System

Abstract

A system is provided.SOLUTION: A system comprising: means for setting a goal of a user; means for inputting an existing schedule of the user; means for generating an optimal daily schedule based on the goal and the existing schedule; means for notifying the user of the generated schedule; means for notifying a start time of a task based on the schedule; means for transmitting a task completion notification at an end time of each task; means for re-generating a schedule in real time when the task is not completed; means for notifying the user of the re-generated schedule; and means for analyzing task execution data of the user and optimizing a long-term schedule.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] For people who have difficulty managing themselves or their time independently, it is difficult to make daily progress toward achieving big goals and dreams. Conventional support systems require users to manage their own schedules and maintain motivation, which often leads to frustration. Furthermore, when unexpected events disrupt the schedule, real-time support is often required. The present invention aims to provide a system that reliably supports the achievement of daily goals without relying on the user's will. [Means for solving the problem]

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

[0006] The system includes a means for setting a user's goals, a means for inputting the user's existing schedule, a means for generating an optimal daily schedule based on the goals and the existing schedule, a means for notifying the user of the generated schedule, a means for notifying the user of task start times based on the schedule, a means for sending a task completion confirmation notification at the end time of each task, a means for regenerating the schedule in real time if a task is not completed, a means for notifying the user of the regenerated schedule, and a means for analyzing the user's task execution data and optimizing the long-term schedule.

[0007] "User" means an individual who uses the system to set goals and manage schedules.

[0008] A "goal" is a purpose with a specific outcome and time frame that the user wants to achieve.

[0009] The "existing schedule" refers to information indicating the user's daily activities and plans.

[0010] "Means for generating a schedule" refers to a function for planning the optimal way to spend a day based on input goals and an existing schedule.

[0011] "Means for notifying the schedule" refers to a function for notifying the user of the generated schedule.

[0012] The "means for notifying the start time of a task" is a function for notifying the user of the start time of execution of each task.

[0013] The "means for sending a confirmation notification of task completion" is a function for confirming the completion status of each task to the user at the end time of the task.

[0014] "Means for regenerating schedules" refers to the functionality for readjusting schedules in real time if tasks are not completed.

[0015] "Task execution data" refers to data that records information on whether or not a user has executed a task.

[0016] "Means for optimizing long-term schedules" refers to a function for analyzing past task execution data and adjusting future schedules. [Brief explanation of the drawings]

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

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

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

[0020] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

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

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

[0023] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0024] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0025] [First embodiment]

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

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

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

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

[0030] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

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

[0032] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

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

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

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

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

[0038] The present invention is a system that optimizes daily time management and provides a feasible schedule for users to achieve their major goals. This system performs the following specific program processing.

[0039] Setting goals and getting existing schedules

[0040] The user launches the app and sets a goal, such as "lose 5 kg in one month." The user then inputs their existing daily schedule, including work hours, sleep times, and meal times, into the app.

[0041] Schedule data transmission and analysis

[0042] Once all the data is entered, the device sends this information to a server, which then generates an optimal daily schedule based on the user's goals and existing schedule. For example, the server might generate a schedule that includes 30 minutes of jogging every morning and 30 minutes of strength training every evening.

[0043] Schedule notifications and alarm settings

[0044] The server sends the generated schedule to the terminal, which then notifies the user. For example, the following schedule is displayed:

[0045] 6:00 AM - Jogging (30 minutes)

[0046] 6:30 AM - Breakfast

[0047] 7:00 AM - Get ready for work

[0048] 8:00 AM - Commute

[0049] 9:00 AM - Start work

[0050] 12:00 PM - Lunch Break (Light Exercise)

[0051] 1:00 PM - Back to work

[0052] 6:00 PM - Finish work

[0053] 7:00 PM - Dinner

[0054] 8:00 PM - Strength Training (30 minutes)

[0055] 9:00 PM - Relaxation Time

[0056] 10:00 PM - Sleep

[0057] Additionally, the device will set an alarm at the start time of each task, for example, a "Start jogging" alarm at 6:00 AM.

[0058] Checking task progress

[0059] At the end of each task, the device sends a task completion confirmation to the user. For example, at 6:30 AM, a confirmation message is displayed asking, "Did you finish jogging?" The user can then respond in the app whether or not the task is complete.

[0060] Rescheduling

[0061] If the user answers "I haven't completed the task," the device sends that information to the server, which then regenerates the schedule in real time based on this information and adjusts the time of the next task, for example, by moving the jogging time to 7:00 AM.

[0062] Long-term schedule optimization

[0063] The server collects and analyzes the user's task execution data, identifying progress and problems. The system further optimizes the schedule for the following week and beyond. For example, if the user is not continuing their jogging routine, the system will make adjustments such as shortening the jogging time and suggesting a different exercise.

[0064] Specific examples

[0065] Let's take the example of a user's goal of "learning English conversation at a daily conversation level in one month." The server generates the following schedule:

[0066] 6:00 AM - English Conversation Listening (30 minutes)

[0067] 6:30 AM - Breakfast

[0068] 7:00 AM - Get ready for work

[0069] 8:00 AM - Commute

[0070] 9:00 AM - Start work

[0071] 12:00 PM - Lunch Break (English Conversation Practice)

[0072] 1:00 PM - Back to work

[0073] 6:00 PM - Finish work

[0074] 7:00 PM - Dinner

[0075] 8:00 PM - English Speaking Practice (30 minutes)

[0076] 9:00 PM - Relaxation Time

[0077] 10:00 PM - Sleep

[0078] This schedule is sent to the device, and an alarm is set at the start time of each task. For example, an alarm for the start of English conversation listening will sound at 6:00 AM.

[0079] If the user has not completed the task, the server regenerates the schedule and sends it to the device again, notifying it of the adjusted schedule, for example, by moving the listening time to 7:00 AM.

[0080] This system allows users to strictly manage their daily schedules and ensure that they continue to make efforts toward achieving their goals.

[0081] The processing flow will be explained below.

[0082] Step 1:

[0083] The user starts the app and goes to the "Goal Setting" screen. For example, they enter a specific goal, such as "lose 5 kg in one month."

[0084] Step 2:

[0085] On the "Enter Existing Schedule" screen, users enter their current lifestyle and daily activity schedule, including work start and end times, meal times, and sleep times.

[0086] Step 3:

[0087] The terminal transmits the data of the goal and the existing schedule to the server.

[0088] Step 4:

[0089] The server analyzes the received data and generates an optimal schedule for achieving the goal, for example, a daily schedule including 30 minutes of jogging every morning and 30 minutes of strength training in the evening.

[0090] Step 5:

[0091] The server transmits the generated schedule to the terminal.

[0092] Step 6:

[0093] The terminal notifies the user of the generated schedule. For example, the following schedule is displayed:

[0094] 6:00 AM - Jogging (30 minutes)

[0095] 6:30 AM - Breakfast

[0096] 7:00 AM - Get ready for work

[0097] 8:00 AM - Commute

[0098] 9:00 AM - Start work

[0099] 12:00 PM - Lunch Break (Light Exercise)

[0100] 1:00 PM - Back to work

[0101] 6:00 PM - Finish work

[0102] 7:00 PM - Dinner

[0103] 8:00 PM - Strength Training (30 minutes)

[0104] 9:00 PM - Relaxation Time

[0105] 10:00 PM - Sleep

[0106] Step 7:

[0107] Your device will set an alarm for the start time of each task, for example, a "Start jogging" alarm at 6:00 AM.

[0108] Step 8:

[0109] The device will send a task completion confirmation at the end of each task, for example, at 6:30 AM it will display the message "Did you finish jogging?"

[0110] Step 9:

[0111] The user responds to the app by completing a task, for example, by saying "I completed my jog."

[0112] Step 10:

[0113] If the user answers "I have not completed my jog," the device sends that information to the server.

[0114] Step 11:

[0115] The server regenerates the schedule in real time based on the information received. For example, it adjusts the schedule as follows:

[0116] 6:30 AM - Jogging (30 minutes)

[0117] 7:00 AM - Breakfast

[0118] 7:30 AM - Get ready for work

[0119] 8:00 AM - Commute

[0120] 9:00 AM - Start work

[0121] 12:00 PM - Lunch Break (Light Exercise)

[0122] 1:00 PM - Back to work

[0123] 6:00 PM - Finish work

[0124] 7:00 PM - Dinner

[0125] 8:00 PM - Strength Training (30 minutes)

[0126] 9:00 PM - Relaxation Time

[0127] 10:00 PM - Sleep

[0128] Step 12:

[0129] The server transmits the regenerated schedule to the terminal.

[0130] Step 13:

[0131] The terminal notifies the user of the regenerated schedule.

[0132] Step 14:

[0133] The server collects and analyzes the user's task execution data, thereby identifying the progress and problems.

[0134] Step 15:

[0135] The server optimizes the schedule for the next week, and if jogging is not performed as scheduled, for example, adjustments are made such as shortening the jogging time and suggesting a different exercise.

[0136] Step 16:

[0137] The server transmits the optimized long-term schedule to the terminal, and the terminal notifies the user of it.

[0138] Example 1

[0139] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0140] Conventional time management systems require users to create their own schedules, which does not necessarily allow for appropriate planning for achieving goals. Furthermore, if a user is unable to complete a task, subsequent schedule adjustments must be made manually, making efficient time management difficult. Furthermore, they lack a mechanism for optimizing schedules to achieve long-term goals. There is a need for a system that can solve these problems and provide effective and flexible time management to help users achieve their goals.

[0141] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0142] In this invention, the server includes a means for setting a user's goals, a means for inputting the user's existing schedule, and a cloud server and a means for using a generative AI model to generate an optimal daily schedule based on the goals and the existing schedule. This makes it possible to automatically generate an efficient and feasible schedule based on the goals set by the user, adjust the schedule in real time according to the daily progress, and support the achievement of long-term goals.

[0143] "User" means an individual or organization that uses the system to set goals and manage schedules.

[0144] "Means for setting goals" refers to a function or interface that allows users to input the goals they wish to achieve into the system.

[0145] "Means for inputting existing schedules" refers to a function or interface that allows users to input their daily plans and activity times into the system.

[0146] A "cloud server" is a server that stores and processes data via the Internet and is responsible for the system's main calculations and data processing.

[0147] A "generative AI model" is an algorithm or program that uses artificial intelligence technology to generate an optimal schedule based on a user's goals and existing schedule.

[0148] "Notification means" refers to a function or device that notifies users of schedules and alarms generated by the system.

[0149] "Means for notifying the start time of a task" refers to a function or device for notifying the user of the time when each task should start.

[0150] The "means for sending a confirmation notification of task completion" is a function or interface for confirming with the user whether or not the task has been completed at the end time of each task.

[0151] "Means for regenerating schedules in real time" refers to a function or system that instantly generates a new schedule based on information when a user does not complete a task.

[0152] "Means for analyzing task execution data and optimizing long-term schedules" refers to a function or program that analyzes users' daily task execution data and continuously adjusts and optimizes schedules.

[0153] The present invention is a system for managing daily tasks by providing an optimal schedule for a user to achieve their goals. Specific examples are shown below.

[0154] Setting goals and getting existing schedules

[0155] The app provides a means for users to launch the app and input the goal they want to achieve. For example, they can set a goal of "lose 5 kg in one month." Next, the app provides a means for users to input their existing schedule (e.g., work hours, sleep hours, meal times). This can be done using a device such as a smartphone or PC.

[0156] Data transmission and analysis

[0157] The device sends the user's input goals and existing schedule to the cloud server. The server then analyzes the input data using a generative AI model to generate an optimal daily schedule. At this time, the following prompt is input to the generative AI model:

[0158] "Please suggest an optimal daily schedule for losing 5 kg in one month."

[0159] Schedule notifications and alarm settings

[0160] The server sends the generated optimal schedule to the device, which then notifies the user. When the user receives the notification, the device sets an alarm at the start time of each task. For example, a notification to start jogging at 6:00 AM is displayed and an alarm sounds.

[0161] Check task progress and adjust in real time

[0162] At the end of each task, the device sends the user a task completion confirmation notification. For example, at 6:30 AM, when the jogging ends, a confirmation notification is displayed asking, "Have you finished jogging?" If the user replies that they have not completed the task, the device sends that information to the server. The server immediately recalculates the schedule, adjusts the time of the next task, and sends it again to the device. This results in an adjustment, such as changing the jogging time to 7:00 AM.

[0163] Long-term schedule optimization

[0164] The server continuously collects and analyzes the user's task execution data, identifying progress and problems and optimizing the schedule for the following week. For example, if the jogging time is too long, the server will suggest shortening the time and suggesting a different exercise.

[0165] Hardware and software examples

[0166] Hardware: smartphones, PCs, cloud servers

[0167] Software: Dedicated app, cloud-based data analysis tools, notification and alarm management system

[0168] Specific examples

[0169] If a user sets a goal of "mastering everyday conversation level English in one month," the server will generate the following schedule:

[0170] 6:00 AM - English Conversation Listening (30 minutes)

[0171] 6:30 AM - Breakfast

[0172] 7:00 AM - Get ready for work

[0173] 8:00 AM - Commute

[0174] 9:00 AM - Start work

[0175] 12:00 PM - Lunch Break (English Conversation Practice)

[0176] 1:00 PM - Back to work

[0177] 6:00 PM - Finish work

[0178] 7:00 PM - Dinner

[0179] 8:00 PM - English Speaking Practice (30 minutes)

[0180] 9:00 PM - Relaxation Time

[0181] 10:00 PM - Sleep

[0182] This schedule is sent to the device, and an alarm is set at the start time of each task. For example, an alarm for the start of English conversation listening will sound at 6:00 AM.

[0183] If the user has not completed the task, the server regenerates the schedule and sends it back to the device, notifying the user of the adjusted schedule. For example, the listening time can be moved to 7:00 AM. This ensures that the user maintains strict control over their daily schedule and continues to work toward achieving their goals.

[0184] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0185] Step 1:

[0186] The user launches the app and sets a goal. As input, the app inputs the goal they want to achieve (e.g., "lose 5 kg in one month"). As output, the app generates the user's goal data, which is used in subsequent processing steps.

[0187] Step 2:

[0188] The user inputs their existing schedule into the app. As input, they input their daily schedule (work time, sleep time, meal time, etc.). As output, the user's existing schedule data is generated. This schedule data is sent to the server along with the goal data.

[0189] Step 3:

[0190] The terminal transmits the input goal data and existing schedule data to the cloud server. As input, the terminal receives the user's goal data and existing schedule data. As output, the terminal generates a transmission request to the cloud server.

[0191] Step 4:

[0192] Based on the goal data and existing schedule data received by the server, an optimal schedule is generated using a generative AI model. The goal data and existing schedule data are received as input. A prompt statement (e.g., "Please suggest an optimal daily schedule for losing 5 kg in one month") is input to the generative AI model, and optimal schedule data is generated as output.

[0193] Step 5:

[0194] The server sends the generated schedule data to the terminal. As input, it receives the generated schedule data. As output, it generates the schedule data as a transmission request to the terminal.

[0195] Step 6:

[0196] The terminal notifies the user of the received schedule data. As input, the received schedule data is processed for display. As output, the schedule is displayed to the user and sent as a notification.

[0197] Step 7:

[0198] The terminal sets an alarm at the start time of each task. As input, it obtains the start time of each task in the schedule data. As output, an alarm is set and a notification is sent to the user at the specified time.

[0199] Step 8:

[0200] At the end time of each task, the terminal sends a confirmation notification of task completion to the user. As input, the end time of each task in the schedule data is obtained. As output, a confirmation notification of task completion is sent to the user.

[0201] Step 9:

[0202] The user responds to the task completion notification. As input, the user enters whether or not the task is completed into the app. As output, task completion data is generated.

[0203] Step 10:

[0204] If the task is not completed, the terminal sends the information to the server. As input, it receives the data of the task not completed. As output, it generates the information of the task not completed as a transmission request to the server.

[0205] Step 11:

[0206] The server regenerates the schedule in real time based on the data of incomplete tasks. As input, it receives the incomplete task data and inputs a prompt sentence again based on the generative AI model (e.g., "Please adjust your schedule, such as moving your jogging time to 7:00 AM."). As output, new schedule data is generated.

[0207] Step 12:

[0208] The server transmits the regenerated schedule data to the terminal. As input, the server receives the regenerated schedule data. As output, the server generates the schedule data as a transmission request to the terminal.

[0209] Step 13:

[0210] The terminal notifies the user of the regenerated schedule data. As input, the terminal processes the regenerated schedule data for display. As output, the schedule is notified to the user again.

[0211] Step 14:

[0212] The server continuously collects and analyzes user task execution data. The collected data is used as input, and the analysis results are generated as output.

[0213] Step 15:

[0214] The server optimizes the schedule for the following week based on the analysis results. The analysis results are received as input. The optimized schedule data for the following week is generated as output.

[0215] Step 16:

[0216] The server transmits the optimized schedule data for the next week and beyond to the terminal. As input, it receives the optimized schedule data. As output, it generates the schedule data as a transmission request to the terminal.

[0217] Step 17:

[0218] The terminal notifies the user of the optimized schedule data for the next week and beyond. As input, the optimized schedule data is processed for display. As output, the schedule is notified to the user.

[0219] (Application example 1)

[0220] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0221] Current factory production management systems do not efficiently manage operation plans for work equipment and machines, resulting in reduced production efficiency and difficulty in achieving production targets. Furthermore, the operating status of production equipment and maintenance plans are not adequately considered, making unplanned shutdowns and delays more likely to occur. Furthermore, work progress is not checked in real time, often resulting in delays in readjusting the production schedule. For these reasons, there was a need for effective production schedule generation and management to improve the efficiency of the entire factory.

[0222] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0223] In this invention, the server includes means for setting production targets to be achieved by factory work equipment and machines, means for inputting operation plans and maintenance plans for production equipment, means for generating an optimal daily schedule based on the targets and existing operation plans, means for notifying the relevant production equipment of work instructions based on the generated schedule, means for sending progress confirmation notifications at the end time of each production task, and means for regenerating the production schedule in real time if a production task is not completed. This makes it possible to maximize production efficiency and ensure the achievement of production targets.

[0224] A "means for setting user goals" is a system or device that allows a factory operator or manager to input production goals to be achieved for the factory's work equipment and machines.

[0225] The "means for inputting the user's existing schedule" refers to an interface or device for inputting the current operation plan and maintenance plan for the factory's work equipment and machines.

[0226] The "means for generating an optimal daily schedule based on the target and existing schedule" refers to an algorithm or software that calculates and generates an optimal daily schedule for the factory's work equipment and machines based on the set target and existing operation plan.

[0227] The "means for notifying the user of the generated schedule" refers to a system or device for notifying a factory operator or manager of the generated schedule.

[0228] The "means for notifying the start time of a task based on the schedule" refers to a system or device for notifying the work equipment or machines in a factory of the start time of each work task based on the schedule.

[0229] The "means for sending a confirmation notification of task completion at the end time of each task" is a system or device that sends a notification at the end time of each work task to confirm whether the task has been completed.

[0230] "Means for regenerating a schedule in real time if a task is not completed" refers to an algorithm or software that recalculates and regenerates the currently set schedule in real time based on information about incomplete tasks.

[0231] The "means for notifying users of the regenerated schedule" refers to a system or device for notifying factory operators or managers of the new regenerated schedule.

[0232] The "means for analyzing user task execution data and optimizing long-term schedules" refers to an analytical algorithm or software for optimizing factory work schedules over the long term based on collected task execution data.

[0233] The "means for setting production targets to be achieved by work equipment and machines in a factory" refers to a system or device for inputting and setting production targets set for work equipment and machines in a factory.

[0234] The "means for inputting the operation plan and maintenance plan of the production equipment" refers to an interface or device for inputting the operation schedule and maintenance schedule of the production equipment.

[0235] The "means for generating an optimal daily schedule based on the above-mentioned targets and existing operation plans" refers to an algorithm or software that calculates and generates an optimal daily schedule for the factory's work equipment and machines based on the set production targets and existing operation plans.

[0236] The "means for notifying the relevant production equipment of work instructions based on the generated schedule" refers to a system or device for notifying the relevant production equipment or machine of each work instruction based on the generated schedule.

[0237] The "means for sending a progress confirmation notification at the end time of each production task" refers to a system or device that sends a notification to confirm the progress of each production task at the end time of that task.

[0238] The "means for regenerating a production schedule in real time when a production task is not completed" refers to an algorithm or software that, when a production task is not completed, recalculates and regenerates the currently set production schedule in real time based on that information.

[0239] This invention is a system that optimizes the operation schedules of factory work equipment and machines and supports the achievement of production targets. Specifically, this describes a system in which factory operators input targets and existing operation plans, a server generates an optimal schedule based on that data, and monitors and adjusts the progress of each task in real time.

[0240] First, a factory operator accesses the system using a control terminal (e.g., a PC or tablet) and sets a production target. This target is specifically defined, for example, to assemble 1,000 products in one day. Next, the current operation plan and maintenance plan are entered into the system. This operation plan includes work time slots and existing maintenance times.

[0241] The server generates an optimal daily schedule based on the input goals and existing schedules. It is desirable to use AI models or machine learning algorithms for this calculation and generation. The generated schedule is notified to the work equipment via the control terminal. Using available cloud database services (e.g., AWS RDS) allows for efficient data management and storage.

[0242] When the start time for each work task arrives, the server notifies the relevant work equipment of the work instructions via the control terminal. The control terminal displays an alarm, such as "Assembly begins at 9:00." The work equipment executes the task, and when it is time to finish, the server checks the progress. This progress check is performed by the control terminal displaying a confirmation message to the operator. For example, a notification may be displayed asking, "Is the 9:00 assembly completed?"

[0243] If a work task is not completed, the operator enters that information into the system. The server regenerates the schedule in real time based on this information and notifies the work equipment of the re-adjusted schedule. Tasks are then rearranged according to this re-generated schedule, optimizing the work plan for the next day.

[0244] In the long term, the server will periodically analyze the task execution data collected and further optimize the schedule for the following week, enabling adjustments to be made to improve the factory's overall production efficiency.

[0245] For example, if a factory's daily production target is 1,000 products, a schedule will be provided that allows the robots to efficiently carry out the work within the specified working hours. This schedule will be strictly managed, and production progress will be checked on an ongoing basis, ensuring that efforts to achieve the target are continued.

[0246] An example of a prompt sentence might be:

[0247] "Generate an optimal task list and schedule for the factory robots between 9:00-12:00 and 13:00-18:00 so that they can efficiently assemble the daily target of 1,000 products."

[0248] In this way, it is a feature of the present invention that the factory's production efficiency is maximized and targets are achieved.

[0249] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0250] Step 1:

[0251] The user sets production targets for the factory's work equipment and machines using a control terminal. At this time, the user inputs the target value (e.g., assemble 1,000 products in one day). Data based on this is sent to the server.

[0252] Step 2:

[0253] Users use a control terminal to input existing operation and maintenance plans into the system. This data is also sent to the server. The input data includes work time slots and maintenance times.

[0254] Step 3:

[0255] The server generates an optimal daily schedule based on the received production targets, operation plans, and maintenance plans. It uses generative AI models and machine learning algorithms to calculate the optimal start and end times for each work task. This generated schedule is then sent from the server to the device.

[0256] Step 4:

[0257] The terminal notifies each piece of work equipment in the factory of the schedule it receives from the server. This notification includes the start and end times of each work task. Each piece of equipment begins operating according to the notified schedule.

[0258] Step 5:

[0259] When the start time for each work task arrives, the terminal sends a start command to the corresponding work equipment. For example, a notification such as "Assembly begins at 9:00" is displayed, and the equipment begins operation.

[0260] Step 6:

[0261] When the end time of each work task arrives, the terminal sends a task completion confirmation to the user. The user checks whether the task is completed and reports the result on the terminal.

[0262] Step 7:

[0263] If a task is not completed, the device sends the information to the server, which regenerates the schedule in real time based on the incomplete information, and the new schedule is sent to the device again.

[0264] Step 8:

[0265] The terminal receives the regenerated schedule and notifies each piece of work equipment of the new instructions, including the adjusted start and end times of each work task.

[0266] Step 9:

[0267] The server collects all task execution data and analyzes it for long-term schedule optimization. It uses machine learning algorithms to further optimize the schedule for the following week and beyond, and sends the results to the device.

[0268] This maximizes factory production efficiency and ensures production targets are met.

[0269] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0270] This invention is a system that optimizes daily time management and provides a feasible schedule for users to achieve their big goals. This system incorporates an emotion engine that recognizes the user's emotions and reflects them in the adjustment of schedules and tasks.

[0271] Setting goals and getting existing schedules

[0272] The user launches the app and sets a goal, such as "lose 5 kg in one month." The user then inputs their existing daily schedule, including work hours, sleep times, and meal times, into the app.

[0273] Schedule data transmission and analysis

[0274] Once all the data is entered, the device sends this information to a server, which then generates an optimal daily schedule based on the user's goals and existing schedule. For example, the device might create a daily schedule that includes 30 minutes of jogging every morning and 30 minutes of strength training in the evening.

