system

Abstract

Provide a system. 【Solution means】 An interface means for the user to input a preset goal, A means for storing the input goal information, A means for generating a task based on the stored goal information, A means for scheduling the generated task over a certain period, A means for synchronizing the arranged schedule with a schedule management system, A communication means for the user to report the progress of a task, A means for storing the reported progress information, A means for adjusting a task based on the stored progress information, A system including a means for notifying the adjusted task.

Description

Technical Field

[0004] , ,

[0005] , ,

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Conventional AI chatbots have insufficient long-term support for goal achievement, and there are problems in scheduling and progress management for achieving the goals set by users. In addition, since users cannot receive appropriate feedback or suggestions according to their own progress, it has been difficult to maintain continuous motivation towards the goals.

Means for Solving the Problems

[0005] The present invention provides an interface means for a user to input pre-set goals and means for storing the input goal information. Furthermore, it includes means for generating tasks based on the stored goal information and means for scheduling the generated tasks over a certain period of time. It also includes means for providing communication means for the user to report the progress of tasks through means for synchronizing the scheduled tasks with a scheduling management system, and means for storing the reported progress information. The system provides appropriate feedback and suggestions to the user through means for adjusting tasks based on the stored progress information and means for notifying the user of the adjusted tasks. As a result, the user can act effectively toward their set goals and maintain sustained motivation.

[0006] "User" refers to an individual or group that uses this system.

[0007] "Interface means" refers to a screen or input device for the user to input a goal.

[0008] "Goal information" refers to data related to the goals set by the user.

[0009] "Storage means" refers to devices for recording target information, such as databases and storage devices.

[0010] "Task generation means" refers to a function that generates specific tasks to be performed in order to achieve a goal, based on the target information.

[0011] "Schedule placement means" refers to a function that places generated tasks over a certain period of time and creates a schedule.

[0012] A "schedule management system" refers to a tool or application for managing schedules and appointments.

[0013] "Communication methods" refer to messaging applications and other communication methods used by users to report the progress of tasks.

[0014] "Progress information" refers to data related to the achievement status of tasks reported by users.

[0015] "Feedback" refers to the responses and suggestions from the system regarding user activities and progress.

[0016] "Means for synchronization" refers to the function of coordinating the schedule with the schedule management system and matching the information.

Brief Description of Drawings

[0017] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12]It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when combined with an emotion engine. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when combined with an emotion engine.

Mode for Carrying Out the Invention

[0018] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0019] First, the terms used in the following description will be explained.

[0020] In the following embodiments, a numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units 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), and the like.

[0021] In the following embodiments, a numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0022] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0023] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0024] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0025] [First Embodiment]

[0026] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0027] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0028] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0029] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0030] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0031] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0032] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0033] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0034] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0035] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0036] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0037] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0038] This invention provides a system for users to set specific goals, schedule the tasks necessary to achieve those goals, and manage their progress. This system functions particularly effectively in business environments and provides a means for users to more easily achieve their long-term goals.

[0039] System Overview

[0040] This system includes an interface for users to set goals, means for generating tasks based on saved goal information, means for placing generated tasks on a schedule, means for synchronizing with a scheduling management system, communication means for reporting progress, and means for adjusting tasks based on saved progress information.

[0041] Program processing

[0042] User Goal Setting

[0043] User: Enter a specific goal, such as "lose 5kg in 100 days," using a dedicated interface.

[0044] Terminal: The goal entered by the user is temporarily saved to a buffer, and a submit button is provided.

[0045] User: Click the submit button to send the target information.

[0046] Terminal: Sends target information to the server in HTTP request format.

[0047] Server: Stores received target information in the database.

[0048] Schedule creation

[0049] Server: Activates the task generation algorithm based on the target information.

[0050] Server: Generates specific tasks (e.g., exercise three times a week, daily meal management tasks).

[0051] Server: Place these tasks on a 100-day schedule.

[0052] Server: Synchronizes schedules generated using the Google Calendar API with the scheduling management system.

[0053] Device: The user's schedule is displayed in Google Calendar.

[0054] Progress Monitoring

[0055] User: Report daily task progress via LINE chat. Send a message like, "I went for a 30-minute run today."

[0056] Terminal: Temporarily stores received progress information and sends it to the server.

[0057] Server: Saves progress information to the database.

[0058] Proposal adjustment

[0059] Server: Analyzes progress data and evaluates the task's completion status.

[0060] Server: Generates new suggestions as needed. For example, it might suggest adjusting the difficulty level or introducing new exercise methods.

[0061] Server: Sends suggestions to users via the LINE API.

[0062] Device: Display new suggestions to users via LINE chat.

[0063] User: Review the new suggestion and take the next step. Accept the suggestion, "Let's try a 10-minute walk today."

[0064] Specific example

[0065] If a user sets a goal of "losing 5kg in 100 days" on the first day, the system automatically generates 100 days' worth of exercise and diet management tasks and registers them in Google Calendar. The user reports daily via LINE chat, "I ran for 30 minutes today," and the server monitors the progress. If exercise is not performed for three consecutive days, the system notifies the user via LINE chat with a new suggestion, such as "Let's start with a light walk today." In this way, users can receive continuous and effective support towards achieving their goals.

[0066] As described above, the present invention realizes a system that provides comprehensive support for effectively achieving user-defined goals.

[0067] The following describes the processing flow.

[0068] Step 1:

[0069] User: Enter a goal, such as "lose 5kg in 100 days," using the dedicated interface.

[0070] Step 2:

[0071] Terminal: Temporarily saves the goal information entered by the user and displays a submit button.

[0072] Step 3:

[0073] User: Click the submit button to send the target information.

[0074] Step 4:

[0075] Terminal: Sends target information to the server in HTTP request format.

[0076] Step 5:

[0077] Server: Stores received target information in the database.

[0078] Step 6:

[0079] Server: Activates the task generation algorithm based on the saved target information.

[0080] Step 7:

[0081] Server: Generates specific tasks (e.g., exercise three times a week or daily meal management).

[0082] Step 8:

[0083] Server: Places the generated tasks into a 100-day schedule.

[0084] Step 9:

[0085] Server: Uses the Google Calendar API to synchronize the generated schedule with the scheduling management system.

[0086] Step 10:

[0087] Device: Displays the user's schedule in Google Calendar.

[0088] Step 11:

[0089] User: Report daily task progress via LINE chat. Send a message like, "I went for a 30-minute run today."

[0090] Step 12:

[0091] Terminal: Temporarily stores received progress information and sends it to the server as an HTTP request.

[0092] Step 13:

[0093] Server: Saves progress information to the database.

[0094] Step 14:

[0095] Server: Analyzes progress data and evaluates task completion status.

[0096] Step 15:

[0097] Server: Generates new suggestions as needed. For example, it might suggest, "Let's try a 10-minute walk today."

[0098] Step 16:

[0099] Server: Sends suggestions to users via the LINE API.

[0100] Step 17:

[0101] Device: Display new suggestions to users via LINE chat.

[0102] Step 18:

[0103] User: Review the suggestion and take the next step. Accept the suggestion, saying, "Let's try a 10-minute walk today."

[0104] (Example 1)

[0105] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0106] Traditional task management systems struggled to effectively generate and schedule tasks based on user-defined goals. In particular, maintaining user motivation was difficult in managing progress toward long-term goals, and there was a lack of proper analysis of progress information and provision of new suggestions.

[0107] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0108] In this invention, the server includes an interface means for the user to input pre-set goals, means for storing the input goal information, means for generating tasks based on the stored goal information, means for scheduling the generated tasks over a certain period of time, means for synchronizing the scheduled tasks with a scheduling management system, communication means for the user to report the progress of tasks, means for storing the reported progress information, means for adjusting tasks based on the stored progress information, means for notifying the user of the adjusted tasks, a server for activating a task generation algorithm, means for synchronizing the generated schedule via an API, and a server for analyzing progress data and generating new suggestions. This enables the user to effectively set and manage long-term goals and receive appropriate suggestions based on their progress.

[0109] "Interface means" refers to an input device or software for the user to input a target.

[0110] "Goal information" refers to data related to the goals that the user has set and aims to achieve.

[0111] A "storage method" is a database or storage device for storing target information and progress information.

[0112] A "task generation algorithm" is a program that automatically generates specific tasks based on objective information.

[0113] "Means of scheduling" refers to a program or function that schedules generated tasks over a specific period of time.

[0114] A "schedule management system" is software or a service used to manage schedules.

[0115] "Communication means" refers to a device or function for receiving progress reports from users.

[0116] "Progress information" refers to data about the progress of tasks performed by the user.

[0117] "Means of adjusting tasks" refers to a program or function that modifies or rearranges the original task based on saved progress information.

[0118] "Means of notification" refers to a device or software used to notify the user after the task has been adjusted.

[0119] A "server" is a computer system used to perform various actions and functions.

[0120] An "API" is an interface that enables communication between different software components.

[0121] A "proposal generation server" is a computer system that analyzes progress data and provides new suggestions to users.

[0122] This invention provides a system for users to set specific goals, schedule the tasks necessary to achieve those goals, and manage their progress. This system functions particularly effectively in business environments and provides a means for users to more easily achieve their long-term goals. Embodiments of this system are described in detail below.

[0123] System Configuration

[0124] This system includes the following main components:

[0125] 1. Interface means: This refers to an input device or software for the user to input a goal. For example, a web interface or a mobile application falls into this category. The user uses this interface to input the goal.

[0126] 2. Storage means: A database or storage device for storing the entered target information and progress information. In this embodiment, a MySQL database is used.

[0127] 3. Task Generation Algorithm: This program generates specific tasks based on objective information. This algorithm is implemented in Python.

[0128] 4. Means of placing tasks on a schedule: This is a program or function that places generated tasks on a schedule over a certain period of time. This is also implemented in Python, and this schedule is synchronized with an online calendar using the Google Calendar API.

[0129] 5. Communication means: A device or function for receiving progress reports from users. In particular, progress is received using a messaging application (e.g., LINE API).

[0130] 6. Means of adjusting tasks: This is a program or function that modifies or rearranges the original task based on saved progress information. This part will also be implemented as a Python script.

[0131] 7. Proposal generation server: This is a computer system that analyzes progress data and generates new proposals.

[0132] Specific example

[0133] Below is a specific example scenario for setting the goal of "losing 5 kg in 100 days."

[0134] First, the user enters a goal, such as "lose 5kg in 100 days," using a dedicated interface. The terminal temporarily stores this goal information in a buffer and displays a send button. When the user clicks the send button, the terminal sends the goal information to the server in the form of an HTTP request. The server stores the received goal information in its database.

[0135] Next, the server activates a task generation algorithm based on the stored goal information. This algorithm generates specific tasks, such as "exercise three times a week" or "daily meal management tasks." These tasks are placed on a 100-day schedule, and the server synchronizes this with an online calendar using the Google Calendar API.

[0136] Users report their daily task progress via LINE. For example, they might send a LINE chat message saying, "I went for a 30-minute run today." The device sends the received progress information to the server, which stores the information in a database. The server analyzes the progress data and generates new suggestions as needed. For example, it might send a suggestion like, "Let's start with a light walk today," to the user via the LINE API. The device then displays this suggestion to the user in a LINE chat.

[0137] Input prompts for the generative AI model

[0138] "Please create a program that automatically generates a schedule and tasks for losing 5kg in 100 days, and manages progress using Google Calendar and LINE. Also, please provide new suggestions if progress is unsatisfactory."

[0139] Thus, the system of the present invention provides integrated management and support for effectively achieving user-defined goals.

[0140] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0141] Step 1:

[0142] The user enters their goal into a dedicated interface.

[0143] Input: A specific goal such as "lose 5kg in 100 days."

[0144] Output: A format in which target information is temporarily stored on the device.

[0145] Specific action: The user enters a goal into a web interface or mobile app and clicks the "Submit" button.

[0146] Step 2:

[0147] The device sends target information to the server.

[0148] Input: Goal information entered by the user.

[0149] Output: Target information is sent to the server in JSON format.

[0150] Specific operation: JavaScript code sends the form data to the server as an HTTP POST request.

[0151] Step 3:

[0152] The server saves the received target information to the database.

[0153] Input: Target information sent from the device.

[0154] Output: Target information is saved to the database.

[0155] Specific operation: Using the Flask framework in Python, received data is stored in a MySQL database using SQL queries.

[0156] Step 4:

[0157] The server activates a task generation algorithm based on the target information.

[0158] Input: Target information stored in the database.

[0159] Output: The generated task list.

[0160] Specific operation: A Python script is launched, generating a task list tailored to the goal.

[0161] Step 5:

[0162] The server places the generated tasks into a 100-day schedule.

[0163] Input: The generated task list.

[0164] Output: Schedule information.

[0165] Specific operation: Arrange the task list in a calendar format, calculate the schedule for each day, and create a 100-day schedule.

[0166] Step 6:

[0167] The server synchronizes schedules generated using the Google Calendar API.

[0168] Input: 100-day schedule.

[0169] Output: Schedule added to Google Calendar.

[0170] Specific action: Call the Google Calendar API and add the schedule information to the user's Google Calendar.

[0171] Step 7:

[0172] The device displays the user's schedule in Google Calendar.

[0173] Input: Current schedule information from the Google Calendar API.

[0174] Output: The schedule displayed in the user's Google Calendar.

[0175] Specific operation: The schedule is displayed through the Google Calendar app or web interface.

[0176] Step 8:

[0177] Users report the progress of their daily tasks via LINE.

[0178] Input: Progress report such as "I went for a 30-minute run today."

[0179] Output: Progress information is temporarily saved to the device.

[0180] Specific action: The user opens the LINE app and sends a progress report to a designated bot.

[0181] Step 9:

[0182] The terminal sends the received progress information to the server.

[0183] Input: Progress information received via LINE.

[0184] Output: Progress information is sent to the server in JSON format.

[0185] Specific operation: Received messages using the LINE Messaging API are temporarily stored and then sent to the server via an HTTP request.

[0186] Step 10:

[0187] The server saves progress information to the database.

[0188] Input: Progress information sent from the device.

[0189] Output: Progress information is saved to the database.

[0190] Specific operation: The received progress information is parsed in JSON format and added to the database using an SQL query.

[0191] Step 11:

[0192] The server analyzes the progress data and evaluates the task's completion status.

[0193] Input: Progress data stored in the database.

[0194] Output: Analysis results and proposed solutions.

[0195] Specific operation: A Python script analyzes progress data and runs an algorithm to evaluate the degree of task completion.

[0196] Step 12:

[0197] The server generates new suggestions as needed.

[0198] Input: Analysis results of progress data.

[0199] Output: New proposal.

[0200] Specific operation: Based on the progress status, an algorithm is applied to suggest the next action, generating a new proposal.

[0201] Step 13:

[0202] The server sends the suggestion to the user via the LINE API.

[0203] Input: Generated suggestion content.

[0204] Output: The suggestion message sent to the user.

[0205] Specific operation: Use the LINE Messaging API to send the generated suggestions to the user as text messages.

[0206] Step 14:

[0207] The device displays new suggestions to the user via LINE chat.

[0208] Input: Suggestion message sent from the server.

[0209] Output: The suggestion message displayed to the user.

[0210] Specific action: A notification will be displayed within the user's LINE app.

[0211] Step 15:

[0212] The user reviews the new proposal and takes the next step.

[0213] Input: Suggestions from the server.

[0214] Output: The user's next action.

[0215] Specific actions: Review the proposal and begin taking action according to the day's schedule.

[0216] (Application Example 1)

[0217] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0218] In conventional factory production, task management and scheduling by robots are often done manually, resulting in inefficiencies and a lack of accuracy. Furthermore, real-time progress monitoring and task adjustments based on progress information are difficult, leading to decreased production efficiency. Additionally, limited communication methods for proper task progress reporting result in insufficient coordination between managers and robots. This creates a challenge in the overall functioning of factory production management.

[0219] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0220] In this invention, the server includes an interface means for a user to input pre-set goals, means for storing the input goal information, means for generating tasks based on the stored goal information, means for scheduling the generated tasks over a certain period of time, means for synchronizing the scheduled tasks with a scheduling management system, communication means for the user to report the progress of tasks, means for storing the reported progress information, means for adjusting tasks based on the stored progress information, means for notifying the user of the adjusted tasks, means for assigning tasks to production equipment, means for monitoring the progress of tasks performed by robots in real time, means for storing and analyzing progress information in a database, and means for fine-tuning tasks and generating new suggestions based on the analysis results. This enables efficient scheduling and management of production tasks by factory robots, and is expected to improve production efficiency through real-time progress monitoring and adjustment.

[0221] "Production equipment" is a general term for the equipment and devices used in manufacturing sites such as factories, and especially includes robots and automated machinery.

[0222] A "task" is a unit of work or activity set up to achieve a specific goal, and refers to the specific work that must be accomplished in a production process.

[0223] "Progress monitoring" is a process of tracking the status of task completion in real time and evaluating the degree of achievement and progress.

[0224] "Task adjustment" is the process of modifying the content and schedule of existing tasks based on the results of progress monitoring.

[0225] "Interface means" refers to the means by which a user inputs instructions into a system, and specifically includes touchscreens and keyboards.

[0226] "Storage methods" refer to means of temporarily or long-term storage of entered information, and specifically include hard disks and databases.

[0227] "Methods for scheduling" refer to methods for planning generated tasks over a certain period and scheduling tasks according to that plan.

[0228] A "schedule management system" is a system for organizing and managing tasks and other work along a timeline, and specifically includes online calendars.

[0229] "Communication methods" refer to means of sending and receiving information between users and systems, and specifically include the internet and messaging applications.

[0230] A "database" is a management system for systematically storing and managing information, enabling the efficient storage, retrieval, and manipulation of multiple datasets.

[0231] "Means of generating proposals" refers to methods for creating new work plans or adjustment plans based on progress data and task status.

[0232] "Means of synchronization" refer to methods for matching information and data across multiple systems and devices, which enables real-time data sharing.

[0233] The system for carrying out this invention provides a comprehensive solution for users to efficiently manage production equipment and effectively perform robotic production tasks. Specific embodiments of this system are described below.

[0234] User Interface

[0235] The interface for users to input pre-set goals can be operated via a touchscreen or keyboard. Using this interface, users can set goals such as "have a robot assemble product A." The entered goal information is temporarily stored in a buffer and then sent to the server. This information is stored in a database and used in subsequent processing.

[0236] Task generation and scheduling

[0237] The server generates tasks based on the goal information set by the user. This task generation process defines specific tasks, such as "installing part A" or "inspection process." The generated tasks are then scheduled over a specific period. Algorithms such as Scikit-learn are used for task scheduling to place tasks within optimal timeframes.

[0238] The generated schedule is synchronized with Google Calendar and other online calendars, allowing users to easily see the overall picture of their tasks through the scheduling management system.

[0239] Progress monitoring and data storage

[0240] As the robot performs each task, its progress is monitored in real time. The MQTT protocol is used for this monitoring, and progress data is sent to a server. This progress information is stored in a database and used for subsequent analysis.

[0241] Adjustments and proposals based on progress information

[0242] The saved progress data is analyzed on the server. If the progress is behind the goal, the server generates new suggestions to fine-tune the task. These suggestions, such as "Let's start with a lighter task," are sent to the user. LINE or other messaging applications are used for these notifications.

[0243] Specific example

[0244] If the factory manager sets on the first day to "assign the assembly task of product A to the robot," the system automatically generates 100 days' worth of assembly and quality check tasks and registers them in Google Calendar. Each time the robot completes a task, progress information is reported sequentially via the MQTT protocol, and the server saves this information to a database. If a task is not completed for three consecutive days, the system notifies the user via LINE chat with a new suggestion, such as "Let's start with a lighter checking process."

[0245] Example of a prompt

[0246] "Generate a schedule for the factory robot to perform the assembly task of part A between 2 PM and 4 PM every day. If the progress report is delayed, generate and submit a new proposal."

[0247] In this way, users can effectively manage production equipment and receive continuous support towards achieving their goals. Furthermore, since robot tasks are managed efficiently, overall production efficiency improves.

[0248] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0249] Step 1:

[0250] To set a goal, the user inputs the specific goal on the terminal using an interface. This input information is temporarily stored in a buffer and, after pressing the send button, is sent to the server in the form of an HTTP request. The server stores the received goal information in its database.

[0251] Input: User-entered goal information (e.g., "Have a robot assemble product A")

[0252] Data processing: Temporarily stored in a buffer, then converted to HTTP request format.

[0253] Output: Target information sent to the server

[0254] Step 2:

[0255] The server invokes a task generation algorithm based on the objective information to generate specific tasks. This uses Scikit-learn to optimally generate tasks that correspond to the objective.

