is the action and due date entered by the user, and the output is the HTTP request sent to the server.

[2009] Step 3:

[2010] The server saves the action to the database

[2011] The server stores the received action and due date in a MySQL database. Specifically, it adds a new record to the database using an INSERT statement. The input is the HTTP request and the output is the record stored in the database.

[2012] Step 4:

[2013] The server sorts the actions by due date

[2014] The server retrieves all actions from the database using a SELECT statement and sorts them by due date using the SQL ORDER BY clause. The input is the action list retrieved from the database, and the output is the sorted action list.

[2015] Step 5:

[2016] The server sends the sorted actions to the terminal.

[2017] The server sends the sorted action list to the terminal in JSON format, so that the terminal can receive the latest action list. The input is the sorted action list, and the output is the JSON data sent to the terminal.

[2018] Step 6:

[2019] The device displays the action

[2020] The terminal displays the received action list in the user interface. The actions are listed in order of their due date. The input is JSON data received from the server, and the output is the action list displayed in the user interface.

[2021] Step 7:

[2022] The user completes the action

[2023] When the user completes an action, they mark it as complete in the application's interface. The input is the user's action, and the output is the action marked as complete.

[2024] Step 8:

[2025] The device notifies the server of the completed action

[2026] The device sends information about the completed action to the server as an HTTP request, which includes the ID of the completed action. The input is the action marked as completed, and the output is the HTTP request sent to the server.

[2027] Step 9:

[2028] The server removes completed actions from the database

[2029] The server uses the received action ID to delete the corresponding action from the database using a DELETE statement. The input is the HTTP request, and the output is the record deleted from the database.

[2030] Step 10:

[2031] The server resorts the outstanding actions

[2032] The server retrieves the incomplete actions from the database again using the SELECT statement and sorts them by due date. The input is the list of incomplete actions retrieved from the database, and the output is the sorted list of incomplete actions.

[2033] Step 11:

[2034] The server sends the updated action list to the device.

[2035] The server sends the updated list of pending actions to the terminal in JSON format. The input is the sorted list of pending actions, and the output is the JSON data sent to the terminal.

[2036] Step 12:

[2037] The device displays the updated action list

[2038] The terminal receives the updated action list and displays it again in the user interface, allowing the user to see the latest pending actions. The input is the JSON data received from the server, and the output is the updated action list displayed in the user interface.

[2039] (Application example 2)

[2040] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[2041] Task management in logistics centers is difficult because multiple tasks occur simultaneously and each has a different deadline. Furthermore, if the information is not reflected immediately after a worker completes a task, there is a risk of unnecessary work being done. Furthermore, if task priorities are not clearly defined, there is a risk that important tasks will be put off.

[2042] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[2043] In this invention, the server includes means for converting abstract tasks into specific actions and deadlines, means for managing the converted actions, means for periodically presenting a list of actions to the user, means for automatically executing simple actions, means for sorting the actions based on deadlines and displaying them in order of the nearest deadline, and means for deleting an action from the list when the user completes it and displaying uncompleted actions. This improves the efficiency of task management in the logistics center and enables important tasks to be appropriately prioritized.

[2044] An "abstract task" is a general task or goal without clearly defined specific actions or deadlines.

[2045] "Specific actions" are the concrete steps or tasks required to accomplish an abstract task.

[2046] A "deadline" is the date by which a particular task or action should be completed.

[2047] A "conversion means" is a method or device for converting abstract tasks into concrete actions and deadlines.

[2048] "Means for managing" refers to the methods and devices for tracking the converted actions and monitoring their progress.

[2049] A "presentation means" refers to a method or device for displaying the action list to the user.

[2050] An "automatic execution means" is a method or device for automatically executing a particular action without user intervention.

[2051] A "means for sorting" is a method or device for sorting actions based on due date.

[2052] "Means for displaying" refers to a method or device for visually indicating the sorted actions to the user.

[2053] "Means for removing the action from the list when completed" refers to a method or device for removing an action from the list when the user completes the action.

[2054] The "means for displaying incomplete actions" refers to a method or device for displaying to the user only the actions that are not completed.

[2055] A system for carrying out the present invention is intended to improve the efficiency of task management in a logistics center. A specific embodiment of this system will be described below.

[2056] System configuration

[2057] The system consists of a server, worker devices (smartphones or smart glasses), and a user interface. The server plays a central role in task management, while the device is used by workers to check tasks and report their completion.

[2058] Program processing

[2059] The server manages tasks using the following means:

[2060] 1. A way to translate abstract tasks into concrete actions and deadlines

[2061] The server converts abstract tasks entered by the logistics center manager into specific actions and deadlines. For example, it converts an abstract task such as "check inventory" into a specific action such as "check inventory by October 10th."

[2062] 2. A way to manage the converted actions

[2063] The server stores the converted actions in a database and tracks the progress of each action, including information such as the action's due date, who is responsible for it, and its status.

[2064] 3. A way to periodically present the user with a list of actions

[2065] The server periodically sends the action list to the worker's device and displays it through a user interface, allowing the worker to see the current tasks and their due dates.