[0275] Schedule notifications and alarm settings

[0276] The server sends the generated schedule to the terminal, which then notifies the user. For example, the following schedule is displayed:

[0277] 6:00 AM - Jogging (30 minutes)

[0278] 6:30 AM - Breakfast

[0279] 7:00 AM - Get ready for work

[0280] 8:00 AM - Commute

[0281] 9:00 AM - Start work

[0282] 12:00 PM - Lunch Break (Light Exercise)

[0283] 1:00 PM - Back to work

[0284] 6:00 PM - Finish work

[0285] 7:00 PM - Dinner

[0286] 8:00 PM - Strength Training (30 minutes)

[0287] 9:00 PM - Relaxation Time

[0288] 10:00 PM - Sleep

[0289] Additionally, the device will set an alarm at the start time of each task, for example, a "Start jogging" alarm at 6:00 AM.

[0290] Checking task progress

[0291] At the end of each task, the device sends a task completion confirmation to the user. For example, at 6:30 AM, a confirmation message is displayed asking, "Did you finish jogging?" The user can then respond in the app whether or not the task is complete.

[0292] Rescheduling

[0293] If the user answers "I haven't completed the task," the device sends that information to the server, which then regenerates the schedule in real time based on this information and adjusts the schedule accordingly, for example, by moving the jogging time to 7:00 AM.

[0294] Use of emotion engine

[0295] This system incorporates an emotion engine that recognizes the user's emotions. The device collects emotional data from the user's facial expressions, tone of voice, etc. and sends it to the server. The server uses this emotional data to adjust the schedule and change task priorities. For example, if the user is feeling stressed, the system will adjust the schedule by increasing time for relaxation and postponing hard tasks.

[0296] Long-term schedule optimization

[0297] The server collects and analyzes the user's task execution data and emotional data. This identifies progress and problems. The system further optimizes the schedule for the following week and beyond. For example, if jogging is not performed as planned, the system will shorten the jogging time and suggest a different exercise. The system also takes into account the user's emotional state when adjusting the schedule.

[0298] Specific examples

[0299] Let's take the example of a user's goal of "learning English conversation at a daily conversation level in one month." The server generates the following schedule:

[0300] 6:00 AM - English Conversation Listening (30 minutes)

[0301] 6:30 AM - Breakfast

[0302] 7:00 AM - Get ready for work

[0303] 8:00 AM - Commute

[0304] 9:00 AM - Start work

[0305] 12:00 PM - Lunch Break (English Conversation Practice)

[0306] 1:00 PM - Back to work

[0307] 6:00 PM - Finish work

[0308] 7:00 PM - Dinner

[0309] 8:00 PM - English Speaking Practice (30 minutes)

[0310] 9:00 PM - Relaxation Time

[0311] 10:00 PM - Sleep

[0312] This schedule is sent to the device, and an alarm is set at the start time of each task. For example, an alarm for the start of English conversation listening will sound at 6:00 AM.

[0313] If the user has not completed the task, the server regenerates the schedule and sends it to the device again, notifying it of the adjusted schedule, for example, by moving the listening time to 7:00 AM.

[0314] The emotion engine also recognizes the user's emotions, and if the user is feeling stressed, for example, it will adjust the system to increase relaxation time and postpone burdensome tasks.

[0315] This system allows users to strictly manage their daily schedules and ensure that they continue to make efforts toward achieving their goals.

[0316] The processing flow will be explained below.

[0317] Step 1:

[0318] The user starts the app and goes to the "Goal Setting" screen. For example, they enter a specific goal, such as "lose 5 kg in one month."

[0319] Step 2:

[0320] On the "Enter Existing Schedule" screen, users enter their current lifestyle and daily activity schedule, including work start and end times, meal times, and sleep times.

[0321] Step 3:

[0322] The terminal transmits the data of the goal and the existing schedule to the server.

[0323] Step 4:

[0324] The server analyzes the received data and generates an optimal schedule for achieving the goal, for example, a daily schedule including 30 minutes of jogging every morning and 30 minutes of strength training in the evening.

[0325] Step 5:

[0326] The server transmits the generated schedule to the terminal.

[0327] Step 6:

[0328] The terminal notifies the user of the generated schedule. For example, the following schedule is displayed:

[0329] 6:00 AM - Jogging (30 minutes)

[0330] 6:30 AM - Breakfast

[0331] 7:00 AM - Get ready for work

[0332] 8:00 AM - Commute

[0333] 9:00 AM - Start work

[0334] 12:00 PM - Lunch Break (Light Exercise)

[0335] 1:00 PM - Back to work

[0336] 6:00 PM - Finish work

[0337] 7:00 PM - Dinner

[0338] 8:00 PM - Strength Training (30 minutes)

[0339] 9:00 PM - Relaxation Time

[0340] 10:00 PM - Sleep

[0341] Step 7:

[0342] Your device will set an alarm for the start time of each task, for example, a "Start jogging" alarm at 6:00 AM.

[0343] Step 8:

[0344] The device will send a task completion confirmation at the end of each task, for example, at 6:30 AM it will display the message "Did you finish jogging?"

[0345] Step 9:

[0346] The user responds to the app by completing a task, for example, by saying "I completed my jog."

[0347] Step 10:

[0348] If the user answers "I have not completed my jog," the device sends that information to the server.

[0349] Step 11:

[0350] The server regenerates the schedule in real time based on the information received. For example, it adjusts the schedule as follows:

[0351] 6:30 AM - Jogging (30 minutes)

[0352] 7:00 AM - Breakfast

[0353] 7:30 AM - Get ready for work

[0354] 8:00 AM - Commute

[0355] 9:00 AM - Start work

[0356] 12:00 PM - Lunch Break (Light Exercise)

[0357] 1:00 PM - Back to work

[0358] 6:00 PM - Finish work

[0359] 7:00 PM - Dinner

[0360] 8:00 PM - Strength Training (30 minutes)

[0361] 9:00 PM - Relaxation Time

[0362] 10:00 PM - Sleep

[0363] Step 12:

[0364] The server transmits the regenerated schedule to the terminal.

[0365] Step 13:

[0366] The terminal notifies the user of the regenerated schedule.

[0367] Step 14:

[0368] Furthermore, the device is equipped with an emotion engine that collects emotional data from the user's facial expressions and tone of voice, and periodically transmits this data to a server.

[0369] Step 15:

[0370] The server analyzes the emotional data to understand the user's stress level and motivation. For example, if the user feels tired, it will suggest taking more rest time.

[0371] Step 16:

[0372] The server adjusts the schedule based on the emotional data. For example, if the user is feeling stressed, the server will increase the amount of time for relaxation and postpone hard tasks.

[0373] Step 17:

[0374] The server transmits the schedule adjusted by the emotion engine to the terminal.

[0375] Step 18:

[0376] The terminal notifies the user of the adjusted schedule.

[0377] Step 19:

[0378] The server collects and analyzes the user's task execution data and emotional data, thereby identifying achievement status and problems.

[0379] Step 20:

[0380] The server optimizes the schedule for the next week, and if jogging is not performed as planned, for example, it will shorten the jogging time and suggest a different exercise. It also takes into account schedule adjustments based on the user's emotions.

[0381] Step 21:

[0382] The server transmits the optimized long-term schedule to the terminal, and the terminal notifies the user of it.

[0383] Specific examples

[0384] Let's take the example of a user's goal of "learning English conversation at a daily conversation level in one month." The server generates the following schedule:

[0385] 6:00 AM - English Conversation Listening (30 minutes)

[0386] 6:30 AM - Breakfast

[0387] 7:00 AM - Get ready for work

[0388] 8:00 AM - Commute

[0389] 9:00 AM - Start work

[0390] 12:00 PM - Lunch Break (English Conversation Practice)

[0391] 1:00 PM - Back to work

[0392] 6:00 PM - Finish work

[0393] 7:00 PM - Dinner

[0394] 8:00 PM - English Speaking Practice (30 minutes)

[0395] 9:00 PM - Relaxation Time

[0396] 10:00 PM - Sleep

[0397] This schedule is sent to the device, and an alarm is set at the start time of each task. For example, an alarm for the start of English conversation listening will sound at 6:00 AM.

[0398] If the user has not completed the task, the server regenerates the schedule and sends it to the device again, notifying it of the adjusted schedule, for example, by moving the listening time to 7:00 AM.

[0399] The emotion engine also recognizes the user's emotions, and if the user is feeling stressed, for example, it will adjust the system to increase relaxation time and postpone burdensome tasks.

[0400] This system allows users to strictly manage their daily schedules and ensure that they continue to make efforts toward achieving their goals.

[0401] Example 2

[0402] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0403] In modern society, time management is essential for achieving individual goals, but maintaining an optimal schedule in a busy daily life is difficult. Furthermore, few existing systems adjust schedules taking into account the user's emotional state, which can increase the user's mental burden. This can lead to a decrease in motivation to achieve goals and make it difficult to achieve results.

[0404] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for setting a user's goal, means for inputting the user's existing schedule, means for generating an optimal daily schedule based on the goal and the existing schedule, means for notifying the user of the generated schedule, means for notifying the user of task start times based on the schedule, means for sending a task completion confirmation notification at the end time of each task, means for regenerating a schedule in real time if a task is not completed, means for notifying the user of the regenerated schedule, means for collecting the user's task execution data and emotion data, means for adjusting the schedule based on the emotion data, and means for analyzing the task execution data and emotion data and optimizing the long-term schedule. This increases the user's goal achievement rate and enables schedule management with less mental burden on the user.

[0405] The "means for setting user goals" provides an interface and functionality for users to input specific goals they wish to achieve.

[0406] The "means for inputting the user's existing schedule" provides an interface and functionality for the user to input and save the current daily activity schedule.

[0407] The "means for generating an optimal daily schedule based on the goals and existing schedule" refers to a means for creating an optimal daily activity plan using algorithms and analytical techniques, using the collected goal data and existing schedule data.

[0408] The "means for notifying the user of the generated schedule" provides a function for displaying or notifying the user of the generated schedule on the user's terminal.

[0409] The "means for notifying the start time of a task based on the schedule" provides an alarm or notification function for notifying the user of the start time of each task according to the set schedule.

[0410] The "means for sending a confirmation notification of task completion at the end time of each task" provides a function for sending a notification to the user at the end time of the task to confirm the completion status of the task.

[0411] "Means for regenerating a schedule in real time if a task is not completed" provides a function to instantly recalculate and create a new schedule if it is determined that the user has not completed a task.

[0412] The "means for notifying the user of the regenerated schedule" provides a function for displaying or notifying the user of the regenerated schedule on the user's terminal.

[0413] "Means for collecting user task execution data and emotional data" refers to providing a function for collecting which tasks a user has performed and the user's emotional state (e.g., facial expressions and tone of voice).

[0414] The "means for adjusting the schedule based on the emotional data" provides a function for analyzing the collected emotional data and changing the tasks and time allocation of the schedule according to the user's mental state.

[0415] The "means for analyzing the task execution data and emotion data and optimizing the long-term schedule" provides a function for analyzing the collected data and optimizing future schedules to help users achieve their long-term goals.

[0416] This invention provides a system that optimizes daily time management and provides a feasible schedule for users to achieve their major goals. The system incorporates an emotion engine that recognizes the user's emotions and reflects them in schedule and task adjustments.

[0417] Hardware and software used

[0418] This system is implemented using the following hardware and software:

[0419] Device: Personal devices such as smartphones and tablets

[0420] Server: Cloud server or dedicated server

[0421] Database: RDBMS such as MySQL or PostgreSQL

[0422] Emotion recognition engine: Sentiment analysis tools such as IBM Watson and Azure Emotion API

[0423] Programming language: Python, JavaScript, etc.

[0424] Communication protocol: HTTP / HTTPS

[0425] System Embodiments

[0426] 1. How users set goals

[0427] The user launches the application and inputs a goal, for example, a specific goal such as "lose 5 kg in one month." This goal is entered through the application's interface (e.g., a text box).

[0428] 2. Enter an existing schedule

[0429] Users enter their daily activities (work time, sleep time, meal time, etc.) into the application, and this data is entered and stored by the application on their smartphone or tablet.

[0430] 3. Data transmission and schedule generation

[0431] The device collects your goals and existing schedule and sends it to a server, which uses an algorithm to generate an optimal daily schedule. For example, it could create a schedule that includes 30 minutes of jogging every morning and 30 minutes of strength training in the evening.

[0432] 4. Schedule notifications and alarm settings

[0433] The server sends the generated schedule back to the device, which then notifies the user of the schedule. An alarm is also set at the start time of each task. For example, an alarm for "start jogging" can be set to ring at 6:00 AM.

[0434] 5. Check the progress of your tasks

[0435] At the end of each task, the device sends the user a confirmation that the task is complete. For example, at 6:30 AM, the device displays the message "Did you finish jogging?" The user can respond in the app.

[0436] 6. Rearrange your schedule

[0437] If the user indicates that the task is not complete, the device sends that information to the server, which then regenerates the schedule and adjusts the time of the next task, for example, moving the jogging time to 7:00 AM.

[0438] 7. Use of Emotion Engines

[0439] The device collects emotional data from the user's facial expressions and tone of voice and sends it to a server. The server uses this data to adjust schedules and change task priorities. For example, if the user is feeling stressed, the device can increase relaxation time and postpone hard tasks.

[0440] 8. Long-term schedule optimization

[0441] The server collects and analyzes the user's task execution and emotional data to optimize the schedule for the following week. For example, if the user does not go jogging as planned, the server will adjust the schedule by shortening the jogging time and suggesting a different exercise.

[0442] Specific examples

[0443] If a user sets a goal of "learning everyday conversational English in one month," the following schedule will be generated:

[0444] 6:00 AM - English Conversation Listening (30 minutes)

[0445] 6:30 AM - Breakfast

[0446] 7:00 AM - Get ready for work

[0447] 8:00 AM - Commute

[0448] 9:00 AM - Start work

[0449] 12:00 PM - Lunch Break (English Conversation Practice)

[0450] 1:00 PM - Back to work

[0451] 6:00 PM - Finish work

[0452] 7:00 PM - Dinner

[0453] 8:00 PM - English Speaking Practice (30 minutes)

[0454] 9:00 PM - Relaxation Time

[0455] 10:00 PM - Sleep

[0456] This schedule is notified to the device, and an alarm is set to ring at 6:00 AM, for example, to "Start English Conversation Listening." If a task is not completed, the server regenerates and resends the schedule. Furthermore, the system recognizes the user's emotions and adjusts the schedule, such as increasing relaxation time, if the user is feeling stressed.

[0457] This creates a system that allows users to strictly manage their daily schedules and ensures that they continue to make efforts toward achieving their goals.

[0458] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0459] Step 1: Set goals and schedule

[0460] The user launches the app and inputs their goal. Specifically, they use the app's interface to set a goal such as "lose 5 kg in one month" or "learn conversational English in one month." Next, they input their existing schedule (work hours, sleep times, meal times, etc.).

[0461] input:

[0462] the goal

[0463] Existing Schedule

[0464] output:

[0465] User data (goal and schedule information)

[0466] Specific behavior:

[0467] The user enters their goal in the text box on the app's "Goal Setting" screen and presses the "Save" button.

[0468] The user inputs an existing schedule on the "Schedule Setting" screen and presses the "Save" button.

[0469] Step 2: Send data and generate schedule

[0470] The device sends user data to a server, which then uses a built-in algorithm to generate an optimal daily schedule, such as a 30-minute morning jog and 30 minutes of strength training in the evening.

[0471] input:

[0472] User data (goal and schedule information)

[0473] output:

[0474] Generated daily schedule

[0475] Specific behavior:

[0476] The terminal sends an HTTP POST request to the server, sending the goal and existing schedule to the server.

[0477] The server receives the data and runs a scheduling algorithm to generate an optimal schedule.

[0478] The server returns the generated schedule to the terminal in JSON format.

[0479] Step 3: Schedule notifications and alarm settings

[0480] The server sends the generated schedule to the terminal, which receives it, notifies the user, and sets an alarm at the start time of each task.

[0481] input:

[0482] Generated daily schedule

[0483] output:

[0484] Schedule Notifications

[0485] Set alarms for the start time of each task

[0486] Specific behavior:

[0487] The server sends the schedule data to the endpoint.

[0488] The terminal receives the schedule data and notifies the user using the smartphone's notification function.

[0489] The app uses the internal alarm function to set an alarm at the specified time.

[0490] Step 4: Check the progress of the task

[0491] At the end of each task, the device will send a task completion confirmation to the user. For example, at 6:30 AM, a confirmation message will be displayed asking, "Did you finish jogging?"

[0492] input:

[0493] Task completion progress

[0494] output:

[0495] Task completion confirmation

[0496] Specific behavior:

[0497] The device sets a system timer that triggers a notification when the task finishes.

[0498] When the task finishes, the app will display a pop-up notification prompting the user to confirm completion.

[0499] The user responds by pressing a "Done" or "Incomplete" button within the app.

[0500] Step 5: Rearrange your schedule

[0501] If the user answers "I have not completed the task," the device sends that information to the server, which then regenerates the schedule in real time.

[0502] input:

[0503] Task completion progress

[0504] output:

[0505] Regenerated Schedule

[0506] Specific behavior:

[0507] The terminal sends the user's response to the server via an HTTP POST request.

[0508] The server executes a rescheduling algorithm based on the received information.

[0509] The server sends the new schedule in JSON format to the device, and the device again sets notifications and alarms for the user.

[0510] Step 6: Use the Emotion Engine

[0511] The device collects emotional data from the user's facial expressions and tone of voice and sends it to the server, which uses the data to adjust schedules and change task priorities.

[0512] input:

[0513] Emotional data (facial expressions and tone of voice)

[0514] output:

[0515] Adjusted Schedule

[0516] Specific behavior:

[0517] The device uses a camera and microphone to collect emotional data.

[0518] The device transmits the collected data to the server in real time.

[0519] The server analyzes the data using a sentiment analysis engine and runs a schedule adjustment algorithm.

[0520] The adjusted schedule is sent to the terminal.

[0521] Step 7: Long-term schedule optimization

[0522] The server collects the user's task execution data and emotional data, analyzes it, and optimizes the schedule for the following week.

[0523] input:

[0524] Task execution data

[0525] Emotional Data

[0526] output:

[0527] Optimized long-term schedule

[0528] Specific behavior:

[0529] The server periodically aggregates all user data and stores it in a database.

[0530] The server uses machine learning algorithms to analyze the data and identify patterns and issues.

[0531] The server generates a new optimized weekly schedule based on the analysis results and sends it to the terminal.

[0532] (Application example 2)

[0533] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0534] Existing time management systems cannot consider individual emotional states when optimizing daily schedules to help users achieve their goals. As a result, emotional factors such as stress and lack of motivation often prevent users from completing their schedules. It is also difficult to readjust schedules in real time when tasks are not completed. This leaves users without the support of an efficient schedule to achieve their set goals.

[0535] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0536] In this invention, the server includes means for setting a user's goals, means for inputting an existing schedule, means for generating an optimal daily schedule based on the goals and the existing schedule, means for notifying the user of the generated schedule, means for notifying the user of task start times based on the schedule, means for sending a task completion confirmation notification at the end time of each task, means for regenerating a schedule in real time if a task is not completed, means for notifying the user of the regenerated schedule, means for recognizing the user's emotions, means for adjusting the schedule based on the emotions, and means for analyzing the user's task execution data and optimizing the long-term schedule. This makes it possible to provide an optimal schedule in real time while taking the user's emotional state into consideration.

[0537] "User" refers to an individual who uses this system and wishes to optimize their schedule to achieve a goal.

[0538] A "goal" is a specific outcome or purpose that a user wants to achieve, such as mastering a particular skill within a certain period of time or taking an action to improve their health.

[0539] "Existing schedule" refers to the user's daily plans and activities, including pre-planned times such as work time, sleep time, and meal time.

[0540] A "daily schedule" refers to a specific daily plan optimized to achieve a user's goals, including the start and end times of each task.

[0541] "Notification" refers to a means of informing the user of important information, such as by using an alarm sound or a screen display.

[0542] A "task" refers to a specific activity or work that a user performs within a daily schedule, such as jogging or studying.

[0543] "Real time" refers to processing that responds to the current progress of the process, for example, regenerating a schedule immediately.

[0544] "Emotions" refers to the user's psychological state, including mental states such as stress and motivation.

[0545] "Means for recognizing emotions" refers to devices or software that collect emotional data from users' facial expressions, tone of voice, etc.

[0546] "Means for adjusting the schedule" refers to a function that modifies or optimizes an already generated daily schedule based on recognized emotion data.

[0547] A "long-term schedule" refers to a plan spanning several weeks to several months to achieve a user's goals, which is optimized by repeating short-term schedules.

[0548] This invention is a system that optimizes daily time management and provides a feasible schedule to help users achieve their set goals. This system incorporates an emotion engine that recognizes the user's emotions and reflects them in schedule and task adjustments.

[0549] Setting goals and getting existing schedules

[0550] The user launches the application and sets a goal, such as "lose 5 kg in one month." After that, the user inputs their existing daily schedule, including work hours, sleep times, and meal times, into the app.

[0551] Schedule data transmission and analysis

[0552] Once all the data is entered, the device sends this information to a server, which then generates an optimal daily schedule based on the user's goals and existing schedule. For example, the device might create a daily schedule that includes 30 minutes of jogging every morning and 30 minutes of strength training in the evening.

[0553] Schedule notifications and alarm settings

[0554] The server sends the generated schedule to the terminal, which then notifies the user. For example, the following schedule is displayed:

[0555] 6:00 AM - Jogging (30 minutes)

[0556] 6:30 AM - Breakfast

[0557] 7:00 AM - Get ready for work

[0558] 8:00 AM - Commute

[0559] 9:00 AM - Start work

[0560] 12:00 PM - Lunch Break (Light Exercise)

[0561] 1:00 PM - Back to work

[0562] 6:00 PM - Finish work

[0563] 7:00 PM - Dinner

[0564] 8:00 PM - Strength Training (30 minutes)

[0565] 9:00 PM - Relaxation Time

[0566] 10:00 PM - Sleep

[0567] Additionally, the device will set an alarm at the start time of each task, for example, a "Start jogging" alarm at 6:00 AM.

[0568] Checking task progress and readjusting tasks

[0569] At the end of each task, the device sends the user a confirmation notification that the task has been completed. For example, at 6:30 AM, a confirmation message is displayed asking, "Have you finished jogging?" The user responds in the app whether or not the task has been completed. If the user replies, "I haven't completed the task," the device sends that information to the server. The server regenerates the schedule in real time based on this information and shifts the time of the next task.

[0570] Use of emotion engine

[0571] This system incorporates an emotion engine that recognizes the user's emotions. The device collects emotional data from the user's facial expressions, tone of voice, etc. and sends it to the server. The server uses this emotional data to adjust the schedule and change task priorities. For example, if the user is feeling stressed, the system will adjust the schedule by increasing time for relaxation and postponing difficult tasks.

[0572] Long-term schedule optimization

[0573] The server collects and analyzes the user's task execution data and emotional data. This identifies progress and problems. The server further optimizes the schedule for the following week and beyond. For example, if jogging is not performed as scheduled, the server may shorten the jogging time and suggest a different exercise. The server also takes into account the user's emotional state when adjusting the schedule.

[0574] Hardware and Software Details

[0575] Hardware: Smartphone, camera and microphone for emotion recognition

[0576] Software: Frontend (React Native), Backend Server (Django)

[0577] On the server side, processing of emotional data and task execution data, real-time schedule regeneration, and long-term data analysis are performed.

[0578] On the device side, it is responsible for providing the user interface, collecting emotional data, and setting and displaying notifications and alarms.

[0579] Examples of concrete examples and prompts

[0580] Specific examples

[0581] Goal: "Learn everyday English conversation skills in one month"

[0582] Emotional data: The user felt stressed in the afternoon, so the adjustment was made to increase relaxation time.

[0583] Example execution flow:

[0584] Users set goals and input their existing schedules.

[0585] The server generates a schedule and notifies the terminal.

[0586] The emotion engine recognizes the user's stress and sends the data to the server.

[0587] The server adds relaxation time and regenerates the schedule.

[0588] The device notifies the user of the adjusted schedule.

[0589] Prompt Sentence Examples

[0590] text

[0591] Set a goal.

[0592] For example, one specific goal is to "master everyday conversation level English in one month."

[0593] Please tell us what tasks are required to achieve your goal, including the approximate time required.

[0594] According to the present invention, the user's daily schedule is optimized according to their emotional state, so that they can effectively achieve their goals.

[0595] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0596] Step 1:

[0597] The user launches the application and sets a goal. In this step, the user enters a specific goal, such as "lose 5 kg in one month."

[0598] Input: User's goal

[0599] Output: Set goal

[0600] What happens: The user enters their goal through the user interface and the app receives that information.

[0601] Step 2:

[0602] The user inputs their existing schedule (work hours, sleep times, meal times, etc.) into the application, which uses this information to plan for achieving their goals.

[0603] Input: User's existing schedule

[0604] Output: Input schedule data

[0605] What it does: The user enters a schedule through the user interface, and the app saves that information.

[0606] Step 3:

[0607] The terminal transmits the set goal and existing schedule data to the server.

[0608] Input: Set goals and existing schedule data

[0609] Output: Data sent to the server

[0610] Specific operation: The device sends data to the server via the network.

[0611] Step 4:

[0612] The server then generates an optimal daily schedule based on the data received, which includes activities such as jogging and strength training.