[0256] Input: Saved target information

[0257] Data processing: Data calculations using task generation algorithms

[0258] Output: A specific task list has been generated (e.g., "Installation of part A", "Checking process")

[0259] Step 3:

[0260] The generated tasks are placed on a schedule over a set period. The server places the tasks in the most suitable time slots and synchronizes them with the online calendar using the Google Calendar API.

[0261] Input: Generated task list

[0262] Data processing: Task scheduling and synchronization with Google Calendar

[0263] Output: Schedule displayed in the scheduling management system

[0264] Step 4:

[0265] As the robot performs each task, its progress is monitored in real time. Progress data is sent from the robot to the server using the MQTT protocol. The server stores the received progress information in a database.

[0266] Input: Progress data sent from the robot

[0267] Data processing: Real-time data collection using the MQTT protocol.

[0268] Output: Progress information saved on the server

[0269] Step 5:

[0270] The server analyzes the stored progress data and evaluates the task's completion status. If progress is behind the target, the server generates new suggestions as needed.

[0271] Input: Saved progress data

[0272] Data processing: Analysis and evaluation of progress data

[0273] Output: New suggestion (e.g., "Let's start with a simple checking process")

[0274] Step 6:

[0275] The server notifies the user of newly generated suggestions. This notification is typically sent using a messaging application, such as LINE Talk. The user then reviews the suggestions and takes the next action.

[0276] Input: Generated proposal

[0277] Data processing: Message generation and sending

[0278] Output: Suggestions notified to the user

[0279] Through the above processing steps, the system can efficiently manage and coordinate production tasks performed by factory robots, providing continuous support to the user.

[0280] Furthermore, an emotion engine for estimating the user's emotion may be combined. That is, the specific processing unit 290 may estimate the user's emotion using the emotion specific model 59 and perform specific processing using the user's emotion.

[0281] The present invention combines an emotion engine with a system that schedules tasks necessary to achieve a goal preset by a user and manages the progress. This system recognizes emotions from text and voice data input by the user and provides appropriate feedback and suggestions based on them. This supports the user to be able to act while maintaining motivation towards the goal continuously.

[0282] Overview of the System

[0283] This system includes interface means for the user to input a goal, means for storing the input goal information, means for generating tasks based on the stored goal information, means for arranging the generated tasks in a schedule, means for synchronizing with a schedule management system, communication means for the user to report task progress, emotion recognition means by an emotion engine, means for adjusting tasks based on the stored progress information and the recognized emotion, and means for notifying the adjusted tasks and feedback.

[0284] Program Processing

[0285] User Goal Setting

[0286] User: Inputs a goal of "losing 5 kg in 100 days" using a dedicated interface.

[0287] Terminal: Temporarily stores the goal information input by the user and displays a send button.

[0288] User: Clicks the send button to send the goal information.

[0289] Terminal: Sends the goal information to the server in the form of an HTTP request.

[0290] Server: Stores received target information in the database.

[0291] Schedule creation

[0292] Server: Activates the task generation algorithm based on the target information.

[0293] Server: Generates specific tasks (e.g., exercise three times a week or daily meal management).

[0294] Server: Place these tasks on a 100-day schedule.

[0295] Server: Synchronizes schedules generated using the Google Calendar API with the scheduling management system.

[0296] Device: The user's schedule is displayed in Google Calendar.

[0297] Progress Monitoring

[0298] User: Report daily task progress via LINE chat. Send a message like, "I went for a 30-minute run today."

[0299] Terminal: Temporarily stores received progress information and sends it to the server as an HTTP request.

[0300] Server: Saves progress information to the database.

[0301] Server: Analyzes received text and audio data using an emotion engine to recognize the user's emotions.

[0302] Proposal adjustment

[0303] Server: Analyzes progress data and recognized sentiment information to evaluate task completion status.

[0304] Server: Generate new suggestions as needed. For example, if the user is feeling stressed, suggest "Let's start with a light walk today."

[0305] Server: Send the suggestion to the user via the LINE API.

[0306] Terminal: Display the new suggestion to the user in LINE Talk.

[0307] [[ID=,12]] User: Confirm the suggestion and move on to the next action. Accept "Let's try a 10 - minute walk today."

[0308] Specific Example [[ID=,19]]

[0309] On the first day, if the user sets "Lose 5 kg in 100 days", the system automatically generates exercise and diet management tasks for 100 days and registers them in Google Calendar. If the user reports "I ran for 30 minutes today" in LINE Talk every day, the server manages the progress and emotions. If the user fails to execute the tasks for three consecutive days, the system checks through the emotion engine whether the user is feeling fatigue or stress, and notifies a new suggestion "Let's start with a light walk today" in LINE Talk. In this way, the user can receive continuous and effective support towards achieving the goal.

[0310] As described above, the present invention realizes a system that provides comprehensive support for effectively achieving the goals set by the user. By introducing the emotion engine, flexible responses according to the user's emotional state become possible, making it easier to maintain motivation and overcome challenges.

[0311] The following describes the processing flow.

[0312] Step 1:

[0313] User: Enter a goal, such as "lose 5kg in 100 days," using the dedicated interface.

[0314] Step 2:

[0315] Terminal: Temporarily saves the goal information entered by the user and displays a submit button.

[0316] Step 3:

[0317] User: Click the submit button to send the target information.

[0318] Step 4:

[0319] Terminal: Sends target information to the server in HTTP request format.

[0320] Step 5:

[0321] Server: Stores received target information in the database.

[0322] Step 6:

[0323] Server: Activates the task generation algorithm based on the saved target information.

[0324] Step 7:

[0325] Server: Generates specific tasks (e.g., exercise three times a week or daily meal management).

[0326] Step 8:

[0327] Server: Places the generated tasks into a 100-day schedule.

[0328] Step 9:

[0329] Server: Uses the Google Calendar API to synchronize the generated schedule with the scheduling management system.

[0330] Step 10:

[0331] Device: Displays the user's schedule in Google Calendar.

[0332] Step 11:

[0333] User: Report daily task progress via LINE chat. Send a message like, "I went for a 30-minute run today."

[0334] Step 12:

[0335] Terminal: Temporarily stores received progress information and sends it to the server as an HTTP request.

[0336] Step 13:

[0337] Server: Saves progress information to the database.

[0338] Step 14:

[0339] Server: Analyzes progress data and evaluates task completion status.

[0340] Step 15:

[0341] Terminal: Sends text data and voice data sent by the user via LINE chat to the emotion engine.

[0342] Step 16:

[0343] Server: The emotion engine analyzes text and audio data to recognize the user's emotions. For example, it determines whether the user is feeling stressed.

[0344] Step 17:

[0345] Server: Combines recognized emotion information and progress data to generate new suggestions as needed. For example, if the user is feeling stressed, it might suggest, "Let's start today with a light walk."

[0346] Step 18:

[0347] Server: Sends suggestions to users via the LINE API.

[0348] Step 19:

[0349] Device: Display new suggestions to users via LINE chat.

[0350] Step 20:

[0351] User: Review the suggestion and take the next step. Accept the suggestion, saying, "Let's try a 10-minute walk today."

[0352] Step 21:

[0353] Server: After the user takes the next action, the new progress data is analyzed again by the sentiment engine, and the feedback loop continues.

[0354] (Example 2)

[0355] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0356] Traditional goal-achievement support systems have problems with efficiently scheduling the tasks necessary to achieve user-defined goals, and lacking appropriate feedback and suggestions tailored to the user's emotional state, as well as task progress management. Therefore, there is a need for a system that supports users in maintaining sustained motivation and taking action towards their goals.

[0357] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0358] In this invention, the server includes information input means for inputting goals set in advance by the user; information storage means for storing the input goal information; task generation means for generating tasks based on the stored goal information; schedule placement means for placing the generated tasks on a schedule over a certain period of time; synchronization means for synchronizing the placed schedule with a schedule management system; communication means for the user to report the progress of tasks; progress information storage means for storing the reported progress information; task adjustment means for adjusting tasks based on progress information and emotion information; notification means for notifying the user of adjusted tasks and suggestions; and emotion recognition means for analyzing the user's emotions. This enables the user to perform tasks while maintaining sustained motivation toward their goals.

[0359] "Information input means" refers to the interface through which the user inputs their goals.

[0360] "Information storage means" refers to data storage means for temporarily or permanently storing the input target information.

[0361] "Task generation means" refers to algorithms or software that generate specific tasks based on stored target information.

[0362] "Schedule placement means" refers to a function or system that places generated tasks on a schedule over a certain period of time.

[0363] "Synchronization means" refers to the function of synchronizing the placed schedule with the schedule management system and electronic calendar.

[0364] "Communication methods" refer to the communication infrastructure and applications that users use to report the progress of tasks.

[0365] "Progress information storage means" refers to a data storage means for saving progress information of tasks reported by users.

[0366] "Task adjustment means" refers to a function that modifies, updates, or proposes new tasks based on progress information and sentiment information.

[0367] "Notification means" refers to communication methods or systems used to notify users of adjusted tasks or new suggestions.

[0368] "Emotion recognition means" refers to algorithms and software used to analyze a user's emotions.

[0369] This invention relates to a system for scheduling tasks and managing progress to achieve user-defined goals. In particular, by incorporating an emotion engine, it is possible to provide appropriate feedback and suggestions according to the user's emotional state, thereby maintaining the user's motivation. This system includes information input means, information storage means, task generation means, schedule placement means, synchronization means, communication means, progress information storage means, task adjustment means, notification means, and emotion recognition means.

[0370] Hardware and software to be used

[0371] 1. Information Input Method: This is an interface for the user to input their goals. This is implemented in a web browser or mobile application.

[0372] 2. Information storage means: A storage system for temporarily storing the entered target information. A SQL-based database management system (DBMS) is used as the database.

[0373] 3. Task generation method: An algorithm that generates specific tasks based on objective information. This may involve using machine learning models or rule-based algorithms.

[0374] 4. Schedule Placement Method: A tool for scheduling generated tasks over a certain period. It can be integrated with a scheduling management system by using the Google Calendar API.

[0375] 5. Synchronization method: A system for synchronizing schedules with electronic calendars such as Google Calendar. This includes an authentication process using OAuth 2.0.

[0376] 6. Communication method: A messaging application for users to report task progress. LINE API or other messaging platforms will be used.

[0377] 7. Progress Information Storage Method: A system that stores progress information reported by users in a database. Data is managed using SQL.

[0378] 8. Task Adjustment Mechanism: A system for adjusting tasks based on progress information and emotional information. It uses an emotional engine to analyze the user's emotions and perform appropriate task adjustments.

[0379] 9. Notification Method: A system for notifying users of adjusted tasks and new suggestions. Notifications are sent using the LINE API.

[0380] 10. Emotion Recognition Methods: Algorithms for analyzing user emotions. Natural language processing (NLP) models and emotion analysis models are used.

[0381] Specific example

[0382] On the first day, when a user sets a goal of "losing 5kg in 100 days," the system automatically generates 100 days' worth of exercise and diet management tasks and registers them in Google Calendar. The user reports daily via LINE chat, "Today I went for a 30-minute run." The server receives this progress information and stores it in a database. It also uses an emotion engine to analyze the user's emotional state. Based on this information, if the user is feeling stressed, it notifies them via LINE chat with new suggestions, such as "Let's start with a light walk today." This allows the user to receive sustained and effective support towards achieving their goal.

[0383] Example of a prompt

[0384] "Set specific exercise and dietary tasks to lose 5kg in 100 days, and design a system to track your daily progress and emotions."

[0385] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0386] Step 1: Goal Setting

[0387] User: Enter your goal using the dedicated interface (e.g., "Lose 5kg in 100 days").

[0388] Input: Goal information entered by the user.

[0389] Output: Temporarily stored data on the interface.

[0390] Specific operation: The user fills in their goal in a dedicated input form and clicks the submit button.

[0391] Step 2: Send target information

[0392] Terminal: Temporarily stores the entered target information and displays a submit button. When the user clicks the submit button, the target information is sent to the server as an HTTP request.

[0393] Input: Temporarily saved target information.

[0394] Output: Target information sent to the server.

[0395] Specific operation: The terminal checks the target information and sends the data to the server in the form of an HTTP request. The POST method is used.

[0396] Step 3: Save the target information

[0397] Server: Stores received target information in the database.

[0398] Input: Target information from the HTTP request.

[0399] Output: Target information stored in the database.

[0400] Specific operation: The server parses the received target information and uses SQL queries to perform INSERT operations on the database.

[0401] Step 4: Task Generation

[0402] Server: Activates a task generation algorithm based on saved goal information to generate specific tasks (e.g., exercise three times a week or daily meal management).

[0403] Input: Target information stored in the database.

[0404] Output: Generated task (template).

[0405] Specific operation: The server generates task content using machine learning algorithms and rule-based algorithms.

[0406] Step 5: Schedule Placement

[0407] Server: Schedules the generated tasks for a set period of time.

[0408] Input: The generated task.

[0409] Output: 100-day schedule.

[0410] Specific operation: The server uses the Calendar API to map tasks to dates and times and place them as schedules.

[0411] Step 6: Synchronize with the scheduling management system

[0412] Server: Synchronizes schedules generated using the Google Calendar API with the scheduling management system.

[0413] Input: A 100-day schedule.

[0414] Output: Schedule synced to Google Calendar.

[0415] Specific operation: The server uses OAuth 2.0 for authentication and synchronizes schedules via the Calendar API.

[0416] Step 7: Progress Report

[0417] User: Report daily task progress via LINE chat (e.g., "I went for a 30-minute run today").

[0418] Input: Progress information reported by the user via LINE chat.

[0419] Output: Temporarily saved progress information.

[0420] Specific action: The user sends progress information in text format via LINE chat.

[0421] Step 8: Send progress information

[0422] Terminal: Temporarily stores received progress information and sends it to the server as an HTTP request.

[0423] Input: Progress information received via LINE chat.

[0424] Output: Progress information sent to the server.

[0425] Specific operation: The terminal checks the received progress information and sends the data to the server in the form of an HTTP request.

[0426] Step 9: Save progress information

[0427] Server: Saves progress information to the database.

[0428] Input: Progress information from the HTTP request.

[0429] Output: Progress information stored in the database.

[0430] Specific operation: The server parses the received progress information and uses SQL queries to perform INSERT operations on the database.

[0431] Step 10: Emotion Recognition

[0432] Server: Analyzes received text and audio data using an emotion engine to recognize the user's emotions.

[0433] Input: Progress information and text or audio data.

[0434] Output: Recognized emotion information.

[0435] Specific operation: The server uses a natural language processing (NLP) model to analyze text data and perform sentiment recognition.

[0436] Step 11: Task Adjustment

[0437] Server: Analyzes progress data and recognized sentiment information, evaluates task completion status, and generates new suggestions.

[0438] Input: Progress information and sentiment information stored in the database.

[0439] Output: Adjusted tasks or new proposals.

[0440] Specific operation: Use machine learning models to analyze progress and sentiment data and generate suggestions to reduce the user's burden as needed.

[0441] Step 12: Notification of Proposal

[0442] Server: Sends suggestions to users via the LINE API.

[0443] Input: Adjusted tasks or new proposals.

[0444] Output: Suggestion notification sent to the user.

[0445] Specific operation: The suggestion is sent to the user's messaging application using the LINE API.

[0446] Step 13: Review and implement the proposal

[0447] User: Review the suggestion and take the next step (e.g., "Let's try a 10-minute walk today").

[0448] Input: Suggestion notification sent from the server.

[0449] Output: New task executed.

[0450] Specific actions: The user reviews the received suggestions and takes action based on them.

[0451] (Application Example 2)

[0452] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0453] Traditional task management systems often assign tasks unilaterally, regardless of the user's emotional state, making it difficult to maintain motivation. Furthermore, in real-world settings such as retail stores, inadequate task and emotional management of staff can lead to decreased work efficiency and customer satisfaction. This can result in accumulated stress and fatigue among staff, ultimately leading to a decline in overall work performance.

[0454] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for storing goal information entered by the user, means for generating tasks based on the stored goal information, and means for scheduling the generated tasks over a certain period of time. This makes it possible to support the user in maintaining motivation and taking action towards their goals. It also includes emotion recognition means for recognizing emotions from text and voice data entered by the user, and means for providing feedback and suggestions based on the recognized emotions. This makes it possible to adjust tasks while taking into account the emotional state of the staff, thereby improving work performance and reducing stress.

[0455] A "user" is an individual or professional who sets goals and manages the progress of tasks.

[0456] "Interface means" refers to the means by which a user inputs a goal, and primarily refers to a graphical user interface (GUI).

[0457] "Goal information" refers to information about the goals that the user has set in advance and wants to achieve.

[0458] "Means of storage" refers to databases and storage devices used to store entered target information and progress information.

[0459] A "task" is a specific job or activity that needs to be performed in order to achieve a goal.

[0460] "Means of scheduling" refers to methods for systematically placing generated tasks within a specific timeframe, such as calendar applications.

[0461] A "schedule management system" is a system used for managing schedules, and includes online calendars and similar tools.

[0462] "Communication methods" refer to communication methods used by users to report the progress of tasks, and include messaging applications, etc.

[0463] "Reported progress information" refers to information that users have reported regarding the results of their task execution using communication methods.

[0464] "Emotion recognition means" refers to systems and algorithms for recognizing emotions from text or voice data entered by the user.

[0465] "Means of providing feedback and suggestions" refers to means of providing appropriate feedback and action suggestions based on perceived emotions, and includes using messaging applications to send notifications.

[0466]

[0467] To implement this invention, a smartphone application called "Smart Staff Manager" is used. The specific configuration and processing details are described below.

[0468] First, the user enters their goal through an interface that allows them to set their own goals. For example, let's say the goal is to "improve customer satisfaction by 20% in 100 days." This goal information is temporarily stored on the smartphone. When the user presses the submit button, the goal information is sent to the server as an HTTP request. The server then stores the received goal information in a database.

[0469] Next, the server activates a task generation algorithm based on the stored goal information to generate specific tasks (e.g., "clean shelves," "replenish product inventory," "customer service"). It then places these generated tasks into a 100-day schedule. The server uses the Google Calendar API to synchronize the generated schedule with an online calendar and display it in the user's calendar.

[0470] Users report the progress of their daily tasks, for example, using a messaging application. For instance, they might use LINE to report, "I finished cleaning the shelves today." The device temporarily stores this progress information and sends it to the server as an HTTP request. The server stores the progress information in a database and analyzes the text and audio data of the progress report using an emotion recognition engine called EmotionRecognizer to understand the user's emotions. Based on this emotion data, the server then adjusts the tasks.

[0471] Based on the emotion recognition information, for example, if the user is feeling stressed, the system generates a suggestion such as "Take a short break and try again" and notifies the user via the LINE API. Conversely, if the user completes a task and their emotion is "joy" or "satisfaction," the system provides feedback such as "Great job! Keep up the good work!"

[0472] This system makes it easier for users to consistently achieve their goals. Furthermore, by adjusting tasks to take staff emotional states into account, it can improve work performance and reduce stress.

[0473] As a concrete example, the system operates based on the following prompt:

[0474] User goal: "Improve customer satisfaction by 20% in 100 days"

[0475] Tasks: "Clean shelves, Restock items, Customer support"

[0476] Emotion data from text: "I'm feeling stressed"

[0477]

[0478] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0479] Step 1:

[0480] The user enters goal information through a dedicated interface. For example, they might enter a goal such as "Increase customer satisfaction by 20% in 100 days." The terminal temporarily stores this input data and displays a submit button for the user to confirm the input. When the user clicks the submit button, the goal information is sent from the terminal to the server as an HTTP request.

[0481] Input: User's goal information

[0482] Output: HTTP request sent to the server

[0483] Step 2:

[0484] The server stores the received target information in a database. Based on the stored target information, it activates a task generation algorithm. This algorithm generates specific tasks such as "cleaning shelves," "replenishing product inventory," and "customer service."

[0485] Input: Target Information

[0486] Output: Generated tasks

[0487] Step 3:

[0488] The server schedules the generated tasks over a 100-day period. Specifically, it uses the Google Calendar API to place each task on a specific date and synchronizes it with the online calendar. This allows users to check their schedule on their smartphone calendar.

[0489] Input: Generated tasks

[0490] Output: Online calendar placed schedule

[0491] Step 4:

[0492] Users report the progress of their daily tasks using a messaging application. For example, they might use LINE to report, "I finished cleaning the shelves today." The device temporarily stores this progress information and sends it to the server as an HTTP request.