[2066] 4. Automating simple actions

[2067] The server automatically executes simple actions when certain conditions are met, such as automatically issuing a replenishment command when inventory falls below a certain level.

[2068] 5. A way to sort actions based on due date, with the most recent due first

[2069] The server sorts the action list based on due date and displays it on the worker's terminal in order of the nearest due date, allowing the worker to process the highest priority tasks first.

[2070] 6. When a user completes an action, a way to remove it from the list and display incomplete actions.

[2071] When a worker reports completion of an action via a terminal, the server removes that action from the list and displays only incomplete actions.

[2072] Hardware and software used

[2073] Hardware: Servers, smartphones, smart glasses

[2074] Software: Python (programming language), database management system (e.g., MySQL), user interface (e.g., React Native)

[2075] Specific examples

[2076] A logistics center worker puts on smart glasses and launches a task management application. The application sorts today's tasks by due date and displays those that need to be completed earliest. When the worker completes the "stock shelves" task, it disappears from the smart glasses display and the next task, "prepare for shipment," appears.

[2077] Prompt Sentence Examples

[2078] Develop an application that uses smart glasses to help logistics center workers efficiently manage their daily tasks. Tasks are sorted by due date and displayed in order of closest due date. When a worker completes a task, it is automatically removed from the list, and incomplete tasks continue to be displayed. Write the program using Python.

[2079] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2080] Step 1:

[2081] The server receives abstract tasks from the logistics center manager. The input is the task outline entered by the manager, and the output is the task converted into specific actions and due dates. The server analyzes the task content and generates specific actions and due dates.

[2082] Step 2:

[2083] The server saves the converted actions in a database. The input is the specific action and due date, and the output is the task information saved in the database. The server records information such as the action details, due date, and responsible person in the database.

[2084] Step 3:

[2085] The server periodically sends an action list to the worker's terminal. The input is task information stored in the database, and the output is an action list displayed on the worker's terminal. The server acquires the task information and presents it to the worker through a user interface.

[2086] Step 4:

[2087] The server automatically executes simple actions when certain conditions are met. The input is task information that meets the conditions, and the output is the result of the automatically executed action. For example, the server may automatically instruct replenishment when inventory falls below a certain level.

[2088] Step 5:

[2089] The server sorts the action list based on the due date and displays it on the worker's terminal in order of the nearest due date. The input is the task information stored in the database, and the output is the sorted action list. The server sorts the list based on the due date of the task, displaying the highest priority tasks at the top.

[2090] Step 6:

[2091] When a user completes an action, the information is sent to the server via the terminal. The input is the reported task information, and the output is an updated action list. The server then removes the completed task from the list and displays only the incomplete tasks.

[2092] Step 7:

[2093] The server updates the action list based on the user's actions. The input is the user's action data, and the output is the latest action list. The server monitors the user's progress and updates the task priority and content as needed.

[2094] Example 3

[2095] Next, a third embodiment of the third embodiment will be described. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[2096] Conventional task management systems require users to manually manage tasks and check their progress, making efficient task management difficult. They also lack the functionality to automatically execute simple actions, which increases the workload for users. Furthermore, they lack sufficient notification functions to periodically check task progress, which increases the risk of users forgetting to complete tasks.

[2097] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[2098] In this invention, the server includes means for converting abstract tasks into specific actions and deadlines, means for managing the converted actions, means for periodically presenting an action list to the user, means for automatically executing simple actions, means for the user to input tasks, means for the server to save the tasks in a database, means for the server to periodically check the tasks, means for the server to notify the user of incomplete tasks, and means for the server to automatically execute simple actions. This allows the user to efficiently manage tasks and progress them without hassle.

[2099] An "abstract task" is a general task or goal without specific actions or deadlines.

[2100] "Specific actions" refer to concrete tasks or procedures that transform abstract tasks into executable forms.

[2101] A "deadline" refers to the date and time when a task or action should be completed.

[2102] An "action list" is a list of specific actions that a user should perform.

[2103] "User" refers to an individual or organization that uses the system to manage tasks.

[2104] A "server" is a computer system that serves as the core of a task management system and stores and processes data.

[2105] A "database" refers to a system for organizing and storing information about tasks and actions.

[2106] "Notification" refers to a message sent by the server to inform the user of the progress of a task or an uncompleted task.

[2107] "Simple actions" refer to tasks that can be automated relatively easily, such as sending emails or setting reminders.

[2108] A "reminder" refers to a notification that reminds a user to perform a specific task or action.

[2109] MODE FOR CARRYING OUT THE INVENTION

[2110] The present invention is a system for improving the efficiency of task management for users, which is realized through the interaction between a server, a terminal, and a user. A specific embodiment of this system will be described below.

[2111] Hardware and software used

[2112] Hardware: Servers, user devices (PCs, smartphones, etc.)

[2113] Software: Task management applications, notification systems, email sending systems, reminder setting systems

[2114] Data processing and calculation

[2115] 1. The user enters a task

[2116] The user uses the terminal to open a task management application.