[0613] Input: User goals and existing schedule data

[0614] Output: Optimized daily schedule

[0615] Specific operation: The algorithm runs on the server and calculates the optimal schedule.

[0616] Step 5:

[0617] The server transmits the generated schedule to the terminal, and the terminal notifies the user.

[0618] Input: Server-generated schedule

[0619] Output: Schedule notified to user

[0620] Specific operation: The server sends schedule data to the device, and the device displays a notification.

[0621] Step 6:

[0622] The device sets an alarm at the start time of each task and notifies the user.

[0623] Input: Generated schedule

[0624] Output: Alarm notified to user

[0625] What happens: Your device sets an alarm and displays a notification or plays an alarm sound at the specified time.

[0626] Step 7:

[0627] At the end of each task, the device sends a task completion confirmation to the user.

[0628] Input: Task end time

[0629] Output: Task completion confirmation notification

[0630] Specific behavior: The device will sound an alarm at the task completion time and display a confirmation notification.

[0631] Step 8:

[0632] The user inputs a response indicating that the task is complete. If the task is not complete, the terminal sends that information to the server.

[0633] Input: Task completion response

[0634] Output: Completion information sent to the server

[0635] Specific operation: The user enters a confirmation response, and the device sends the information to the server.

[0636] Step 9:

[0637] The server regenerates the schedule in real time based on the user's task completion information and sends it to the terminal.

[0638] Input: Incomplete task information

[0639] Output: Regenerated schedule

[0640] Specific operation: The server recalculates, generates a new schedule, and sends it to the terminal.

[0641] Step 10:

[0642] The terminal notifies the user of the regenerated schedule.

[0643] Input: Server-generated schedule

[0644] Output: Regeneration schedule notified to the user

[0645] Specific behavior: The device receives the new schedule and notifies it.

[0646] Step 11:

[0647] The device collects the user's emotional data and sends it to the server. The emotional data includes facial expression analysis and tone of voice analysis.

[0648] Input: User emotion data

[0649] Output: Emotion data sent to the server

[0650] Specific operation: The device uses the camera and microphone to collect emotion data and transmits it to the server.

[0651] Step 12:

[0652] The server adjusts the schedule based on the emotion data and generates a new schedule.

[0653] Input: Emotion data

[0654] Output: Adjusted schedule

[0655] Specific operation: The server analyzes the emotion data and adjusts the schedule based on the results.

[0656] Step 13:

[0657] To optimize long-term schedules, the server collects and analyzes users' task execution data and emotional data.

[0658] Input: User task execution data and emotion data

[0659] Output: Optimized schedule

[0660] How it works: The server accumulates data and uses algorithms to optimize the long-term schedule.

[0661] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0662] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0663] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0664] [Second embodiment]

[0665] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0666] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0667] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0668] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0669] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0670] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0671] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0672] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0673] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0674] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0675] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0676] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0677] The present invention is a system that optimizes daily time management and provides a feasible schedule for users to achieve their major goals. This system performs the following specific program processing.

[0678] Setting goals and getting existing schedules

[0679] The user launches the app and sets a goal, such as "lose 5 kg in one month." The user then inputs their existing daily schedule, including work hours, sleep times, and meal times, into the app.

[0680] Schedule data transmission and analysis

[0681] Once all the data is entered, the device sends this information to a server, which then generates an optimal daily schedule based on the user's goals and existing schedule. For example, the server might generate a schedule that includes 30 minutes of jogging every morning and 30 minutes of strength training every evening.

[0682] Schedule notifications and alarm settings

[0683] The server sends the generated schedule to the terminal, which then notifies the user. For example, the following schedule is displayed:

[0684] 6:00 AM - Jogging (30 minutes)

[0685] 6:30 AM - Breakfast

[0686] 7:00 AM - Get ready for work

[0687] 8:00 AM - Commute

[0688] 9:00 AM - Start work

[0689] 12:00 PM - Lunch Break (Light Exercise)

[0690] 1:00 PM - Back to work

[0691] 6:00 PM - Finish work

[0692] 7:00 PM - Dinner

[0693] 8:00 PM - Strength Training (30 minutes)

[0694] 9:00 PM - Relaxation Time

[0695] 10:00 PM - Sleep

[0696] Additionally, the device will set an alarm at the start time of each task, for example, a "Start jogging" alarm at 6:00 AM.

[0697] Checking task progress

[0698] At the end of each task, the device sends a task completion confirmation to the user. For example, at 6:30 AM, a confirmation message is displayed asking, "Did you finish jogging?" The user can then respond in the app whether or not the task is complete.

[0699] Rescheduling

[0700] If the user answers "I haven't completed the task," the device sends that information to the server, which then regenerates the schedule in real time based on this information and adjusts the time of the next task, for example, by moving the jogging time to 7:00 AM.

[0701] Long-term schedule optimization

[0702] The server collects and analyzes the user's task execution data, identifying progress and problems. The system further optimizes the schedule for the following week and beyond. For example, if the user is not continuing their jogging routine, the system will make adjustments such as shortening the jogging time and suggesting a different exercise.

[0703] Specific examples

[0704] Let's take the example of a user's goal of "learning English conversation at a daily conversation level in one month." The server generates the following schedule:

[0705] 6:00 AM - English Conversation Listening (30 minutes)

[0706] 6:30 AM - Breakfast

[0707] 7:00 AM - Get ready for work

[0708] 8:00 AM - Commute

[0709] 9:00 AM - Start work

[0710] 12:00 PM - Lunch Break (English Conversation Practice)

[0711] 1:00 PM - Back to work

[0712] 6:00 PM - Finish work

[0713] 7:00 PM - Dinner

[0714] 8:00 PM - English Speaking Practice (30 minutes)

[0715] 9:00 PM - Relaxation Time

[0716] 10:00 PM - Sleep

[0717] This schedule is sent to the device, and an alarm is set at the start time of each task. For example, an alarm for the start of English conversation listening will sound at 6:00 AM.

[0718] If the user has not completed the task, the server regenerates the schedule and sends it to the device again, notifying it of the adjusted schedule, for example, by moving the listening time to 7:00 AM.

[0719] This system allows users to strictly manage their daily schedules and ensure that they continue to make efforts toward achieving their goals.

[0720] The processing flow will be explained below.

[0721] Step 1:

[0722] The user starts the app and goes to the "Goal Setting" screen. For example, they enter a specific goal, such as "lose 5 kg in one month."

[0723] Step 2:

[0724] On the "Enter Existing Schedule" screen, users enter their current lifestyle and daily activity schedule, including work start and end times, meal times, and sleep times.

[0725] Step 3:

[0726] The terminal transmits the data of the goal and the existing schedule to the server.

[0727] Step 4:

[0728] The server analyzes the received data and generates an optimal schedule for achieving the goal, for example, a daily schedule including 30 minutes of jogging every morning and 30 minutes of strength training in the evening.

[0729] Step 5:

[0730] The server transmits the generated schedule to the terminal.

[0731] Step 6:

[0732] The terminal notifies the user of the generated schedule. For example, the following schedule is displayed:

[0733] 6:00 AM - Jogging (30 minutes)

[0734] 6:30 AM - Breakfast

[0735] 7:00 AM - Get ready for work

[0736] 8:00 AM - Commute

[0737] 9:00 AM - Start work

[0738] 12:00 PM - Lunch Break (Light Exercise)

[0739] 1:00 PM - Back to work

[0740] 6:00 PM - Finish work

[0741] 7:00 PM - Dinner

[0742] 8:00 PM - Strength Training (30 minutes)

[0743] 9:00 PM - Relaxation Time

[0744] 10:00 PM - Sleep

[0745] Step 7:

[0746] Your device will set an alarm for the start time of each task, for example, a "Start jogging" alarm at 6:00 AM.

[0747] Step 8:

[0748] The device will send a task completion confirmation at the end of each task, for example, at 6:30 AM it will display the message "Did you finish jogging?"

[0749] Step 9:

[0750] The user responds to the app by completing a task, for example, by saying "I completed my jog."

[0751] Step 10:

[0752] If the user answers "I have not completed my jog," the device sends that information to the server.

[0753] Step 11:

[0754] The server regenerates the schedule in real time based on the information received. For example, it adjusts the schedule as follows:

[0755] 6:30 AM - Jogging (30 minutes)

[0756] 7:00 AM - Breakfast

[0757] 7:30 AM - Get ready for work

[0758] 8:00 AM - Commute

[0759] 9:00 AM - Start work

[0760] 12:00 PM - Lunch Break (Light Exercise)

[0761] 1:00 PM - Back to work

[0762] 6:00 PM - Finish work

[0763] 7:00 PM - Dinner

[0764] 8:00 PM - Strength Training (30 minutes)

[0765] 9:00 PM - Relaxation Time

[0766] 10:00 PM - Sleep

[0767] Step 12:

[0768] The server transmits the regenerated schedule to the terminal.

[0769] Step 13:

[0770] The terminal notifies the user of the regenerated schedule.

[0771] Step 14:

[0772] The server collects and analyzes the user's task execution data, thereby identifying the progress and problems.

[0773] Step 15:

[0774] The server optimizes the schedule for the next week, and if jogging is not performed as scheduled, for example, adjustments are made such as shortening the jogging time and suggesting a different exercise.

[0775] Step 16:

[0776] The server transmits the optimized long-term schedule to the terminal, and the terminal notifies the user of it.

[0777] Example 1

[0778] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0779] Conventional time management systems require users to create their own schedules, which does not necessarily allow for appropriate planning for achieving goals. Furthermore, if a user is unable to complete a task, subsequent schedule adjustments must be made manually, making efficient time management difficult. Furthermore, they lack a mechanism for optimizing schedules to achieve long-term goals. There is a need for a system that can solve these problems and provide effective and flexible time management to help users achieve their goals.

[0780] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0781] In this invention, the server includes a means for setting a user's goals, a means for inputting the user's existing schedule, and a cloud server and a means for using a generative AI model to generate an optimal daily schedule based on the goals and the existing schedule. This makes it possible to automatically generate an efficient and feasible schedule based on the goals set by the user, adjust the schedule in real time according to the daily progress, and support the achievement of long-term goals.

[0782] "User" means an individual or organization that uses the system to set goals and manage schedules.

[0783] "Means for setting goals" refers to a function or interface that allows users to input the goals they wish to achieve into the system.

[0784] "Means for inputting existing schedules" refers to a function or interface that allows users to input their daily plans and activity times into the system.

[0785] A "cloud server" is a server that stores and processes data via the Internet and is responsible for the system's main calculations and data processing.

[0786] A "generative AI model" is an algorithm or program that uses artificial intelligence technology to generate an optimal schedule based on a user's goals and existing schedule.

[0787] "Notification means" refers to a function or device that notifies users of schedules and alarms generated by the system.

[0788] "Means for notifying the start time of a task" refers to a function or device for notifying the user of the time when each task should start.

[0789] The "means for sending a confirmation notification of task completion" is a function or interface for confirming with the user whether or not the task has been completed at the end time of each task.

[0790] "Means for regenerating schedules in real time" refers to a function or system that instantly generates a new schedule based on information when a user does not complete a task.

[0791] "Means for analyzing task execution data and optimizing long-term schedules" refers to a function or program that analyzes users' daily task execution data and continuously adjusts and optimizes schedules.

[0792] The present invention is a system for managing daily tasks by providing an optimal schedule for a user to achieve their goals. Specific examples are shown below.

[0793] Setting goals and getting existing schedules

[0794] The app provides a means for users to launch the app and input the goal they want to achieve. For example, they can set a goal of "lose 5 kg in one month." Next, the app provides a means for users to input their existing schedule (e.g., work hours, sleep hours, meal times). This can be done using a device such as a smartphone or PC.

[0795] Data transmission and analysis

[0796] The device sends the user's input goals and existing schedule to the cloud server. The server then analyzes the input data using a generative AI model to generate an optimal daily schedule. At this time, the following prompt is input to the generative AI model:

[0797] "Please suggest an optimal daily schedule for losing 5 kg in one month."

[0798] Schedule notifications and alarm settings

[0799] The server sends the generated optimal schedule to the device, which then notifies the user. When the user receives the notification, the device sets an alarm at the start time of each task. For example, a notification to start jogging at 6:00 AM is displayed and an alarm sounds.

[0800] Check task progress and adjust in real time

[0801] At the end of each task, the device sends the user a task completion confirmation notification. For example, at 6:30 AM, when the jogging ends, a confirmation notification is displayed asking, "Have you finished jogging?" If the user replies that they have not completed the task, the device sends that information to the server. The server immediately recalculates the schedule, adjusts the time of the next task, and sends it again to the device. This results in an adjustment, such as changing the jogging time to 7:00 AM.

[0802] Long-term schedule optimization

[0803] The server continuously collects and analyzes the user's task execution data, identifying progress and problems and optimizing the schedule for the following week. For example, if the jogging time is too long, the server will suggest shortening the time and suggesting a different exercise.

[0804] Hardware and software examples

[0805] Hardware: smartphones, PCs, cloud servers

[0806] Software: Dedicated app, cloud-based data analysis tools, notification and alarm management system

[0807] Specific examples

[0808] If a user sets a goal of "mastering everyday conversation level English in one month," the server will generate the following schedule:

[0809] 6:00 AM - English Conversation Listening (30 minutes)

[0810] 6:30 AM - Breakfast

[0811] 7:00 AM - Get ready for work

[0812] 8:00 AM - Commute

[0813] 9:00 AM - Start work

[0814] 12:00 PM - Lunch Break (English Conversation Practice)

[0815] 1:00 PM - Back to work

[0816] 6:00 PM - Finish work

[0817] 7:00 PM - Dinner

[0818] 8:00 PM - English Speaking Practice (30 minutes)

[0819] 9:00 PM - Relaxation Time

[0820] 10:00 PM - Sleep

[0821] This schedule is sent to the device, and an alarm is set at the start time of each task. For example, an alarm for the start of English conversation listening will sound at 6:00 AM.

[0822] If the user has not completed the task, the server regenerates the schedule and sends it back to the device, notifying the user of the adjusted schedule. For example, the listening time can be moved to 7:00 AM. This ensures that the user maintains strict control over their daily schedule and continues to work toward achieving their goals.

[0823] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0824] Step 1:

[0825] The user launches the app and sets a goal. As input, the app inputs the goal they want to achieve (e.g., "lose 5 kg in one month"). As output, the app generates the user's goal data, which is used in subsequent processing steps.

[0826] Step 2:

[0827] The user inputs their existing schedule into the app. As input, they input their daily schedule (work time, sleep time, meal time, etc.). As output, the user's existing schedule data is generated. This schedule data is sent to the server along with the goal data.

[0828] Step 3:

[0829] The terminal transmits the input goal data and existing schedule data to the cloud server. As input, the terminal receives the user's goal data and existing schedule data. As output, the terminal generates a transmission request to the cloud server.

[0830] Step 4:

[0831] Based on the goal data and existing schedule data received by the server, an optimal schedule is generated using a generative AI model. The goal data and existing schedule data are received as input. A prompt statement (e.g., "Please suggest an optimal daily schedule for losing 5 kg in one month") is input to the generative AI model, and optimal schedule data is generated as output.

[0832] Step 5:

[0833] The server sends the generated schedule data to the terminal. As input, it receives the generated schedule data. As output, it generates the schedule data as a transmission request to the terminal.

[0834] Step 6:

[0835] The terminal notifies the user of the received schedule data. As input, the received schedule data is processed for display. As output, the schedule is displayed to the user and sent as a notification.

[0836] Step 7:

[0837] The terminal sets an alarm at the start time of each task. As input, it obtains the start time of each task in the schedule data. As output, an alarm is set and a notification is sent to the user at the specified time.

[0838] Step 8:

[0839] At the end time of each task, the terminal sends a confirmation notification of task completion to the user. As input, the end time of each task in the schedule data is obtained. As output, a confirmation notification of task completion is sent to the user.

[0840] Step 9:

[0841] The user responds to the task completion notification. As input, the user enters whether or not the task is completed into the app. As output, task completion data is generated.

[0842] Step 10:

[0843] If the task is not completed, the terminal sends the information to the server. As input, it receives the data of the task not completed. As output, it generates the information of the task not completed as a transmission request to the server.

[0844] Step 11:

[0845] The server regenerates the schedule in real time based on the data of incomplete tasks. As input, it receives the incomplete task data and inputs a prompt sentence again based on the generative AI model (e.g., "Please adjust your schedule, such as moving your jogging time to 7:00 AM."). As output, new schedule data is generated.

[0846] Step 12:

[0847] The server transmits the regenerated schedule data to the terminal. As input, the server receives the regenerated schedule data. As output, the server generates the schedule data as a transmission request to the terminal.

[0848] Step 13:

[0849] The terminal notifies the user of the regenerated schedule data. As input, the terminal processes the regenerated schedule data for display. As output, the schedule is notified to the user again.

[0850] Step 14:

[0851] The server continuously collects and analyzes user task execution data. The collected data is used as input, and the analysis results are generated as output.

[0852] Step 15:

[0853] The server optimizes the schedule for the following week based on the analysis results. The analysis results are received as input. The optimized schedule data for the following week is generated as output.

[0854] Step 16:

[0855] The server transmits the optimized schedule data for the next week and beyond to the terminal. As input, it receives the optimized schedule data. As output, it generates the schedule data as a transmission request to the terminal.

[0856] Step 17:

[0857] The terminal notifies the user of the optimized schedule data for the next week and beyond. As input, the optimized schedule data is processed for display. As output, the schedule is notified to the user.

[0858] (Application example 1)

[0859] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0860] Current factory production management systems do not efficiently manage operation plans for work equipment and machines, resulting in reduced production efficiency and difficulty in achieving production targets. Furthermore, the operating status of production equipment and maintenance plans are not adequately considered, making unplanned shutdowns and delays more likely to occur. Furthermore, work progress is not checked in real time, often resulting in delays in readjusting the production schedule. For these reasons, there was a need for effective production schedule generation and management to improve the efficiency of the entire factory.

[0861] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0862] In this invention, the server includes means for setting production targets to be achieved by factory work equipment and machines, means for inputting operation plans and maintenance plans for production equipment, means for generating an optimal daily schedule based on the targets and existing operation plans, means for notifying the relevant production equipment of work instructions based on the generated schedule, means for sending progress confirmation notifications at the end time of each production task, and means for regenerating the production schedule in real time if a production task is not completed. This makes it possible to maximize production efficiency and ensure the achievement of production targets.

[0863] A "means for setting user goals" is a system or device that allows a factory operator or manager to input production goals to be achieved for the factory's work equipment and machines.

[0864] The "means for inputting the user's existing schedule" refers to an interface or device for inputting the current operation plan and maintenance plan for the factory's work equipment and machines.

[0865] The "means for generating an optimal daily schedule based on the target and existing schedule" refers to an algorithm or software that calculates and generates an optimal daily schedule for the factory's work equipment and machines based on the set target and existing operation plan.

[0866] The "means for notifying the user of the generated schedule" refers to a system or device for notifying a factory operator or manager of the generated schedule.

[0867] The "means for notifying the start time of a task based on the schedule" refers to a system or device for notifying the work equipment or machines in a factory of the start time of each work task based on the schedule.

[0868] The "means for sending a confirmation notification of task completion at the end time of each task" is a system or device that sends a notification at the end time of each work task to confirm whether the task has been completed.

[0869] "Means for regenerating a schedule in real time if a task is not completed" refers to an algorithm or software that recalculates and regenerates the currently set schedule in real time based on information about incomplete tasks.

[0870] The "means for notifying users of the regenerated schedule" refers to a system or device for notifying factory operators or managers of the new regenerated schedule.

[0871] The "means for analyzing user task execution data and optimizing long-term schedules" refers to an analytical algorithm or software for optimizing factory work schedules over the long term based on collected task execution data.

[0872] The "means for setting production targets to be achieved by work equipment and machines in a factory" refers to a system or device for inputting and setting production targets set for work equipment and machines in a factory.

[0873] The "means for inputting the operation plan and maintenance plan of the production equipment" refers to an interface or device for inputting the operation schedule and maintenance schedule of the production equipment.

[0874] The "means for generating an optimal daily schedule based on the above-mentioned targets and existing operation plans" refers to an algorithm or software that calculates and generates an optimal daily schedule for the factory's work equipment and machines based on the set production targets and existing operation plans.

[0875] The "means for notifying the relevant production equipment of work instructions based on the generated schedule" refers to a system or device for notifying the relevant production equipment or machine of each work instruction based on the generated schedule.

[0876] The "means for sending a progress confirmation notification at the end time of each production task" refers to a system or device that sends a notification to confirm the progress of each production task at the end time of that task.

[0877] The "means for regenerating a production schedule in real time when a production task is not completed" refers to an algorithm or software that, when a production task is not completed, recalculates and regenerates the currently set production schedule in real time based on that information.

[0878] This invention is a system that optimizes the operation schedules of factory work equipment and machines and supports the achievement of production targets. Specifically, this describes a system in which factory operators input targets and existing operation plans, a server generates an optimal schedule based on that data, and monitors and adjusts the progress of each task in real time.

[0879] First, a factory operator accesses the system using a control terminal (e.g., a PC or tablet) and sets a production target. This target is specifically defined, for example, to assemble 1,000 products in one day. Next, the current operation plan and maintenance plan are entered into the system. This operation plan includes work time slots and existing maintenance times.

[0880] The server generates an optimal daily schedule based on the input goals and existing schedules. It is desirable to use AI models or machine learning algorithms for this calculation and generation. The generated schedule is notified to the work equipment via the control terminal. Using available cloud database services (e.g., AWS RDS) allows for efficient data management and storage.

[0881] When the start time for each work task arrives, the server notifies the relevant work equipment of the work instructions via the control terminal. The control terminal displays an alarm, such as "Assembly begins at 9:00." The work equipment executes the task, and when it is time to finish, the server checks the progress. This progress check is performed by the control terminal displaying a confirmation message to the operator. For example, a notification may be displayed asking, "Is the 9:00 assembly completed?"

[0882] If a work task is not completed, the operator enters that information into the system. The server regenerates the schedule in real time based on this information and notifies the work equipment of the re-adjusted schedule. Tasks are then rearranged according to this re-generated schedule, optimizing the work plan for the next day.

[0883] In the long term, the server will periodically analyze the task execution data collected and further optimize the schedule for the following week, enabling adjustments to be made to improve the factory's overall production efficiency.

[0884] For example, if a factory's daily production target is 1,000 products, a schedule will be provided that allows the robots to efficiently carry out the work within the specified working hours. This schedule will be strictly managed, and production progress will be checked on an ongoing basis, ensuring that efforts to achieve the target are continued.

[0885] An example of a prompt sentence might be:

[0886] "Generate an optimal task list and schedule for the factory robots between 9:00-12:00 and 13:00-18:00 so that they can efficiently assemble the daily target of 1,000 products."

[0887] In this way, it is a feature of the present invention that the factory's production efficiency is maximized and targets are achieved.

[0888] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0889] Step 1:

[0890] The user sets production targets for the factory's work equipment and machines using a control terminal. At this time, the user inputs the target value (e.g., assemble 1,000 products in one day). Data based on this is sent to the server.

[0891] Step 2:

[0892] Users use a control terminal to input existing operation and maintenance plans into the system. This data is also sent to the server. The input data includes work time slots and maintenance times.

[0893] Step 3:

[0894] The server generates an optimal daily schedule based on the received production targets, operation plans, and maintenance plans. It uses generative AI models and machine learning algorithms to calculate the optimal start and end times for each work task. This generated schedule is then sent from the server to the device.

[0895] Step 4:

[0896] The terminal notifies each piece of work equipment in the factory of the schedule it receives from the server. This notification includes the start and end times of each work task. Each piece of equipment begins operating according to the notified schedule.

[0897] Step 5:

[0898] When the start time for each work task arrives, the terminal sends a start command to the corresponding work equipment. For example, a notification such as "Assembly begins at 9:00" is displayed, and the equipment begins operation.

[0899] Step 6:

[0900] When the end time of each work task arrives, the terminal sends a task completion confirmation to the user. The user checks whether the task is completed and reports the result on the terminal.

[0901] Step 7:

[0902] If a task is not completed, the device sends the information to the server, which regenerates the schedule in real time based on the incomplete information, and the new schedule is sent to the device again.

[0903] Step 8:

[0904] The terminal receives the regenerated schedule and notifies each piece of work equipment of the new instructions, including the adjusted start and end times of each work task.

[0905] Step 9:

[0906] The server collects all task execution data and analyzes it for long-term schedule optimization. It uses machine learning algorithms to further optimize the schedule for the following week and beyond, and sends the results to the device.

[0907] This maximizes factory production efficiency and ensures production targets are met.

[0908] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0909] This invention is a system that optimizes daily time management and provides a feasible schedule for users to achieve their big goals. This system incorporates an emotion engine that recognizes the user's emotions and reflects them in the adjustment of schedules and tasks.

[0910] Setting goals and getting existing schedules

[0911] The user launches the app and sets a goal, such as "lose 5 kg in one month." The user then inputs their existing daily schedule, including work hours, sleep times, and meal times, into the app.

[0912] Schedule data transmission and analysis

[0913] Once all the data is entered, the device sends this information to a server, which then generates an optimal daily schedule based on the user's goals and existing schedule. For example, the device might create a daily schedule that includes 30 minutes of jogging every morning and 30 minutes of strength training in the evening.