[0493] Input: Task progress information

[0494] Output: HTTP request sent to the server

[0495] Step 5:

[0496] The server stores the received progress information in a database. Next, it uses an emotion recognition engine to analyze the text and audio data included in the progress report to recognize the user's emotions. For example, it extracts emotional states such as "stress" or "satisfaction" from the text.

[0497] Input: Task progress information

[0498] Output: Recognized emotion data

[0499] Step 6:

[0500] The server generates feedback and suggestions based on recognized emotion data and task progress information. For example, if the user is identified as "stressed," it might suggest, "Try taking a short break." This feedback and suggestions are then communicated to the user via the LINE API.

[0501] Input: Recognized emotion data, task progress information

[0502] Output: Feedback and suggestions notified to the user.

[0503] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0504] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include those described above. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions shown by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0505] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0506] [Second Embodiment]

[0507] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0508] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0509] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0510] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0511] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0512] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0513] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0514] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0515] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0516] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0517] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0518] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0519] This invention provides a system for users to set specific goals, schedule the tasks necessary to achieve those goals, and manage their progress. This system functions particularly effectively in business environments and provides a means for users to more easily achieve their long-term goals.

[0520] System Overview

[0521] This system includes an interface for users to set goals, means for generating tasks based on saved goal information, means for placing generated tasks on a schedule, means for synchronizing with a scheduling management system, communication means for reporting progress, and means for adjusting tasks based on saved progress information.

[0522] Program processing

[0523] User Goal Setting

[0524] User: Enter a specific goal, such as "lose 5kg in 100 days," using a dedicated interface.

[0525] Terminal: The goal entered by the user is temporarily saved to a buffer, and a submit button is provided.

[0526] User: Click the submit button to send the target information.

[0527] Terminal: Sends target information to the server in HTTP request format.

[0528] Server: Stores received target information in the database.

[0529] Schedule creation

[0530] Server: Activates the task generation algorithm based on the target information.

[0531] Server: Generates specific tasks (e.g., exercise three times a week, daily meal management tasks).

[0532] Server: Place these tasks on a 100-day schedule.

[0533] Server: Synchronizes schedules generated using the Google Calendar API with the scheduling management system.

[0534] Device: The user's schedule is displayed in Google Calendar.

[0535] Progress Monitoring

[0536] User: Report daily task progress via LINE chat. Send a message like, "I went for a 30-minute run today."

[0537] Terminal: Temporarily stores received progress information and sends it to the server.

[0538] Server: Saves progress information to the database.

[0539] Proposal adjustment

[0540] Server: Analyzes progress data and evaluates the task's completion status.

[0541] Server: Generates new suggestions as needed. For example, it might suggest adjusting the difficulty level or introducing new exercise methods.

[0542] Server: Sends suggestions to users via the LINE API.

[0543] Device: Display new suggestions to users via LINE chat.

[0544] User: Review the new suggestion and take the next step. Accept the suggestion, "Let's try a 10-minute walk today."

[0545] Specific example

[0546] If a user sets a goal of "losing 5kg in 100 days" on the first day, the system automatically generates 100 days' worth of exercise and diet management tasks and registers them in Google Calendar. The user reports daily via LINE chat, "I ran for 30 minutes today," and the server monitors the progress. If exercise is not performed for three consecutive days, the system notifies the user via LINE chat with a new suggestion, such as "Let's start with a light walk today." In this way, users can receive continuous and effective support towards achieving their goals.

[0547] As described above, the present invention realizes a system that provides comprehensive support for effectively achieving user-defined goals.

[0548] The following describes the processing flow.

[0549] Step 1:

[0550] User: Enter a goal, such as "lose 5kg in 100 days," using the dedicated interface.

[0551] Step 2:

[0552] Terminal: Temporarily saves the goal information entered by the user and displays a submit button.

[0553] Step 3:

[0554] User: Click the submit button to send the target information.

[0555] Step 4:

[0556] Terminal: Sends target information to the server in HTTP request format.

[0557] Step 5:

[0558] Server: Stores received target information in the database.

[0559] Step 6:

[0560] Server: Activates the task generation algorithm based on the saved target information.

[0561] Step 7:

[0562] Server: Generates specific tasks (e.g., exercise three times a week or daily meal management).

[0563] Step 8:

[0564] Server: Places the generated tasks into a 100-day schedule.

[0565] Step 9:

[0566] Server: Uses the Google Calendar API to synchronize the generated schedule with the scheduling management system.

[0567] Step 10:

[0568] Device: Displays the user's schedule in Google Calendar.

[0569] Step 11:

[0570] User: Report daily task progress via LINE chat. Send a message like, "I went for a 30-minute run today."

[0571] Step 12:

[0572] Terminal: Temporarily stores received progress information and sends it to the server as an HTTP request.

[0573] Step 13:

[0574] Server: Saves progress information to the database.

[0575] Step 14:

[0576] Server: Analyzes progress data and evaluates task completion status.

[0577] Step 15:

[0578] Server: Generates new suggestions as needed. For example, it might suggest, "Let's try a 10-minute walk today."

[0579] Step 16:

[0580] Server: Sends suggestions to users via the LINE API.

[0581] Step 17:

[0582] Device: Display new suggestions to users via LINE chat.

[0583] Step 18:

[0584] User: Review the suggestion and take the next step. Accept the suggestion, saying, "Let's try a 10-minute walk today."

[0585] (Example 1)

[0586] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0587] Traditional task management systems struggled to effectively generate and schedule tasks based on user-defined goals. In particular, maintaining user motivation was difficult in managing progress toward long-term goals, and there was a lack of proper analysis of progress information and provision of new suggestions.

[0588] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0589] In this invention, the server includes an interface means for the user to input pre-set goals, means for storing the input goal information, means for generating tasks based on the stored goal information, means for scheduling the generated tasks over a certain period of time, means for synchronizing the scheduled tasks with a scheduling management system, communication means for the user to report the progress of tasks, means for storing the reported progress information, means for adjusting tasks based on the stored progress information, means for notifying the user of the adjusted tasks, a server for activating a task generation algorithm, means for synchronizing the generated schedule via an API, and a server for analyzing progress data and generating new suggestions. This enables the user to effectively set and manage long-term goals and receive appropriate suggestions based on their progress.

[0590] "Interface means" refers to an input device or software for the user to input a target.

[0591] "Goal information" refers to data related to the goals that the user has set and aims to achieve.

[0592] A "storage method" is a database or storage device for storing target information and progress information.

[0593] A "task generation algorithm" is a program that automatically generates specific tasks based on objective information.

[0594] "Means of scheduling" refers to a program or function that schedules generated tasks over a specific period of time.

[0595] A "schedule management system" is software or a service used to manage schedules.

[0596] "Communication means" refers to a device or function for receiving progress reports from users.

[0597] "Progress information" refers to data about the progress of tasks performed by the user.

[0598] "Means of adjusting tasks" refers to a program or function that modifies or rearranges the original task based on saved progress information.

[0599] "Means of notification" refers to a device or software used to notify the user after the task has been adjusted.

[0600] A "server" is a computer system used to perform various actions and functions.

[0601] An "API" is an interface that enables communication between different software components.

[0602] A "proposal generation server" is a computer system that analyzes progress data and provides new suggestions to users.

[0603] This invention provides a system for users to set specific goals, schedule the tasks necessary to achieve those goals, and manage their progress. This system functions particularly effectively in business environments and provides a means for users to more easily achieve their long-term goals. Embodiments of this system are described in detail below.

[0604] System Configuration

[0605] This system includes the following main components:

[0606] 1. Interface means: This refers to an input device or software for the user to input a goal. For example, a web interface or a mobile application falls into this category. The user uses this interface to input the goal.

[0607] 2. Storage means: A database or storage device for storing the entered target information and progress information. In this embodiment, a MySQL database is used.

[0608] 3. Task Generation Algorithm: This program generates specific tasks based on objective information. This algorithm is implemented in Python.

[0609] 4. Means of placing tasks on a schedule: This is a program or function that places generated tasks on a schedule over a certain period of time. This is also implemented in Python, and this schedule is synchronized with an online calendar using the Google Calendar API.

[0610] 5. Communication means: A device or function for receiving progress reports from users. In particular, progress is received using a messaging application (e.g., LINE API).

[0611] 6. Means of adjusting tasks: This is a program or function that modifies or rearranges the original task based on saved progress information. This part will also be implemented as a Python script.

[0612] 7. Proposal generation server: This is a computer system that analyzes progress data and generates new proposals.

[0613] Specific example

[0614] Below is a specific example scenario for setting the goal of "losing 5 kg in 100 days."

[0615] First, the user enters a goal, such as "lose 5kg in 100 days," using a dedicated interface. The terminal temporarily stores this goal information in a buffer and displays a send button. When the user clicks the send button, the terminal sends the goal information to the server in the form of an HTTP request. The server stores the received goal information in its database.

[0616] Next, the server activates a task generation algorithm based on the stored goal information. This algorithm generates specific tasks, such as "exercise three times a week" or "daily meal management tasks." These tasks are placed on a 100-day schedule, and the server synchronizes this with an online calendar using the Google Calendar API.

[0617] Users report their daily task progress via LINE. For example, they might send a LINE chat message saying, "I went for a 30-minute run today." The device sends the received progress information to the server, which stores the information in a database. The server analyzes the progress data and generates new suggestions as needed. For example, it might send a suggestion like, "Let's start with a light walk today," to the user via the LINE API. The device then displays this suggestion to the user in a LINE chat.

[0618] Input prompts for the generative AI model

[0619] "Please create a program that automatically generates a schedule and tasks for losing 5kg in 100 days, and manages progress using Google Calendar and LINE. Also, please provide new suggestions if progress is unsatisfactory."

[0620] Thus, the system of the present invention provides integrated management and support for effectively achieving user-defined goals.

[0621] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0622] Step 1:

[0623] The user enters their goal into a dedicated interface.

[0624] Input: A specific goal such as "lose 5kg in 100 days."

[0625] Output: A format in which target information is temporarily stored on the device.

[0626] Specific action: The user enters a goal into a web interface or mobile app and clicks the "Submit" button.

[0627] Step 2:

[0628] The device sends target information to the server.

[0629] Input: Goal information entered by the user.

[0630] Output: Target information is sent to the server in JSON format.

[0631] Specific operation: JavaScript code sends the form data to the server as an HTTP POST request.

[0632] Step 3:

[0633] The server saves the received target information to the database.

[0634] Input: Target information sent from the device.

[0635] Output: Target information is saved to the database.

[0636] Specific operation: Using the Flask framework in Python, received data is stored in a MySQL database using SQL queries.

[0637] Step 4:

[0638] The server activates a task generation algorithm based on the target information.

[0639] Input: Target information stored in the database.

[0640] Output: The generated task list.

[0641] Specific operation: A Python script is launched, generating a task list tailored to the goal.

[0642] Step 5:

[0643] The server places the generated tasks into a 100-day schedule.

[0644] Input: The generated task list.

[0645] Output: Schedule information.

[0646] Specific operation: Arrange the task list in a calendar format, calculate the schedule for each day, and create a 100-day schedule.

[0647] Step 6:

[0648] The server synchronizes schedules generated using the Google Calendar API.

[0649] Input: 100-day schedule.

[0650] Output: Schedule added to Google Calendar.

[0651] Specific action: Call the Google Calendar API and add the schedule information to the user's Google Calendar.

[0652] Step 7:

[0653] The device displays the user's schedule in Google Calendar.

[0654] Input: Current schedule information from the Google Calendar API.

[0655] Output: The schedule displayed in the user's Google Calendar.

[0656] Specific operation: The schedule is displayed through the Google Calendar app or web interface.

[0657] Step 8:

[0658] Users report the progress of their daily tasks via LINE.

[0659] Input: Progress report such as "I went for a 30-minute run today."

[0660] Output: Progress information is temporarily saved to the device.

[0661] Specific action: The user opens the LINE app and sends a progress report to a designated bot.

[0662] Step 9:

[0663] The terminal sends the received progress information to the server.

[0664] Input: Progress information received via LINE.

[0665] Output: Progress information is sent to the server in JSON format.

[0666] Specific operation: Received messages using the LINE Messaging API are temporarily stored and then sent to the server via an HTTP request.

[0667] Step 10:

[0668] The server saves progress information to the database.

[0669] Input: Progress information sent from the device.

[0670] Output: Progress information is saved to the database.

[0671] Specific operation: The received progress information is parsed in JSON format and added to the database using an SQL query.

[0672] Step 11:

[0673] The server analyzes the progress data and evaluates the task's completion status.

[0674] Input: Progress data stored in the database.

[0675] Output: Analysis results and proposed solutions.

[0676] Specific operation: A Python script analyzes progress data and runs an algorithm to evaluate the degree of task completion.

[0677] Step 12:

[0678] The server generates new suggestions as needed.

[0679] Input: Analysis results of progress data.

[0680] Output: New proposal.

[0681] Specific operation: Based on the progress status, an algorithm is applied to suggest the next action, generating a new proposal.

[0682] Step 13:

[0683] The server sends the suggestion to the user via the LINE API.

[0684] Input: Generated suggestion content.

[0685] Output: The suggestion message sent to the user.

[0686] Specific operation: Use the LINE Messaging API to send the generated suggestions to the user as text messages.

[0687] Step 14:

[0688] The device displays new suggestions to the user via LINE chat.

[0689] Input: Suggestion message sent from the server.

[0690] Output: The suggestion message displayed to the user.

[0691] Specific action: A notification will be displayed within the user's LINE app.

[0692] Step 15:

[0693] The user reviews the new proposal and takes the next step.

[0694] Input: Suggestions from the server.

[0695] Output: The user's next action.

[0696] Specific actions: Review the proposal and begin taking action according to the day's schedule.

[0697] (Application Example 1)

[0698] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0699] In conventional factory production, task management and scheduling by robots are often done manually, resulting in inefficiencies and a lack of accuracy. Furthermore, real-time progress monitoring and task adjustments based on progress information are difficult, leading to decreased production efficiency. Additionally, limited communication methods for proper task progress reporting result in insufficient coordination between managers and robots. This creates a challenge in the overall functioning of factory production management.

[0700] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0701] In this invention, the server includes an interface means for a user to input pre-set goals, means for storing the input goal information, means for generating tasks based on the stored goal information, means for scheduling the generated tasks over a certain period of time, means for synchronizing the scheduled tasks with a scheduling management system, communication means for the user to report the progress of tasks, means for storing the reported progress information, means for adjusting tasks based on the stored progress information, means for notifying the user of the adjusted tasks, means for assigning tasks to production equipment, means for monitoring the progress of tasks performed by robots in real time, means for storing and analyzing progress information in a database, and means for fine-tuning tasks and generating new suggestions based on the analysis results. This enables efficient scheduling and management of production tasks by factory robots, and is expected to improve production efficiency through real-time progress monitoring and adjustment.

[0702] "Production equipment" is a general term for the equipment and devices used in manufacturing sites such as factories, and especially includes robots and automated machinery.

[0703] A "task" is a unit of work or activity set up to achieve a specific goal, and refers to the specific work that must be accomplished in a production process.

[0704] "Progress monitoring" is a process of tracking the status of task completion in real time and evaluating the degree of achievement and progress.

[0705] "Task adjustment" is the process of modifying the content and schedule of existing tasks based on the results of progress monitoring.

[0706] "Interface means" refers to the means by which a user inputs instructions into a system, and specifically includes touchscreens and keyboards.

[0707] "Storage methods" refer to means of temporarily or long-term storage of entered information, and specifically include hard disks and databases.

[0708] "Methods for scheduling" refer to methods for planning generated tasks over a certain period and scheduling tasks according to that plan.

[0709] A "schedule management system" is a system for organizing and managing tasks and other work along a timeline, and specifically includes online calendars.

[0710] "Communication methods" refer to means of sending and receiving information between users and systems, and specifically include the internet and messaging applications.

[0711] A "database" is a management system for systematically storing and managing information, enabling the efficient storage, retrieval, and manipulation of multiple datasets.

[0712] "Means of generating proposals" refers to methods for creating new work plans or adjustment plans based on progress data and task status.

[0713] "Means of synchronization" refer to methods for matching information and data across multiple systems and devices, which enables real-time data sharing.

[0714] The system for carrying out this invention provides a comprehensive solution for users to efficiently manage production equipment and effectively perform robotic production tasks. Specific embodiments of this system are described below.

[0715] User Interface

[0716] The interface for users to input pre-set goals can be operated via a touchscreen or keyboard. Using this interface, users can set goals such as "have a robot assemble product A." The entered goal information is temporarily stored in a buffer and then sent to the server. This information is stored in a database and used in subsequent processing.

[0717] Task generation and scheduling

[0718] The server generates tasks based on the goal information set by the user. This task generation process defines specific tasks, such as "installing part A" or "inspection process." The generated tasks are then scheduled over a specific period. Algorithms such as Scikit-learn are used for task scheduling to place tasks within optimal timeframes.

[0719] The generated schedule is synchronized with Google Calendar and other online calendars, allowing users to easily see the overall picture of their tasks through the scheduling management system.

[0720] Progress monitoring and data storage

[0721] As the robot performs each task, its progress is monitored in real time. The MQTT protocol is used for this monitoring, and progress data is sent to a server. This progress information is stored in a database and used for subsequent analysis.

[0722] Adjustments and proposals based on progress information

[0723] The saved progress data is analyzed on the server. If the progress is behind the goal, the server generates new suggestions to fine-tune the task. These suggestions, such as "Let's start with a lighter task," are sent to the user. LINE or other messaging applications are used for these notifications.

[0724] Specific example

[0725] If the factory manager sets on the first day to "assign the assembly task of product A to the robot," the system automatically generates 100 days' worth of assembly and quality check tasks and registers them in Google Calendar. Each time the robot completes a task, progress information is reported sequentially via the MQTT protocol, and the server saves this information to a database. If a task is not completed for three consecutive days, the system notifies the user via LINE chat with a new suggestion, such as "Let's start with a lighter checking process."

[0726] Example of a prompt

[0727] "Generate a schedule for the factory robot to perform the assembly task of part A between 2 PM and 4 PM every day. If the progress report is delayed, generate and submit a new proposal."

[0728] In this way, users can effectively manage production equipment and receive continuous support towards achieving their goals. Furthermore, since robot tasks are managed efficiently, overall production efficiency improves.

[0729] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0730] Step 1:

[0731] To set a goal, the user inputs the specific goal on the terminal using an interface. This input information is temporarily stored in a buffer and, after pressing the send button, is sent to the server in the form of an HTTP request. The server stores the received goal information in its database.

[0732] Input: User-entered goal information (e.g., "Have a robot assemble product A")

[0733] Data processing: Temporarily stored in a buffer, then converted to HTTP request format.

[0734] Output: Target information sent to the server

[0735] Step 2:

[0736] The server invokes a task generation algorithm based on the objective information to generate specific tasks. This uses Scikit-learn to optimally generate tasks that correspond to the objective.

[0737] Input: Saved target information

[0738] Data processing: Data calculations using task generation algorithms

[0739] Output: A specific task list has been generated (e.g., "Installation of part A", "Checking process")

[0740] Step 3:

[0741] The generated tasks are placed on a schedule over a set period. The server places the tasks in the most suitable time slots and synchronizes them with the online calendar using the Google Calendar API.

[0742] Input: Generated task list

[0743] Data processing: Task scheduling and synchronization with Google Calendar

[0744] Output: Schedule displayed in the scheduling management system

[0745] Step 4:

[0746] As the robot performs each task, its progress is monitored in real time. Progress data is sent from the robot to the server using the MQTT protocol. The server stores the received progress information in a database.

[0747] Input: Progress data sent from the robot

[0748] Data processing: Real-time data collection using the MQTT protocol.

[0749] Output: Progress information saved on the server

[0750] Step 5:

[0751] The server analyzes the stored progress data and evaluates the task's completion status. If progress is behind the target, the server generates new suggestions as needed.

[0752] Input: Saved progress data

[0753] Data processing: Analysis and evaluation of progress data

[0754] Output: New suggestion (e.g., "Let's start with a simple checking process")

[0755] Step 6:

[0756] The server notifies the user of newly generated suggestions. This notification is typically sent using a messaging application, such as LINE Talk. The user then reviews the suggestions and takes the next action.

[0757] Input: Generated proposal

[0758] Data processing: Message generation and sending

[0759] Output: Suggestions notified to the user

[0760] Through the above processing steps, the system can efficiently manage and coordinate production tasks performed by factory robots, providing continuous support to the user.

[0761] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0762] This invention combines an emotion engine with a system that schedules and manages the progress of tasks necessary to achieve pre-set goals for the user. The system recognizes emotions from text and voice data entered by the user and provides appropriate feedback and suggestions based on those emotions. This helps users maintain sustained motivation and action towards their goals.