[2117] The user enters a new task and enters the required information (task name, due date, reminder settings, etc.).

[2118] Example: A user enters a task "Prepare for a meeting" and sets the due date to "Tomorrow at 10:00 AM."

[2119] 2. The server saves the task in the database

[2120] After the user inputs the task, the terminal sends the information to the server.

[2121] The server stores the received task information in a database.

[2122] Example: The server saves the task "Prepare for meeting" in the database.

[2123] 3. The server periodically checks for tasks

[2124] The server checks the database at a set time (for example, 9:00 every morning) and retrieves any uncompleted tasks.

[2125] The server lists the acquired incomplete tasks.

[2126] Example: Every morning at 9am the server checks the database and lists all outstanding tasks.

[2127] 4. The server notifies the user of outstanding tasks

[2128] The server notifies the user's terminal of the list of uncompleted tasks.

[2129] The user receives a notification on the device and checks the incomplete tasks.

[2130] Example: The server sends a notification to the user's smartphone saying, "Good morning. You have uncompleted tasks. Please check them."

[2131] 5. The server automatically executes simple actions

[2132] The server periodically checks simple actions set by the user (e.g., "send email" or "set reminder").

[2133] When the conditions are met, the server automatically calls an email sending system or a reminder setting system to perform an action.

[2134] Example: If a user sets a task to "set a reminder every Monday," the server will call the reminder setting system every Monday and automatically set the reminder.

[2135] Specific examples

[2136] Presenting an action list

[2137] Every morning at 9:00, the server retrieves the user's uncompleted tasks from the database and notifies the user's smartphone.

[2138] For example: "Good morning. You have some uncompleted tasks. Please take a look."

[2139] Automatic execution of simple actions

[2140] If a user sets a task to "set a reminder every Monday," the server will call the reminder setting system every Monday and automatically set the reminder.

[2141] For example: "I've set a reminder. Our next meeting is on Monday at 10am."

[2142] Example prompts for generative AI models

[2143] "Please create a program that notifies the user of their incomplete tasks every morning at 9am."

[2144] "Create a program that automatically executes simple actions set by the user."

[2145] In this way, the user can efficiently manage his or her tasks and progress the tasks without any hassle. The flow of the specific processing in the third embodiment will be described with reference to FIG.

[2146] Step 1:

[2147] The user enters a task

[2148] Input: The user uses a device to open a task management application and enter a new task.

[2149] Data processing: The application receives information entered by the user, such as task name, deadline, and reminder settings.

[2150] Output: The terminal sends the input task information to the server.

[2151] Specific behavior: The user clicks the "Add new task" button, enters the task name "Prepare for meeting", sets the due date to "Tomorrow at 10:00 AM", and clicks the "Save" button.

[2152] Step 2:

[2153] The server saves the task in a database

[2154] Input: Task information sent from the terminal.

[2155] Data processing: The server analyzes the task information received and converts it into a format suitable for saving in the database.

[2156] Output: The server saves the task information to the database and sends a confirmation message to the terminal.

[2157] Specific operation: The server saves the task "Prepare for meeting" to the database and sends a confirmation message "Task saved successfully" to the terminal.

[2158] Step 3:

[2159] The server periodically checks for tasks

[2160] Input: Task information stored in the database.

[2161] Data processing: The server queries the database at a set time (for example, every morning at 9:00) to retrieve incomplete tasks.

[2162] Output: List of open tasks retrieved by the server.

[2163] What it does: Every morning at 9am, the server checks the database and lists all uncompleted tasks.

[2164] Step 4:

[2165] The server notifies the user of outstanding tasks

[2166] Input: A list of open tasks.

[2167] Data processing: The server converts the list of incomplete tasks into a format that can be sent to the user's device.

[2168] Output: The server notifies the user of the list of uncompleted tasks on their device.

[2169] Specific behavior: The server sends a notification to the user's smartphone saying, "Good morning. You have uncompleted tasks. Please check them."

[2170] Step 5:

[2171] The server automatically executes simple actions

[2172] Input: A simple action set by the user (e.g., "send email" or "set reminder").

[2173] Data processing: When the conditions are met, the server automatically calls an email sending system or reminder setting system to execute an action.

[2174] Output: The server performs a simple action and notifies the user of the result.

[2175] Specific behavior: If a user sets a task to "set a reminder every Monday," the server will call the reminder setting system every Monday and automatically set the reminder.

[2176] (Application example 3) ...

Claims

1. A means of translating abstract tasks into concrete actions and deadlines; A means for managing the converted actions; a means for periodically presenting to a user an action list including the action; means for automatically executing the action when a predetermined condition is satisfied; means for detecting an emotional state of a user; means for controlling automatic execution of a task in response to said emotional state; means for identifying outstanding tasks at a predetermined time and performing or pausing the outstanding tasks based on said emotional state; A system including:

2. The system further includes a means for providing feedback to the user on the execution status of the embodied action. The system of claim 1 .

3. and a means for controlling automatic execution of the task using a generative AI model based on a prompt sentence corresponding to the user's emotion. The system of claim 1 .

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