[0914] Schedule notifications and alarm settings

[0915] The server sends the generated schedule to the terminal, which then notifies the user. For example, the following schedule is displayed:

[0916] 6:00 AM - Jogging (30 minutes)

[0917] 6:30 AM - Breakfast

[0918] 7:00 AM - Get ready for work

[0919] 8:00 AM - Commute

[0920] 9:00 AM - Start work

[0921] 12:00 PM - Lunch Break (Light Exercise)

[0922] 1:00 PM - Back to work

[0923] 6:00 PM - Finish work

[0924] 7:00 PM - Dinner

[0925] 8:00 PM - Strength Training (30 minutes)

[0926] 9:00 PM - Relaxation Time

[0927] 10:00 PM - Sleep

[0928] Additionally, the device will set an alarm at the start time of each task, for example, a "Start jogging" alarm at 6:00 AM.

[0929] Checking task progress

[0930] At the end of each task, the device sends a task completion confirmation to the user. For example, at 6:30 AM, a confirmation message is displayed asking, "Did you finish jogging?" The user can then respond in the app whether or not the task is complete.

[0931] Rescheduling

[0932] If the user answers "I haven't completed the task," the device sends that information to the server, which then regenerates the schedule in real time based on this information and adjusts the schedule accordingly, for example, by moving the jogging time to 7:00 AM.

[0933] Use of emotion engine

[0934] This system incorporates an emotion engine that recognizes the user's emotions. The device collects emotional data from the user's facial expressions, tone of voice, etc. and sends it to the server. The server uses this emotional data to adjust the schedule and change task priorities. For example, if the user is feeling stressed, the system will adjust the schedule by increasing time for relaxation and postponing hard tasks.

[0935] Long-term schedule optimization

[0936] The server collects and analyzes the user's task execution data and emotional data. This identifies progress and problems. The system further optimizes the schedule for the following week and beyond. For example, if jogging is not performed as planned, the system will shorten the jogging time and suggest a different exercise. The system also takes into account the user's emotional state when adjusting the schedule.

[0937] Specific examples

[0938] Let's take the example of a user's goal of "learning English conversation at a daily conversation level in one month." The server generates the following schedule:

[0939] 6:00 AM - English Conversation Listening (30 minutes)

[0940] 6:30 AM - Breakfast

[0941] 7:00 AM - Get ready for work

[0942] 8:00 AM - Commute

[0943] 9:00 AM - Start work

[0944] 12:00 PM - Lunch Break (English Conversation Practice)

[0945] 1:00 PM - Back to work

[0946] 6:00 PM - Finish work

[0947] 7:00 PM - Dinner

[0948] 8:00 PM - English Speaking Practice (30 minutes)

[0949] 9:00 PM - Relaxation Time

[0950] 10:00 PM - Sleep

[0951] This schedule is sent to the device, and an alarm is set at the start time of each task. For example, an alarm for the start of English conversation listening will sound at 6:00 AM.

[0952] If the user has not completed the task, the server regenerates the schedule and sends it to the device again, notifying it of the adjusted schedule, for example, by moving the listening time to 7:00 AM.

[0953] The emotion engine also recognizes the user's emotions, and if the user is feeling stressed, for example, it will adjust the system to increase relaxation time and postpone burdensome tasks.

[0954] This system allows users to strictly manage their daily schedules and ensure that they continue to make efforts toward achieving their goals.

[0955] The processing flow will be explained below.

[0956] Step 1:

[0957] The user starts the app and goes to the "Goal Setting" screen. For example, they enter a specific goal, such as "lose 5 kg in one month."

[0958] Step 2:

[0959] On the "Enter Existing Schedule" screen, users enter their current lifestyle and daily activity schedule, including work start and end times, meal times, and sleep times.

[0960] Step 3:

[0961] The terminal transmits the data of the goal and the existing schedule to the server.

[0962] Step 4:

[0963] The server analyzes the received data and generates an optimal schedule for achieving the goal, for example, a daily schedule including 30 minutes of jogging every morning and 30 minutes of strength training in the evening.

[0964] Step 5:

[0965] The server transmits the generated schedule to the terminal.

[0966] Step 6:

[0967] The terminal notifies the user of the generated schedule. For example, the following schedule is displayed:

[0968] 6:00 AM - Jogging (30 minutes)

[0969] 6:30 AM - Breakfast

[0970] 7:00 AM - Get ready for work

[0971] 8:00 AM - Commute

[0972] 9:00 AM - Start work

[0973] 12:00 PM - Lunch Break (Light Exercise)

[0974] 1:00 PM - Back to work

[0975] 6:00 PM - Finish work

[0976] 7:00 PM - Dinner

[0977] 8:00 PM - Strength Training (30 minutes)

[0978] 9:00 PM - Relaxation Time

[0979] 10:00 PM - Sleep

[0980] Step 7:

[0981] Your device will set an alarm for the start time of each task, for example, a "Start jogging" alarm at 6:00 AM.

[0982] Step 8:

[0983] The device will send a task completion confirmation at the end of each task, for example, at 6:30 AM it will display the message "Did you finish jogging?"

[0984] Step 9:

[0985] The user responds to the app by completing a task, for example, by saying "I completed my jog."

[0986] Step 10:

[0987] If the user answers "I have not completed my jog," the device sends that information to the server.

[0988] Step 11:

[0989] The server regenerates the schedule in real time based on the information received. For example, it adjusts the schedule as follows:

[0990] 6:30 AM - Jogging (30 minutes)

[0991] 7:00 AM - Breakfast

[0992] 7:30 AM - Get ready for work

[0993] 8:00 AM - Commute

[0994] 9:00 AM - Start work

[0995] 12:00 PM - Lunch Break (Light Exercise)

[0996] 1:00 PM - Back to work

[0997] 6:00 PM - Finish work

[0998] 7:00 PM - Dinner

[0999] 8:00 PM - Strength Training (30 minutes)

[1000] 9:00 PM - Relaxation Time

[1001] 10:00 PM - Sleep

[1002] Step 12:

[1003] The server transmits the regenerated schedule to the terminal.

[1004] Step 13:

[1005] The terminal notifies the user of the regenerated schedule.

[1006] Step 14:

[1007] Furthermore, the device is equipped with an emotion engine that collects emotional data from the user's facial expressions and tone of voice, and periodically transmits this data to a server.

[1008] Step 15:

[1009] The server analyzes the emotional data to understand the user's stress level and motivation. For example, if the user feels tired, it will suggest taking more rest time.

[1010] Step 16:

[1011] The server adjusts the schedule based on the emotional data. For example, if the user is feeling stressed, the server will increase the amount of time for relaxation and postpone hard tasks.

[1012] Step 17:

[1013] The server transmits the schedule adjusted by the emotion engine to the terminal.

[1014] Step 18:

[1015] The terminal notifies the user of the adjusted schedule.

[1016] Step 19:

[1017] The server collects and analyzes the user's task execution data and emotional data, thereby identifying achievement status and problems.

[1018] Step 20:

[1019] The server optimizes the schedule for the next week, and if jogging is not performed as planned, for example, it will shorten the jogging time and suggest a different exercise. It also takes into account schedule adjustments based on the user's emotions.

[1020] Step 21:

[1021] The server transmits the optimized long-term schedule to the terminal, and the terminal notifies the user of it.

[1022] Specific examples

[1023] Let's take the example of a user's goal of "learning English conversation at a daily conversation level in one month." The server generates the following schedule:

[1024] 6:00 AM - English Conversation Listening (30 minutes)

[1025] 6:30 AM - Breakfast

[1026] 7:00 AM - Get ready for work

[1027] 8:00 AM - Commute

[1028] 9:00 AM - Start work

[1029] 12:00 PM - Lunch Break (English Conversation Practice)

[1030] 1:00 PM - Back to work

[1031] 6:00 PM - Finish work

[1032] 7:00 PM - Dinner

[1033] 8:00 PM - English Speaking Practice (30 minutes)

[1034] 9:00 PM - Relaxation Time

[1035] 10:00 PM - Sleep

[1036] This schedule is sent to the device, and an alarm is set at the start time of each task. For example, an alarm for the start of English conversation listening will sound at 6:00 AM.

[1037] If the user has not completed the task, the server regenerates the schedule and sends it to the device again, notifying it of the adjusted schedule, for example, by moving the listening time to 7:00 AM.

[1038] The emotion engine also recognizes the user's emotions, and if the user is feeling stressed, for example, it will adjust the system to increase relaxation time and postpone burdensome tasks.

[1039] This system allows users to strictly manage their daily schedules and ensure that they continue to make efforts toward achieving their goals.

[1040] Example 2

[1041] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1042] In modern society, time management is essential for achieving individual goals, but maintaining an optimal schedule in a busy daily life is difficult. Furthermore, few existing systems adjust schedules taking into account the user's emotional state, which can increase the user's mental burden. This can lead to a decrease in motivation to achieve goals and make it difficult to achieve results.

[1043] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for setting a user's goal, means for inputting the user's existing schedule, means for generating an optimal daily schedule based on the goal and the existing schedule, means for notifying the user of the generated schedule, means for notifying the user of task start times based on the schedule, means for sending a task completion confirmation notification at the end time of each task, means for regenerating a schedule in real time if a task is not completed, means for notifying the user of the regenerated schedule, means for collecting the user's task execution data and emotion data, means for adjusting the schedule based on the emotion data, and means for analyzing the task execution data and emotion data and optimizing the long-term schedule. This increases the user's goal achievement rate and enables schedule management with less mental burden on the user.

[1044] The "means for setting user goals" provides an interface and functionality for users to input specific goals they wish to achieve.

[1045] The "means for inputting the user's existing schedule" provides an interface and functionality for the user to input and save the current daily activity schedule.

[1046] The "means for generating an optimal daily schedule based on the goals and existing schedule" refers to a means for creating an optimal daily activity plan using algorithms and analytical techniques, using the collected goal data and existing schedule data.

[1047] The "means for notifying the user of the generated schedule" provides a function for displaying or notifying the user of the generated schedule on the user's terminal.

[1048] The "means for notifying the start time of a task based on the schedule" provides an alarm or notification function for notifying the user of the start time of each task according to the set schedule.

[1049] The "means for sending a confirmation notification of task completion at the end time of each task" provides a function for sending a notification to the user at the end time of the task to confirm the completion status of the task.

[1050] "Means for regenerating a schedule in real time if a task is not completed" provides a function to instantly recalculate and create a new schedule if it is determined that the user has not completed a task.

[1051] The "means for notifying the user of the regenerated schedule" provides a function for displaying or notifying the user of the regenerated schedule on the user's terminal.

[1052] "Means for collecting user task execution data and emotional data" refers to providing a function for collecting which tasks a user has performed and the user's emotional state (e.g., facial expressions and tone of voice).

[1053] The "means for adjusting the schedule based on the emotional data" provides a function for analyzing the collected emotional data and changing the tasks and time allocation of the schedule according to the user's mental state.

[1054] The "means for analyzing the task execution data and emotion data and optimizing the long-term schedule" provides a function for analyzing the collected data and optimizing future schedules to help users achieve their long-term goals.

[1055] This invention provides a system that optimizes daily time management and provides a feasible schedule for users to achieve their major goals. The system incorporates an emotion engine that recognizes the user's emotions and reflects them in schedule and task adjustments.

[1056] Hardware and software used

[1057] This system is implemented using the following hardware and software:

[1058] Device: Personal devices such as smartphones and tablets

[1059] Server: Cloud server or dedicated server

[1060] Database: RDBMS such as MySQL or PostgreSQL

[1061] Emotion recognition engine: Sentiment analysis tools such as IBM Watson and Azure Emotion API

[1062] Programming language: Python, JavaScript, etc.

[1063] Communication protocol: HTTP / HTTPS

[1064] System Embodiments

[1065] 1. How users set goals

[1066] The user launches the application and inputs a goal, for example, a specific goal such as "lose 5 kg in one month." This goal is entered through the application's interface (e.g., a text box).

[1067] 2. Enter an existing schedule

[1068] Users enter their daily activities (work time, sleep time, meal time, etc.) into the application, and this data is entered and stored by the application on their smartphone or tablet.

[1069] 3. Data transmission and schedule generation

[1070] The device collects your goals and existing schedule and sends it to a server, which uses an algorithm to generate an optimal daily schedule. For example, it could create a schedule that includes 30 minutes of jogging every morning and 30 minutes of strength training in the evening.

[1071] 4. Schedule notifications and alarm settings

[1072] The server sends the generated schedule back to the device, which then notifies the user of the schedule. An alarm is also set at the start time of each task. For example, an alarm for "start jogging" can be set to ring at 6:00 AM.

[1073] 5. Check the progress of your tasks

[1074] At the end of each task, the device sends the user a confirmation that the task is complete. For example, at 6:30 AM, the device displays the message "Did you finish jogging?" The user can respond in the app.

[1075] 6. Rearrange your schedule

[1076] If the user indicates that the task is not complete, the device sends that information to the server, which then regenerates the schedule and adjusts the time of the next task, for example, moving the jogging time to 7:00 AM.

[1077] 7. Use of Emotion Engines

[1078] The device collects emotional data from the user's facial expressions and tone of voice and sends it to a server. The server uses this data to adjust schedules and change task priorities. For example, if the user is feeling stressed, the device can increase relaxation time and postpone hard tasks.

[1079] 8. Long-term schedule optimization

[1080] The server collects and analyzes the user's task execution and emotional data to optimize the schedule for the following week. For example, if the user does not go jogging as planned, the server will adjust the schedule by shortening the jogging time and suggesting a different exercise.

[1081] Specific examples

[1082] If a user sets a goal of "learning everyday conversational English in one month," the following schedule will be generated:

[1083] 6:00 AM - English Conversation Listening (30 minutes)

[1084] 6:30 AM - Breakfast

[1085] 7:00 AM - Get ready for work

[1086] 8:00 AM - Commute

[1087] 9:00 AM - Start work

[1088] 12:00 PM - Lunch Break (English Conversation Practice)

[1089] 1:00 PM - Back to work

[1090] 6:00 PM - Finish work

[1091] 7:00 PM - Dinner

[1092] 8:00 PM - English Speaking Practice (30 minutes)

[1093] 9:00 PM - Relaxation Time

[1094] 10:00 PM - Sleep

[1095] This schedule is notified to the device, and an alarm is set to ring at 6:00 AM, for example, to "Start English Conversation Listening." If a task is not completed, the server regenerates and resends the schedule. Furthermore, the system recognizes the user's emotions and adjusts the schedule, such as increasing relaxation time, if the user is feeling stressed.

[1096] This creates a system that allows users to strictly manage their daily schedules and ensures that they continue to make efforts toward achieving their goals.

[1097] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1098] Step 1: Set goals and schedule

[1099] The user launches the app and inputs their goal. Specifically, they use the app's interface to set a goal such as "lose 5 kg in one month" or "learn conversational English in one month." Next, they input their existing schedule (work hours, sleep times, meal times, etc.).

[1100] input:

[1101] the goal

[1102] Existing Schedule

[1103] output:

[1104] User data (goal and schedule information)

[1105] Specific behavior:

[1106] The user enters their goal in the text box on the app's "Goal Setting" screen and presses the "Save" button.

[1107] The user inputs an existing schedule on the "Schedule Setting" screen and presses the "Save" button.

[1108] Step 2: Send data and generate schedule

[1109] The device sends user data to a server, which then uses a built-in algorithm to generate an optimal daily schedule, such as a 30-minute morning jog and 30 minutes of strength training in the evening.

[1110] input:

[1111] User data (goal and schedule information)

[1112] output:

[1113] Generated daily schedule

[1114] Specific behavior:

[1115] The terminal sends an HTTP POST request to the server, sending the goal and existing schedule to the server.

[1116] The server receives the data and runs a scheduling algorithm to generate an optimal schedule.

[1117] The server returns the generated schedule to the terminal in JSON format.

[1118] Step 3: Schedule notifications and alarm settings

[1119] The server sends the generated schedule to the terminal, which receives it, notifies the user, and sets an alarm at the start time of each task.

[1120] input:

[1121] Generated daily schedule

[1122] output:

[1123] Schedule Notifications

[1124] Set alarms for the start time of each task

[1125] Specific behavior:

[1126] The server sends the schedule data to the endpoint.

[1127] The terminal receives the schedule data and notifies the user using the smartphone's notification function.

[1128] The app uses the internal alarm function to set an alarm at the specified time.

[1129] Step 4: Check the progress of the task

[1130] At the end of each task, the device will send a task completion confirmation to the user. For example, at 6:30 AM, a confirmation message will be displayed asking, "Did you finish jogging?"

[1131] input:

[1132] Task completion progress

[1133] output:

[1134] Task completion confirmation

[1135] Specific behavior:

[1136] The device sets a system timer that triggers a notification when the task finishes.

[1137] When the task finishes, the app will display a pop-up notification prompting the user to confirm completion.

[1138] The user responds by pressing a "Done" or "Incomplete" button within the app.

[1139] Step 5: Rearrange your schedule

[1140] If the user answers "I have not completed the task," the device sends that information to the server, which then regenerates the schedule in real time.

[1141] input:

[1142] Task completion progress

[1143] output:

[1144] Regenerated Schedule

[1145] Specific behavior:

[1146] The terminal sends the user's response to the server via an HTTP POST request.

[1147] The server executes a rescheduling algorithm based on the received information.

[1148] The server sends the new schedule in JSON format to the device, and the device again sets notifications and alarms for the user.

[1149] Step 6: Use the Emotion Engine

[1150] The device collects emotional data from the user's facial expressions and tone of voice and sends it to the server, which uses the data to adjust schedules and change task priorities.

[1151] input:

[1152] Emotional data (facial expressions and tone of voice)

[1153] output:

[1154] Adjusted Schedule

[1155] Specific behavior:

[1156] The device uses a camera and microphone to collect emotional data.

[1157] The device transmits the collected data to the server in real time.

[1158] The server analyzes the data using a sentiment analysis engine and runs a schedule adjustment algorithm.

[1159] The adjusted schedule is sent to the terminal.

[1160] Step 7: Long-term schedule optimization

[1161] The server collects the user's task execution data and emotional data, analyzes it, and optimizes the schedule for the following week.

[1162] input:

[1163] Task execution data

[1164] Emotional Data

[1165] output:

[1166] Optimized long-term schedule

[1167] Specific behavior:

[1168] The server periodically aggregates all user data and stores it in a database.

[1169] The server uses machine learning algorithms to analyze the data and identify patterns and issues.

[1170] The server generates a new optimized weekly schedule based on the analysis results and sends it to the terminal.

[1171] (Application example 2)

[1172] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1173] Existing time management systems cannot consider individual emotional states when optimizing daily schedules to help users achieve their goals. As a result, emotional factors such as stress and lack of motivation often prevent users from completing their schedules. It is also difficult to readjust schedules in real time when tasks are not completed. This leaves users without the support of an efficient schedule to achieve their set goals.

[1174] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1175] In this invention, the server includes means for setting a user's goals, means for inputting an existing schedule, means for generating an optimal daily schedule based on the goals and the existing schedule, means for notifying the user of the generated schedule, means for notifying the user of task start times based on the schedule, means for sending a task completion confirmation notification at the end time of each task, means for regenerating a schedule in real time if a task is not completed, means for notifying the user of the regenerated schedule, means for recognizing the user's emotions, means for adjusting the schedule based on the emotions, and means for analyzing the user's task execution data and optimizing the long-term schedule. This makes it possible to provide an optimal schedule in real time while taking the user's emotional state into consideration.

[1176] "User" refers to an individual who uses this system and wishes to optimize their schedule to achieve a goal.

[1177] A "goal" is a specific outcome or purpose that a user wants to achieve, such as mastering a particular skill within a certain period of time or taking an action to improve their health.

[1178] "Existing schedule" refers to the user's daily plans and activities, including pre-planned times such as work time, sleep time, and meal time.

[1179] A "daily schedule" refers to a specific daily plan optimized to achieve a user's goals, including the start and end times of each task.

[1180] "Notification" refers to a means of informing the user of important information, such as by using an alarm sound or a screen display.

[1181] A "task" refers to a specific activity or work that a user performs within a daily schedule, such as jogging or studying.

[1182] "Real time" refers to processing that responds to the current progress of the process, for example, regenerating a schedule immediately.

[1183] "Emotions" refers to the user's psychological state, including mental states such as stress and motivation.

[1184] "Means for recognizing emotions" refers to devices or software that collect emotional data from users' facial expressions, tone of voice, etc.

[1185] "Means for adjusting the schedule" refers to a function that modifies or optimizes an already generated daily schedule based on recognized emotion data.

[1186] A "long-term schedule" refers to a plan spanning several weeks to several months to achieve a user's goals, which is optimized by repeating short-term schedules.

[1187] This invention is a system that optimizes daily time management and provides a feasible schedule to help users achieve their set goals. This system incorporates an emotion engine that recognizes the user's emotions and reflects them in schedule and task adjustments.

[1188] Setting goals and getting existing schedules

[1189] The user launches the application and sets a goal, such as "lose 5 kg in one month." After that, the user inputs their existing daily schedule, including work hours, sleep times, and meal times, into the app.

[1190] Schedule data transmission and analysis

[1191] Once all the data is entered, the device sends this information to a server, which then generates an optimal daily schedule based on the user's goals and existing schedule. For example, the device might create a daily schedule that includes 30 minutes of jogging every morning and 30 minutes of strength training in the evening.

[1192] Schedule notifications and alarm settings

[1193] The server sends the generated schedule to the terminal, which then notifies the user. For example, the following schedule is displayed:

[1194] 6:00 AM - Jogging (30 minutes)

[1195] 6:30 AM - Breakfast

[1196] 7:00 AM - Get ready for work

[1197] 8:00 AM - Commute

[1198] 9:00 AM - Start work

[1199] 12:00 PM - Lunch Break (Light Exercise)

[1200] 1:00 PM - Back to work

[1201] 6:00 PM - Finish work

[1202] 7:00 PM - Dinner

[1203] 8:00 PM - Strength Training (30 minutes)

[1204] 9:00 PM - Relaxation Time

[1205] 10:00 PM - Sleep

[1206] Additionally, the device will set an alarm at the start time of each task, for example, a "Start jogging" alarm at 6:00 AM.

[1207] Checking task progress and readjusting tasks

[1208] At the end of each task, the device sends the user a confirmation notification that the task has been completed. For example, at 6:30 AM, a confirmation message is displayed asking, "Have you finished jogging?" The user responds in the app whether or not the task has been completed. If the user replies, "I haven't completed the task," the device sends that information to the server. The server regenerates the schedule in real time based on this information and shifts the time of the next task.

[1209] Use of emotion engine

[1210] This system incorporates an emotion engine that recognizes the user's emotions. The device collects emotional data from the user's facial expressions, tone of voice, etc. and sends it to the server. The server uses this emotional data to adjust the schedule and change task priorities. For example, if the user is feeling stressed, the system will adjust the schedule by increasing time for relaxation and postponing difficult tasks.

[1211] Long-term schedule optimization

[1212] The server collects and analyzes the user's task execution data and emotional data. This identifies progress and problems. The server further optimizes the schedule for the following week and beyond. For example, if jogging is not performed as scheduled, the server may shorten the jogging time and suggest a different exercise. The server also takes into account the user's emotional state when adjusting the schedule.

[1213] Hardware and Software Details

[1214] Hardware: Smartphone, camera and microphone for emotion recognition

[1215] Software: Frontend (React Native), Backend Server (Django)

[1216] On the server side, processing of emotional data and task execution data, real-time schedule regeneration, and long-term data analysis are performed.

[1217] On the device side, it is responsible for providing the user interface, collecting emotional data, and setting and displaying notifications and alarms.

[1218] Examples of concrete examples and prompts

[1219] Specific examples

[1220] Goal: "Learn everyday English conversation skills in one month"

[1221] Emotional data: The user felt stressed in the afternoon, so the adjustment was made to increase relaxation time.

[1222] Example execution flow:

[1223] Users set goals and input their existing schedules.

[1224] The server generates a schedule and notifies the terminal.

[1225] The emotion engine recognizes the user's stress and sends the data to the server.

[1226] The server adds relaxation time and regenerates the schedule.

[1227] The device notifies the user of the adjusted schedule.

[1228] Prompt Sentence Examples

[1229] text

[1230] Set a goal.

[1231] For example, one specific goal is to "master everyday conversation level English in one month."

[1232] Please tell us what tasks are required to achieve your goal, including the approximate time required.

[1233] According to the present invention, the user's daily schedule is optimized according to their emotional state, so that they can effectively achieve their goals.

[1234] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1235] Step 1:

[1236] The user launches the application and sets a goal. In this step, the user enters a specific goal, such as "lose 5 kg in one month."

[1237] Input: User's goal

[1238] Output: Set goal

[1239] What happens: The user enters their goal through the user interface and the app receives that information.

[1240] Step 2:

[1241] The user inputs their existing schedule (work hours, sleep times, meal times, etc.) into the application, which uses this information to plan for achieving their goals.

[1242] Input: User's existing schedule

[1243] Output: Input schedule data

[1244] What it does: The user enters a schedule through the user interface, and the app saves that information.