[0763] System Overview

[0764] This system includes an interface for users to input goals, means for storing the inputted goal information, means for generating tasks based on the stored goal information, means for scheduling the generated tasks, means for synchronizing with a scheduling management system, means for users to report task progress, means for emotion recognition using an emotion engine, means for adjusting tasks based on stored progress information and recognized emotions, and means for notifying users of adjusted tasks and feedback.

[0765] Program processing

[0766] User Goal Setting

[0767] User: Enter a goal, such as "lose 5kg in 100 days," using the dedicated interface.

[0768] Terminal: Temporarily saves the goal information entered by the user and displays a submit button.

[0769] User: Click the submit button to send the target information.

[0770] Terminal: Sends target information to the server in HTTP request format.

[0771] Server: Stores received target information in the database.

[0772] Schedule creation

[0773] Server: Activates the task generation algorithm based on the target information.

[0774] Server: Generates specific tasks (e.g., exercise three times a week or daily meal management).

[0775] Server: Place these tasks on a 100-day schedule.

[0776] Server: Synchronizes schedules generated using the Google Calendar API with the scheduling management system.

[0777] Device: The user's schedule is displayed in Google Calendar.

[0778] Progress Monitoring

[0779] User: Report daily task progress via LINE chat. Send a message like, "I went for a 30-minute run today."

[0780] Terminal: Temporarily stores received progress information and sends it to the server as an HTTP request.

[0781] Server: Saves progress information to the database.

[0782] Server: Analyzes received text and audio data using an emotion engine to recognize the user's emotions.

[0783] Proposal adjustment

[0784] Server: Analyzes progress data and recognized sentiment information to evaluate task completion status.

[0785] Server: Generates new suggestions as needed. For example, if the user is feeling stressed, it might suggest, "Let's start today with a light walk."

[0786] Server: Sends suggestions to users via the LINE API.

[0787] Device: Display new suggestions to users via LINE chat.

[0788] User: Review the suggestion and take the next step. Accept the suggestion, saying, "Let's try a 10-minute walk today."

[0789] Specific example

[0790] If a user sets a goal of "losing 5kg in 100 days" on the first day, the system automatically generates 100 days' worth of exercise and diet management tasks and registers them in Google Calendar. The user reports daily via LINE chat, "I ran for 30 minutes today," and the server manages their progress and emotions. If the user fails to complete tasks for three consecutive days, the system uses an emotion engine to check if the user is feeling fatigued or stressed and notifies them via LINE chat with a new suggestion, such as "Let's start with a light walk today." In this way, users can receive sustained and effective support towards achieving their goals.

[0791] As described above, the present invention realizes a system that provides comprehensive support for effectively achieving user-set goals. By introducing an emotion engine, flexible responses according to the user's emotional state become possible, making it easier to maintain motivation and overcome challenges.

[0792] The following describes the processing flow.

[0793] Step 1:

[0794] User: Enter a goal, such as "lose 5kg in 100 days," using the dedicated interface.

[0795] Step 2:

[0796] Terminal: Temporarily saves the goal information entered by the user and displays a submit button.

[0797] Step 3:

[0798] User: Click the submit button to send the target information.

[0799] Step 4:

[0800] Terminal: Sends target information to the server in HTTP request format.

[0801] Step 5:

[0802] Server: Stores received target information in the database.

[0803] Step 6:

[0804] Server: Activates the task generation algorithm based on the saved target information.

[0805] Step 7:

[0806] Server: Generates specific tasks (e.g., exercise three times a week or daily meal management).

[0807] Step 8:

[0808] Server: Places the generated tasks into a 100-day schedule.

[0809] Step 9:

[0810] Server: Uses the Google Calendar API to synchronize the generated schedule with the scheduling management system.

[0811] Step 10:

[0812] Device: Displays the user's schedule in Google Calendar.

[0813] Step 11:

[0814] User: Report daily task progress via LINE chat. Send a message like, "I went for a 30-minute run today."

[0815] Step 12:

[0816] Terminal: Temporarily stores received progress information and sends it to the server as an HTTP request.

[0817] Step 13:

[0818] Server: Saves progress information to the database.

[0819] Step 14:

[0820] Server: Analyzes progress data and evaluates task completion status.

[0821] Step 15:

[0822] Terminal: Sends text data and voice data sent by the user via LINE chat to the emotion engine.

[0823] Step 16:

[0824] Server: The emotion engine analyzes text and audio data to recognize the user's emotions. For example, it determines whether the user is feeling stressed.

[0825] Step 17:

[0826] Server: Combines recognized emotion information and progress data to generate new suggestions as needed. For example, if the user is feeling stressed, it might suggest, "Let's start today with a light walk."

[0827] Step 18:

[0828] Server: Sends suggestions to users via the LINE API.

[0829] Step 19:

[0830] Device: Display new suggestions to users via LINE chat.

[0831] Step 20:

[0832] User: Review the suggestion and take the next step. Accept the suggestion, saying, "Let's try a 10-minute walk today."

[0833] Step 21:

[0834] Server: After the user takes the next action, the new progress data is analyzed again by the sentiment engine, and the feedback loop continues.

[0835] (Example 2)

[0836] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0837] Traditional goal-achievement support systems have problems with efficiently scheduling the tasks necessary to achieve user-defined goals, and lacking appropriate feedback and suggestions tailored to the user's emotional state, as well as task progress management. Therefore, there is a need for a system that supports users in maintaining sustained motivation and taking action towards their goals.

[0838] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0839] In this invention, the server includes information input means for inputting goals set in advance by the user; information storage means for storing the input goal information; task generation means for generating tasks based on the stored goal information; schedule placement means for placing the generated tasks on a schedule over a certain period of time; synchronization means for synchronizing the placed schedule with a schedule management system; communication means for the user to report the progress of tasks; progress information storage means for storing the reported progress information; task adjustment means for adjusting tasks based on progress information and emotion information; notification means for notifying the user of adjusted tasks and suggestions; and emotion recognition means for analyzing the user's emotions. This enables the user to perform tasks while maintaining sustained motivation toward their goals.

[0840] "Information input means" refers to the interface through which the user inputs their goals.

[0841] "Information storage means" refers to data storage means for temporarily or permanently storing the input target information.

[0842] "Task generation means" refers to algorithms or software that generate specific tasks based on stored target information.

[0843] "Schedule placement means" refers to a function or system that places generated tasks on a schedule over a certain period of time.

[0844] "Synchronization means" refers to the function of synchronizing the placed schedule with the schedule management system and electronic calendar.

[0845] "Communication methods" refer to the communication infrastructure and applications that users use to report the progress of tasks.

[0846] "Progress information storage means" refers to a data storage means for saving progress information of tasks reported by users.

[0847] "Task adjustment means" refers to a function that modifies, updates, or proposes new tasks based on progress information and sentiment information.

[0848] "Notification means" refers to communication methods or systems used to notify users of adjusted tasks or new suggestions.

[0849] "Emotion recognition means" refers to algorithms and software used to analyze a user's emotions.

[0850] This invention relates to a system for scheduling tasks and managing progress to achieve user-defined goals. In particular, by incorporating an emotion engine, it is possible to provide appropriate feedback and suggestions according to the user's emotional state, thereby maintaining the user's motivation. This system includes information input means, information storage means, task generation means, schedule placement means, synchronization means, communication means, progress information storage means, task adjustment means, notification means, and emotion recognition means.

[0851] Hardware and software to be used

[0852] 1. Information Input Method: This is an interface for the user to input their goals. This is implemented in a web browser or mobile application.

[0853] 2. Information storage means: A storage system for temporarily storing the entered target information. A SQL-based database management system (DBMS) is used as the database.

[0854] 3. Task generation method: An algorithm that generates specific tasks based on objective information. This may involve using machine learning models or rule-based algorithms.

[0855] 4. Schedule Placement Method: A tool for scheduling generated tasks over a certain period. It can be integrated with a scheduling management system by using the Google Calendar API.

[0856] 5. Synchronization method: A system for synchronizing schedules with electronic calendars such as Google Calendar. This includes an authentication process using OAuth 2.0.

[0857] 6. Communication method: A messaging application for users to report task progress. LINE API or other messaging platforms will be used.

[0858] 7. Progress Information Storage Method: A system that stores progress information reported by users in a database. Data is managed using SQL.

[0859] 8. Task Adjustment Mechanism: A system for adjusting tasks based on progress information and emotional information. It uses an emotional engine to analyze the user's emotions and perform appropriate task adjustments.

[0860] 9. Notification Method: A system for notifying users of adjusted tasks and new suggestions. Notifications are sent using the LINE API.

[0861] 10. Emotion Recognition Methods: Algorithms for analyzing user emotions. Natural language processing (NLP) models and emotion analysis models are used.

[0862] Specific example

[0863] On the first day, when a user sets a goal of "losing 5kg in 100 days," the system automatically generates 100 days' worth of exercise and diet management tasks and registers them in Google Calendar. The user reports daily via LINE chat, "Today I went for a 30-minute run." The server receives this progress information and stores it in a database. It also uses an emotion engine to analyze the user's emotional state. Based on this information, if the user is feeling stressed, it notifies them via LINE chat with new suggestions, such as "Let's start with a light walk today." This allows the user to receive sustained and effective support towards achieving their goal.

[0864] Example of a prompt

[0865] "Set specific exercise and dietary tasks to lose 5kg in 100 days, and design a system to track your daily progress and emotions."

[0866] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0867] Step 1: Goal Setting

[0868] User: Enter your goal using the dedicated interface (e.g., "Lose 5kg in 100 days").

[0869] Input: Goal information entered by the user.

[0870] Output: Temporarily stored data on the interface.

[0871] Specific operation: The user fills in their goal in a dedicated input form and clicks the submit button.

[0872] Step 2: Send target information

[0873] Terminal: Temporarily stores the entered target information and displays a submit button. When the user clicks the submit button, the target information is sent to the server as an HTTP request.

[0874] Input: Temporarily saved target information.

[0875] Output: Target information sent to the server.

[0876] Specific operation: The terminal checks the target information and sends the data to the server in the form of an HTTP request. The POST method is used.

[0877] Step 3: Save the target information

[0878] Server: Stores received target information in the database.

[0879] Input: Target information from the HTTP request.

[0880] Output: Target information stored in the database.

[0881] Specific operation: The server parses the received target information and uses SQL queries to perform INSERT operations on the database.

[0882] Step 4: Task Generation

[0883] Server: Activates a task generation algorithm based on saved goal information to generate specific tasks (e.g., exercise three times a week or daily meal management).

[0884] Input: Target information stored in the database.

[0885] Output: Generated task (template).

[0886] Specific operation: The server generates task content using machine learning algorithms and rule-based algorithms.

[0887] Step 5: Schedule Placement

[0888] Server: Schedules the generated tasks for a set period of time.

[0889] Input: The generated task.

[0890] Output: 100-day schedule.

[0891] Specific operation: The server uses the Calendar API to map tasks to dates and times and place them as schedules.

[0892] Step 6: Synchronize with the scheduling management system

[0893] Server: Synchronizes schedules generated using the Google Calendar API with the scheduling management system.

[0894] Input: A 100-day schedule.

[0895] Output: Schedule synced to Google Calendar.

[0896] Specific operation: The server uses OAuth 2.0 for authentication and synchronizes schedules via the Calendar API.

[0897] Step 7: Progress Report

[0898] User: Report daily task progress via LINE chat (e.g., "I went for a 30-minute run today").

[0899] Input: Progress information reported by the user via LINE chat.

[0900] Output: Temporarily saved progress information.

[0901] Specific action: The user sends progress information in text format via LINE chat.

[0902] Step 8: Send progress information

[0903] Terminal: Temporarily stores received progress information and sends it to the server as an HTTP request.

[0904] Input: Progress information received via LINE chat.

[0905] Output: Progress information sent to the server.

[0906] Specific operation: The terminal checks the received progress information and sends the data to the server in the form of an HTTP request.

[0907] Step 9: Save progress information

[0908] Server: Saves progress information to the database.

[0909] Input: Progress information from the HTTP request.

[0910] Output: Progress information stored in the database.

[0911] Specific operation: The server parses the received progress information and uses SQL queries to perform INSERT operations on the database.

[0912] Step 10: Emotion Recognition

[0913] Server: Analyzes received text and audio data using an emotion engine to recognize the user's emotions.

[0914] Input: Progress information and text or audio data.

[0915] Output: Recognized emotion information.

[0916] Specific operation: The server uses a natural language processing (NLP) model to analyze text data and perform sentiment recognition.

[0917] Step 11: Task Adjustment

[0918] Server: Analyzes progress data and recognized sentiment information, evaluates task completion status, and generates new suggestions.

[0919] Input: Progress information and sentiment information stored in the database.

[0920] Output: Adjusted tasks or new proposals.

[0921] Specific operation: Use machine learning models to analyze progress and sentiment data and generate suggestions to reduce the user's burden as needed.

[0922] Step 12: Notification of Proposal

[0923] Server: Sends suggestions to users via the LINE API.

[0924] Input: Adjusted tasks or new proposals.

[0925] Output: Suggestion notification sent to the user.

[0926] Specific operation: The suggestion is sent to the user's messaging application using the LINE API.

[0927] Step 13: Review and implement the proposal

[0928] User: Review the suggestion and take the next step (e.g., "Let's try a 10-minute walk today").

[0929] Input: Suggestion notification sent from the server.

[0930] Output: New task executed.

[0931] Specific actions: The user reviews the received suggestions and takes action based on them.

[0932] (Application Example 2)

[0933] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0934] Traditional task management systems often assign tasks unilaterally, regardless of the user's emotional state, making it difficult to maintain motivation. Furthermore, in real-world settings such as retail stores, inadequate task and emotional management of staff can lead to decreased work efficiency and customer satisfaction. This can result in accumulated stress and fatigue among staff, ultimately leading to a decline in overall work performance.

[0935] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for storing goal information entered by the user, means for generating tasks based on the stored goal information, and means for scheduling the generated tasks over a certain period of time. This makes it possible to support the user in maintaining motivation and taking action towards their goals. It also includes emotion recognition means for recognizing emotions from text and voice data entered by the user, and means for providing feedback and suggestions based on the recognized emotions. This makes it possible to adjust tasks while taking into account the emotional state of the staff, thereby improving work performance and reducing stress.

[0936] A "user" is an individual or professional who sets goals and manages the progress of tasks.

[0937] "Interface means" refers to the means by which a user inputs a goal, and primarily refers to a graphical user interface (GUI).

[0938] "Goal information" refers to information about the goals that the user has set in advance and wants to achieve.

[0939] "Means of storage" refers to databases and storage devices used to store entered target information and progress information.

[0940] A "task" is a specific job or activity that needs to be performed in order to achieve a goal.

[0941] "Means of scheduling" refers to methods for systematically placing generated tasks within a specific timeframe, such as calendar applications.

[0942] A "schedule management system" is a system used for managing schedules, and includes online calendars and similar tools.

[0943] "Communication methods" refer to communication methods used by users to report the progress of tasks, and include messaging applications, etc.

[0944] "Reported progress information" refers to information that users have reported regarding the results of their task execution using communication methods.

[0945] "Emotion recognition means" refers to systems and algorithms for recognizing emotions from text or voice data entered by the user.

[0946] "Means of providing feedback and suggestions" refers to means of providing appropriate feedback and action suggestions based on perceived emotions, and includes using messaging applications to send notifications.

[0947]

[0948] To implement this invention, a smartphone application called "Smart Staff Manager" is used. The specific configuration and processing details are described below.

[0949] First, the user enters their goal through an interface that allows them to set their own goals. For example, let's say the goal is to "improve customer satisfaction by 20% in 100 days." This goal information is temporarily stored on the smartphone. When the user presses the submit button, the goal information is sent to the server as an HTTP request. The server then stores the received goal information in a database.

[0950] Next, the server activates a task generation algorithm based on the stored goal information to generate specific tasks (e.g., "clean shelves," "replenish product inventory," "customer service"). It then places these generated tasks into a 100-day schedule. The server uses the Google Calendar API to synchronize the generated schedule with an online calendar and display it in the user's calendar.

[0951] Users report the progress of their daily tasks, for example, using a messaging application. For instance, they might use LINE to report, "I finished cleaning the shelves today." The device temporarily stores this progress information and sends it to the server as an HTTP request. The server stores the progress information in a database and analyzes the text and audio data of the progress report using an emotion recognition engine called EmotionRecognizer to understand the user's emotions. Based on this emotion data, the server then adjusts the tasks.

[0952] Based on the emotion recognition information, for example, if the user is feeling stressed, the system generates a suggestion such as "Take a short break and try again" and notifies the user via the LINE API. Conversely, if the user completes a task and their emotion is "joy" or "satisfaction," the system provides feedback such as "Great job! Keep up the good work!"

[0953] This system makes it easier for users to consistently achieve their goals. Furthermore, by adjusting tasks to take staff emotional states into account, it can improve work performance and reduce stress.

[0954] As a concrete example, the system operates based on the following prompt:

[0955] User goal: "Improve customer satisfaction by 20% in 100 days"

[0956] Tasks: "Clean shelves, Restock items, Customer support"

[0957] Emotion data from text: "I'm feeling stressed"

[0958]

[0959] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0960] Step 1:

[0961] The user enters goal information through a dedicated interface. For example, they might enter a goal such as "Increase customer satisfaction by 20% in 100 days." The terminal temporarily stores this input data and displays a submit button for the user to confirm the input. When the user clicks the submit button, the goal information is sent from the terminal to the server as an HTTP request.

[0962] Input: User's goal information

[0963] Output: HTTP request sent to the server

[0964] Step 2:

[0965] The server stores the received target information in a database. Based on the stored target information, it activates a task generation algorithm. This algorithm generates specific tasks such as "cleaning shelves," "replenishing product inventory," and "customer service."

[0966] Input: Target Information

[0967] Output: Generated tasks

[0968] Step 3:

[0969] The server schedules the generated tasks over a 100-day period. Specifically, it uses the Google Calendar API to place each task on a specific date and synchronizes it with the online calendar. This allows users to check their schedule on their smartphone calendar.

[0970] Input: Generated tasks

[0971] Output: Online calendar placed schedule

[0972] Step 4:

[0973] Users report the progress of their daily tasks using a messaging application. For example, they might use LINE to report, "I finished cleaning the shelves today." The device temporarily stores this progress information and sends it to the server as an HTTP request.

[0974] Input: Task progress information

[0975] Output: HTTP request sent to the server

[0976] Step 5:

[0977] The server stores the received progress information in a database. Next, it uses an emotion recognition engine to analyze the text and audio data included in the progress report to recognize the user's emotions. For example, it extracts emotional states such as "stress" or "satisfaction" from the text.

[0978] Input: Task progress information

[0979] Output: Recognized emotion data

[0980] Step 6:

[0981] The server generates feedback and suggestions based on recognized emotion data and task progress information. For example, if the user is identified as "stressed," it might suggest, "Try taking a short break." This feedback and suggestions are then communicated to the user via the LINE API.

[0982] Input: Recognized emotion data, task progress information

[0983] Output: Feedback and suggestions notified to the user.

[0984] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0985] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include those described above. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions shown by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0986] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0987] [Third Embodiment]

[0988] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0989] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0990] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0991] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0992] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0993] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0994] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0995] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0996] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0997] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0998] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0999] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[1000] This invention provides a system for users to set specific goals, schedule the tasks necessary to achieve those goals, and manage their progress. This system functions particularly effectively in business environments and provides a means for users to more easily achieve their long-term goals.

[1001] System Overview

[1002] This system includes an interface for users to set goals, means for generating tasks based on saved goal information, means for placing generated tasks on a schedule, means for synchronizing with a scheduling management system, communication means for reporting progress, and means for adjusting tasks based on saved progress information.

[1003] Program processing

[1004] User Goal Setting

[1005] User: Enter a specific goal, such as "lose 5kg in 100 days," using a dedicated interface.

[1006] Terminal: The goal entered by the user is temporarily saved to a buffer, and a submit button is provided.

[1007] User: Click the submit button to send the target information.

[1008] Terminal: Sends target information to the server in HTTP request format.

[1009] Server: Stores received target information in the database.

[1010] Schedule creation

[1011] Server: Activates the task generation algorithm based on the target information.

[1012] Server: Generates specific tasks (e.g., exercise three times a week, daily meal management tasks).

[1013] Server: Place these tasks on a 100-day schedule.

[1014] Server: Synchronizes schedules generated using the Google Calendar API with the scheduling management system.

[1015] Device: The user's schedule is displayed in Google Calendar.

[1016] Progress Monitoring

[1017] User: Report daily task progress via LINE chat. Send a message like, "I went for a 30-minute run today."

[1018] Terminal: Temporarily stores received progress information and sends it to the server.

[1019] Server: Saves progress information to the database.

[1020] Proposal adjustment

[1021] Server: Analyzes progress data and evaluates the task's completion status.

[1022] Server: Generates new suggestions as needed. For example, it might suggest adjusting the difficulty level or introducing new exercise methods.

[1023] Server: Sends suggestions to users via the LINE API.

[1024] Device: Display new suggestions to users via LINE chat.

[1025] User: Review the new suggestion and take the next step. Accept the suggestion, "Let's try a 10-minute walk today."

[1026] Specific example

[1027] If a user sets a goal of "losing 5kg in 100 days" on the first day, the system automatically generates 100 days' worth of exercise and diet management tasks and registers them in Google Calendar. The user reports daily via LINE chat, "I ran for 30 minutes today," and the server monitors the progress. If exercise is not performed for three consecutive days, the system notifies the user via LINE chat with a new suggestion, such as "Let's start with a light walk today." In this way, users can receive continuous and effective support towards achieving their goals.

[1028] As described above, the present invention realizes a system that provides comprehensive support for effectively achieving user-defined goals.

[1029] The following describes the processing flow.

[1030] Step 1:

[1031] User: Enter a goal, such as "lose 5kg in 100 days," using the dedicated interface.

[1032] Step 2:

[1033] Terminal: Temporarily saves the goal information entered by the user and displays a submit button.

[1034] Step 3:

[1035] User: Click the submit button to send the target information.

[1036] Step 4:

[1037] Terminal: Sends target information to the server in HTTP request format.

[1038] Step 5:

[1039] Server: Stores received target information in the database.

[1040] Step 6:

[1041] Server: Activates the task generation algorithm based on the saved target information.

[1042] Step 7:

[1043] Server: Generates specific tasks (e.g., exercise three times a week or daily meal management).

[1044] Step 8:

[1045] Server: Places the generated tasks into a 100-day schedule.

[1046] Step 9:

[1047] Server: Uses the Google Calendar API to synchronize the generated schedule with the scheduling management system.

[1048] Step 10:

[1049] Device: Displays the user's schedule in Google Calendar.

[1050] Step 11:

[1051] User: Report daily task progress via LINE chat. Send a message like, "I went for a 30-minute run today."

[1052] Step 12:

[1053] Terminal: Temporarily stores received progress information and sends it to the server as an HTTP request.

[1054] Step 13:

[1055] Server: Saves progress information to the database.

[1056] Step 14:

[1057] Server: Analyzes progress data and evaluates task completion status.

[1058] Step 15:

[1059] Server: Generates new suggestions as needed. For example, it might suggest, "Let's try a 10-minute walk today."

[1060] Step 16:

[1061] Server: Sends suggestions to users via the LINE API.

[1062] Step 17:

[1063] Device: Display new suggestions to users via LINE chat.

[1064] Step 18:

[1065] User: Review the suggestion and take the next step. Accept the suggestion, saying, "Let's try a 10-minute walk today."

[1066] (Example 1)

[1067] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1068] Traditional task management systems struggled to effectively generate and schedule tasks based on user-defined goals. In particular, maintaining user motivation was difficult in managing progress toward long-term goals, and there was a lack of proper analysis of progress information and provision of new suggestions.

[1069] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1070] In this invention, the server includes an interface means for the user to input pre-set goals, means for storing the input goal information, means for generating tasks based on the stored goal information, means for scheduling the generated tasks over a certain period of time, means for synchronizing the scheduled tasks with a scheduling management system, communication means for the user to report the progress of tasks, means for storing the reported progress information, means for adjusting tasks based on the stored progress information, means for notifying the user of the adjusted tasks, a server for activating a task generation algorithm, means for synchronizing the generated schedule via an API, and a server for analyzing progress data and generating new suggestions. This enables the user to effectively set and manage long-term goals and receive appropriate suggestions based on their progress.

[1071] "Interface means" refers to an input device or software for the user to input a target.

[1072] "Goal information" refers to data related to the goals that the user has set and aims to achieve.

[1073] A "storage method" is a database or storage device for storing target information and progress information.

[1074] A "task generation algorithm" is a program that automatically generates specific tasks based on objective information.

[1075] "Means of scheduling" refers to a program or function that schedules generated tasks over a specific period of time.

[1076] A "schedule management system" is software or a service used to manage schedules.

[1077] "Communication means" refers to a device or function for receiving progress reports from users.

[1078] "Progress information" refers to data about the progress of tasks performed by the user.

[1079] "Means of adjusting tasks" refers to a program or function that modifies or rearranges the original task based on saved progress information.

[1080] "Means of notification" refers to a device or software used to notify the user after the task has been adjusted.

[1081] A "server" is a computer system used to perform various actions and functions.

[1082] An "API" is an interface that enables communication between different software components.

[1083] A "proposal generation server" is a computer system that analyzes progress data and provides new suggestions to users.

[1084] This invention provides a system for users to set specific goals, schedule the tasks necessary to achieve those goals, and manage their progress. This system functions particularly effectively in business environments and provides a means for users to more easily achieve their long-term goals. Embodiments of this system are described in detail below.

[1085] System Configuration

[1086] This system includes the following main components:

[1087] 1. Interface means: This refers to an input device or software for the user to input a goal. For example, a web interface or a mobile application falls into this category. The user uses this interface to input the goal.

[1088] 2. Storage means: A database or storage device for storing the entered target information and progress information. In this embodiment, a MySQL database is used.

[1089] 3. Task Generation Algorithm: This program generates specific tasks based on objective information. This algorithm is implemented in Python.

[1090] 4. Means of placing tasks on a schedule: This is a program or function that places generated tasks on a schedule over a certain period of time. This is also implemented in Python, and this schedule is synchronized with an online calendar using the Google Calendar API.

[1091] 5. Communication means: A device or function for receiving progress reports from users. In particular, progress is received using a messaging application (e.g., LINE API).

[1092] 6. Means of adjusting tasks: This is a program or function that modifies or rearranges the original task based on saved progress information. This part will also be implemented as a Python script.

[1093] 7. Proposal generation server: This is a computer system that analyzes progress data and generates new proposals.

[1094] Specific example

[1095] Below is a specific example scenario for setting the goal of "losing 5 kg in 100 days."

[1096] First, the user enters a goal, such as "lose 5kg in 100 days," using a dedicated interface. The terminal temporarily stores this goal information in a buffer and displays a send button. When the user clicks the send button, the terminal sends the goal information to the server in the form of an HTTP request. The server stores the received goal information in its database.

[1097] Next, the server activates a task generation algorithm based on the stored goal information. This algorithm generates specific tasks, such as "exercise three times a week" or "daily meal management tasks." These tasks are placed on a 100-day schedule, and the server synchronizes this with an online calendar using the Google Calendar API.

[1098] Users report their daily task progress via LINE. For example, they might send a LINE chat message saying, "I went for a 30-minute run today." The device sends the received progress information to the server, which stores the information in a database. The server analyzes the progress data and generates new suggestions as needed. For example, it might send a suggestion like, "Let's start with a light walk today," to the user via the LINE API. The device then displays this suggestion to the user in a LINE chat.

[1099] Input prompts for the generative AI model

[1100] "Please create a program that automatically generates a schedule and tasks for losing 5kg in 100 days, and manages progress using Google Calendar and LINE. Also, please provide new suggestions if progress is unsatisfactory."

[1101] Thus, the system of the present invention provides integrated management and support for effectively achieving user-defined goals.

[1102] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1103] Step 1:

[1104] The user enters their goal into a dedicated interface.

[1105] Input: A specific goal such as "lose 5kg in 100 days."

[1106] Output: A format in which target information is temporarily stored on the device.

[1107] Specific action: The user enters a goal into a web interface or mobile app and clicks the "Submit" button.

[1108] Step 2:

[1109] The device sends target information to the server.

[1110] Input: Goal information entered by the user.

[1111] Output: Target information is sent to the server in JSON format.

[1112] Specific operation: JavaScript code sends the form data to the server as an HTTP POST request.

[1113] Step 3:

[1114] The server saves the received target information to the database.

[1115] Input: Target information sent from the device.

[1116] Output: Target information is saved to the database.

[1117] Specific operation: Using the Flask framework in Python, received data is stored in a MySQL database using SQL queries.

[1118] Step 4:

[1119] The server activates a task generation algorithm based on the target information.

[1120] Input: Target information stored in the database.

[1121] Output: The generated task list.

[1122] Specific operation: A Python script is launched, generating a task list tailored to the goal.

[1123] Step 5:

[1124] The server places the generated tasks into a 100-day schedule.

[1125] Input: The generated task list.

[1126] Output: Schedule information.

[1127] Specific operation: Arrange the task list in a calendar format, calculate the schedule for each day, and create a 100-day schedule.

[1128] Step 6:

[1129] The server synchronizes schedules generated using the Google Calendar API.

[1130] Input: 100-day schedule.

[1131] Output: Schedule added to Google Calendar.

[1132] Specific action: Call the Google Calendar API and add the schedule information to the user's Google Calendar.

[1133] Step 7:

[1134] The device displays the user's schedule in Google Calendar.

[1135] Input: Current schedule information from the Google Calendar API.

[1136] Output: The schedule displayed in the user's Google Calendar.

[1137] Specific operation: The schedule is displayed through the Google Calendar app or web interface.

[1138] Step 8:

[1139] Users report the progress of their daily tasks via LINE.

[1140] Input: Progress report such as "I went for a 30-minute run today."

[1141] Output: Progress information is temporarily saved to the device.

[1142] Specific action: The user opens the LINE app and sends a progress report to a designated bot.

[1143] Step 9:

[1144] The terminal sends the received progress information to the server.

[1145] Input: Progress information received via LINE.

[1146] Output: Progress information is sent to the server in JSON format.

[1147] Specific operation: Received messages using the LINE Messaging API are temporarily stored and then sent to the server via an HTTP request.

[1148] Step 10:

[1149] The server saves progress information to the database.

[1150] Input: Progress information sent from the device.

[1151] Output: Progress information is saved to the database.

[1152] Specific operation: The received progress information is parsed in JSON format and added to the database using an SQL query.

[1153] Step 11:

[1154] The server analyzes the progress data and evaluates the task's completion status.

[1155] Input: Progress data stored in the database.

[1156] Output: Analysis results and proposed solutions.

[1157] Specific operation: A Python script analyzes progress data and runs an algorithm to evaluate the degree of task completion.

[1158] Step 12:

[1159] The server generates new suggestions as needed.

[1160] Input: Analysis results of progress data.

[1161] Output: New proposal.

[1162] Specific operation: Based on the progress status, an algorithm is applied to suggest the next action, generating a new proposal.

[1163] Step 13:

[1164] The server sends the suggestion to the user via the LINE API.

[1165] Input: Generated suggestion content.

[1166] Output: The suggestion message sent to the user.

[1167] Specific operation: Use the LINE Messaging API to send the generated suggestions to the user as text messages.

[1168] Step 14:

[1169] The device displays new suggestions to the user via LINE chat.

[1170] Input: Suggestion message sent from the server.

[1171] Output: The suggestion message displayed to the user.

[1172] Specific action: A notification will be displayed within the user's LINE app.

[1173] Step 15:

[1174] The user reviews the new proposal and takes the next step.

[1175] Input: Suggestions from the server.

[1176] Output: The user's next action.

[1177] Specific actions: Review the proposal and begin taking action according to the day's schedule.

[1178] (Application Example 1)

[1179] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1180] In conventional factory production, task management and scheduling by robots are often done manually, resulting in inefficiencies and a lack of accuracy. Furthermore, real-time progress monitoring and task adjustments based on progress information are difficult, leading to decreased production efficiency. Additionally, limited communication methods for proper task progress reporting result in insufficient coordination between managers and robots. This creates a challenge in the overall functioning of factory production management.

[1181] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1182] In this invention, the server includes an interface means for a user to input pre-set goals, means for storing the input goal information, means for generating tasks based on the stored goal information, means for scheduling the generated tasks over a certain period of time, means for synchronizing the scheduled tasks with a scheduling management system, communication means for the user to report the progress of tasks, means for storing the reported progress information, means for adjusting tasks based on the stored progress information, means for notifying the user of the adjusted tasks, means for assigning tasks to production equipment, means for monitoring the progress of tasks performed by robots in real time, means for storing and analyzing progress information in a database, and means for fine-tuning tasks and generating new suggestions based on the analysis results. This enables efficient scheduling and management of production tasks by factory robots, and is expected to improve production efficiency through real-time progress monitoring and adjustment.

[1183] "Production equipment" is a general term for the equipment and devices used in manufacturing sites such as factories, and especially includes robots and automated machinery.

[1184] A "task" is a unit of work or activity set up to achieve a specific goal, and refers to the specific work that must be accomplished in a production process.

[1185] "Progress monitoring" is a process of tracking the status of task completion in real time and evaluating the degree of achievement and progress.

[1186] "Task adjustment" is the process of modifying the content and schedule of existing tasks based on the results of progress monitoring.

[1187] "Interface means" refers to the means by which a user inputs instructions into a system, and specifically includes touchscreens and keyboards.

[1188] "Storage methods" refer to means of temporarily or long-term storage of entered information, and specifically include hard disks and databases.

[1189] "Methods for scheduling" refer to methods for planning generated tasks over a certain period and scheduling tasks according to that plan.

[1190] A "schedule management system" is a system for organizing and managing tasks and other work along a timeline, and specifically includes online calendars.

[1191] "Communication methods" refer to means of sending and receiving information between users and systems, and specifically include the internet and messaging applications.

[1192] A "database" is a management system for systematically storing and managing information, enabling the efficient storage, retrieval, and manipulation of multiple datasets.

[1193] "Means of generating proposals" refers to methods for creating new work plans or adjustment plans based on progress data and task status.

[1194] "Means of synchronization" refer to methods for matching information and data across multiple systems and devices, which enables real-time data sharing.

[1195] The system for carrying out this invention provides a comprehensive solution for users to efficiently manage production equipment and effectively perform robotic production tasks. Specific embodiments of this system are described below.

[1196] User Interface

[1197] The interface for users to input pre-set goals can be operated via a touchscreen or keyboard. Using this interface, users can set goals such as "have a robot assemble product A." The entered goal information is temporarily stored in a buffer and then sent to the server. This information is stored in a database and used in subsequent processing.

[1198] Task generation and scheduling

[1199] The server generates tasks based on the goal information set by the user. This task generation process defines specific tasks, such as "installing part A" or "inspection process." The generated tasks are then scheduled over a specific period. Algorithms such as Scikit-learn are used for task scheduling to place tasks within optimal timeframes.

[1200] The generated schedule is synchronized with Google Calendar and other online calendars, allowing users to easily see the overall picture of their tasks through the scheduling management system.

[1201] Progress monitoring and data storage

[1202] As the robot performs each task, its progress is monitored in real time. The MQTT protocol is used for this monitoring, and progress data is sent to a server. This progress information is stored in a database and used for subsequent analysis.

[1203] Adjustments and proposals based on progress information

[1204] The saved progress data is analyzed on the server. If the progress is behind the goal, the server generates new suggestions to fine-tune the task. These suggestions, such as "Let's start with a lighter task," are sent to the user. LINE or other messaging applications are used for these notifications.

[1205] Specific example

[1206] If the factory manager sets on the first day to "assign the assembly task of product A to the robot," the system automatically generates 100 days' worth of assembly and quality check tasks and registers them in Google Calendar. Each time the robot completes a task, progress information is reported sequentially via the MQTT protocol, and the server saves this information to a database. If a task is not completed for three consecutive days, the system notifies the user via LINE chat with a new suggestion, such as "Let's start with a lighter checking process."

[1207] Example of a prompt

[1208] "Generate a schedule for the factory robot to perform the assembly task of part A between 2 PM and 4 PM every day. If the progress report is delayed, generate and submit a new proposal."

[1209] In this way, users can effectively manage production equipment and receive continuous support towards achieving their goals. Furthermore, since robot tasks are managed efficiently, overall production efficiency improves.

[1210] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1211] Step 1:

[1212] To set a goal, the user inputs the specific goal on the terminal using an interface. This input information is temporarily stored in a buffer and, after pressing the send button, is sent to the server in the form of an HTTP request. The server stores the received goal information in its database.

[1213] Input: User-entered goal information (e.g., "Have a robot assemble product A")

[1214] Data processing: Temporarily stored in a buffer, then converted to HTTP request format.

[1215] Output: Target information sent to the server

[1216] Step 2:

[1217] The server invokes a task generation algorithm based on the objective information to generate specific tasks. This uses Scikit-learn to optimally generate tasks that correspond to the objective.

[1218] Input: Saved target information

[1219] Data processing: Data calculations using task generation algorithms

[1220] Output: A specific task list has been generated (e.g., "Installation of part A", "Checking process")

[1221] Step 3:

[1222] The generated tasks are placed on a schedule over a set period. The server places the tasks in the most suitable time slots and synchronizes them with the online calendar using the Google Calendar API.

[1223] Input: Generated task list

[1224] Data processing: Task scheduling and synchronization with Google Calendar

[1225] Output: Schedule displayed in the scheduling management system

[1226] Step 4:

[1227] As the robot performs each task, its progress is monitored in real time. Progress data is sent from the robot to the server using the MQTT protocol. The server stores the received progress information in a database.

[1228] Input: Progress data sent from the robot

[1229] Data processing: Real-time data collection using the MQTT protocol.

[1230] Output: Progress information saved on the server

[1231] Step 5:

[1232] The server analyzes the stored progress data and evaluates the task's completion status. If progress is behind the target, the server generates new suggestions as needed.

[1233] Input: Saved progress data

[1234] Data processing: Analysis and evaluation of progress data

[1235] Output: New suggestion (e.g., "Let's start with a simple checking process")

[1236] Step 6:

[1237] The server notifies the user of newly generated suggestions. This notification is typically sent using a messaging application, such as LINE Talk. The user then reviews the suggestions and takes the next action.

[1238] Input: Generated proposal

[1239] Data processing: Message generation and sending

[1240] Output: Suggestions notified to the user

[1241] Through the above processing steps, the system can efficiently manage and coordinate production tasks performed by factory robots, providing continuous support to the user.

[1242] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1243] This invention combines an emotion engine with a system that schedules and manages the progress of tasks necessary to achieve pre-set goals for the user. The system recognizes emotions from text and voice data entered by the user and provides appropriate feedback and suggestions based on those emotions. This helps users maintain sustained motivation and action towards their goals.

[1244] System Overview

[1245] This system includes an interface for users to input goals, means for storing the inputted goal information, means for generating tasks based on the stored goal information, means for scheduling the generated tasks, means for synchronizing with a scheduling management system, means for users to report task progress, means for emotion recognition using an emotion engine, means for adjusting tasks based on stored progress information and recognized emotions, and means for notifying users of adjusted tasks and feedback.

[1246] Program processing

[1247] User Goal Setting

[1248] User: Enter a goal, such as "lose 5kg in 100 days," using the dedicated interface.

[1249] Terminal: Temporarily saves the goal information entered by the user and displays a submit button.

[1250] User: Click the submit button to send the target information.

[1251] Terminal: Sends target information to the server in HTTP request format.

[1252] Server: Stores received target information in the database.

[1253] Schedule creation

[1254] Server: Activates the task generation algorithm based on the target information.

[1255] Server: Generates specific tasks (e.g., exercise three times a week or daily meal management).

[1256] Server: Place these tasks on a 100-day schedule.

[1257] Server: Synchronizes schedules generated using the Google Calendar API with the scheduling management system.

[1258] Device: The user's schedule is displayed in Google Calendar.

[1259] Progress Monitoring

[1260] User: Report daily task progress via LINE chat. Send a message like, "I went for a 30-minute run today."

[1261] Terminal: Temporarily stores received progress information and sends it to the server as an HTTP request.

[1262] Server: Saves progress information to the database.

[1263] Server: Analyzes received text and audio data using an emotion engine to recognize the user's emotions.

[1264] Proposal adjustment

[1265] Server: Analyzes progress data and recognized sentiment information to evaluate task completion status.

[1266] Server: Generates new suggestions as needed. For example, if the user is feeling stressed, it might suggest, "Let's start today with a light walk."

[1267] Server: Sends suggestions to users via the LINE API.

[1268] Device: Display new suggestions to users via LINE chat.

[1269] User: Review the suggestion and take the next step. Accept the suggestion, saying, "Let's try a 10-minute walk today."