[1245] Step 3:

[1246] The terminal transmits the set goal and existing schedule data to the server.

[1247] Input: Set goals and existing schedule data

[1248] Output: Data sent to the server

[1249] Specific operation: The device sends data to the server via the network.

[1250] Step 4:

[1251] The server then generates an optimal daily schedule based on the data received, which includes activities such as jogging and strength training.

[1252] Input: User goals and existing schedule data

[1253] Output: Optimized daily schedule

[1254] Specific operation: The algorithm runs on the server and calculates the optimal schedule.

[1255] Step 5:

[1256] The server transmits the generated schedule to the terminal, and the terminal notifies the user.

[1257] Input: Server-generated schedule

[1258] Output: Schedule notified to user

[1259] Specific operation: The server sends schedule data to the device, and the device displays a notification.

[1260] Step 6:

[1261] The device sets an alarm at the start time of each task and notifies the user.

[1262] Input: Generated schedule

[1263] Output: Alarm notified to user

[1264] What happens: Your device sets an alarm and displays a notification or plays an alarm sound at the specified time.

[1265] Step 7:

[1266] At the end of each task, the device sends a task completion confirmation to the user.

[1267] Input: Task end time

[1268] Output: Task completion confirmation notification

[1269] Specific behavior: The device will sound an alarm at the task completion time and display a confirmation notification.

[1270] Step 8:

[1271] The user inputs a response indicating that the task is complete. If the task is not complete, the terminal sends that information to the server.

[1272] Input: Task completion response

[1273] Output: Completion information sent to the server

[1274] Specific operation: The user enters a confirmation response, and the device sends the information to the server.

[1275] Step 9:

[1276] The server regenerates the schedule in real time based on the user's task completion information and sends it to the terminal.

[1277] Input: Incomplete task information

[1278] Output: Regenerated schedule

[1279] Specific operation: The server recalculates, generates a new schedule, and sends it to the terminal.

[1280] Step 10:

[1281] The terminal notifies the user of the regenerated schedule.

[1282] Input: Server-generated schedule

[1283] Output: Regeneration schedule notified to the user

[1284] Specific behavior: The device receives the new schedule and notifies it.

[1285] Step 11:

[1286] The device collects the user's emotional data and sends it to the server. The emotional data includes facial expression analysis and tone of voice analysis.

[1287] Input: User emotion data

[1288] Output: Emotion data sent to the server

[1289] Specific operation: The device uses the camera and microphone to collect emotion data and transmits it to the server.

[1290] Step 12:

[1291] The server adjusts the schedule based on the emotion data and generates a new schedule.

[1292] Input: Emotion data

[1293] Output: Adjusted schedule

[1294] Specific operation: The server analyzes the emotion data and adjusts the schedule based on the results.

[1295] Step 13:

[1296] To optimize long-term schedules, the server collects and analyzes users' task execution data and emotional data.

[1297] Input: User task execution data and emotion data

[1298] Output: Optimized schedule

[1299] How it works: The server accumulates data and uses algorithms to optimize the long-term schedule.

[1300] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1301] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1302] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1303] [Third embodiment]

[1304] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1305] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1306] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1307] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1308] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1309] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1310] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1311] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1312] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1313] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1314] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1315] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1316] The present invention is a system that optimizes daily time management and provides a feasible schedule for users to achieve their major goals. This system performs the following specific program processing.

[1317] Setting goals and getting existing schedules

[1318] The user launches the app and sets a goal, such as "lose 5 kg in one month." The user then inputs their existing daily schedule, including work hours, sleep times, and meal times, into the app.

[1319] Schedule data transmission and analysis

[1320] Once all the data is entered, the device sends this information to a server, which then generates an optimal daily schedule based on the user's goals and existing schedule. For example, the server might generate a schedule that includes 30 minutes of jogging every morning and 30 minutes of strength training every evening.

[1321] Schedule notifications and alarm settings

[1322] The server sends the generated schedule to the terminal, which then notifies the user. For example, the following schedule is displayed:

[1323] 6:00 AM - Jogging (30 minutes)

[1324] 6:30 AM - Breakfast

[1325] 7:00 AM - Get ready for work

[1326] 8:00 AM - Commute

[1327] 9:00 AM - Start work

[1328] 12:00 PM - Lunch Break (Light Exercise)

[1329] 1:00 PM - Back to work

[1330] 6:00 PM - Finish work

[1331] 7:00 PM - Dinner

[1332] 8:00 PM - Strength Training (30 minutes)

[1333] 9:00 PM - Relaxation Time

[1334] 10:00 PM - Sleep

[1335] Additionally, the device will set an alarm at the start time of each task, for example, a "Start jogging" alarm at 6:00 AM.

[1336] Checking task progress

[1337] At the end of each task, the device sends a task completion confirmation to the user. For example, at 6:30 AM, a confirmation message is displayed asking, "Did you finish jogging?" The user can then respond in the app whether or not the task is complete.

[1338] Rescheduling

[1339] If the user answers "I haven't completed the task," the device sends that information to the server, which then regenerates the schedule in real time based on this information and adjusts the time of the next task, for example, by moving the jogging time to 7:00 AM.

[1340] Long-term schedule optimization

[1341] The server collects and analyzes the user's task execution data, identifying progress and problems. The system further optimizes the schedule for the following week and beyond. For example, if the user is not continuing their jogging routine, the system will make adjustments such as shortening the jogging time and suggesting a different exercise.

[1342] Specific examples

[1343] Let's take the example of a user's goal of "learning English conversation at a daily conversation level in one month." The server generates the following schedule:

[1344] 6:00 AM - English Conversation Listening (30 minutes)

[1345] 6:30 AM - Breakfast

[1346] 7:00 AM - Get ready for work

[1347] 8:00 AM - Commute

[1348] 9:00 AM - Start work

[1349] 12:00 PM - Lunch Break (English Conversation Practice)

[1350] 1:00 PM - Back to work

[1351] 6:00 PM - Finish work

[1352] 7:00 PM - Dinner

[1353] 8:00 PM - English Speaking Practice (30 minutes)

[1354] 9:00 PM - Relaxation Time

[1355] 10:00 PM - Sleep

[1356] This schedule is sent to the device, and an alarm is set at the start time of each task. For example, an alarm for the start of English conversation listening will sound at 6:00 AM.

[1357] If the user has not completed the task, the server regenerates the schedule and sends it to the device again, notifying it of the adjusted schedule, for example, by moving the listening time to 7:00 AM.

[1358] This system allows users to strictly manage their daily schedules and ensure that they continue to make efforts toward achieving their goals.

[1359] The processing flow will be explained below.

[1360] Step 1:

[1361] The user starts the app and goes to the "Goal Setting" screen. For example, they enter a specific goal, such as "lose 5 kg in one month."

[1362] Step 2:

[1363] On the "Enter Existing Schedule" screen, users enter their current lifestyle and daily activity schedule, including work start and end times, meal times, and sleep times.

[1364] Step 3:

[1365] The terminal transmits the data of the goal and the existing schedule to the server.

[1366] Step 4:

[1367] The server analyzes the received data and generates an optimal schedule for achieving the goal, for example, a daily schedule including 30 minutes of jogging every morning and 30 minutes of strength training in the evening.

[1368] Step 5:

[1369] The server transmits the generated schedule to the terminal.

[1370] Step 6:

[1371] The terminal notifies the user of the generated schedule. For example, the following schedule is displayed:

[1372] 6:00 AM - Jogging (30 minutes)

[1373] 6:30 AM - Breakfast

[1374] 7:00 AM - Get ready for work

[1375] 8:00 AM - Commute

[1376] 9:00 AM - Start work

[1377] 12:00 PM - Lunch Break (Light Exercise)

[1378] 1:00 PM - Back to work

[1379] 6:00 PM - Finish work

[1380] 7:00 PM - Dinner

[1381] 8:00 PM - Strength Training (30 minutes)

[1382] 9:00 PM - Relaxation Time

[1383] 10:00 PM - Sleep

[1384] Step 7:

[1385] Your device will set an alarm for the start time of each task, for example, a "Start jogging" alarm at 6:00 AM.

[1386] Step 8:

[1387] The device will send a task completion confirmation at the end of each task, for example, at 6:30 AM it will display the message "Did you finish jogging?"

[1388] Step 9:

[1389] The user responds to the app by completing a task, for example, by saying "I completed my jog."

[1390] Step 10:

[1391] If the user answers "I have not completed my jog," the device sends that information to the server.

[1392] Step 11:

[1393] The server regenerates the schedule in real time based on the information received. For example, it adjusts the schedule as follows:

[1394] 6:30 AM - Jogging (30 minutes)

[1395] 7:00 AM - Breakfast

[1396] 7:30 AM - Get ready for work

[1397] 8:00 AM - Commute

[1398] 9:00 AM - Start work

[1399] 12:00 PM - Lunch Break (Light Exercise)

[1400] 1:00 PM - Back to work

[1401] 6:00 PM - Finish work

[1402] 7:00 PM - Dinner

[1403] 8:00 PM - Strength Training (30 minutes)

[1404] 9:00 PM - Relaxation Time

[1405] 10:00 PM - Sleep

[1406] Step 12:

[1407] The server transmits the regenerated schedule to the terminal.

[1408] Step 13:

[1409] The terminal notifies the user of the regenerated schedule.

[1410] Step 14:

[1411] The server collects and analyzes the user's task execution data, thereby identifying the progress and problems.

[1412] Step 15:

[1413] The server optimizes the schedule for the next week, and if jogging is not performed as scheduled, for example, adjustments are made such as shortening the jogging time and suggesting a different exercise.

[1414] Step 16:

[1415] The server transmits the optimized long-term schedule to the terminal, and the terminal notifies the user of it.

[1416] Example 1

[1417] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1418] Conventional time management systems require users to create their own schedules, which does not necessarily allow for appropriate planning for achieving goals. Furthermore, if a user is unable to complete a task, subsequent schedule adjustments must be made manually, making efficient time management difficult. Furthermore, they lack a mechanism for optimizing schedules to achieve long-term goals. There is a need for a system that can solve these problems and provide effective and flexible time management to help users achieve their goals.

[1419] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1420] In this invention, the server includes a means for setting a user's goals, a means for inputting the user's existing schedule, and a cloud server and a means for using a generative AI model to generate an optimal daily schedule based on the goals and the existing schedule. This makes it possible to automatically generate an efficient and feasible schedule based on the goals set by the user, adjust the schedule in real time according to the daily progress, and support the achievement of long-term goals.

[1421] "User" means an individual or organization that uses the system to set goals and manage schedules.

[1422] "Means for setting goals" refers to a function or interface that allows users to input the goals they wish to achieve into the system.

[1423] "Means for inputting existing schedules" refers to a function or interface that allows users to input their daily plans and activity times into the system.

[1424] A "cloud server" is a server that stores and processes data via the Internet and is responsible for the system's main calculations and data processing.

[1425] A "generative AI model" is an algorithm or program that uses artificial intelligence technology to generate an optimal schedule based on a user's goals and existing schedule.

[1426] "Notification means" refers to a function or device that notifies users of schedules and alarms generated by the system.

[1427] "Means for notifying the start time of a task" refers to a function or device for notifying the user of the time when each task should start.

[1428] The "means for sending a confirmation notification of task completion" is a function or interface for confirming with the user whether or not the task has been completed at the end time of each task.

[1429] "Means for regenerating schedules in real time" refers to a function or system that instantly generates a new schedule based on information when a user does not complete a task.

[1430] "Means for analyzing task execution data and optimizing long-term schedules" refers to a function or program that analyzes users' daily task execution data and continuously adjusts and optimizes schedules.

[1431] The present invention is a system for managing daily tasks by providing an optimal schedule for a user to achieve their goals. Specific examples are shown below.

[1432] Setting goals and getting existing schedules

[1433] The app provides a means for users to launch the app and input the goal they want to achieve. For example, they can set a goal of "lose 5 kg in one month." Next, the app provides a means for users to input their existing schedule (e.g., work hours, sleep hours, meal times). This can be done using a device such as a smartphone or PC.

[1434] Data transmission and analysis

[1435] The device sends the user's input goals and existing schedule to the cloud server. The server then analyzes the input data using a generative AI model to generate an optimal daily schedule. At this time, the following prompt is input to the generative AI model:

[1436] "Please suggest an optimal daily schedule for losing 5 kg in one month."

[1437] Schedule notifications and alarm settings

[1438] The server sends the generated optimal schedule to the device, which then notifies the user. When the user receives the notification, the device sets an alarm at the start time of each task. For example, a notification to start jogging at 6:00 AM is displayed and an alarm sounds.

[1439] Check task progress and adjust in real time

[1440] At the end of each task, the device sends the user a task completion confirmation notification. For example, at 6:30 AM, when the jogging ends, a confirmation notification is displayed asking, "Have you finished jogging?" If the user replies that they have not completed the task, the device sends that information to the server. The server immediately recalculates the schedule, adjusts the time of the next task, and sends it again to the device. This results in an adjustment, such as changing the jogging time to 7:00 AM.

[1441] Long-term schedule optimization

[1442] The server continuously collects and analyzes the user's task execution data, identifying progress and problems and optimizing the schedule for the following week. For example, if the jogging time is too long, the server will suggest shortening the time and suggesting a different exercise.

[1443] Hardware and software examples

[1444] Hardware: smartphones, PCs, cloud servers

[1445] Software: Dedicated app, cloud-based data analysis tools, notification and alarm management system

[1446] Specific examples

[1447] If a user sets a goal of "mastering everyday conversation level English in one month," the server will generate the following schedule:

[1448] 6:00 AM - English Conversation Listening (30 minutes)

[1449] 6:30 AM - Breakfast

[1450] 7:00 AM - Get ready for work

[1451] 8:00 AM - Commute

[1452] 9:00 AM - Start work

[1453] 12:00 PM - Lunch Break (English Conversation Practice)

[1454] 1:00 PM - Back to work

[1455] 6:00 PM - Finish work

[1456] 7:00 PM - Dinner

[1457] 8:00 PM - English Speaking Practice (30 minutes)

[1458] 9:00 PM - Relaxation Time

[1459] 10:00 PM - Sleep

[1460] This schedule is sent to the device, and an alarm is set at the start time of each task. For example, an alarm for the start of English conversation listening will sound at 6:00 AM.

[1461] If the user has not completed the task, the server regenerates the schedule and sends it back to the device, notifying the user of the adjusted schedule. For example, the listening time can be moved to 7:00 AM. This ensures that the user maintains strict control over their daily schedule and continues to work toward achieving their goals.

[1462] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1463] Step 1:

[1464] The user launches the app and sets a goal. As input, the app inputs the goal they want to achieve (e.g., "lose 5 kg in one month"). As output, the app generates the user's goal data, which is used in subsequent processing steps.

[1465] Step 2:

[1466] The user inputs their existing schedule into the app. As input, they input their daily schedule (work time, sleep time, meal time, etc.). As output, the user's existing schedule data is generated. This schedule data is sent to the server along with the goal data.

[1467] Step 3:

[1468] The terminal transmits the input goal data and existing schedule data to the cloud server. As input, the terminal receives the user's goal data and existing schedule data. As output, the terminal generates a transmission request to the cloud server.

[1469] Step 4:

[1470] Based on the goal data and existing schedule data received by the server, an optimal schedule is generated using a generative AI model. The goal data and existing schedule data are received as input. A prompt statement (e.g., "Please suggest an optimal daily schedule for losing 5 kg in one month") is input to the generative AI model, and optimal schedule data is generated as output.

[1471] Step 5:

[1472] The server sends the generated schedule data to the terminal. As input, it receives the generated schedule data. As output, it generates the schedule data as a transmission request to the terminal.

[1473] Step 6:

[1474] The terminal notifies the user of the received schedule data. As input, the received schedule data is processed for display. As output, the schedule is displayed to the user and sent as a notification.

[1475] Step 7:

[1476] The terminal sets an alarm at the start time of each task. As input, it obtains the start time of each task in the schedule data. As output, an alarm is set and a notification is sent to the user at the specified time.

[1477] Step 8:

[1478] At the end time of each task, the terminal sends a confirmation notification of task completion to the user. As input, the end time of each task in the schedule data is obtained. As output, a confirmation notification of task completion is sent to the user.

[1479] Step 9:

[1480] The user responds to the task completion notification. As input, the user enters whether or not the task is completed into the app. As output, task completion data is generated.

[1481] Step 10:

[1482] If the task is not completed, the terminal sends the information to the server. As input, it receives the data of the task not completed. As output, it generates the information of the task not completed as a transmission request to the server.

[1483] Step 11:

[1484] The server regenerates the schedule in real time based on the data of incomplete tasks. As input, it receives the incomplete task data and inputs a prompt sentence again based on the generative AI model (e.g., "Please adjust your schedule, such as moving your jogging time to 7:00 AM."). As output, new schedule data is generated.

[1485] Step 12:

[1486] The server transmits the regenerated schedule data to the terminal. As input, the server receives the regenerated schedule data. As output, the server generates the schedule data as a transmission request to the terminal.

[1487] Step 13:

[1488] The terminal notifies the user of the regenerated schedule data. As input, the terminal processes the regenerated schedule data for display. As output, the schedule is notified to the user again.

[1489] Step 14:

[1490] The server continuously collects and analyzes user task execution data. The collected data is used as input, and the analysis results are generated as output.

[1491] Step 15:

[1492] The server optimizes the schedule for the following week based on the analysis results. The analysis results are received as input. The optimized schedule data for the following week is generated as output.

[1493] Step 16:

[1494] The server transmits the optimized schedule data for the next week and beyond to the terminal. As input, it receives the optimized schedule data. As output, it generates the schedule data as a transmission request to the terminal.

[1495] Step 17:

[1496] The terminal notifies the user of the optimized schedule data for the next week and beyond. As input, the optimized schedule data is processed for display. As output, the schedule is notified to the user.

[1497] (Application example 1)

[1498] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1499] Current factory production management systems do not efficiently manage operation plans for work equipment and machines, resulting in reduced production efficiency and difficulty in achieving production targets. Furthermore, the operating status of production equipment and maintenance plans are not adequately considered, making unplanned shutdowns and delays more likely to occur. Furthermore, work progress is not checked in real time, often resulting in delays in readjusting the production schedule. For these reasons, there was a need for effective production schedule generation and management to improve the efficiency of the entire factory.

[1500] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1501] In this invention, the server includes means for setting production targets to be achieved by factory work equipment and machines, means for inputting operation plans and maintenance plans for production equipment, means for generating an optimal daily schedule based on the targets and existing operation plans, means for notifying the relevant production equipment of work instructions based on the generated schedule, means for sending progress confirmation notifications at the end time of each production task, and means for regenerating the production schedule in real time if a production task is not completed. This makes it possible to maximize production efficiency and ensure the achievement of production targets.

[1502] A "means for setting user goals" is a system or device that allows a factory operator or manager to input production goals to be achieved for the factory's work equipment and machines.

[1503] The "means for inputting the user's existing schedule" refers to an interface or device for inputting the current operation plan and maintenance plan for the factory's work equipment and machines.

[1504] The "means for generating an optimal daily schedule based on the target and existing schedule" refers to an algorithm or software that calculates and generates an optimal daily schedule for the factory's work equipment and machines based on the set target and existing operation plan.

[1505] The "means for notifying the user of the generated schedule" refers to a system or device for notifying a factory operator or manager of the generated schedule.

[1506] The "means for notifying the start time of a task based on the schedule" refers to a system or device for notifying the work equipment or machines in a factory of the start time of each work task based on the schedule.

[1507] The "means for sending a confirmation notification of task completion at the end time of each task" is a system or device that sends a notification at the end time of each work task to confirm whether the task has been completed.

[1508] "Means for regenerating a schedule in real time if a task is not completed" refers to an algorithm or software that recalculates and regenerates the currently set schedule in real time based on information about incomplete tasks.

[1509] The "means for notifying users of the regenerated schedule" refers to a system or device for notifying factory operators or managers of the new regenerated schedule.

[1510] The "means for analyzing user task execution data and optimizing long-term schedules" refers to an analytical algorithm or software for optimizing factory work schedules over the long term based on collected task execution data.

[1511] The "means for setting production targets to be achieved by work equipment and machines in a factory" refers to a system or device for inputting and setting production targets set for work equipment and machines in a factory.

[1512] The "means for inputting the operation plan and maintenance plan of the production equipment" refers to an interface or device for inputting the operation schedule and maintenance schedule of the production equipment.

[1513] The "means for generating an optimal daily schedule based on the above-mentioned targets and existing operation plans" refers to an algorithm or software that calculates and generates an optimal daily schedule for the factory's work equipment and machines based on the set production targets and existing operation plans.

[1514] The "means for notifying the relevant production equipment of work instructions based on the generated schedule" refers to a system or device for notifying the relevant production equipment or machine of each work instruction based on the generated schedule.

[1515] The "means for sending a progress confirmation notification at the end time of each production task" refers to a system or device that sends a notification to confirm the progress of each production task at the end time of that task.

[1516] The "means for regenerating a production schedule in real time when a production task is not completed" refers to an algorithm or software that, when a production task is not completed, recalculates and regenerates the currently set production schedule in real time based on that information.

[1517] This invention is a system that optimizes the operation schedules of factory work equipment and machines and supports the achievement of production targets. Specifically, this describes a system in which factory operators input targets and existing operation plans, a server generates an optimal schedule based on that data, and monitors and adjusts the progress of each task in real time.

[1518] First, a factory operator accesses the system using a control terminal (e.g., a PC or tablet) and sets a production target. This target is specifically defined, for example, to assemble 1,000 products in one day. Next, the current operation plan and maintenance plan are entered into the system. This operation plan includes work time slots and existing maintenance times.

[1519] The server generates an optimal daily schedule based on the input goals and existing schedules. It is desirable to use AI models or machine learning algorithms for this calculation and generation. The generated schedule is notified to the work equipment via the control terminal. Using available cloud database services (e.g., AWS RDS) allows for efficient data management and storage.

[1520] When the start time for each work task arrives, the server notifies the relevant work equipment of the work instructions via the control terminal. The control terminal displays an alarm, such as "Assembly begins at 9:00." The work equipment executes the task, and when it is time to finish, the server checks the progress. This progress check is performed by the control terminal displaying a confirmation message to the operator. For example, a notification may be displayed asking, "Is the 9:00 assembly completed?"

[1521] If a work task is not completed, the operator enters that information into the system. The server regenerates the schedule in real time based on this information and notifies the work equipment of the re-adjusted schedule. Tasks are then rearranged according to this re-generated schedule, optimizing the work plan for the next day.

[1522] In the long term, the server will periodically analyze the task execution data collected and further optimize the schedule for the following week, enabling adjustments to be made to improve the factory's overall production efficiency.

[1523] For example, if a factory's daily production target is 1,000 products, a schedule will be provided that allows the robots to efficiently carry out the work within the specified working hours. This schedule will be strictly managed, and production progress will be checked on an ongoing basis, ensuring that efforts to achieve the target are continued.

[1524] An example of a prompt sentence might be:

[1525] "Generate an optimal task list and schedule for the factory robots between 9:00-12:00 and 13:00-18:00 so that they can efficiently assemble the daily target of 1,000 products."

[1526] In this way, it is a feature of the present invention that the factory's production efficiency is maximized and targets are achieved.

[1527] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1528] Step 1:

[1529] The user sets production targets for the factory's work equipment and machines using a control terminal. At this time, the user inputs the target value (e.g., assemble 1,000 products in one day). Data based on this is sent to the server.

[1530] Step 2:

[1531] Users use a control terminal to input existing operation and maintenance plans into the system. This data is also sent to the server. The input data includes work time slots and maintenance times.

[1532] Step 3:

[1533] The server generates an optimal daily schedule based on the received production targets, operation plans, and maintenance plans. It uses generative AI models and machine learning algorithms to calculate the optimal start and end times for each work task. This generated schedule is then sent from the server to the device.

[1534] Step 4:

[1535] The terminal notifies each piece of work equipment in the factory of the schedule it receives from the server. This notification includes the start and end times of each work task. Each piece of equipment begins operating according to the notified schedule.

[1536] Step 5:

[1537] When the start time for each work task arrives, the terminal sends a start command to the corresponding work equipment. For example, a notification such as "Assembly begins at 9:00" is displayed, and the equipment begins operation.

[1538] Step 6:

[1539] When the end time of each work task arrives, the terminal sends a task completion confirmation to the user. The user checks whether the task is completed and reports the result on the terminal.

[1540] Step 7:

[1541] If a task is not completed, the device sends the information to the server, which regenerates the schedule in real time based on the incomplete information, and the new schedule is sent to the device again.

[1542] Step 8:

[1543] The terminal receives the regenerated schedule and notifies each piece of work equipment of the new instructions, including the adjusted start and end times of each work task.

[1544] Step 9:

[1545] The server collects all task execution data and analyzes it for long-term schedule optimization. It uses machine learning algorithms to further optimize the schedule for the following week and beyond, and sends the results to the device.

[1546] This maximizes factory production efficiency and ensures production targets are met.

[1547] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1548] This invention is a system that optimizes daily time management and provides a feasible schedule for users to achieve their big goals. This system incorporates an emotion engine that recognizes the user's emotions and reflects them in the adjustment of schedules and tasks.