[1270] Specific example

[1271] If a user sets a goal of "losing 5kg in 100 days" on the first day, the system automatically generates 100 days' worth of exercise and diet management tasks and registers them in Google Calendar. The user reports daily via LINE chat, "I ran for 30 minutes today," and the server manages their progress and emotions. If the user fails to complete tasks for three consecutive days, the system uses an emotion engine to check if the user is feeling fatigued or stressed and notifies them via LINE chat with a new suggestion, such as "Let's start with a light walk today." In this way, users can receive sustained and effective support towards achieving their goals.

[1272] As described above, the present invention realizes a system that provides comprehensive support for effectively achieving user-set goals. By introducing an emotion engine, flexible responses according to the user's emotional state become possible, making it easier to maintain motivation and overcome challenges.

[1273] The following describes the processing flow.

[1274] Step 1:

[1275] User: Enter a goal, such as "lose 5kg in 100 days," using the dedicated interface.

[1276] Step 2:

[1277] Terminal: Temporarily saves the goal information entered by the user and displays a submit button.

[1278] Step 3:

[1279] User: Click the submit button to send the target information.

[1280] Step 4:

[1281] Terminal: Sends target information to the server in HTTP request format.

[1282] Step 5:

[1283] Server: Stores received target information in the database.

[1284] Step 6:

[1285] Server: Activates the task generation algorithm based on the saved target information.

[1286] Step 7:

[1287] Server: Generates specific tasks (e.g., exercise three times a week or daily meal management).

[1288] Step 8:

[1289] Server: Places the generated tasks into a 100-day schedule.

[1290] Step 9:

[1291] Server: Uses the Google Calendar API to synchronize the generated schedule with the scheduling management system.

[1292] Step 10:

[1293] Device: Displays the user's schedule in Google Calendar.

[1294] Step 11:

[1295] User: Report daily task progress via LINE chat. Send a message like, "I went for a 30-minute run today."

[1296] Step 12:

[1297] Terminal: Temporarily stores received progress information and sends it to the server as an HTTP request.

[1298] Step 13:

[1299] Server: Saves progress information to the database.

[1300] Step 14:

[1301] Server: Analyzes progress data and evaluates task completion status.

[1302] Step 15:

[1303] Terminal: Sends text data and voice data sent by the user via LINE chat to the emotion engine.

[1304] Step 16:

[1305] Server: The emotion engine analyzes text and audio data to recognize the user's emotions. For example, it determines whether the user is feeling stressed.

[1306] Step 17:

[1307] Server: Combines recognized emotion information and progress data to generate new suggestions as needed. For example, if the user is feeling stressed, it might suggest, "Let's start today with a light walk."

[1308] Step 18:

[1309] Server: Sends suggestions to users via the LINE API.

[1310] Step 19:

[1311] Device: Display new suggestions to users via LINE chat.

[1312] Step 20:

[1313] User: Review the suggestion and take the next step. Accept the suggestion, saying, "Let's try a 10-minute walk today."

[1314] Step 21:

[1315] Server: After the user takes the next action, the new progress data is analyzed again by the sentiment engine, and the feedback loop continues.

[1316] (Example 2)

[1317] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1318] Traditional goal-achievement support systems have problems with efficiently scheduling the tasks necessary to achieve user-defined goals, and lacking appropriate feedback and suggestions tailored to the user's emotional state, as well as task progress management. Therefore, there is a need for a system that supports users in maintaining sustained motivation and taking action towards their goals.

[1319] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1320] In this invention, the server includes information input means for inputting goals set in advance by the user; information storage means for storing the input goal information; task generation means for generating tasks based on the stored goal information; schedule placement means for placing the generated tasks on a schedule over a certain period of time; synchronization means for synchronizing the placed schedule with a schedule management system; communication means for the user to report the progress of tasks; progress information storage means for storing the reported progress information; task adjustment means for adjusting tasks based on progress information and emotion information; notification means for notifying the user of adjusted tasks and suggestions; and emotion recognition means for analyzing the user's emotions. This enables the user to perform tasks while maintaining sustained motivation toward their goals.

[1321] "Information input means" refers to the interface through which the user inputs their goals.

[1322] "Information storage means" refers to data storage means for temporarily or permanently storing the input target information.

[1323] "Task generation means" refers to algorithms or software that generate specific tasks based on stored target information.

[1324] "Schedule placement means" refers to a function or system that places generated tasks on a schedule over a certain period of time.

[1325] "Synchronization means" refers to the function of synchronizing the placed schedule with the schedule management system and electronic calendar.

[1326] "Communication methods" refer to the communication infrastructure and applications that users use to report the progress of tasks.

[1327] "Progress information storage means" refers to a data storage means for saving progress information of tasks reported by users.

[1328] "Task adjustment means" refers to a function that modifies, updates, or proposes new tasks based on progress information and sentiment information.

[1329] "Notification means" refers to communication methods or systems used to notify users of adjusted tasks or new suggestions.

[1330] "Emotion recognition means" refers to algorithms and software used to analyze a user's emotions.

[1331] This invention relates to a system for scheduling tasks and managing progress to achieve user-defined goals. In particular, by incorporating an emotion engine, it is possible to provide appropriate feedback and suggestions according to the user's emotional state, thereby maintaining the user's motivation. This system includes information input means, information storage means, task generation means, schedule placement means, synchronization means, communication means, progress information storage means, task adjustment means, notification means, and emotion recognition means.

[1332] Hardware and software to be used

[1333] 1. Information Input Method: This is an interface for the user to input their goals. This is implemented in a web browser or mobile application.

[1334] 2. Information storage means: A storage system for temporarily storing the entered target information. A SQL-based database management system (DBMS) is used as the database.

[1335] 3. Task generation method: An algorithm that generates specific tasks based on objective information. This may involve using machine learning models or rule-based algorithms.

[1336] 4. Schedule Placement Method: A tool for scheduling generated tasks over a certain period. It can be integrated with a scheduling management system by using the Google Calendar API.

[1337] 5. Synchronization method: A system for synchronizing schedules with electronic calendars such as Google Calendar. This includes an authentication process using OAuth 2.0.

[1338] 6. Communication method: A messaging application for users to report task progress. LINE API or other messaging platforms will be used.

[1339] 7. Progress Information Storage Method: A system that stores progress information reported by users in a database. Data is managed using SQL.

[1340] 8. Task Adjustment Mechanism: A system for adjusting tasks based on progress information and emotional information. It uses an emotional engine to analyze the user's emotions and perform appropriate task adjustments.

[1341] 9. Notification Method: A system for notifying users of adjusted tasks and new suggestions. Notifications are sent using the LINE API.

[1342] 10. Emotion Recognition Methods: Algorithms for analyzing user emotions. Natural language processing (NLP) models and emotion analysis models are used.

[1343] Specific example

[1344] On the first day, when a user sets a goal of "losing 5kg in 100 days," the system automatically generates 100 days' worth of exercise and diet management tasks and registers them in Google Calendar. The user reports daily via LINE chat, "Today I went for a 30-minute run." The server receives this progress information and stores it in a database. It also uses an emotion engine to analyze the user's emotional state. Based on this information, if the user is feeling stressed, it notifies them via LINE chat with new suggestions, such as "Let's start with a light walk today." This allows the user to receive sustained and effective support towards achieving their goal.

[1345] Example of a prompt

[1346] "Set specific exercise and dietary tasks to lose 5kg in 100 days, and design a system to track your daily progress and emotions."

[1347] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1348] Step 1: Goal Setting

[1349] User: Enter your goal using the dedicated interface (e.g., "Lose 5kg in 100 days").

[1350] Input: Goal information entered by the user.

[1351] Output: Temporarily stored data on the interface.

[1352] Specific operation: The user fills in their goal in a dedicated input form and clicks the submit button.

[1353] Step 2: Send target information

[1354] Terminal: Temporarily stores the entered target information and displays a submit button. When the user clicks the submit button, the target information is sent to the server as an HTTP request.

[1355] Input: Temporarily saved target information.

[1356] Output: Target information sent to the server.

[1357] Specific operation: The terminal checks the target information and sends the data to the server in the form of an HTTP request. The POST method is used.

[1358] Step 3: Save the target information

[1359] Server: Stores received target information in the database.

[1360] Input: Target information from the HTTP request.

[1361] Output: Target information stored in the database.

[1362] Specific operation: The server parses the received target information and uses SQL queries to perform INSERT operations on the database.

[1363] Step 4: Task Generation

[1364] Server: Activates a task generation algorithm based on saved goal information to generate specific tasks (e.g., exercise three times a week or daily meal management).

[1365] Input: Target information stored in the database.

[1366] Output: Generated task (template).

[1367] Specific operation: The server generates task content using machine learning algorithms and rule-based algorithms.

[1368] Step 5: Schedule Placement

[1369] Server: Schedules the generated tasks for a set period of time.

[1370] Input: The generated task.

[1371] Output: 100-day schedule.

[1372] Specific operation: The server uses the Calendar API to map tasks to dates and times and place them as schedules.

[1373] Step 6: Synchronize with the scheduling management system

[1374] Server: Synchronizes schedules generated using the Google Calendar API with the scheduling management system.

[1375] Input: A 100-day schedule.

[1376] Output: Schedule synced to Google Calendar.

[1377] Specific operation: The server uses OAuth 2.0 for authentication and synchronizes schedules via the Calendar API.

[1378] Step 7: Progress Report

[1379] User: Report daily task progress via LINE chat (e.g., "I went for a 30-minute run today").

[1380] Input: Progress information reported by the user via LINE chat.

[1381] Output: Temporarily saved progress information.

[1382] Specific action: The user sends progress information in text format via LINE chat.

[1383] Step 8: Send progress information

[1384] Terminal: Temporarily stores received progress information and sends it to the server as an HTTP request.

[1385] Input: Progress information received via LINE chat.

[1386] Output: Progress information sent to the server.

[1387] Specific operation: The terminal checks the received progress information and sends the data to the server in the form of an HTTP request.

[1388] Step 9: Save progress information

[1389] Server: Saves progress information to the database.

[1390] Input: Progress information from the HTTP request.

[1391] Output: Progress information stored in the database.

[1392] Specific operation: The server parses the received progress information and uses SQL queries to perform INSERT operations on the database.

[1393] Step 10: Emotion Recognition

[1394] Server: Analyzes received text and audio data using an emotion engine to recognize the user's emotions.

[1395] Input: Progress information and text or audio data.

[1396] Output: Recognized emotion information.

[1397] Specific operation: The server uses a natural language processing (NLP) model to analyze text data and perform sentiment recognition.

[1398] Step 11: Task Adjustment

[1399] Server: Analyzes progress data and recognized sentiment information, evaluates task completion status, and generates new suggestions.

[1400] Input: Progress information and sentiment information stored in the database.

[1401] Output: Adjusted tasks or new proposals.

[1402] Specific operation: Use machine learning models to analyze progress and sentiment data and generate suggestions to reduce the user's burden as needed.

[1403] Step 12: Notification of Proposal

[1404] Server: Sends suggestions to users via the LINE API.

[1405] Input: Adjusted tasks or new proposals.

[1406] Output: Suggestion notification sent to the user.

[1407] Specific operation: The suggestion is sent to the user's messaging application using the LINE API.

[1408] Step 13: Review and implement the proposal

[1409] User: Review the suggestion and take the next step (e.g., "Let's try a 10-minute walk today").

[1410] Input: Suggestion notification sent from the server.

[1411] Output: New task executed.

[1412] Specific actions: The user reviews the received suggestions and takes action based on them.

[1413] (Application Example 2)

[1414] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1415] Traditional task management systems often assign tasks unilaterally, regardless of the user's emotional state, making it difficult to maintain motivation. Furthermore, in real-world settings such as retail stores, inadequate task and emotional management of staff can lead to decreased work efficiency and customer satisfaction. This can result in accumulated stress and fatigue among staff, ultimately leading to a decline in overall work performance.

[1416] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for storing goal information entered by the user, means for generating tasks based on the stored goal information, and means for scheduling the generated tasks over a certain period of time. This makes it possible to support the user in maintaining motivation and taking action towards their goals. It also includes emotion recognition means for recognizing emotions from text and voice data entered by the user, and means for providing feedback and suggestions based on the recognized emotions. This makes it possible to adjust tasks while taking into account the emotional state of the staff, thereby improving work performance and reducing stress.

[1417] A "user" is an individual or professional who sets goals and manages the progress of tasks.

[1418] "Interface means" refers to the means by which a user inputs a goal, and primarily refers to a graphical user interface (GUI).

[1419] "Goal information" refers to information about the goals that the user has set in advance and wants to achieve.

[1420] "Means of storage" refers to databases and storage devices used to store entered target information and progress information.

[1421] A "task" is a specific job or activity that needs to be performed in order to achieve a goal.

[1422] "Means of scheduling" refers to methods for systematically placing generated tasks within a specific timeframe, such as calendar applications.

[1423] A "schedule management system" is a system used for managing schedules, and includes online calendars and similar tools.

[1424] "Communication methods" refer to communication methods used by users to report the progress of tasks, and include messaging applications, etc.

[1425] "Reported progress information" refers to information that users have reported regarding the results of their task execution using communication methods.

[1426] "Emotion recognition means" refers to systems and algorithms for recognizing emotions from text or voice data entered by the user.

[1427] "Means of providing feedback and suggestions" refers to means of providing appropriate feedback and action suggestions based on perceived emotions, and includes using messaging applications to send notifications.

[1428]

[1429] To implement this invention, a smartphone application called "Smart Staff Manager" is used. The specific configuration and processing details are described below.

[1430] First, the user enters their goal through an interface that allows them to set their own goals. For example, let's say the goal is to "improve customer satisfaction by 20% in 100 days." This goal information is temporarily stored on the smartphone. When the user presses the submit button, the goal information is sent to the server as an HTTP request. The server then stores the received goal information in a database.

[1431] Next, the server activates a task generation algorithm based on the stored goal information to generate specific tasks (e.g., "clean shelves," "replenish product inventory," "customer service"). It then places these generated tasks into a 100-day schedule. The server uses the Google Calendar API to synchronize the generated schedule with an online calendar and display it in the user's calendar.

[1432] Users report the progress of their daily tasks, for example, using a messaging application. For instance, they might use LINE to report, "I finished cleaning the shelves today." The device temporarily stores this progress information and sends it to the server as an HTTP request. The server stores the progress information in a database and analyzes the text and audio data of the progress report using an emotion recognition engine called EmotionRecognizer to understand the user's emotions. Based on this emotion data, the server then adjusts the tasks.

[1433] Based on the emotion recognition information, for example, if the user is feeling stressed, the system generates a suggestion such as "Take a short break and try again" and notifies the user via the LINE API. Conversely, if the user completes a task and their emotion is "joy" or "satisfaction," the system provides feedback such as "Great job! Keep up the good work!"

[1434] This system makes it easier for users to consistently achieve their goals. Furthermore, by adjusting tasks to take staff emotional states into account, it can improve work performance and reduce stress.

[1435] As a concrete example, the system operates based on the following prompt:

[1436] User goal: "Improve customer satisfaction by 20% in 100 days"

[1437] Tasks: "Clean shelves, Restock items, Customer support"

[1438] Emotion data from text: "I'm feeling stressed"

[1439]

[1440] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1441] Step 1:

[1442] The user enters goal information through a dedicated interface. For example, they might enter a goal such as "Increase customer satisfaction by 20% in 100 days." The terminal temporarily stores this input data and displays a submit button for the user to confirm the input. When the user clicks the submit button, the goal information is sent from the terminal to the server as an HTTP request.

[1443] Input: User's goal information

[1444] Output: HTTP request sent to the server

[1445] Step 2:

[1446] The server stores the received target information in a database. Based on the stored target information, it activates a task generation algorithm. This algorithm generates specific tasks such as "cleaning shelves," "replenishing product inventory," and "customer service."

[1447] Input: Target Information

[1448] Output: Generated tasks

[1449] Step 3:

[1450] The server schedules the generated tasks over a 100-day period. Specifically, it uses the Google Calendar API to place each task on a specific date and synchronizes it with the online calendar. This allows users to check their schedule on their smartphone calendar.

[1451] Input: Generated tasks

[1452] Output: Online calendar placed schedule

[1453] Step 4:

[1454] Users report the progress of their daily tasks using a messaging application. For example, they might use LINE to report, "I finished cleaning the shelves today." The device temporarily stores this progress information and sends it to the server as an HTTP request.

[1455] Input: Task progress information

[1456] Output: HTTP request sent to the server

[1457] Step 5:

[1458] The server stores the received progress information in a database. Next, it uses an emotion recognition engine to analyze the text and audio data included in the progress report to recognize the user's emotions. For example, it extracts emotional states such as "stress" or "satisfaction" from the text.

[1459] Input: Task progress information

[1460] Output: Recognized emotion data

[1461] Step 6:

[1462] The server generates feedback and suggestions based on recognized emotion data and task progress information. For example, if the user is identified as "stressed," it might suggest, "Try taking a short break." This feedback and suggestions are then communicated to the user via the LINE API.

[1463] Input: Recognized emotion data, task progress information

[1464] Output: Feedback and suggestions notified to the user.

[1465] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1466] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include those described above. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions shown by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1467] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[1468] [Fourth Embodiment]

[1469] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1470] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1471] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1472] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[1473] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1474] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1475] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1476] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[1477] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1478] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1479] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1480] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1481] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1482] This invention provides a system for users to set specific goals, schedule the tasks necessary to achieve those goals, and manage their progress. This system functions particularly effectively in business environments and provides a means for users to more easily achieve their long-term goals.

[1483] System Overview

[1484] This system includes an interface for users to set goals, means for generating tasks based on saved goal information, means for placing generated tasks on a schedule, means for synchronizing with a scheduling management system, communication means for reporting progress, and means for adjusting tasks based on saved progress information.

[1485] Program processing

[1486] User Goal Setting

[1487] User: Enter a specific goal, such as "lose 5kg in 100 days," using a dedicated interface.

[1488] Terminal: The goal entered by the user is temporarily saved to a buffer, and a submit button is provided.

[1489] User: Click the submit button to send the target information.

[1490] Terminal: Sends target information to the server in HTTP request format.

[1491] Server: Stores received target information in the database.

[1492] Schedule creation

[1493] Server: Activates the task generation algorithm based on the target information.

[1494] Server: Generates specific tasks (e.g., exercise three times a week, daily meal management tasks).

[1495] Server: Place these tasks on a 100-day schedule.

[1496] Server: Synchronizes schedules generated using the Google Calendar API with the scheduling management system.

[1497] Device: The user's schedule is displayed in Google Calendar.

[1498] Progress Monitoring

[1499] User: Report daily task progress via LINE chat. Send a message like, "I went for a 30-minute run today."

[1500] Terminal: Temporarily stores received progress information and sends it to the server.

[1501] Server: Saves progress information to the database.

[1502] Proposal adjustment

[1503] Server: Analyzes progress data and evaluates the task's completion status.

[1504] Server: Generates new suggestions as needed. For example, it might suggest adjusting the difficulty level or introducing new exercise methods.

[1505] Server: Sends suggestions to users via the LINE API.

[1506] Device: Display new suggestions to users via LINE chat.

[1507] User: Review the new suggestion and take the next step. Accept the suggestion, "Let's try a 10-minute walk today."

[1508] Specific example

[1509] If a user sets a goal of "losing 5kg in 100 days" on the first day, the system automatically generates 100 days' worth of exercise and diet management tasks and registers them in Google Calendar. The user reports daily via LINE chat, "I ran for 30 minutes today," and the server monitors the progress. If exercise is not performed for three consecutive days, the system notifies the user via LINE chat with a new suggestion, such as "Let's start with a light walk today." In this way, users can receive continuous and effective support towards achieving their goals.

[1510] As described above, the present invention realizes a system that provides comprehensive support for effectively achieving user-defined goals.

[1511] The following describes the processing flow.

[1512] Step 1:

[1513] User: Enter a goal, such as "lose 5kg in 100 days," using the dedicated interface.

[1514] Step 2:

[1515] Terminal: Temporarily saves the goal information entered by the user and displays a submit button.

[1516] Step 3:

[1517] User: Click the submit button to send the target information.

[1518] Step 4:

[1519] Terminal: Sends target information to the server in HTTP request format.

[1520] Step 5:

[1521] Server: Stores received target information in the database.

[1522] Step 6:

[1523] Server: Activates the task generation algorithm based on the saved target information.

[1524] Step 7:

[1525] Server: Generates specific tasks (e.g., exercise three times a week or daily meal management).

[1526] Step 8:

[1527] Server: Places the generated tasks into a 100-day schedule.

[1528] Step 9:

[1529] Server: Uses the Google Calendar API to synchronize the generated schedule with the scheduling management system.

[1530] Step 10:

[1531] Device: Displays the user's schedule in Google Calendar.

[1532] Step 11:

[1533] User: Report daily task progress via LINE chat. Send a message like, "I went for a 30-minute run today."

[1534] Step 12:

[1535] Terminal: Temporarily stores received progress information and sends it to the server as an HTTP request.

[1536] Step 13:

[1537] Server: Saves progress information to the database.

[1538] Step 14:

[1539] Server: Analyzes progress data and evaluates task completion status.

[1540] Step 15:

[1541] Server: Generates new suggestions as needed. For example, it might suggest, "Let's try a 10-minute walk today."

[1542] Step 16:

[1543] Server: Sends suggestions to users via the LINE API.

[1544] Step 17:

[1545] Device: Display new suggestions to users via LINE chat.

[1546] Step 18:

[1547] User: Review the suggestion and take the next step. Accept the suggestion, saying, "Let's try a 10-minute walk today."

[1548] (Example 1)

[1549] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1550] Traditional task management systems struggled to effectively generate and schedule tasks based on user-defined goals. In particular, maintaining user motivation was difficult in managing progress toward long-term goals, and there was a lack of proper analysis of progress information and provision of new suggestions.

[1551] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1552] In this invention, the server includes an interface means for the user to input pre-set goals, means for storing the input goal information, means for generating tasks based on the stored goal information, means for scheduling the generated tasks over a certain period of time, means for synchronizing the scheduled tasks with a scheduling management system, communication means for the user to report the progress of tasks, means for storing the reported progress information, means for adjusting tasks based on the stored progress information, means for notifying the user of the adjusted tasks, a server for activating a task generation algorithm, means for synchronizing the generated schedule via an API, and a server for analyzing progress data and generating new suggestions. This enables the user to effectively set and manage long-term goals and receive appropriate suggestions based on their progress.

[1553] "Interface means" refers to an input device or software for the user to input a target.

[1554] "Goal information" refers to data related to the goals that the user has set and aims to achieve.

[1555] A "storage method" is a database or storage device for storing target information and progress information.

[1556] A "task generation algorithm" is a program that automatically generates specific tasks based on objective information.

[1557] "Means of scheduling" refers to a program or function that schedules generated tasks over a specific period of time.

[1558] A "schedule management system" is software or a service used to manage schedules.

[1559] "Communication means" refers to a device or function for receiving progress reports from users.

[1560] "Progress information" refers to data about the progress of tasks performed by the user.

[1561] "Means of adjusting tasks" refers to a program or function that modifies or rearranges the original task based on saved progress information.

[1562] "Means of notification" refers to a device or software used to notify the user after the task has been adjusted.

[1563] A "server" is a computer system used to perform various actions and functions.

[1564] An "API" is an interface that enables communication between different software components.

[1565] A "proposal generation server" is a computer system that analyzes progress data and provides new suggestions to users.

[1566] This invention provides a system for users to set specific goals, schedule the tasks necessary to achieve those goals, and manage their progress. This system functions particularly effectively in business environments and provides a means for users to more easily achieve their long-term goals. Embodiments of this system are described in detail below.

[1567] System Configuration

[1568] This system includes the following main components:

[1569] 1. Interface means: This refers to an input device or software for the user to input a goal. For example, a web interface or a mobile application falls into this category. The user uses this interface to input the goal.

[1570] 2. Storage means: A database or storage device for storing the entered target information and progress information. In this embodiment, a MySQL database is used.

[1571] 3. Task Generation Algorithm: This program generates specific tasks based on objective information. This algorithm is implemented in Python.

[1572] 4. Means of placing tasks on a schedule: This is a program or function that places generated tasks on a schedule over a certain period of time. This is also implemented in Python, and this schedule is synchronized with an online calendar using the Google Calendar API.

[1573] 5. Communication means: A device or function for receiving progress reports from users. In particular, progress is received using a messaging application (e.g., LINE API).

[1574] 6. Means of adjusting tasks: This is a program or function that modifies or rearranges the original task based on saved progress information. This part will also be implemented as a Python script.

[1575] 7. Proposal generation server: This is a computer system that analyzes progress data and generates new proposals.

[1576] Specific example

[1577] Below is a specific example scenario for setting the goal of "losing 5 kg in 100 days."

[1578] First, the user enters a goal, such as "lose 5kg in 100 days," using a dedicated interface. The terminal temporarily stores this goal information in a buffer and displays a send button. When the user clicks the send button, the terminal sends the goal information to the server in the form of an HTTP request. The server stores the received goal information in its database.

[1579] Next, the server activates a task generation algorithm based on the stored goal information. This algorithm generates specific tasks, such as "exercise three times a week" or "daily meal management tasks." These tasks are placed on a 100-day schedule, and the server synchronizes this with an online calendar using the Google Calendar API.

[1580] Users report their daily task progress via LINE. For example, they might send a LINE chat message saying, "I went for a 30-minute run today." The device sends the received progress information to the server, which stores the information in a database. The server analyzes the progress data and generates new suggestions as needed. For example, it might send a suggestion like, "Let's start with a light walk today," to the user via the LINE API. The device then displays this suggestion to the user in a LINE chat.

[1581] Input prompts for the generative AI model

[1582] "Please create a program that automatically generates a schedule and tasks for losing 5kg in 100 days, and manages progress using Google Calendar and LINE. Also, please provide new suggestions if progress is unsatisfactory."

[1583] Thus, the system of the present invention provides integrated management and support for effectively achieving user-defined goals.

[1584] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1585] Step 1:

[1586] The user enters their goal into a dedicated interface.

[1587] Input: A specific goal such as "lose 5kg in 100 days."

[1588] Output: A format in which target information is temporarily stored on the device.

[1589] Specific action: The user enters a goal into a web interface or mobile app and clicks the "Submit" button.

[1590] Step 2:

[1591] The device sends target information to the server.

[1592] Input: Goal information entered by the user.

[1593] Output: Target information is sent to the server in JSON format.

[1594] Specific operation: JavaScript code sends the form data to the server as an HTTP POST request.

[1595] Step 3:

[1596] The server saves the received target information to the database.

[1597] Input: Target information sent from the device.

[1598] Output: Target information is saved to the database.

[1599] Specific operation: Using the Flask framework in Python, received data is stored in a MySQL database using SQL queries.

[1600] Step 4:

[1601] The server activates a task generation algorithm based on the target information.

[1602] Input: Target information stored in the database.

[1603] Output: The generated task list.

[1604] Specific operation: A Python script is launched, generating a task list tailored to the goal.

[1605] Step 5:

[1606] The server places the generated tasks into a 100-day schedule.

[1607] Input: The generated task list.

[1608] Output: Schedule information.

[1609] Specific operation: Arrange the task list in a calendar format, calculate the schedule for each day, and create a 100-day schedule.

[1610] Step 6:

[1611] The server synchronizes schedules generated using the Google Calendar API.

[1612] Input: 100-day schedule.

[1613] Output: Schedule added to Google Calendar.

[1614] Specific action: Call the Google Calendar API and add the schedule information to the user's Google Calendar.

[1615] Step 7:

[1616] The device displays the user's schedule in Google Calendar.

[1617] Input: Current schedule information from the Google Calendar API.

[1618] Output: The schedule displayed in the user's Google Calendar.

[1619] Specific operation: The schedule is displayed through the Google Calendar app or web interface.

[1620] Step 8:

[1621] Users report the progress of their daily tasks via LINE.

[1622] Input: Progress report such as "I went for a 30-minute run today."

[1623] Output: Progress information is temporarily saved to the device.

[1624] Specific action: The user opens the LINE app and sends a progress report to a designated bot.

[1625] Step 9:

[1626] The terminal sends the received progress information to the server.

[1627] Input: Progress information received via LINE.

[1628] Output: Progress information is sent to the server in JSON format.

[1629] Specific operation: Received messages using the LINE Messaging API are temporarily stored and then sent to the server via an HTTP request.

[1630] Step 10:

[1631] The server saves progress information to the database.

[1632] Input: Progress information sent from the device.

[1633] Output: Progress information is saved to the database.

[1634] Specific operation: The received progress information is parsed in JSON format and added to the database using an SQL query.

[1635] Step 11:

[1636] The server analyzes the progress data and evaluates the task's completion status.

[1637] Input: Progress data stored in the database.

[1638] Output: Analysis results and proposed solutions.

[1639] Specific operation: A Python script analyzes progress data and runs an algorithm to evaluate the degree of task completion.

[1640] Step 12:

[1641] The server generates new suggestions as needed.

[1642] Input: Analysis results of progress data.

[1643] Output: New proposal.

[1644] Specific operation: Based on the progress status, an algorithm is applied to suggest the next action, generating a new proposal.

[1645] Step 13:

[1646] The server sends the suggestion to the user via the LINE API.

[1647] Input: Generated suggestion content.

[1648] Output: The suggestion message sent to the user.

[1649] Specific operation: Use the LINE Messaging API to send the generated suggestions to the user as text messages.

[1650] Step 14:

[1651] The device displays new suggestions to the user via LINE chat.

[1652] Input: Suggestion message sent from the server.

[1653] Output: The suggestion message displayed to the user.

[1654] Specific action: A notification will be displayed within the user's LINE app.

[1655] Step 15:

[1656] The user reviews the new proposal and takes the next step.

[1657] Input: Suggestions from the server.

[1658] Output: The user's next action.

[1659] Specific actions: Review the proposal and begin taking action according to the day's schedule.

[1660] (Application Example 1)

[1661] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1662] In conventional factory production, task management and scheduling by robots are often done manually, resulting in inefficiencies and a lack of accuracy. Furthermore, real-time progress monitoring and task adjustments based on progress information are difficult, leading to decreased production efficiency. Additionally, limited communication methods for proper task progress reporting result in insufficient coordination between managers and robots. This creates a challenge in the overall functioning of factory production management.

[1663] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1664] In this invention, the server includes an interface means for a user to input pre-set goals, means for storing the input goal information, means for generating tasks based on the stored goal information, means for scheduling the generated tasks over a certain period of time, means for synchronizing the scheduled tasks with a scheduling management system, communication means for the user to report the progress of tasks, means for storing the reported progress information, means for adjusting tasks based on the stored progress information, means for notifying the user of the adjusted tasks, means for assigning tasks to production equipment, means for monitoring the progress of tasks performed by robots in real time, means for storing and analyzing progress information in a database, and means for fine-tuning tasks and generating new suggestions based on the analysis results. This enables efficient scheduling and management of production tasks by factory robots, and is expected to improve production efficiency through real-time progress monitoring and adjustment.

[1665] "Production equipment" is a general term for the equipment and devices used in manufacturing sites such as factories, and especially includes robots and automated machinery.

[1666] A "task" is a unit of work or activity set up to achieve a specific goal, and refers to the specific work that must be accomplished in a production process.

[1667] "Progress monitoring" is a process of tracking the status of task completion in real time and evaluating the degree of achievement and progress.

[1668] "Task adjustment" is the process of modifying the content and schedule of existing tasks based on the results of progress monitoring.

[1669] "Interface means" refers to the means by which a user inputs instructions into a system, and specifically includes touchscreens and keyboards.

[1670] "Storage methods" refer to means of temporarily or long-term storage of entered information, and specifically include hard disks and databases.

[1671] "Methods for scheduling" refer to methods for planning generated tasks over a certain period and scheduling tasks according to that plan.

[1672] A "schedule management system" is a system for organizing and managing tasks and other work along a timeline, and specifically includes online calendars.

[1673] "Communication methods" refer to means of sending and receiving information between users and systems, and specifically include the internet and messaging applications.

[1674] A "database" is a management system for systematically storing and managing information, enabling the efficient storage, retrieval, and manipulation of multiple datasets.

[1675] "Means of generating proposals" refers to methods for creating new work plans or adjustment plans based on progress data and task status.

[1676] "Means of synchronization" refer to methods for matching information and data across multiple systems and devices, which enables real-time data sharing.

[1677] The system for carrying out this invention provides a comprehensive solution for users to efficiently manage production equipment and effectively perform robotic production tasks. Specific embodiments of this system are described below.

[1678] User Interface

[1679] The interface for users to input pre-set goals can be operated via a touchscreen or keyboard. Using this interface, users can set goals such as "have a robot assemble product A." The entered goal information is temporarily stored in a buffer and then sent to the server. This information is stored in a database and used in subsequent processing.

[1680] Task generation and scheduling

[1681] The server generates tasks based on the goal information set by the user. This task generation process defines specific tasks, such as "installing part A" or "inspection process." The generated tasks are then scheduled over a specific period. Algorithms such as Scikit-learn are used for task scheduling to place tasks within optimal timeframes.

[1682] The generated schedule is synchronized with Google Calendar and other online calendars, allowing users to easily see the overall picture of their tasks through the scheduling management system.

[1683] Progress monitoring and data storage

[1684] As the robot performs each task, its progress is monitored in real time. The MQTT protocol is used for this monitoring, and progress data is sent to a server. This progress information is stored in a database and used for subsequent analysis.

[1685] Adjustments and proposals based on progress information

[1686] The saved progress data is analyzed on the server. If the progress is behind the goal, the server generates new suggestions to fine-tune the task. These suggestions, such as "Let's start with a lighter task," are sent to the user. LINE or other messaging applications are used for these notifications.

[1687] Specific example

[1688] If the factory manager sets on the first day to "assign the assembly task of product A to the robot," the system automatically generates 100 days' worth of assembly and quality check tasks and registers them in Google Calendar. Each time the robot completes a task, progress information is reported sequentially via the MQTT protocol, and the server saves this information to a database. If a task is not completed for three consecutive days, the system notifies the user via LINE chat with a new suggestion, such as "Let's start with a lighter checking process."

[1689] Example of a prompt

[1690] "Generate a schedule for the factory robot to perform the assembly task of part A between 2 PM and 4 PM every day. If the progress report is delayed, generate and submit a new proposal."

[1691] In this way, users can effectively manage production equipment and receive continuous support towards achieving their goals. Furthermore, since robot tasks are managed efficiently, overall production efficiency improves.

[1692] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1693] Step 1:

[1694] To set a goal, the user inputs the specific goal on the terminal using an interface. This input information is temporarily stored in a buffer and, after pressing the send button, is sent to the server in the form of an HTTP request. The server stores the received goal information in its database.

[1695] Input: User-entered goal information (e.g., "Have a robot assemble product A")

[1696] Data processing: Temporarily stored in a buffer, then converted to HTTP request format.

[1697] Output: Target information sent to the server

[1698] Step 2:

[1699] The server invokes a task generation algorithm based on the objective information to generate specific tasks. This uses Scikit-learn to optimally generate tasks that correspond to the objective.

[1700] Input: Saved target information

[1701] Data processing: Data calculations using task generation algorithms

[1702] Output: A specific task list has been generated (e.g., "Installation of part A", "Checking process")

[1703] Step 3:

[1704] The generated tasks are placed on a schedule over a set period. The server places the tasks in the most suitable time slots and synchronizes them with the online calendar using the Google Calendar API.

[1705] Input: Generated task list

[1706] Data processing: Task scheduling and synchronization with Google Calendar

[1707] Output: Schedule displayed in the scheduling management system

[1708] Step 4:

[1709] As the robot performs each task, its progress is monitored in real time. Progress data is sent from the robot to the server using the MQTT protocol. The server stores the received progress information in a database.

[1710] Input: Progress data sent from the robot

[1711] Data processing: Real-time data collection using the MQTT protocol.

[1712] Output: Progress information saved on the server

[1713] Step 5:

[1714] The server analyzes the stored progress data and evaluates the task's completion status. If progress is behind the target, the server generates new suggestions as needed.

[1715] Input: Saved progress data

[1716] Data processing: Analysis and evaluation of progress data

[1717] Output: New suggestion (e.g., "Let's start with a simple checking process")

[1718] Step 6:

[1719] The server notifies the user of newly generated suggestions. This notification is typically sent using a messaging application, such as LINE Talk. The user then reviews the suggestions and takes the next action.

[1720] Input: Generated proposal

[1721] Data processing: Message generation and sending

[1722] Output: Suggestions notified to the user

[1723] Through the above processing steps, the system can efficiently manage and coordinate production tasks performed by factory robots, providing continuous support to the user.

[1724] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1725] This invention combines an emotion engine with a system that schedules and manages the progress of tasks necessary to achieve pre-set goals for the user. The system recognizes emotions from text and voice data entered by the user and provides appropriate feedback and suggestions based on those emotions. This helps users maintain sustained motivation and action towards their goals.

[1726] System Overview

[1727] This system includes an interface for users to input goals, means for storing the inputted goal information, means for generating tasks based on the stored goal information, means for scheduling the generated tasks, means for synchronizing with a scheduling management system, means for users to report task progress, means for emotion recognition using an emotion engine, means for adjusting tasks based on stored progress information and recognized emotions, and means for notifying users of adjusted tasks and feedback.

[1728] Program processing

[1729] User Goal Setting

[1730] User: Enter a goal, such as "lose 5kg in 100 days," using the dedicated interface.

[1731] Terminal: Temporarily saves the goal information entered by the user and displays a submit button.

[1732] User: Click the submit button to send the target information.

[1733] Terminal: Sends target information to the server in HTTP request format.

[1734] Server: Stores received target information in the database.

[1735] Schedule creation

[1736] Server: Activates the task generation algorithm based on the target information.

[1737] Server: Generates specific tasks (e.g., exercise three times a week or daily meal management).

[1738] Server: Place these tasks on a 100-day schedule.

[1739] Server: Synchronizes schedules generated using the Google Calendar API with the scheduling management system.

[1740] Device: The user's schedule is displayed in Google Calendar.

[1741] Progress Monitoring

[1742] User: Report daily task progress via LINE chat. Send a message like, "I went for a 30-minute run today."

[1743] Terminal: Temporarily stores received progress information and sends it to the server as an HTTP request.

[1744] Server: Saves progress information to the database.

[1745] Server: Analyzes received text and audio data using an emotion engine to recognize the user's emotions.

[1746] Proposal adjustment

[1747] Server: Analyzes progress data and recognized sentiment information to evaluate task completion status.

[1748] Server: Generates new suggestions as needed. For example, if the user is feeling stressed, it might suggest, "Let's start today with a light walk."

[1749] Server: Sends suggestions to users via the LINE API.

[1750] Device: Display new suggestions to users via LINE chat.

[1751] User: Review the suggestion and take the next step. Accept the suggestion, saying, "Let's try a 10-minute walk today."

[1752] Specific example

[1753] If a user sets a goal of "losing 5kg in 100 days" on the first day, the system automatically generates 100 days' worth of exercise and diet management tasks and registers them in Google Calendar. The user reports daily via LINE chat, "I ran for 30 minutes today," and the server manages their progress and emotions. If the user fails to complete tasks for three consecutive days, the system uses an emotion engine to check if the user is feeling fatigued or stressed and notifies them via LINE chat with a new suggestion, such as "Let's start with a light walk today." In this way, users can receive sustained and effective support towards achieving their goals.

[1754] As described above, the present invention realizes a system that provides comprehensive support for effectively achieving user-set goals. By introducing an emotion engine, flexible responses according to the user's emotional state become possible, making it easier to maintain motivation and overcome challenges.

[1755] The following describes the processing flow.

[1756] Step 1:

[1757] User: Enter a goal, such as "lose 5kg in 100 days," using the dedicated interface.

[1758] Step 2:

[1759] Terminal: Temporarily saves the goal information entered by the user and displays a submit button.

[1760] Step 3:

[1761] User: Click the submit button to send the target information.

[1762] Step 4:

[1763] Terminal: Sends target information to the server in HTTP request format.

[1764] Step 5:

[1765] Server: Stores received target information in the database.

[1766] Step 6:

[1767] Server: Activates the task generation algorithm based on the saved target information.

[1768] Step 7:

[1769] Server: Generates specific tasks (e.g., exercise three times a week or daily meal management).

[1770] Step 8:

[1771] Server: Places the generated tasks into a 100-day schedule.

[1772] Step 9:

[1773] Server: Uses the Google Calendar API to synchronize the generated schedule with the scheduling management system.

[1774] Step 10:

[1775] Device: Displays the user's schedule in Google Calendar.

[1776] Step 11:

[1777] User: Report daily task progress via LINE chat. Send a message like, "I went for a 30-minute run today."

[1778] Step 12:

[1779] Terminal: Temporarily stores received progress information and sends it to the server as an HTTP request.

[1780] Step 13:

[1781] Server: Saves progress information to the database.

[1782] Step 14:

[1783] Server: Analyzes progress data and evaluates task completion status.