[1549] Setting goals and getting existing schedules

[1550] The user launches the app and sets a goal, such as "lose 5 kg in one month." The user then inputs their existing daily schedule, including work hours, sleep times, and meal times, into the app.

[1551] Schedule data transmission and analysis

[1552] Once all the data is entered, the device sends this information to a server, which then generates an optimal daily schedule based on the user's goals and existing schedule. For example, the device might create a daily schedule that includes 30 minutes of jogging every morning and 30 minutes of strength training in the evening.

[1553] Schedule notifications and alarm settings

[1554] The server sends the generated schedule to the terminal, which then notifies the user. For example, the following schedule is displayed:

[1555] 6:00 AM - Jogging (30 minutes)

[1556] 6:30 AM - Breakfast

[1557] 7:00 AM - Get ready for work

[1558] 8:00 AM - Commute

[1559] 9:00 AM - Start work

[1560] 12:00 PM - Lunch Break (Light Exercise)

[1561] 1:00 PM - Back to work

[1562] 6:00 PM - Finish work

[1563] 7:00 PM - Dinner

[1564] 8:00 PM - Strength Training (30 minutes)

[1565] 9:00 PM - Relaxation Time

[1566] 10:00 PM - Sleep

[1567] Additionally, the device will set an alarm at the start time of each task, for example, a "Start jogging" alarm at 6:00 AM.

[1568] Checking task progress

[1569] At the end of each task, the device sends a task completion confirmation to the user. For example, at 6:30 AM, a confirmation message is displayed asking, "Did you finish jogging?" The user can then respond in the app whether or not the task is complete.

[1570] Rescheduling

[1571] If the user answers "I haven't completed the task," the device sends that information to the server, which then regenerates the schedule in real time based on this information and adjusts the schedule accordingly, for example, by moving the jogging time to 7:00 AM.

[1572] Use of emotion engine

[1573] This system incorporates an emotion engine that recognizes the user's emotions. The device collects emotional data from the user's facial expressions, tone of voice, etc. and sends it to the server. The server uses this emotional data to adjust the schedule and change task priorities. For example, if the user is feeling stressed, the system will adjust the schedule by increasing time for relaxation and postponing hard tasks.

[1574] Long-term schedule optimization

[1575] The server collects and analyzes the user's task execution data and emotional data. This identifies progress and problems. The system further optimizes the schedule for the following week and beyond. For example, if jogging is not performed as planned, the system will shorten the jogging time and suggest a different exercise. The system also takes into account the user's emotional state when adjusting the schedule.

[1576] Specific examples

[1577] Let's take the example of a user's goal of "learning English conversation at a daily conversation level in one month." The server generates the following schedule:

[1578] 6:00 AM - English Conversation Listening (30 minutes)

[1579] 6:30 AM - Breakfast

[1580] 7:00 AM - Get ready for work

[1581] 8:00 AM - Commute

[1582] 9:00 AM - Start work

[1583] 12:00 PM - Lunch Break (English Conversation Practice)

[1584] 1:00 PM - Back to work

[1585] 6:00 PM - Finish work

[1586] 7:00 PM - Dinner

[1587] 8:00 PM - English Speaking Practice (30 minutes)

[1588] 9:00 PM - Relaxation Time

[1589] 10:00 PM - Sleep

[1590] This schedule is sent to the device, and an alarm is set at the start time of each task. For example, an alarm for the start of English conversation listening will sound at 6:00 AM.

[1591] If the user has not completed the task, the server regenerates the schedule and sends it to the device again, notifying it of the adjusted schedule, for example, by moving the listening time to 7:00 AM.

[1592] The emotion engine also recognizes the user's emotions, and if the user is feeling stressed, for example, it will adjust the system to increase relaxation time and postpone burdensome tasks.

[1593] This system allows users to strictly manage their daily schedules and ensure that they continue to make efforts toward achieving their goals.

[1594] The processing flow will be explained below.

[1595] Step 1:

[1596] The user starts the app and goes to the "Goal Setting" screen. For example, they enter a specific goal, such as "lose 5 kg in one month."

[1597] Step 2:

[1598] On the "Enter Existing Schedule" screen, users enter their current lifestyle and daily activity schedule, including work start and end times, meal times, and sleep times.

[1599] Step 3:

[1600] The terminal transmits the data of the goal and the existing schedule to the server.

[1601] Step 4:

[1602] The server analyzes the received data and generates an optimal schedule for achieving the goal, for example, a daily schedule including 30 minutes of jogging every morning and 30 minutes of strength training in the evening.

[1603] Step 5:

[1604] The server transmits the generated schedule to the terminal.

[1605] Step 6:

[1606] The terminal notifies the user of the generated schedule. For example, the following schedule is displayed:

[1607] 6:00 AM - Jogging (30 minutes)

[1608] 6:30 AM - Breakfast

[1609] 7:00 AM - Get ready for work

[1610] 8:00 AM - Commute

[1611] 9:00 AM - Start work

[1612] 12:00 PM - Lunch Break (Light Exercise)

[1613] 1:00 PM - Back to work

[1614] 6:00 PM - Finish work

[1615] 7:00 PM - Dinner

[1616] 8:00 PM - Strength Training (30 minutes)

[1617] 9:00 PM - Relaxation Time

[1618] 10:00 PM - Sleep

[1619] Step 7:

[1620] Your device will set an alarm for the start time of each task, for example, a "Start jogging" alarm at 6:00 AM.

[1621] Step 8:

[1622] The device will send a task completion confirmation at the end of each task, for example, at 6:30 AM it will display the message "Did you finish jogging?"

[1623] Step 9:

[1624] The user responds to the app by completing a task, for example, by saying "I completed my jog."

[1625] Step 10:

[1626] If the user answers "I have not completed my jog," the device sends that information to the server.

[1627] Step 11:

[1628] The server regenerates the schedule in real time based on the information received. For example, it adjusts the schedule as follows:

[1629] 6:30 AM - Jogging (30 minutes)

[1630] 7:00 AM - Breakfast

[1631] 7:30 AM - Get ready for work

[1632] 8:00 AM - Commute

[1633] 9:00 AM - Start work

[1634] 12:00 PM - Lunch Break (Light Exercise)

[1635] 1:00 PM - Back to work

[1636] 6:00 PM - Finish work

[1637] 7:00 PM - Dinner

[1638] 8:00 PM - Strength Training (30 minutes)

[1639] 9:00 PM - Relaxation Time

[1640] 10:00 PM - Sleep

[1641] Step 12:

[1642] The server transmits the regenerated schedule to the terminal.

[1643] Step 13:

[1644] The terminal notifies the user of the regenerated schedule.

[1645] Step 14:

[1646] Furthermore, the device is equipped with an emotion engine that collects emotional data from the user's facial expressions and tone of voice, and periodically transmits this data to a server.

[1647] Step 15:

[1648] The server analyzes the emotional data to understand the user's stress level and motivation. For example, if the user feels tired, it will suggest taking more rest time.

[1649] Step 16:

[1650] The server adjusts the schedule based on the emotional data. For example, if the user is feeling stressed, the server will increase the amount of time for relaxation and postpone hard tasks.

[1651] Step 17:

[1652] The server transmits the schedule adjusted by the emotion engine to the terminal.

[1653] Step 18:

[1654] The terminal notifies the user of the adjusted schedule.

[1655] Step 19:

[1656] The server collects and analyzes the user's task execution data and emotional data, thereby identifying achievement status and problems.

[1657] Step 20:

[1658] The server optimizes the schedule for the next week, and if jogging is not performed as planned, for example, it will shorten the jogging time and suggest a different exercise. It also takes into account schedule adjustments based on the user's emotions.

[1659] Step 21:

[1660] The server transmits the optimized long-term schedule to the terminal, and the terminal notifies the user of it.

[1661] Specific examples

[1662] Let's take the example of a user's goal of "learning English conversation at a daily conversation level in one month." The server generates the following schedule:

[1663] 6:00 AM - English Conversation Listening (30 minutes)

[1664] 6:30 AM - Breakfast

[1665] 7:00 AM - Get ready for work

[1666] 8:00 AM - Commute

[1667] 9:00 AM - Start work

[1668] 12:00 PM - Lunch Break (English Conversation Practice)

[1669] 1:00 PM - Back to work

[1670] 6:00 PM - Finish work

[1671] 7:00 PM - Dinner

[1672] 8:00 PM - English Speaking Practice (30 minutes)

[1673] 9:00 PM - Relaxation Time

[1674] 10:00 PM - Sleep

[1675] This schedule is sent to the device, and an alarm is set at the start time of each task. For example, an alarm for the start of English conversation listening will sound at 6:00 AM.

[1676] If the user has not completed the task, the server regenerates the schedule and sends it to the device again, notifying it of the adjusted schedule, for example, by moving the listening time to 7:00 AM.

[1677] The emotion engine also recognizes the user's emotions, and if the user is feeling stressed, for example, it will adjust the system to increase relaxation time and postpone burdensome tasks.

[1678] This system allows users to strictly manage their daily schedules and ensure that they continue to make efforts toward achieving their goals.

[1679] Example 2

[1680] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1681] In modern society, time management is essential for achieving individual goals, but maintaining an optimal schedule in a busy daily life is difficult. Furthermore, few existing systems adjust schedules taking into account the user's emotional state, which can increase the user's mental burden. This can lead to a decrease in motivation to achieve goals and make it difficult to achieve results.

[1682] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for setting a user's goal, means for inputting the user's existing schedule, means for generating an optimal daily schedule based on the goal and the existing schedule, means for notifying the user of the generated schedule, means for notifying the user of task start times based on the schedule, means for sending a task completion confirmation notification at the end time of each task, means for regenerating a schedule in real time if a task is not completed, means for notifying the user of the regenerated schedule, means for collecting the user's task execution data and emotion data, means for adjusting the schedule based on the emotion data, and means for analyzing the task execution data and emotion data and optimizing the long-term schedule. This increases the user's goal achievement rate and enables schedule management with less mental burden on the user.

[1683] The "means for setting user goals" provides an interface and functionality for users to input specific goals they wish to achieve.

[1684] The "means for inputting the user's existing schedule" provides an interface and functionality for the user to input and save the current daily activity schedule.

[1685] The "means for generating an optimal daily schedule based on the goals and existing schedule" refers to a means for creating an optimal daily activity plan using algorithms and analytical techniques, using the collected goal data and existing schedule data.

[1686] The "means for notifying the user of the generated schedule" provides a function for displaying or notifying the user of the generated schedule on the user's terminal.

[1687] The "means for notifying the start time of a task based on the schedule" provides an alarm or notification function for notifying the user of the start time of each task according to the set schedule.

[1688] The "means for sending a confirmation notification of task completion at the end time of each task" provides a function for sending a notification to the user at the end time of the task to confirm the completion status of the task.

[1689] "Means for regenerating a schedule in real time if a task is not completed" provides a function to instantly recalculate and create a new schedule if it is determined that the user has not completed a task.

[1690] The "means for notifying the user of the regenerated schedule" provides a function for displaying or notifying the user of the regenerated schedule on the user's terminal.

[1691] "Means for collecting user task execution data and emotional data" refers to providing a function for collecting which tasks a user has performed and the user's emotional state (e.g., facial expressions and tone of voice).

[1692] The "means for adjusting the schedule based on the emotional data" provides a function for analyzing the collected emotional data and changing the tasks and time allocation of the schedule according to the user's mental state.

[1693] The "means for analyzing the task execution data and emotion data and optimizing the long-term schedule" provides a function for analyzing the collected data and optimizing future schedules to help users achieve their long-term goals.

[1694] This invention provides a system that optimizes daily time management and provides a feasible schedule for users to achieve their major goals. The system incorporates an emotion engine that recognizes the user's emotions and reflects them in schedule and task adjustments.

[1695] Hardware and software used

[1696] This system is implemented using the following hardware and software:

[1697] Device: Personal devices such as smartphones and tablets

[1698] Server: Cloud server or dedicated server

[1699] Database: RDBMS such as MySQL or PostgreSQL

[1700] Emotion recognition engine: Sentiment analysis tools such as IBM Watson and Azure Emotion API

[1701] Programming language: Python, JavaScript, etc.

[1702] Communication protocol: HTTP / HTTPS

[1703] System Embodiments

[1704] 1. How users set goals

[1705] The user launches the application and inputs a goal, for example, a specific goal such as "lose 5 kg in one month." This goal is entered through the application's interface (e.g., a text box).

[1706] 2. Enter an existing schedule

[1707] Users enter their daily activities (work time, sleep time, meal time, etc.) into the application, and this data is entered and stored by the application on their smartphone or tablet.

[1708] 3. Data transmission and schedule generation

[1709] The device collects your goals and existing schedule and sends it to a server, which uses an algorithm to generate an optimal daily schedule. For example, it could create a schedule that includes 30 minutes of jogging every morning and 30 minutes of strength training in the evening.

[1710] 4. Schedule notifications and alarm settings

[1711] The server sends the generated schedule back to the device, which then notifies the user of the schedule. An alarm is also set at the start time of each task. For example, an alarm for "start jogging" can be set to ring at 6:00 AM.

[1712] 5. Check the progress of your tasks

[1713] At the end of each task, the device sends the user a confirmation that the task is complete. For example, at 6:30 AM, the device displays the message "Did you finish jogging?" The user can respond in the app.

[1714] 6. Rearrange your schedule

[1715] If the user indicates that the task is not complete, the device sends that information to the server, which then regenerates the schedule and adjusts the time of the next task, for example, moving the jogging time to 7:00 AM.

[1716] 7. Use of Emotion Engines

[1717] The device collects emotional data from the user's facial expressions and tone of voice and sends it to a server. The server uses this data to adjust schedules and change task priorities. For example, if the user is feeling stressed, the device can increase relaxation time and postpone hard tasks.

[1718] 8. Long-term schedule optimization

[1719] The server collects and analyzes the user's task execution and emotional data to optimize the schedule for the following week. For example, if the user does not go jogging as planned, the server will adjust the schedule by shortening the jogging time and suggesting a different exercise.

[1720] Specific examples

[1721] If a user sets a goal of "learning everyday conversational English in one month," the following schedule will be generated:

[1722] 6:00 AM - English Conversation Listening (30 minutes)

[1723] 6:30 AM - Breakfast

[1724] 7:00 AM - Get ready for work

[1725] 8:00 AM - Commute

[1726] 9:00 AM - Start work

[1727] 12:00 PM - Lunch Break (English Conversation Practice)

[1728] 1:00 PM - Back to work

[1729] 6:00 PM - Finish work

[1730] 7:00 PM - Dinner

[1731] 8:00 PM - English Speaking Practice (30 minutes)

[1732] 9:00 PM - Relaxation Time

[1733] 10:00 PM - Sleep

[1734] This schedule is notified to the device, and an alarm is set to ring at 6:00 AM, for example, to "Start English Conversation Listening." If a task is not completed, the server regenerates and resends the schedule. Furthermore, the system recognizes the user's emotions and adjusts the schedule, such as increasing relaxation time, if the user is feeling stressed.

[1735] This creates a system that allows users to strictly manage their daily schedules and ensures that they continue to make efforts toward achieving their goals.

[1736] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1737] Step 1: Set goals and schedule

[1738] The user launches the app and inputs their goal. Specifically, they use the app's interface to set a goal such as "lose 5 kg in one month" or "learn conversational English in one month." Next, they input their existing schedule (work hours, sleep times, meal times, etc.).

[1739] input:

[1740] the goal

[1741] Existing Schedule

[1742] output:

[1743] User data (goal and schedule information)

[1744] Specific behavior:

[1745] The user enters their goal in the text box on the app's "Goal Setting" screen and presses the "Save" button.

[1746] The user inputs an existing schedule on the "Schedule Setting" screen and presses the "Save" button.

[1747] Step 2: Send data and generate schedule

[1748] The device sends user data to a server, which then uses a built-in algorithm to generate an optimal daily schedule, such as a 30-minute morning jog and 30 minutes of strength training in the evening.

[1749] input:

[1750] User data (goal and schedule information)

[1751] output:

[1752] Generated daily schedule

[1753] Specific behavior:

[1754] The terminal sends an HTTP POST request to the server, sending the goal and existing schedule to the server.

[1755] The server receives the data and runs a scheduling algorithm to generate an optimal schedule.

[1756] The server returns the generated schedule to the terminal in JSON format.

[1757] Step 3: Schedule notifications and alarm settings

[1758] The server sends the generated schedule to the terminal, which receives it, notifies the user, and sets an alarm at the start time of each task.

[1759] input:

[1760] Generated daily schedule

[1761] output:

[1762] Schedule Notifications

[1763] Set alarms for the start time of each task

[1764] Specific behavior:

[1765] The server sends the schedule data to the endpoint.

[1766] The terminal receives the schedule data and notifies the user using the smartphone's notification function.

[1767] The app uses the internal alarm function to set an alarm at the specified time.

[1768] Step 4: Check the progress of the task

[1769] At the end of each task, the device will send a task completion confirmation to the user. For example, at 6:30 AM, a confirmation message will be displayed asking, "Did you finish jogging?"

[1770] input:

[1771] Task completion progress

[1772] output:

[1773] Task completion confirmation

[1774] Specific behavior:

[1775] The device sets a system timer that triggers a notification when the task finishes.

[1776] When the task finishes, the app will display a pop-up notification prompting the user to confirm completion.

[1777] The user responds by pressing a "Done" or "Incomplete" button within the app.

[1778] Step 5: Rearrange your schedule

[1779] If the user answers "I have not completed the task," the device sends that information to the server, which then regenerates the schedule in real time.

[1780] input:

[1781] Task completion progress

[1782] output:

[1783] Regenerated Schedule

[1784] Specific behavior:

[1785] The terminal sends the user's response to the server via an HTTP POST request.

[1786] The server executes a rescheduling algorithm based on the received information.

[1787] The server sends the new schedule in JSON format to the device, and the device again sets notifications and alarms for the user.

[1788] Step 6: Use the Emotion Engine

[1789] The device collects emotional data from the user's facial expressions and tone of voice and sends it to the server, which uses the data to adjust schedules and change task priorities.

[1790] input:

[1791] Emotional data (facial expressions and tone of voice)

[1792] output:

[1793] Adjusted Schedule

[1794] Specific behavior:

[1795] The device uses a camera and microphone to collect emotional data.

[1796] The device transmits the collected data to the server in real time.

[1797] The server analyzes the data using a sentiment analysis engine and runs a schedule adjustment algorithm.

[1798] The adjusted schedule is sent to the terminal.

[1799] Step 7: Long-term schedule optimization

[1800] The server collects the user's task execution data and emotional data, analyzes it, and optimizes the schedule for the following week.

[1801] input:

[1802] Task execution data

[1803] Emotional Data

[1804] output:

[1805] Optimized long-term schedule

[1806] Specific behavior:

[1807] The server periodically aggregates all user data and stores it in a database.

[1808] The server uses machine learning algorithms to analyze the data and identify patterns and issues.

[1809] The server generates a new optimized weekly schedule based on the analysis results and sends it to the terminal.

[1810] (Application example 2)

[1811] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1812] Existing time management systems cannot consider individual emotional states when optimizing daily schedules to help users achieve their goals. As a result, emotional factors such as stress and lack of motivation often prevent users from completing their schedules. It is also difficult to readjust schedules in real time when tasks are not completed. This leaves users without the support of an efficient schedule to achieve their set goals.

[1813] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1814] In this invention, the server includes means for setting a user's goals, means for inputting an existing schedule, means for generating an optimal daily schedule based on the goals and the existing schedule, means for notifying the user of the generated schedule, means for notifying the user of task start times based on the schedule, means for sending a task completion confirmation notification at the end time of each task, means for regenerating a schedule in real time if a task is not completed, means for notifying the user of the regenerated schedule, means for recognizing the user's emotions, means for adjusting the schedule based on the emotions, and means for analyzing the user's task execution data and optimizing the long-term schedule. This makes it possible to provide an optimal schedule in real time while taking the user's emotional state into consideration.

[1815] "User" refers to an individual who uses this system and wishes to optimize their schedule to achieve a goal.

[1816] A "goal" is a specific outcome or purpose that a user wants to achieve, such as mastering a particular skill within a certain period of time or taking an action to improve their health.

[1817] "Existing schedule" refers to the user's daily plans and activities, including pre-planned times such as work time, sleep time, and meal time.

[1818] A "daily schedule" refers to a specific daily plan optimized to achieve a user's goals, including the start and end times of each task.

[1819] "Notification" refers to a means of informing the user of important information, such as by using an alarm sound or a screen display.

[1820] A "task" refers to a specific activity or work that a user performs within a daily schedule, such as jogging or studying.

[1821] "Real time" refers to processing that responds to the current progress of the process, for example, regenerating a schedule immediately.

[1822] "Emotions" refers to the user's psychological state, including mental states such as stress and motivation.

[1823] "Means for recognizing emotions" refers to devices or software that collect emotional data from users' facial expressions, tone of voice, etc.

[1824] "Means for adjusting the schedule" refers to a function that modifies or optimizes an already generated daily schedule based on recognized emotion data.

[1825] A "long-term schedule" refers to a plan spanning several weeks to several months to achieve a user's goals, which is optimized by repeating short-term schedules.

[1826] This invention is a system that optimizes daily time management and provides a feasible schedule to help users achieve their set goals. This system incorporates an emotion engine that recognizes the user's emotions and reflects them in schedule and task adjustments.

[1827] Setting goals and getting existing schedules

[1828] The user launches the application and sets a goal, such as "lose 5 kg in one month." After that, the user inputs their existing daily schedule, including work hours, sleep times, and meal times, into the app.

[1829] Schedule data transmission and analysis

[1830] Once all the data is entered, the device sends this information to a server, which then generates an optimal daily schedule based on the user's goals and existing schedule. For example, the device might create a daily schedule that includes 30 minutes of jogging every morning and 30 minutes of strength training in the evening.

[1831] Schedule notifications and alarm settings

[1832] The server sends the generated schedule to the terminal, which then notifies the user. For example, the following schedule is displayed:

[1833] 6:00 AM - Jogging (30 minutes)

[1834] 6:30 AM - Breakfast

[1835] 7:00 AM - Get ready for work

[1836] 8:00 AM - Commute

[1837] 9:00 AM - Start work

[1838] 12:00 PM - Lunch Break (Light Exercise)

[1839] 1:00 PM - Back to work

[1840] 6:00 PM - Finish work

[1841] 7:00 PM - Dinner

[1842] 8:00 PM - Strength Training (30 minutes)

[1843] 9:00 PM - Relaxation Time

[1844] 10:00 PM - Sleep

[1845] Additionally, the device will set an alarm at the start time of each task, for example, a "Start jogging" alarm at 6:00 AM.

[1846] Checking task progress and readjusting tasks

[1847] At the end of each task, the device sends the user a confirmation notification that the task has been completed. For example, at 6:30 AM, a confirmation message is displayed asking, "Have you finished jogging?" The user responds in the app whether or not the task has been completed. If the user replies, "I haven't completed the task," the device sends that information to the server. The server regenerates the schedule in real time based on this information and shifts the time of the next task.

[1848] Use of emotion engine

[1849] This system incorporates an emotion engine that recognizes the user's emotions. The device collects emotional data from the user's facial expressions, tone of voice, etc. and sends it to the server. The server uses this emotional data to adjust the schedule and change task priorities. For example, if the user is feeling stressed, the system will adjust the schedule by increasing time for relaxation and postponing difficult tasks.

[1850] Long-term schedule optimization

[1851] The server collects and analyzes the user's task execution data and emotional data. This identifies progress and problems. The server further optimizes the schedule for the following week and beyond. For example, if jogging is not performed as scheduled, the server may shorten the jogging time and suggest a different exercise. The server also takes into account the user's emotional state when adjusting the schedule.

[1852] Hardware and Software Details

[1853] Hardware: Smartphone, camera and microphone for emotion recognition

[1854] Software: Frontend (React Native), Backend Server (Django)

[1855] On the server side, processing of emotional data and task execution data, real-time schedule regeneration, and long-term data analysis are performed.

[1856] On the device side, it is responsible for providing the user interface, collecting emotional data, and setting and displaying notifications and alarms.

[1857] Examples of concrete examples and prompts

[1858] Specific examples

[1859] Goal: "Learn everyday English conversation skills in one month"

[1860] Emotional data: The user felt stressed in the afternoon, so the adjustment was made to increase relaxation time.

[1861] Example execution flow:

[1862] Users set goals and input their existing schedules.

[1863] The server generates a schedule and notifies the terminal.

[1864] The emotion engine recognizes the user's stress and sends the data to the server.

[1865] The server adds relaxation time and regenerates the schedule.

[1866] The device notifies the user of the adjusted schedule.

[1867] Prompt Sentence Examples

[1868] text

[1869] Set a goal.

[1870] For example, one specific goal is to "master everyday conversation level English in one month."

[1871] Please tell us what tasks are required to achieve your goal, including the approximate time required.

[1872] According to the present invention, the user's daily schedule is optimized according to their emotional state, so that they can effectively achieve their goals.

[1873] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1874] Step 1:

[1875] The user launches the application and sets a goal. In this step, the user enters a specific goal, such as "lose 5 kg in one month."

[1876] Input: User's goal

[1877] Output: Set goal

[1878] What happens: The user enters their goal through the user interface and the app receives that information.