[1784] Step 15:

[1785] Terminal: Sends text data and voice data sent by the user via LINE chat to the emotion engine.

[1786] Step 16:

[1787] Server: The emotion engine analyzes text and audio data to recognize the user's emotions. For example, it determines whether the user is feeling stressed.

[1788] Step 17:

[1789] Server: Combines recognized emotion information and progress data to generate new suggestions as needed. For example, if the user is feeling stressed, it might suggest, "Let's start today with a light walk."

[1790] Step 18:

[1791] Server: Sends suggestions to users via the LINE API.

[1792] Step 19:

[1793] Device: Display new suggestions to users via LINE chat.

[1794] Step 20:

[1795] User: Review the suggestion and take the next step. Accept the suggestion, saying, "Let's try a 10-minute walk today."

[1796] Step 21:

[1797] Server: After the user takes the next action, the new progress data is analyzed again by the sentiment engine, and the feedback loop continues.

[1798] (Example 2)

[1799] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1800] Traditional goal-achievement support systems have problems with efficiently scheduling the tasks necessary to achieve user-defined goals, and lacking appropriate feedback and suggestions tailored to the user's emotional state, as well as task progress management. Therefore, there is a need for a system that supports users in maintaining sustained motivation and taking action towards their goals.

[1801] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1802] In this invention, the server includes information input means for inputting goals set in advance by the user; information storage means for storing the input goal information; task generation means for generating tasks based on the stored goal information; schedule placement means for placing the generated tasks on a schedule over a certain period of time; synchronization means for synchronizing the placed schedule with a schedule management system; communication means for the user to report the progress of tasks; progress information storage means for storing the reported progress information; task adjustment means for adjusting tasks based on progress information and emotion information; notification means for notifying the user of adjusted tasks and suggestions; and emotion recognition means for analyzing the user's emotions. This enables the user to perform tasks while maintaining sustained motivation toward their goals.

[1803] "Information input means" refers to the interface through which the user inputs their goals.

[1804] "Information storage means" refers to data storage means for temporarily or permanently storing the input target information.

[1805] "Task generation means" refers to algorithms or software that generate specific tasks based on stored target information.

[1806] "Schedule placement means" refers to a function or system that places generated tasks on a schedule over a certain period of time.

[1807] "Synchronization means" refers to the function of synchronizing the placed schedule with the schedule management system and electronic calendar.

[1808] "Communication methods" refer to the communication infrastructure and applications that users use to report the progress of tasks.

[1809] "Progress information storage means" refers to a data storage means for saving progress information of tasks reported by users.

[1810] "Task adjustment means" refers to a function that modifies, updates, or proposes new tasks based on progress information and sentiment information.

[1811] "Notification means" refers to communication methods or systems used to notify users of adjusted tasks or new suggestions.

[1812] "Emotion recognition means" refers to algorithms and software used to analyze a user's emotions.

[1813] This invention relates to a system for scheduling tasks and managing progress to achieve user-defined goals. In particular, by incorporating an emotion engine, it is possible to provide appropriate feedback and suggestions according to the user's emotional state, thereby maintaining the user's motivation. This system includes information input means, information storage means, task generation means, schedule placement means, synchronization means, communication means, progress information storage means, task adjustment means, notification means, and emotion recognition means.

[1814] Hardware and software to be used

[1815] 1. Information Input Method: This is an interface for the user to input their goals. This is implemented in a web browser or mobile application.

[1816] 2. Information storage means: A storage system for temporarily storing the entered target information. A SQL-based database management system (DBMS) is used as the database.

[1817] 3. Task generation method: An algorithm that generates specific tasks based on objective information. This may involve using machine learning models or rule-based algorithms.

[1818] 4. Schedule Placement Method: A tool for scheduling generated tasks over a certain period. It can be integrated with a scheduling management system by using the Google Calendar API.

[1819] 5. Synchronization method: A system for synchronizing schedules with electronic calendars such as Google Calendar. This includes an authentication process using OAuth 2.0.

[1820] 6. Communication method: A messaging application for users to report task progress. LINE API or other messaging platforms will be used.

[1821] 7. Progress Information Storage Method: A system that stores progress information reported by users in a database. Data is managed using SQL.

[1822] 8. Task Adjustment Mechanism: A system for adjusting tasks based on progress information and emotional information. It uses an emotional engine to analyze the user's emotions and perform appropriate task adjustments.

[1823] 9. Notification Method: A system for notifying users of adjusted tasks and new suggestions. Notifications are sent using the LINE API.

[1824] 10. Emotion Recognition Methods: Algorithms for analyzing user emotions. Natural language processing (NLP) models and emotion analysis models are used.

[1825] Specific example

[1826] On the first day, when a user sets a goal of "losing 5kg in 100 days," the system automatically generates 100 days' worth of exercise and diet management tasks and registers them in Google Calendar. The user reports daily via LINE chat, "Today I went for a 30-minute run." The server receives this progress information and stores it in a database. It also uses an emotion engine to analyze the user's emotional state. Based on this information, if the user is feeling stressed, it notifies them via LINE chat with new suggestions, such as "Let's start with a light walk today." This allows the user to receive sustained and effective support towards achieving their goal.

[1827] Example of a prompt

[1828] "Set specific exercise and dietary tasks to lose 5kg in 100 days, and design a system to track your daily progress and emotions."

[1829] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1830] Step 1: Goal Setting

[1831] User: Enter your goal using the dedicated interface (e.g., "Lose 5kg in 100 days").

[1832] Input: Goal information entered by the user.

[1833] Output: Temporarily stored data on the interface.

[1834] Specific operation: The user fills in their goal in a dedicated input form and clicks the submit button.

[1835] Step 2: Send target information

[1836] Terminal: Temporarily stores the entered target information and displays a submit button. When the user clicks the submit button, the target information is sent to the server as an HTTP request.

[1837] Input: Temporarily saved target information.

[1838] Output: Target information sent to the server.

[1839] Specific operation: The terminal checks the target information and sends the data to the server in the form of an HTTP request. The POST method is used.

[1840] Step 3: Save the target information

[1841] Server: Stores received target information in the database.

[1842] Input: Target information from the HTTP request.

[1843] Output: Target information stored in the database.

[1844] Specific operation: The server parses the received target information and uses SQL queries to perform INSERT operations on the database.

[1845] Step 4: Task Generation

[1846] Server: Activates a task generation algorithm based on saved goal information to generate specific tasks (e.g., exercise three times a week or daily meal management).

[1847] Input: Target information stored in the database.

[1848] Output: Generated task (template).

[1849] Specific operation: The server generates task content using machine learning algorithms and rule-based algorithms.

[1850] Step 5: Schedule Placement

[1851] Server: Schedules the generated tasks for a set period of time.

[1852] Input: The generated task.

[1853] Output: 100-day schedule.

[1854] Specific operation: The server uses the Calendar API to map tasks to dates and times and place them as schedules.

[1855] Step 6: Synchronize with the scheduling management system

[1856] Server: Synchronizes schedules generated using the Google Calendar API with the scheduling management system.

[1857] Input: A 100-day schedule.

[1858] Output: Schedule synced to Google Calendar.

[1859] Specific operation: The server uses OAuth 2.0 for authentication and synchronizes schedules via the Calendar API.

[1860] Step 7: Progress Report

[1861] User: Report daily task progress via LINE chat (e.g., "I went for a 30-minute run today").

[1862] Input: Progress information reported by the user via LINE chat.

[1863] Output: Temporarily saved progress information.

[1864] Specific action: The user sends progress information in text format via LINE chat.

[1865] Step 8: Send progress information

[1866] Terminal: Temporarily stores received progress information and sends it to the server as an HTTP request.

[1867] Input: Progress information received via LINE chat.

[1868] Output: Progress information sent to the server.

[1869] Specific operation: The terminal checks the received progress information and sends the data to the server in the form of an HTTP request.

[1870] Step 9: Save progress information

[1871] Server: Saves progress information to the database.

[1872] Input: Progress information from the HTTP request.

[1873] Output: Progress information stored in the database.

[1874] Specific operation: The server parses the received progress information and uses SQL queries to perform INSERT operations on the database.

[1875] Step 10: Emotion Recognition

[1876] Server: Analyzes received text and audio data using an emotion engine to recognize the user's emotions.

[1877] Input: Progress information and text or audio data.

[1878] Output: Recognized emotion information.

[1879] Specific operation: The server uses a natural language processing (NLP) model to analyze text data and perform sentiment recognition.

[1880] Step 11: Task Adjustment

[1881] Server: Analyzes progress data and recognized sentiment information, evaluates task completion status, and generates new suggestions.

[1882] Input: Progress information and sentiment information stored in the database.

[1883] Output: Adjusted tasks or new proposals.

[1884] Specific operation: Use machine learning models to analyze progress and sentiment data and generate suggestions to reduce the user's burden as needed.

[1885] Step 12: Notification of Proposal

[1886] Server: Sends suggestions to users via the LINE API.

[1887] Input: Adjusted tasks or new proposals.

[1888] Output: Suggestion notification sent to the user.

[1889] Specific operation: The suggestion is sent to the user's messaging application using the LINE API.

[1890] Step 13: Review and implement the proposal

[1891] User: Review the suggestion and take the next step (e.g., "Let's try a 10-minute walk today").

[1892] Input: Suggestion notification sent from the server.

[1893] Output: New task executed.

[1894] Specific actions: The user reviews the received suggestions and takes action based on them.

[1895] (Application Example 2)

[1896] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1897] Traditional task management systems often assign tasks unilaterally, regardless of the user's emotional state, making it difficult to maintain motivation. Furthermore, in real-world settings such as retail stores, inadequate task and emotional management of staff can lead to decreased work efficiency and customer satisfaction. This can result in accumulated stress and fatigue among staff, ultimately leading to a decline in overall work performance.

[1898] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for storing goal information entered by the user, means for generating tasks based on the stored goal information, and means for scheduling the generated tasks over a certain period of time. This makes it possible to support the user in maintaining motivation and taking action towards their goals. It also includes emotion recognition means for recognizing emotions from text and voice data entered by the user, and means for providing feedback and suggestions based on the recognized emotions. This makes it possible to adjust tasks while taking into account the emotional state of the staff, thereby improving work performance and reducing stress.

[1899] A "user" is an individual or professional who sets goals and manages the progress of tasks.

[1900] "Interface means" refers to the means by which a user inputs a goal, and primarily refers to a graphical user interface (GUI).

[1901] "Goal information" refers to information about the goals that the user has set in advance and wants to achieve.

[1902] "Means of storage" refers to databases and storage devices used to store entered target information and progress information.

[1903] A "task" is a specific job or activity that needs to be performed in order to achieve a goal.

[1904] "Means of scheduling" refers to methods for systematically placing generated tasks within a specific timeframe, such as calendar applications.

[1905] A "schedule management system" is a system used for managing schedules, and includes online calendars and similar tools.

[1906] "Communication methods" refer to communication methods used by users to report the progress of tasks, and include messaging applications, etc.

[1907] "Reported progress information" refers to information that users have reported regarding the results of their task execution using communication methods.

[1908] "Emotion recognition means" refers to systems and algorithms for recognizing emotions from text or voice data entered by the user.

[1909] "Means of providing feedback and suggestions" refers to means of providing appropriate feedback and action suggestions based on perceived emotions, and includes using messaging applications to send notifications.

[1910]

[1911] To implement this invention, a smartphone application called "Smart Staff Manager" is used. The specific configuration and processing details are described below.

[1912] First, the user enters their goal through an interface that allows them to set their own goals. For example, let's say the goal is to "improve customer satisfaction by 20% in 100 days." This goal information is temporarily stored on the smartphone. When the user presses the submit button, the goal information is sent to the server as an HTTP request. The server then stores the received goal information in a database.

[1913] Next, the server activates a task generation algorithm based on the stored goal information to generate specific tasks (e.g., "clean shelves," "replenish product inventory," "customer service"). It then places these generated tasks into a 100-day schedule. The server uses the Google Calendar API to synchronize the generated schedule with an online calendar and display it in the user's calendar.

[1914] Users report the progress of their daily tasks, for example, using a messaging application. For instance, they might use LINE to report, "I finished cleaning the shelves today." The device temporarily stores this progress information and sends it to the server as an HTTP request. The server stores the progress information in a database and analyzes the text and audio data of the progress report using an emotion recognition engine called EmotionRecognizer to understand the user's emotions. Based on this emotion data, the server then adjusts the tasks.

[1915] Based on the emotion recognition information, for example, if the user is feeling stressed, the system generates a suggestion such as "Take a short break and try again" and notifies the user via the LINE API. Conversely, if the user completes a task and their emotion is "joy" or "satisfaction," the system provides feedback such as "Great job! Keep up the good work!"

[1916] This system makes it easier for users to consistently achieve their goals. Furthermore, by adjusting tasks to take staff emotional states into account, it can improve work performance and reduce stress.

[1917] As a concrete example, the system operates based on the following prompt:

[1918] User goal: "Improve customer satisfaction by 20% in 100 days"

[1919] Tasks: "Clean shelves, Restock items, Customer support"

[1920] Emotion data from text: "I'm feeling stressed"

[1921]

[1922] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1923] Step 1:

[1924] The user enters goal information through a dedicated interface. For example, they might enter a goal such as "Increase customer satisfaction by 20% in 100 days." The terminal temporarily stores this input data and displays a submit button for the user to confirm the input. When the user clicks the submit button, the goal information is sent from the terminal to the server as an HTTP request.

[1925] Input: User's goal information

[1926] Output: HTTP request sent to the server

[1927] Step 2:

[1928] The server stores the received target information in a database. Based on the stored target information, it activates a task generation algorithm. This algorithm generates specific tasks such as "cleaning shelves," "replenishing product inventory," and "customer service."

[1929] Input: Target Information

[1930] Output: Generated tasks

[1931] Step 3:

[1932] The server schedules the generated tasks over a 100-day period. Specifically, it uses the Google Calendar API to place each task on a specific date and synchronizes it with the online calendar. This allows users to check their schedule on their smartphone calendar.

[1933] Input: Generated tasks

[1934] Output: Online calendar placed schedule

[1935] Step 4:

[1936] Users report the progress of their daily tasks using a messaging application. For example, they might use LINE to report, "I finished cleaning the shelves today." The device temporarily stores this progress information and sends it to the server as an HTTP request.

[1937] Input: Task progress information

[1938] Output: HTTP request sent to the server

[1939] Step 5:

[1940] The server stores the received progress information in a database. Next, it uses an emotion recognition engine to analyze the text and audio data included in the progress report to recognize the user's emotions. For example, it extracts emotional states such as "stress" or "satisfaction" from the text.

[1941] Input: Task progress information

[1942] Output: Recognized emotion data

[1943] Step 6:

[1944] The server generates feedback and suggestions based on recognized emotion data and task progress information. For example, if the user is identified as "stressed," it might suggest, "Try taking a short break." This feedback and suggestions are then communicated to the user via the LINE API.

[1945] Input: Recognized emotion data, task progress information

[1946] Output: Feedback and suggestions notified to the user.

[1947] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1948] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1949] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[1950] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1951] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[1952] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[1953] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[1954] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[1955] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[1956] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[1957] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[1958] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[1959] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[1960] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1961] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[1962] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[1963] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[1964] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[1965] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[1966] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[1967] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[1968] The following is further disclosed regarding the embodiments described above.

[1969] (Claim 1)

[1970] An interface means for the user to input pre-set goals,

[1971] A means for saving the input target information,

[1972] A means for generating tasks based on saved target information,

[1973] A means of scheduling the generated tasks over a certain period of time,

[1974] A means of synchronizing the assigned schedule with the schedule management system,

[1975] A means of communication for users to report the progress of a task,

[1976] A means of saving the reported progress information,

[1977] A means of adjusting tasks based on saved progress information,

[1978] A system that includes means for notifying about coordinated tasks.

[1979] (Claim 2)

[1980] The system according to claim 1, further comprising means for synchronizing the configured schedule with an online calendar.

[1981] (Claim 3)

[1982] The system according to claim 1, wherein the means of communication for the user to report the progress of a task is to use a messaging application.

[1983] "Example 1"

[1984] (Claim 1)

[1985] An interface means for the user to input pre-set goals,

[1986] A means for saving the input target information,

[1987] A means for generating tasks based on saved target information,

[1988] A means of scheduling the generated tasks over a certain period of time,

[1989] A means of synchronizing the assigned schedule with the schedule management system,

[1990] A means of communication for users to report the progress of a task,

[1991] A means of saving the reported progress information,

[1992] A means of adjusting tasks based on saved progress information,

[1993] A means of notifying about coordinated tasks,

[1994] A server that starts the task generation algorithm,

[1995] A means of synchronizing the generated schedule via an API,

[1996] A system that includes a server that analyzes progress data and generates new proposals.

[1997] (Claim 2)

[1998] The means further include for synchronizing the configured schedule with an online calendar.

[1999] The system according to claim 1.

[2000] (Claim 3)

[2001] The means of communication for the user to report the progress of the task is to use a messaging application.

[2002] The system according to claim 1.

[2003] "Application Example 1"

[2004] (Claim 1)

[2005] An interface means for the user to input pre-set goals,

[2006] A means for saving the input target information,

[2007] A means for generating tasks based on saved target information,

[2008] A means of scheduling the generated tasks over a certain period of time,

[2009] A means of synchronizing the assigned schedule with the schedule management system,

[2010] A means of communication for users to report the progress of a task,

[2011] A means of saving the reported progress information,

[2012] A means of adjusting tasks based on saved progress information,

[2013] A means of notifying about coordinated tasks,

[2014] Means for assigning tasks to production equipment,

[2015] A means of monitoring the progress of tasks performed by robots in real time,

[2016] A means of saving and analyzing progress information in a database,

[2017] A system that includes means for fine-tuning tasks and generating new proposals based on analysis results.

[2018] (Claim 2)

[2019] The system according to claim 1, further comprising means for synchronizing the configured schedule with an online calendar.

[2020] (Claim 3)

[2021] The system according to claim 1, wherein the means of communication for the user to report the progress of a task is to use a messaging application.

[2022] "Example 2 of combining an emotion engine"

[2023] (Claim 1)

[2024] An information input method for the user to input pre-set goals,

[2025] Information storage means for storing input target information,

[2026] A task generation means that generates tasks based on stored target information,

[2027] A scheduling means for placing generated tasks on a schedule over a certain period of time,

[2028] A synchronization method for syncing the assigned schedule with the schedule management system,

[2029] A means of communication for users to report the progress of a task,

[2030] A means for storing reported progress information,

[2031] A task adjustment means that adjusts tasks based on progress information and emotional information,

[2032] A notification system for notifying about adjusted tasks and suggestions,

[2033] A system that includes emotion recognition means for analyzing the user's emotions.

[2034] (Claim 2)

[2035] The system according to claim 1, further comprising synchronization means for synchronizing the arranged schedule with an electronic calendar.

[2036] (Claim 3)

[2037] The system according to claim 1, wherein the means of communication for the user to report the progress of a task is to use a messaging application.

[2038] "Application example 2 when combining with an emotional engine"

[2039] (Claim 1)

[2040] An interface means for the user to input pre-set goals,

[2041] A means for saving the input target information,

[2042] A means for generating tasks based on saved target information,

[2043] A means of scheduling the generated tasks over a certain period of time,

[2044] A means of synchronizing the assigned schedule with the schedule management system,

[2045] A means of communication for users to report the progress of a task,

[2046] A means of saving the reported progress information,

[2047] A means of adjusting tasks based on saved progress information,

[2048] A means of notifying adjusted tasks and feedback,

[2049] An emotion recognition means for recognizing emotions from text and voice data entered by the user,

[2050] Means of providing feedback and suggestions based on recognized emotions,

[2051] A system that includes this.

[2052] (Claim 2)

[2053] The means further include for synchronizing the configured schedule with an online calendar.

[2054] The system according to claim 1.

[2055] (Claim 3)

[2056] The means of communication for the user to report the progress of the task is to use a messaging application.

[2057] and includes means of providing feedback and suggestions based on recognized emotions,

[2058] The system according to claim 1. [Explanation of Symbols]

[2059] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. An interface means for the user to input pre-set goals, A means for saving the input target information, A means for generating tasks based on saved target information, A means of scheduling the generated tasks over a certain period of time, A means of synchronizing the assigned schedule with the schedule management system, A means of communication for users to report the progress of a task, A means of saving the reported progress information, A means of adjusting tasks based on saved progress information, A system that includes means for notifying about coordinated tasks.

2. The system according to claim 1, further comprising means for synchronizing the configured schedule with an online calendar.

3. The system according to claim 1, wherein the means of communication for the user to report the progress of a task is to use a messaging application.

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