[1879] Step 2:

[1880] The user inputs their existing schedule (work hours, sleep times, meal times, etc.) into the application, which uses this information to plan for achieving their goals.

[1881] Input: User's existing schedule

[1882] Output: Input schedule data

[1883] What it does: The user enters a schedule through the user interface, and the app saves that information.

[1884] Step 3:

[1885] The terminal transmits the set goal and existing schedule data to the server.

[1886] Input: Set goals and existing schedule data

[1887] Output: Data sent to the server

[1888] Specific operation: The device sends data to the server via the network.

[1889] Step 4:

[1890] The server then generates an optimal daily schedule based on the data received, which includes activities such as jogging and strength training.

[1891] Input: User goals and existing schedule data

[1892] Output: Optimized daily schedule

[1893] Specific operation: The algorithm runs on the server and calculates the optimal schedule.

[1894] Step 5:

[1895] The server transmits the generated schedule to the terminal, and the terminal notifies the user.

[1896] Input: Server-generated schedule

[1897] Output: Schedule notified to user

[1898] Specific operation: The server sends schedule data to the device, and the device displays a notification.

[1899] Step 6:

[1900] The device sets an alarm at the start time of each task and notifies the user.

[1901] Input: Generated schedule

[1902] Output: Alarm notified to user

[1903] What happens: Your device sets an alarm and displays a notification or plays an alarm sound at the specified time.

[1904] Step 7:

[1905] At the end of each task, the device sends a task completion confirmation to the user.

[1906] Input: Task end time

[1907] Output: Task completion confirmation notification

[1908] Specific behavior: The device will sound an alarm at the task completion time and display a confirmation notification.

[1909] Step 8:

[1910] The user inputs a response indicating that the task is complete. If the task is not complete, the terminal sends that information to the server.

[1911] Input: Task completion response

[1912] Output: Completion information sent to the server

[1913] Specific operation: The user enters a confirmation response, and the device sends the information to the server.

[1914] Step 9:

[1915] The server regenerates the schedule in real time based on the user's task completion information and sends it to the terminal.

[1916] Input: Incomplete task information

[1917] Output: Regenerated schedule

[1918] Specific operation: The server recalculates, generates a new schedule, and sends it to the terminal.

[1919] Step 10:

[1920] The terminal notifies the user of the regenerated schedule.

[1921] Input: Server-generated schedule

[1922] Output: Regeneration schedule notified to the user

[1923] Specific behavior: The device receives the new schedule and notifies it.

[1924] Step 11:

[1925] The device collects the user's emotional data and sends it to the server. The emotional data includes facial expression analysis and tone of voice analysis.

[1926] Input: User emotion data

[1927] Output: Emotion data sent to the server

[1928] Specific operation: The device uses the camera and microphone to collect emotion data and transmits it to the server.

[1929] Step 12:

[1930] The server adjusts the schedule based on the emotion data and generates a new schedule.

[1931] Input: Emotion data

[1932] Output: Adjusted schedule

[1933] Specific operation: The server analyzes the emotion data and adjusts the schedule based on the results.

[1934] Step 13:

[1935] To optimize long-term schedules, the server collects and analyzes users' task execution data and emotional data.

[1936] Input: User task execution data and emotion data

[1937] Output: Optimized schedule

[1938] How it works: The server accumulates data and uses algorithms to optimize the long-term schedule.

[1939] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1940] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1941] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1942] [Fourth embodiment]

[1943] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1944] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1945] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1946] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1947] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1948] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1949] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1950] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1951] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1952] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1953] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1954] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1955] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1956] The present invention is a system that optimizes daily time management and provides a feasible schedule for users to achieve their major goals. This system performs the following specific program processing.

[1957] Setting goals and getting existing schedules

[1958] The user launches the app and sets a goal, such as "lose 5 kg in one month." The user then inputs their existing daily schedule, including work hours, sleep times, and meal times, into the app.

[1959] Schedule data transmission and analysis

[1960] Once all the data is entered, the device sends this information to a server, which then generates an optimal daily schedule based on the user's goals and existing schedule. For example, the server might generate a schedule that includes 30 minutes of jogging every morning and 30 minutes of strength training every evening.

[1961] Schedule notifications and alarm settings

[1962] The server sends the generated schedule to the terminal, which then notifies the user. For example, the following schedule is displayed:

[1963] 6:00 AM - Jogging (30 minutes)

[1964] 6:30 AM - Breakfast

[1965] 7:00 AM - Get ready for work

[1966] 8:00 AM - Commute

[1967] 9:00 AM - Start work

[1968] 12:00 PM - Lunch Break (Light Exercise)

[1969] 1:00 PM - Back to work

[1970] 6:00 PM - Finish work

[1971] 7:00 PM - Dinner

[1972] 8:00 PM - Strength Training (30 minutes)

[1973] 9:00 PM - Relaxation Time

[1974] 10:00 PM - Sleep

[1975] Additionally, the device will set an alarm at the start time of each task, for example, a "Start jogging" alarm at 6:00 AM.

[1976] Checking task progress

[1977] At the end of each task, the device sends a task completion confirmation to the user. For example, at 6:30 AM, a confirmation message is displayed asking, "Did you finish jogging?" The user can then respond in the app whether or not the task is complete.

[1978] Rescheduling

[1979] If the user answers "I haven't completed the task," the device sends that information to the server, which then regenerates the schedule in real time based on this information and adjusts the time of the next task, for example, by moving the jogging time to 7:00 AM.

[1980] Long-term schedule optimization

[1981] The server collects and analyzes the user's task execution data, identifying progress and problems. The system further optimizes the schedule for the following week and beyond. For example, if the user is not continuing their jogging routine, the system will make adjustments such as shortening the jogging time and suggesting a different exercise.

[1982] Specific examples

[1983] Let's take the example of a user's goal of "learning English conversation at a daily conversation level in one month." The server generates the following schedule:

[1984] 6:00 AM - English Conversation Listening (30 minutes)

[1985] 6:30 AM - Breakfast

[1986] 7:00 AM - Get ready for work

[1987] 8:00 AM - Commute

[1988] 9:00 AM - Start work

[1989] 12:00 PM - Lunch Break (English Conversation Practice)

[1990] 1:00 PM - Back to work

[1991] 6:00 PM - Finish work

[1992] 7:00 PM - Dinner

[1993] 8:00 PM - English Speaking Practice (30 minutes)

[1994] 9:00 PM - Relaxation Time

[1995] 10:00 PM - Sleep

[1996] This schedule is sent to the device, and an alarm is set at the start time of each task. For example, an alarm for the start of English conversation listening will sound at 6:00 AM.

[1997] If the user has not completed the task, the server regenerates the schedule and sends it to the device again, notifying it of the adjusted schedule, for example, by moving the listening time to 7:00 AM.

[1998] This system allows users to strictly manage their daily schedules and ensure that they continue to make efforts toward achieving their goals.

[1999] The processing flow will be explained below.

[2000] Step 1:

[2001] The user starts the app and goes to the "Goal Setting" screen. For example, they enter a specific goal, such as "lose 5 kg in one month."

[2002] Step 2:

[2003] On the "Enter Existing Schedule" screen, users enter their current lifestyle and daily activity schedule, including work start and end times, meal times, and sleep times.

[2004] Step 3:

[2005] The terminal transmits the data of the goal and the existing schedule to the server.

[2006] Step 4:

[2007] The server analyzes the received data and generates an optimal schedule for achieving the goal, for example, a daily schedule including 30 minutes of jogging every morning and 30 minutes of strength training in the evening.

[2008] Step 5:

[2009] The server transmits the generated schedule to the terminal.

[2010] Step 6:

[2011] The terminal notifies the user of the generated schedule. For example, the following schedule is displayed:

[2012] 6:00 AM - Jogging (30 minutes)

[2013] 6:30 AM - Breakfast

[2014] 7:00 AM - Get ready for work

[2015] 8:00 AM - Commute

[2016] 9:00 AM - Start work

[2017] 12:00 PM - Lunch Break (Light Exercise)

[2018] 1:00 PM - Back to work

[2019] 6:00 PM - Finish work

[2020] 7:00 PM - Dinner

[2021] 8:00 PM - Strength Training (30 minutes)

[2022] 9:00 PM - Relaxation Time

[2023] 10:00 PM - Sleep

[2024] Step 7:

[2025] Your device will set an alarm for the start time of each task, for example, a "Start jogging" alarm at 6:00 AM.

[2026] Step 8:

[2027] The device will send a task completion confirmation at the end of each task, for example, at 6:30 AM it will display the message "Did you finish jogging?"

[2028] Step 9:

[2029] The user responds to the app by completing a task, for example, by saying "I completed my jog."

[2030] Step 10:

[2031] If the user answers "I have not completed my jog," the device sends that information to the server.

[2032] Step 11:

[2033] The server regenerates the schedule in real time based on the information received. For example, it adjusts the schedule as follows:

[2034] 6:30 AM - Jogging (30 minutes)

[2035] 7:00 AM - Breakfast

[2036] 7:30 AM - Get ready for work

[2037] 8:00 AM - Commute

[2038] 9:00 AM - Start work

[2039] 12:00 PM - Lunch Break (Light Exercise)

[2040] 1:00 PM - Back to work

[2041] 6:00 PM - Finish work

[2042] 7:00 PM - Dinner

[2043] 8:00 PM - Strength Training (30 minutes)

[2044] 9:00 PM - Relaxation Time

[2045] 10:00 PM - Sleep

[2046] Step 12:

[2047] The server transmits the regenerated schedule to the terminal.

[2048] Step 13:

[2049] The terminal notifies the user of the regenerated schedule.

[2050] Step 14:

[2051] The server collects and analyzes the user's task execution data, thereby identifying the progress and problems.

[2052] Step 15:

[2053] The server optimizes the schedule for the next week, and if jogging is not performed as scheduled, for example, adjustments are made such as shortening the jogging time and suggesting a different exercise.

[2054] Step 16:

[2055] The server transmits the optimized long-term schedule to the terminal, and the terminal notifies the user of it.

[2056] Example 1

[2057] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2058] Conventional time management systems require users to create their own schedules, which does not necessarily allow for appropriate planning for achieving goals. Furthermore, if a user is unable to complete a task, subsequent schedule adjustments must be made manually, making efficient time management difficult. Furthermore, they lack a mechanism for optimizing schedules to achieve long-term goals. There is a need for a system that can solve these problems and provide effective and flexible time management to help users achieve their goals.

[2059] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[2060] In this invention, the server includes a means for setting a user's goals, a means for inputting the user's existing schedule, and a cloud server and a means for using a generative AI model to generate an optimal daily schedule based on the goals and the existing schedule. This makes it possible to automatically generate an efficient and feasible schedule based on the goals set by the user, adjust the schedule in real time according to the daily progress, and support the achievement of long-term goals.

[2061] "User" means an individual or organization that uses the system to set goals and manage schedules.

[2062] "Means for setting goals" refers to a function or interface that allows users to input the goals they wish to achieve into the system.

[2063] "Means for inputting existing schedules" refers to a function or interface that allows users to input their daily plans and activity times into the system.

[2064] A "cloud server" is a server that stores and processes data via the Internet and is responsible for the system's main calculations and data processing.

[2065] A "generative AI model" is an algorithm or program that uses artificial intelligence technology to generate an optimal schedule based on a user's goals and existing schedule.

[2066] "Notification means" refers to a function or device that notifies users of schedules and alarms generated by the system.

[2067] "Means for notifying the start time of a task" refers to a function or device for notifying the user of the time when each task should start.

[2068] The "means for sending a confirmation notification of task completion" is a function or interface for confirming with the user whether or not the task has been completed at the end time of each task.

[2069] "Means for regenerating schedules in real time" refers to a function or system that instantly generates a new schedule based on information when a user does not complete a task.

[2070] "Means for analyzing task execution data and optimizing long-term schedules" refers to a function or program that analyzes users' daily task execution data and continuously adjusts and optimizes schedules.

[2071] The present invention is a system for managing daily tasks by providing an optimal schedule for a user to achieve their goals. Specific examples are shown below.

[2072] Setting goals and getting existing schedules

[2073] The app provides a means for users to launch the app and input the goal they want to achieve. For example, they can set a goal of "lose 5 kg in one month." Next, the app provides a means for users to input their existing schedule (e.g., work hours, sleep hours, meal times). This can be done using a device such as a smartphone or PC.

[2074] Data transmission and analysis

[2075] The device sends the user's input goals and existing schedule to the cloud server. The server then analyzes the input data using a generative AI model to generate an optimal daily schedule. At this time, the following prompt is input to the generative AI model:

[2076] "Please suggest an optimal daily schedule for losing 5 kg in one month."

[2077] Schedule notifications and alarm settings

[2078] The server sends the generated optimal schedule to the device, which then notifies the user. When the user receives the notification, the device sets an alarm at the start time of each task. For example, a notification to start jogging at 6:00 AM is displayed and an alarm sounds.

[2079] Check task progress and adjust in real time

[2080] At the end of each task, the device sends the user a task completion confirmation notification. For example, at 6:30 AM, when the jogging ends, a confirmation notification is displayed asking, "Have you finished jogging?" If the user replies that they have not completed the task, the device sends that information to the server. The server immediately recalculates the schedule, adjusts the time of the next task, and sends it again to the device. This results in an adjustment, such as changing the jogging time to 7:00 AM.

[2081] Long-term schedule optimization

[2082] The server continuously collects and analyzes the user's task execution data, identifying progress and problems and optimizing the schedule for the following week. For example, if the jogging time is too long, the server will suggest shortening the time and suggesting a different exercise.

[2083] Hardware and software examples

[2084] Hardware: smartphones, PCs, cloud servers

[2085] Software: Dedicated app, cloud-based data analysis tools, notification and alarm management system

[2086] Specific examples

[2087] If a user sets a goal of "mastering everyday conversation level English in one month," the server will generate the following schedule:

[2088] 6:00 AM - English Conversation Listening (30 minutes)

[2089] 6:30 AM - Breakfast

[2090] 7:00 AM - Get ready for work

[2091] 8:00 AM - Commute

[2092] 9:00 AM - Start work

[2093] 12:00 PM - Lunch Break (English Conversation Practice)

[2094] 1:00 PM - Back to work

[2095] 6:00 PM - Finish work

[2096] 7:00 PM - Dinner

[2097] 8:00 PM - English Speaking Practice (30 minutes)

[2098] 9:00 PM - Relaxation Time

[2099] 10:00 PM - Sleep

[2100] This schedule is sent to the device, and an alarm is set at the start time of each task. For example, an alarm for the start of English conversation listening will sound at 6:00 AM.

[2101] If the user has not completed the task, the server regenerates the schedule and sends it back to the device, notifying the user of the adjusted schedule. For example, the listening time can be moved to 7:00 AM. This ensures that the user maintains strict control over their daily schedule and continues to work toward achieving their goals.

[2102] The flow of the identification process in the first embodiment will be described with reference to FIG.

[2103] Step 1:

[2104] The user launches the app and sets a goal. As input, the app inputs the goal they want to achieve (e.g., "lose 5 kg in one month"). As output, the app generates the user's goal data, which is used in subsequent processing steps.

[2105] Step 2:

[2106] The user inputs their existing schedule into the app. As input, they input their daily schedule (work time, sleep time, meal time, etc.). As output, the user's existing schedule data is generated. This schedule data is sent to the server along with the goal data.

[2107] Step 3:

[2108] The terminal transmits the input goal data and existing schedule data to the cloud server. As input, the terminal receives the user's goal data and existing schedule data. As output, the terminal generates a transmission request to the cloud server.

[2109] Step 4:

[2110] Based on the goal data and existing schedule data received by the server, an optimal schedule is generated using a generative AI model. The goal data and existing schedule data are received as input. A prompt statement (e.g., "Please suggest an optimal daily schedule for losing 5 kg in one month") is input to the generative AI model, and optimal schedule data is generated as output.

[2111] Step 5:

[2112] The server sends the generated schedule data to the terminal. As input, it receives the generated schedule data. As output, it generates the schedule data as a transmission request to the terminal.

[2113] Step 6:

[2114] The terminal notifies the user of the received schedule data. As input, the received schedule data is processed for display. As output, the schedule is displayed to the user and sent as a notification.

[2115] Step 7:

[2116] The terminal sets an alarm at the start time of each task. As input, it obtains the start time of each task in the schedule data. As output, an alarm is set and a notification is sent to the user at the specified time.

[2117] Step 8:

[2118] At the end time of each task, the terminal sends a confirmation notification of task completion to the user. As input, the end time of each task in the schedule data is obtained. As output, a confirmation notification of task completion is sent to the user.

[2119] Step 9:

[2120] The user responds to the task completion notification. As input, the user enters whether or not the task is completed into the app. As output, task completion data is generated.

[2121] Step 10:

[2122] If the task is not completed, the terminal sends the information to the server. As input, it receives the data of the task not completed. As output, it generates the information of the task not completed as a transmission request to the server.

[2123] Step 11:

[2124] The server regenerates the schedule in real time based on the data of incomplete tasks. As input, it receives the incomplete task data and inputs a prompt sentence again based on the generative AI model (e.g., "Please adjust your schedule, such as moving your jogging time to 7:00 AM."). As output, new schedule data is generated.

[2125] Step 12:

[2126] The server transmits the regenerated schedule data to the terminal. As input, the server receives the regenerated schedule data. As output, the server generates the schedule data as a transmission request to the terminal.

[2127] Step 13:

[2128] The terminal notifies the user of the regenerated schedule data. As input, the terminal processes the regenerated schedule data for display. As output, the schedule is notified to the user again.

[2129] Step 14:

[2130] The server continuously collects and analyzes user task execution data. The collected data is used as input, and the analysis results are generated as output.

[2131] Step 15:

[2132] The server optimizes the schedule for the following week based on the analysis results. The analysis results are received as input. The optimized schedule data for the following week is generated as output.

[2133] Step 16:

[2134] The server transmits the optimized schedule data for the next week and beyond to the terminal. As input, it receives the optimized schedule data. As output, it generates the schedule data as a transmission request to the terminal.

[2135] Step 17:

[2136] The terminal notifies the user of the optimized schedule data for the next week and beyond. As input, the optimized schedule data is processed for display. As output, the schedule is notified to the user.

[2137] (Application example 1)

[2138] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2139] Current factory production management systems do not efficiently manage operation plans for work equipment and machines, resulting in reduced production efficiency and difficulty in achieving production targets. Furthermore, the operating status of production equipment and maintenance plans are not adequately considered, making unplanned shutdowns and delays more likely to occur. Furthermore, work progress is not checked in real time, often resulting in delays in readjusting the production schedule. For these reasons, there was a need for effective production schedule generation and management to improve the efficiency of the entire factory.

[2140] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[2141] In this invention, the server includes means for setting production targets to be achieved by factory work equipment and machines, means for inputting operation plans and maintenance plans for production equipment, means for generating an optimal daily schedule based on the targets and existing operation plans, means for notifying the relevant production equipment of work instructions based on the generated schedule, means for sending progress confirmation notifications at the end time of each production task, and means for regenerating the production schedule in real time if a production task is not completed. This makes it possible to maximize production efficiency and ensure the achievement of production targets.

[2142] A "means for setting user goals" is a system or device that allows a factory operator or manager to input production goals to be achieved for the factory's work equipment and machines.

[2143] The "means for inputting the user's existing schedule" refers to an interface or device for inputting the current operation plan and maintenance plan for the factory's work equipment and machines.

[2144] The "means for generating an optimal daily schedule based on the target and existing schedule" refers to an algorithm or software that calculates and generates an optimal daily schedule for the factory's work equipment and machines based on the set target and existing operation plan.

[2145] The "means for notifying the user of the generated schedule" refers to a system or device for notifying a factory operator or manager of the generated schedule.

[2146] The "means for notifying the start time of a task based on the schedule" refers to a system or device for notifying the work equipment or machines in a factory of the start time of each work task based on the schedule.

[2147] The "means for sending a confirmation notification of task completion at the end time of each task" is a system or device that sends a notification at the end time of each work task to confirm whether the task has been completed.

[2148] "Means for regenerating a schedule in real time if a task is not completed" refers to an algorithm or software that recalculates and regenerates the currently set schedule in real time based on information about incomplete tasks.

[2149] The "means for notifying users of the regenerated schedule" refers to a system or device for notifying factory operators or managers of the new regenerated schedule.

[2150] The "means for analyzing user task execution data and optimizing long-term schedules" refers to an analytical algorithm or software for optimizing factory work schedules over the long term based on collected task execution data.

[2151] The "means for setting production targets to be achieved by work equipment and machines in a factory" refers to a system or device for inputting and setting production targets set for work equipment and machines in a factory.

[2152] The "means for inputting the operation plan and maintenance plan of the production equipment" refers to an interface or device for inputting the operation schedule and maintenance schedule of the production equipment.

[2153] The "means for generating an optimal daily schedule based on the above-mentioned targets and existing operation plans" refers to an algorithm or software that calculates and generates an optimal daily schedule for the factory's work equipment and machines based on the set production targets and existing operation plans.

[2154] The "means for notifying the relevant production equipment of work instructions based on the generated schedule" refers to a system or device for notifying the relevant production equipment or machine of each work instruction based on the generated schedule.

[2155] The "means for sending a progress confirmation notification at the end time of each production task" refers to a system or device that sends a notification to confirm the progress of each production task at the end time of that task.

[2156] The "means for regenerating a production schedule in real time when a production task is not completed" refers to an algorithm or software that, when a production task is not completed, recalculates and regenerates the currently set production schedule in real time based on that information.

[2157] This invention is a system that optimizes the operation schedules of factory work equipment and machines and supports the achievement of production targets. Specifically, this describes a system in which factory operators input targets and existing operation plans, a server generates an optimal schedule based on that data, and monitors and adjusts the progress of each task in real time.

[2158] First, a factory operator accesses the system using a control terminal (e.g., a PC or tablet) and sets a production target. This target is specifically defined, for example, to assemble 1,000 products in one day. Next, the current operation plan and maintenance plan are entered into the system. This operation plan includes work time slots and existing maintenance times.

[2159] The server generates an optimal daily schedule based on the input goals and existing schedules. It is desirable to use AI models or machine learning algorithms for this calculation and generation. The generated schedule is notified to the work equipment via the control terminal. Using available cloud database services (e.g., AWS RDS) allows for efficient data management and storage.

[2160] When the start time for each work task arrives, the server notifies the relevant work equipment of the work instructions via the control terminal. The control terminal displays an alarm, such as "Assembly begins at 9:00." The work equipment executes the task, and when it is time to finish, the server checks the progress. This progress check is performed by the control terminal displaying a confirmation message to the operator. For example, a notification may be displayed asking, "Is the 9:00 assembly completed?"

[2161] If a work task is not completed, the operator enters that information into the system. The server regenerates the schedule in real time based on this information and notifies the work equipment of the re-adjusted schedule. Tasks are then rearranged according to this re-generated schedule, optimizing the work plan for the next day.

[2162] In the long term, the server will periodically analyze the task execution data collected and further optimize the schedule for the following week, enabling adjustments to be made to improve the factory's overall production efficiency.

[2163] For example, if a factory's daily production target is 1,000 products, a schedule will be provided that allows the robots to efficiently carry out the work within the specified working hours. This schedule will be strictly managed, and production progress will be checked on an ongoing basis, ensuring that efforts to achieve the target are continued.

[2164] An example of a prompt sentence might be:

[2165] "Generate an optimal task list and schedule for the factory robots between 9:00-12:00 and 13:00-18:00 so that they can efficiently assemble the daily target of 1,000 products."

[2166] In this way, it is a feature of the present invention that the factory's production efficiency is maximized and targets are achieved.

[2167] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2168] Step 1:

[2169] The user sets production targets for the factory's work equipment and machines using a control terminal. At this time, the user inputs the target value (e.g., assemble 1,000 products in one day). Data based on this is sent to the server.

[2170] Step 2:

[2171] Users use a control terminal to input existing operation and maintenance plans into the system. This data is also sent to the server. The input data includes work time slots and maintenance times.

[2172] Step 3:

[2173] The server generates an optimal daily schedule based on the received production targets, operation plans, and maintenance plans. It uses generative AI models and machine learning algorithms to calculate the optimal start and end times for each work task. This generated schedule is then sent from the server to the device.

[2174] Step 4:

[2175] The terminal notifies each piece of work equipment in the factory of the schedule it receives from the server. This notification includes the start and end times of each work task. Each piece of equipment begins operating according to the notified schedule.

[2176] Step 5:

[2177] When the start time for each work task arrives, the terminal sends a start command to the corresponding work equipment. For example, a notification such as "Assembly begins at 9:00" is displayed, and the equipment begins operation.

[2178] Step 6:

[2179] When the end time of each work task arrives, the terminal sends a task completion confirmation to the user. The user checks whether the task is completed and reports the result on the terminal.

[2180] Step 7:

[2181] If a task is not completed, the device sends the information to the server, which regenerates the schedule in real time based on the incomplete information, and the new schedule is sent to the device again.

[2182] Step 8:

[2183] The terminal receives the regenerated schedule and notifies each piece of work equipment of the new instructions, including the adjusted start and end times of each work task.

[2184] Step 9:

[2185] The server collects all task execution data and analyzes it for long-term schedule optimization. It uses machine learning algorithms to further optimize the schedule for the following week and beyond, and sends the results to the device.

[2186] This maximizes factory production efficiency and ensures production targets are met.

[2187] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[2188] This invention is a system that optimizes daily time management and provides a feasible schedule for users to achieve their big goals. This system incorporates an emotion engine that recognizes the user's emotions and reflects them in the adjustment of schedules and tasks.

[2189] Setting goals and getting existing schedules

[2190] The user launches the app and sets a goal, such as "lose 5 kg in one month." The user then inputs their existing daily schedule, including work hours, sleep times, and meal times, into the app.

[2191] Schedule data transmission and analysis

[2192] Once all the data is entered, the device sends this information to a server, which then generates an optimal daily schedule based on the user's goals and existing schedule. For example, the device might create a daily schedule that includes 30 minutes of jogging every morning and 30 minutes of strength training in the evening.

[2193] Schedule notifications and alarm settings

[2194] The server sends the generated schedule to the terminal, which then notifies the user. For example, the following schedule is displayed:

[2195] 6:00 AM - Jogging (30 minutes)

[2196] 6:30 AM - Breakfast

[2197] 7:00 AM - Get ready for work

[2198] 8:00 AM - Commute

[2199] 9:00 AM - Start work

[2200] 12:00 PM - Lunch Break (Light Exercise)

[2201] 1:00 PM - Back to work

[2202] 6:00 PM - Finish work

[2203] 7:00 PM - Dinner

[2204] 8:00 PM - Strength Training (30 minutes)

[2205] 9:00 PM - Relaxation Time

[2206] 10:00 PM - Sleep

[2207] Additionally, the device will set an alarm at the start time of each task, for example, a "Start jogging" alarm at 6:00 AM.

[2208] Checking task progress

[2209] At the end of each task, the device sends a task completion confirmation to the user. For example, at 6:30 AM, a confirmation message is displayed asking, "Did you finish jogging?" The user can then respond in the app whether or not the task is complete.

[2210] Rescheduling

[2211] If the user answers "I haven't completed the task," the device sends that information to the server, which then regenerates the schedule in real time based on this information and adjusts the schedule accordingly, for example, by moving the jogging time to 7:00 AM.

[2212] Use of emotion engine

[2213] This system incorporates an emotion engine that recognizes the user's emotions. The device collects emotional data from the user's facial expressions, tone of voice, etc. and sends it to the server. The server uses this emotional data to adjust the schedule and change task priorities. For example, if the user is feeling stressed, the system will adjust the schedule by increasing time for relaxation and postponing hard tasks.

[2214] Long-term schedule optimization

[2215] The server collects and analyzes the user's task execution data and emotional data. This identifies progress and problems. The system further optimizes the schedule for the following week and beyond. For example, if jogging is not performed as planned, the system will shorten the jogging time and suggest a different exercise. The system also takes into account the user's emotional state when adjusting the schedule.

[2216] Specific examples

[2217] Let's take the example of a user's goal of "learning English conversation at a daily conversation level in one month." The server generates the following schedule:

[2218] 6:00 AM - English Conversation Listening (30 minutes)

[2219] 6:30 AM - Breakfast

[2220] 7:00 AM - Get ready for work

[2221] 8:00 AM - Commute

[2222] 9:00 AM - Start work

[2223] 12:00 PM - Lunch Break (English Conversation Practice)

[2224] 1:00 PM - Back to work

[2225] 6:00 PM - Finish work

[2226] 7:00 PM - Dinner

[2227] 8:00 PM - English Speaking Practice (30 minutes)

[2228] 9:00 PM - Relaxation Time

[2229] 10:00 PM - Sleep

[2230] This schedule is sent to the device, and an alarm is set at the start time of each task. For example, an alarm for the start of English conversation listening will sound at 6:00 AM.

[2231] If the user has not completed the task, the server regenerates the schedule and sends it to the device again, notifying it of the adjusted schedule, for example, by moving the listening time to 7:00 AM.

[2232] The emotion engine also recognizes the user's emotions, and if the user is feeling stressed, for example, it will adjust the system to increase relaxation time and postpone burdensome tasks.

[2233] This system allows users to strictly manage their daily schedules and ensure that they continue to make efforts toward achieving their goals.

[2234] The processing flow will be explained below.

[2235] Step 1:

[2236] The user starts the app and goes to the "Goal Setting" screen. For example, they enter a specific goal, such as "lose 5 kg in one month."

[2237] Step 2:

[2238] On the "Enter Existing Schedule" screen, users enter their current lifestyle and daily activity schedule, including work start and end times, meal times, and sleep times.

[2239] Step 3:

[2240] The terminal transmits the data of the goal and the existing schedule to the server.

[2241] Step 4:

[2242] The server analyzes the received data and generates an optimal schedule for achieving the goal, for example, a daily schedule including 30 minutes of jogging every morning and 30 minutes of strength training in the evening.

[2243] Step 5:

[2244] The server transmits the generated schedule to the terminal.

[2245] Step 6:

[2246] The terminal notifies the user of the generated schedule. For example, the following schedule is displayed:

[2247] 6:00 AM - Jogging (30 minutes)

[2248] 6:30 AM - Breakfast

[2249] 7:00 AM - Get ready for work

[2250] 8:00 AM - Commute

[2251] 9:00 AM - Start work

[2252] 12:00 PM - Lunch Break (Light Exercise)

[2253] 1:00 PM - Back to work

[2254] 6:00 PM - Finish work

[2255] 7:00 PM - Dinner

[2256] 8:00 PM - Strength Training (30 minutes)

[2257] 9:00 PM - Relaxation Time

[2258] 10:00 PM - Sleep

[2259] Step 7:

[2260] Your device will set an alarm for the start time of each task, for example, a "Start jogging" alarm at 6:00 AM.

[2261] Step 8:

[2262] The device will send a task completion confirmation at the end of each task, for example, at 6:30 AM it will display the message "Did you finish jogging?"

[2263] Step 9:

[2264] The user responds to the app by completing a task, for example, by saying "I completed my jog."

[2265] Step 10:

[2266] If the user answers "I have not completed my jog," the device sends that information to the server.

[2267] Step 11:

[2268] The server regenerates the schedule in real time based on the information received. For example, it adjusts the schedule as follows:

[2269] 6:30 AM - Jogging (30 minutes)

[2270] 7:00 AM - Breakfast

[2271] 7:30 AM - Get ready for work

[2272] 8:00 AM - Commute

[2273] 9:00 AM - Start work

[2274] 12:00 PM - Lunch Break (Light Exercise)

[2275] 1:00 PM - Back to work

[2276] 6:00 PM - Finish work

[2277] 7:00 PM - Dinner

[2278] 8:00 PM - Strength Training (30 minutes)

[2279] 9:00 PM - Relaxation Time

[2280] 10:00 PM - Sleep

[2281] Step 12:

[2282] The server transmits the regenerated schedule to the terminal.

[2283] Step 13:

[2284] The terminal notifies the user of the regenerated schedule.

[2285] Step 14:

[2286] Furthermore, the device is equipped with an emotion engine that collects emotional data from the user's facial expressions and tone of voice, and periodically transmits this data to a server.

[2287] Step 15:

[2288] The server analyzes the emotional data to understand the user's stress level and motivation. For example, if the user feels tired, it will suggest taking more rest time.

[2289] Step 16:

[2290] The server adjusts the schedule based on the emotional data. For example, if the user is feeling stressed, the server will increase the amount of time for relaxation and postpone hard tasks.

[2291] Step 17:

[2292] The server transmits the schedule adjusted by the emotion engine to the terminal.

[2293] Step 18:

[2294] The terminal notifies the user of the adjusted schedule.

[2295] Step 19:

[2296] The server collects and analyzes the user's task execution data and emotional data, thereby identifying achievement status and problems.

[2297] Step 20:

[2298] The server optimizes the schedule for the next week, and if jogging is not performed as planned, for example, it will shorten the jogging time and suggest a different exercise. It also takes into account schedule adjustments based on the user's emotions.

[2299] Step 21:

[2300] The server transmits the optimized long-term schedule to the terminal, and the terminal notifies the user of it.

[2301] Specific examples

[2302] Let's take the example of a user's goal of "learning English conversation at a daily conversation level in one month." The server generates the following schedule:

[2303] 6:00 AM - English Conversation Listening (30 minutes)

[2304] 6:30 AM - Breakfast

[2305] 7:00 AM - Get ready for work

[2306] 8:00 AM - Commute

[2307] 9:00 AM - Start work

[2308] 12:00 PM - Lunch Break (English Conversation Practice)

[2309] 1:00 PM - Back to work

[2310] 6:00 PM - Finish work

[2311] 7:00 PM - Dinner

[2312] 8:00 PM - English Speaking Practice (30 minutes)

[2313] 9:00 PM - Relaxation Time

[2314] 10:00 PM - Sleep

[2315] This schedule is sent to the device, and an alarm is set at the start time of each task. For example, an alarm for the start of English conversation listening will sound at 6:00 AM.

[2316] If the user has not completed the task, the server regenerates the schedule and sends it to the device again, notifying it of the adjusted schedule, for example, by moving the listening time to 7:00 AM.

[2317] The emotion engine also recognizes the user's emotions, and if the user is feeling stressed, for example, it will adjust the system to increase relaxation time and postpone burdensome tasks.

[2318] This system allows users to strictly manage their daily schedules and ensure that they continue to make efforts toward achieving their goals.

[2319] Example 2

[2320] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2321] In modern society, time management is essential for achieving individual goals, but maintaining an optimal schedule in a busy daily life is difficult. Furthermore, few existing systems adjust schedules taking into account the user's emotional state, which can increase the user's mental burden. This can lead to a decrease in motivation to achieve goals and make it difficult to achieve results.

[2322] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for setting a user's goal, means for inputting the user's existing schedule, means for generating an optimal daily schedule based on the goal and the existing schedule, means for notifying the user of the generated schedule, means for notifying the user of task start times based on the schedule, means for sending a task completion confirmation notification at the end time of each task, means for regenerating a schedule in real time if a task is not completed, means for notifying the user of the regenerated schedule, means for collecting the user's task execution data and emotion data, means for adjusting the schedule based on the emotion data, and means for analyzing the task execution data and emotion data and optimizing the long-term schedule. This increases the user's goal achievement rate and enables schedule management with less mental burden on the user.

[2323] The "means for setting user goals" provides an interface and functionality for users to input specific goals they wish to achieve.

[2324] The "means for inputting the user's existing schedule" provides an interface and functionality for the user to input and save the current daily activity schedule.

[2325] The "means for generating an optimal daily schedule based on the goals and existing schedule" refers to a means for creating an optimal daily activity plan using algorithms and analytical techniques, using the collected goal data and existing schedule data.

[2326] The "means for notifying the user of the generated schedule" provides a function for displaying or notifying the user of the generated schedule on the user's terminal.

[2327] The "means for notifying the start time of a task based on the schedule" provides an alarm or notification function for notifying the user of the start time of each task according to the set schedule.

[2328] The "means for sending a confirmation notification of task completion at the end time of each task" provides a function for sending a notification to the user at the end time of the task to confirm the completion status of the task.

[2329] "Means for regenerating a schedule in real time if a task is not completed" provides a function to instantly recalculate and create a new schedule if it is determined that the user has not completed a task.

[2330] The "means for notifying the user of the regenerated schedule" provides a function for displaying or notifying the user of the regenerated schedule on the user's terminal.

[2331] "Means for collecting user task execution data and emotional data" refers to providing a function for collecting which tasks a user has performed and the user's emotional state (e.g., facial expressions and tone of voice).

[2332] The "means for adjusting the schedule based on the emotional data" provides a function for analyzing the collected emotional data and changing the tasks and time allocation of the schedule according to the user's mental state.

[2333] The "means for analyzing the task execution data and emotion data and optimizing the long-term schedule" provides a function for analyzing the collected data and optimizing future schedules to help users achieve their long-term goals.

[2334] This invention provides a system that optimizes daily time management and provides a feasible schedule for users to achieve their major goals. The system incorporates an emotion engine that recognizes the user's emotions and reflects them in schedule and task adjustments.

[2335] Hardware and software used

[2336] This system is implemented using the following hardware and software:

[2337] Device: Personal devices such as smartphones and tablets

[2338] Server: Cloud server or dedicated server

[2339] Database: RDBMS such as MySQL or PostgreSQL

[2340] Emotion recognition engine: Sentiment analysis tools such as IBM Watson and Azure Emotion API

[2341] Programming language: Python, JavaScript, etc.

[2342] Communication protocol: HTTP / HTTPS

[2343] System Embodiments

[2344] 1. How users set goals

[2345] The user launches the application and inputs a goal, for example, a specific goal such as "lose 5 kg in one month." This goal is entered through the application's interface (e.g., a text box).

[2346] 2. Enter an existing schedule

[2347] Users enter their daily activities (work time, sleep time, meal time, etc.) into the application, and this data is entered and stored by the application on their smartphone or tablet.

[2348] 3. Data transmission and schedule generation

[2349] The device collects your goals and existing schedule and sends it to a server, which uses an algorithm to generate an optimal daily schedule. For example, it could create a schedule that includes 30 minutes of jogging every morning and 30 minutes of strength training in the evening.

[2350] 4. Schedule notifications and alarm settings

[2351] The server sends the generated schedule back to the device, which then notifies the user of the schedule. An alarm is also set at the start time of each task. For example, an alarm for "start jogging" can be set to ring at 6:00 AM.

[2352] 5. Check the progress of your tasks

[2353] At the end of each task, the device sends the user a confirmation that the task is complete. For example, at 6:30 AM, the device displays the message "Did you finish jogging?" The user can respond in the app.

[2354] 6. Rearrange your schedule

[2355] If the user indicates that the task is not complete, the device sends that information to the server, which then regenerates the schedule and adjusts the time of the next task, for example, moving the jogging time to 7:00 AM.

[2356] 7. Use of Emotion Engines

[2357] The device collects emotional data from the user's facial expressions and tone of voice and sends it to a server. The server uses this data to adjust schedules and change task priorities. For example, if the user is feeling stressed, the device can increase relaxation time and postpone hard tasks.

[2358] 8. Long-term schedule optimization

[2359] The server collects and analyzes the user's task execution and emotional data to optimize the schedule for the following week. For example, if the user does not go jogging as planned, the server will adjust the schedule by shortening the jogging time and suggesting a different exercise.

[2360] Specific examples

[2361] If a user sets a goal of "learning everyday conversational English in one month," the following schedule will be generated:

[2362] 6:00 AM - English Conversation Listening (30 minutes)

[2363] 6:30 AM - Breakfast

[2364] 7:00 AM - Get ready for work

[2365] 8:00 AM - Commute

[2366] 9:00 AM - Start work

[2367] 12:00 PM - Lunch Break (English Conversation Practice)

[2368] 1:00 PM - Back to work

[2369] 6:00 PM - Finish work

[2370] 7:00 PM - Dinner

[2371] 8:00 PM - English Speaking Practice (30 minutes)

[2372] 9:00 PM - Relaxation Time

[2373] 10:00 PM - Sleep

[2374] This schedule is notified to the device, and an alarm is set to ring at 6:00 AM, for example, to "Start English Conversation Listening." If a task is not completed, the server regenerates and resends the schedule. Furthermore, the system recognizes the user's emotions and adjusts the schedule, such as increasing relaxation time, if the user is feeling stressed.

[2375] This creates a system that allows users to strictly manage their daily schedules and ensures that they continue to make efforts toward achieving their goals.

[2376] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2377] Step 1: Set goals and schedule

[2378] The user launches the app and inputs their goal. Specifically, they use the app's interface to set a goal such as "lose 5 kg in one month" or "learn conversational English in one month." Next, they input their existing schedule (work hours, sleep times, meal times, etc.).

[2379] input:

[2380] the goal

[2381] Existing Schedule

[2382] output:

[2383] User data (goal and schedule information)

[2384] Specific behavior:

[2385] The user enters their goal in the text box on the app's "Goal Setting" screen and presses the "Save" button.

[2386] The user inputs an existing schedule on the "Schedule Setting" screen and presses the "Save" button.

[2387] Step 2: Send data and generate schedule

[2388] The device sends user data to a server, which then uses a built-in algorithm to generate an optimal daily schedule, such as a 30-minute morning jog and 30 minutes of strength training in the evening.

[2389] input:

[2390] User data (goal and schedule information)

[2391] output:

[2392] Generated daily schedule

[2393] Specific behavior:

[2394] The terminal sends an HTTP POST request to the server, sending the goal and existing schedule to the server.

[2395] The server receives the data and runs a scheduling algorithm to generate an optimal schedule.

[2396] The server returns the generated schedule to the terminal in JSON format.

[2397] Step 3: Schedule notifications and alarm settings

[2398] The server sends the generated schedule to the terminal, which receives it, notifies the user, and sets an alarm at the start time of each task.

[2399] input:

[2400] Generated daily schedule

[2401] output:

[2402] Schedule Notifications

[2403] Set alarms for the start time of each task

[2404] Specific behavior:

[2405] The server sends the schedule data to the endpoint.

[2406] The terminal receives the schedule data and notifies the user using the smartphone's notification function.

[2407] The app uses the internal alarm function to set an alarm at the specified time.

[2408] Step 4: Check the progress of the task

[2409] At the end of each task, the device will send a task completion confirmation to the user. For example, at 6:30 AM, a confirmation message will be displayed asking, "Did you finish jogging?"

[2410] input:

[2411] Task completion progress

[2412] output:

[2413] Task completion confirmation

[2414] Specific behavior:

[2415] The device sets a system timer that triggers a notification when the task finishes.

[2416] When the task finishes, the app will display a pop-up notification prompting the user to confirm completion.

[2417] The user responds by pressing a "Done" or "Incomplete" button within the app.

[2418] Step 5: Rearrange your schedule

[2419] If the user answers "I have not completed the task," the device sends that information to the server, which then regenerates the schedule in real time.

[2420] input:

[2421] Task completion progress

[2422] output:

[2423] Regenerated Schedule

[2424] Specific behavior:

[2425] The terminal sends the user's response to the server via an HTTP POST request.

[2426] The server executes a rescheduling algorithm based on the received information.

[2427] The server sends the new schedule in JSON format to the device, and the device again sets notifications and alarms for the user.

[2428] Step 6: Use the Emotion Engine

[2429] The device collects emotional data from the user's facial expressions and tone of voice and sends it to the server, which uses the data to adjust schedules and change task priorities.

[2430] input:

[2431] Emotional data (facial expressions and tone of voice)

[2432] output:

[2433] Adjusted Schedule

[2434] Specific behavior:

[2435] The device uses a camera and microphone to collect emotional data.

[2436] The device transmits the collected data to the server in real time.

[2437] The server analyzes the data using a sentiment analysis engine and runs a schedule adjustment algorithm.

[2438] The adjusted schedule is sent to the terminal.

[2439] Step 7: Long-term schedule optimization

[2440] The server collects the user's task execution data and emotional data, analyzes it, and optimizes the schedule for the following week.

[2441] input:

[2442] Task execution data

[2443] Emotional Data

[2444] output:

[2445] Optimized long-term schedule

[2446] Specific behavior:

[2447] The server periodically aggregates all user data and stores it in a database.

[2448] The server uses machine learning algorithms to analyze the data and identify patterns and issues.

[2449] The server generates a new optimized weekly schedule based on the analysis results and sends it to the terminal.

[2450] (Application example 2)

[2451] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2452] Existing time management systems cannot consider individual emotional states when optimizing daily schedules to help users achieve their goals. As a result, emotional factors such as stress and lack of motivation often prevent users from completing their schedules. It is also difficult to readjust schedules in real time when tasks are not completed. This leaves users without the support of an efficient schedule to achieve their set goals.

[2453] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[2454] In this invention, the server includes means for setting a user's goals, means for inputting an existing schedule, means for generating an optimal daily schedule based on the goals and the existing schedule, means for notifying the user of the generated schedule, means for notifying the user of task start times based on the schedule, means for sending a task completion confirmation notification at the end time of each task, means for regenerating a schedule in real time if a task is not completed, means for notifying the user of the regenerated schedule, means for recognizing the user's emotions, means for adjusting the schedule based on the emotions, and means for analyzing the user's task execution data and optimizing the long-term schedule. This makes it possible to provide an optimal schedule in real time while taking the user's emotional state into consideration.

[2455] "User" refers to an individual who uses this system and wishes to optimize their schedule to achieve a goal.

[2456] A "goal" is a specific outcome or purpose that a user wants to achieve, such as mastering a particular skill within a certain period of time or taking an action to improve their health.

[2457] "Existing schedule" refers to the user's daily plans and activities, including pre-planned times such as work time, sleep time, and meal time.

[2458] A "daily schedule" refers to a specific daily plan optimized to achieve a user's goals, including the start and end times of each task.

[2459] "Notification" refers to a means of informing the user of important information, such as by using an alarm sound or a screen display.

[2460] A "task" refers to a specific activity or work that a user performs within a daily schedule, such as jogging or studying.

[2461] "Real time" refers to processing that responds to the current progress of the process, for example, regenerating a schedule immediately.

[2462] "Emotions" refers to the user's psychological state, including mental states such as stress and motivation.

[2463] "Means for recognizing emotions" refers to devices or software that collect emotional data from users' facial expressions, tone of voice, etc.

[2464] "Means for adjusting the schedule" refers to a function that modifies or optimizes an already generated daily schedule based on recognized emotion data.

[2465] A "long-term schedule" refers to a plan spanning several weeks to several months to achieve a user's goals, which is optimized by repeating short-term schedules.

[2466] This invention is a system that optimizes daily time management and provides a feasible schedule to help users achieve their set goals. This system incorporates an emotion engine that recognizes the user's emotions and reflects them in schedule and task adjustments.

[2467] Setting goals and getting existing schedules

[2468] The user launches the application and sets a goal, such as "lose 5 kg in one month." After that, the user inputs their existing daily schedule, including work hours, sleep times, and meal times, into the app.

[2469] Schedule data transmission and analysis

[2470] Once all the data is entered, the device sends this information to a server, which then generates an optimal daily schedule based on the user's goals and existing schedule. For example, the device might create a daily schedule that includes 30 minutes of jogging every morning and 30 minutes of strength training in the evening.

[2471] Schedule notifications and alarm settings

[2472] The server sends the generated schedule to the terminal, which then notifies the user. For example, the following schedule is displayed:

[2473] 6:00 AM - Jogging (30 minutes)

[2474] 6:30 AM - Breakfast

[2475] 7:00 AM - Get ready for work

[2476] 8:00 AM - Commute

[2477] 9:00 AM - Start work

[2478] 12:00 PM - Lunch Break (Light Exercise)

[2479] 1:00 PM - Back to work

[2480] 6:00 PM - Finish work

[2481] 7:00 PM - Dinner

[2482] 8:00 PM - Strength Training (30 minutes)

[2483] 9:00 PM - Relaxation Time

[2484] 10:00 PM - Sleep

[2485] Additionally, the device will set an alarm at the start time of each task, for example, a "Start jogging" alarm at 6:00 AM.

[2486] Checking task progress and readjusting tasks

[2487] At the end of each task, the device sends the user a confirmation notification that the task has been completed. For example, at 6:30 AM, a confirmation message is displayed asking, "Have you finished jogging?" The user responds in the app whether or not the task has been completed. If the user replies, "I haven't completed the task," the device sends that information to the server. The server regenerates the schedule in real time based on this information and shifts the time of the next task.

[2488] Use of emotion engine

[2489] This system incorporates an emotion engine that recognizes the user's emotions. The device collects emotional data from the user's facial expressions, tone of voice, etc. and sends it to the server. The server uses this emotional data to adjust the schedule and change task priorities. For example, if the user is feeling stressed, the system will adjust the schedule by increasing time for relaxation and postponing difficult tasks.

[2490] Long-term schedule optimization

[2491] The server collects and analyzes the user's task execution data and emotional data. This identifies progress and problems. The server further optimizes the schedule for the following week and beyond. For example, if jogging is not performed as scheduled, the server may shorten the jogging time and suggest a different exercise. The server also takes into account the user's emotional state when adjusting the schedule.

[2492] Hardware and Software Details

[2493] Hardware: Smartphone, camera and microphone for emotion recognition

[2494] Software: Frontend (React Native), Backend Server (Django)

[2495] On the server side, processing of emotional data and task execution data, real-time schedule regeneration, and long-term data analysis are performed.

[2496] On the device side, it is responsible for providing the user interface, collecting emotional data, and setting and displaying notifications and alarms.

[2497] Examples of concrete examples and prompts

[2498] Specific examples ...

Claims

1. a means of setting user goals; a means for inputting the user's existing schedule; means for generating an optimal daily schedule based on the goals and an existing schedule; means for notifying a user of the generated schedule; means for notifying a start time of a task based on the schedule; means for sending a task completion confirmation at the end time of each task; A means to regenerate the schedule in real time if a task is not completed; means for notifying a user of the regenerated schedule; A means for analyzing user task execution data and optimizing long-term schedules; A system including:

2. means for receiving a response confirming completion of the user's task; means for regenerating a schedule in real time based on said responses; The system of claim 1 .

3. Includes a means to analyze users' task execution data and optimize their schedule for the next week. The system of claim 1 .

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