System

Abstract

A system is provided.SOLUTION: A system comprising: means for receiving task information from a user; means for generating a task based on the task information; means for storing the generated task as a schedule; means for generating a reminder based on the schedule; and means for notifying the user of the generated reminder.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] In today's busy lives, users are required to effectively manage numerous tasks and schedules. However, in conventional schedule management systems, creating reminders and adding tasks is often done manually, placing a heavy burden on users. This makes it difficult for users to efficiently manage tasks and remember to complete them. [Means for solving the problem]

[0005] The present invention solves the above-mentioned problems by providing a system that includes a means for receiving task information from a user, generating a task based on the task information, saving the generated task as a schedule, and a means for generating a reminder based on the schedule and notifying the user of the generated reminder. Furthermore, the system includes a means for setting the date of the generated reminder to a random date 1 to 3 days before the task's due date, allowing the user to efficiently manage tasks. Furthermore, the system includes a means for acquiring and displaying the user's entire schedule, allowing the user to easily check their own schedule.

[0006] "User" refers to a user of the system.

[0007] "Task information" refers to information that includes details such as the name of the task, deadline, and content.

[0008] A "task" refers to a specific task or activity designated for a user to perform.

[0009] A "schedule" refers to a table that manages a user's multiple tasks and their deadlines in chronological order.

[0010] A "reminder" is a message or alert that notifies a user that a particular task is approaching its deadline.

[0011] "System" refers to a set of devices and software configurations that have multiple functions for task management and reminder generation.

[0012] "Means" refers to a technical method or device for achieving a specific function.

[0013] "Generate" refers to creating new information or data based on specific information or data.

[0014] "Storing" refers to recording generated data and information within a system and keeping it in a state where it can be accessed later.

[0015] "Notify" refers to the action of informing a user of specific information.

[0016] "Display" refers to providing data or information visually to a user. [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 relates to a system for efficiently managing user tasks and generating reminders. The system of the present invention has the functions of generating tasks based on user input, saving them as schedules, and generating and notifying reminders when task deadlines approach.

[0039] Adding a task

[0040] When a user wants to add a new task, they enter the task name and deadline. The device receives this and sends the task information to the server. The server creates a new task based on the received information and adds it to the user's schedule list. For example, if a user sets a task called "Meeting" for October 15, 2023, the system will create a task based on this information and save it in the schedule. If the task is added successfully, the server will return a confirmation message to the device.

[0041] Generate reminders

[0042] When a user requests to create a reminder, the device sends a reminder creation request to the server. The server retrieves all tasks from the user's schedule and creates a reminder for each task. The reminder date is set to a random date 1 to 3 days before the task's due date. For example, a "Meeting" reminder is set for October 12, 2023. The generated reminder is notified to the user and displayed on the device.

[0043] Get schedule

[0044] When a user wants to check their entire schedule, the device sends a schedule retrieval request to the server. The server retrieves all of the user's tasks and returns them to the device as a list. The device displays this list to the user, allowing the user to easily check the schedule. For example, if the user's schedule includes a "meeting" and a "presentation," the details will be displayed on the device.

[0045] In this way, the system of the present invention supports users in efficiently managing tasks and ensuring that deadlines are not forgotten. Specifically, it automates the processes of task creation, saving, reminder creation and notification, and schedule acquisition and display, thereby reducing the burden on users.

[0046] The processing flow will be explained below.

[0047] Adding a task

[0048] Step 1:

[0049] The user inputs the task name and deadline date into the terminal.

[0050] Step 2:

[0051] The terminal receives input from the user and requests the add_task method from the server.

[0052] Step 3:

[0053] The server creates a new task based on the received task name and due date. Specifically, it constructs the task information in a dictionary format (e.g., {"task_name": "Meeting", "due_date": datetime(2023, 10, 15)}).

[0054] Step 4:

[0055] The server adds the generated task information to the user's schedule list.

[0056] Step 5:

[0057] The server will send a confirmation message back to the terminal indicating that the task was added successfully.

[0058] Step 6:

[0059] The terminal displays a confirmation message to the user.

[0060] Generate reminders

[0061] Step 1:

[0062] The user requests that a reminder be created.

[0063] Step 2:

[0064] The device calls the generate_reminders method to send a reminder generation request to the server.

[0065] Step 3:

[0066] The server retrieves all tasks from the user's schedule.

[0067] Step 4:

[0068] For each task, the server randomly selects a date between 1 and 3 days before the due date and generates a reminder. For example, if the due date for a "Meeting" is October 15, 2023, the server sets the reminder for October 12, 13, or 14, 2023.

[0069] Step 5:

[0070] The server stores the generated reminders in a list, keeping only tasks beyond the current date.

[0071] Step 6:

[0072] The server returns the reminder list to the terminal.

[0073] Step 7:

[0074] The terminal displays the received reminder list to the user.

[0075] Get schedule

[0076] Step 1:

[0077] The user requests confirmation of the entire schedule.

[0078] Step 2:

[0079] The terminal calls the get_schedule method to send a schedule acquisition request to the server.

[0080] Step 3:

[0081] The server gets all the user's tasks from the schedule list.

[0082] Step 4:

[0083] The server returns the acquired schedule list to the terminal.

[0084] Step 5:

[0085] The terminal displays the received schedule list to the user. For example, if the schedule includes "meeting" and "presentation," the details of these are displayed.

[0086] Example 1

[0087] 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."

[0088] Conventional task management systems have the drawback of requiring users to manually add tasks and set reminders, and the fixed reminder dates limit flexible notification options. Furthermore, they lack the functionality to easily check the entire schedule, making it difficult for users to efficiently manage tasks.

[0089] 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.

[0090] In this invention, the server includes a means for receiving task information from a user, a means for generating a task based on the task information, a means for storing the generated task in a database, a means for generating a message confirming that the task has been successfully added and notifying the user, a means for generating a reminder based on the schedule, and a means for notifying the user of the generated reminder. This allows the user to efficiently manage tasks and receive flexible reminder notifications. It also allows the user to easily check the entire schedule in list format.

[0091] "User" refers to an individual or organization that uses the system.

[0092] "Task information" refers to information such as task name and deadline date that a user enters into the system.

[0093] A "task" refers to a schedule or work item that a user registers in the system.

[0094] "Database" refers to the storage device within the system that stores and manages data such as generated tasks and reminders.

[0095] "Schedule" refers to list or calendar-style data in which a user's tasks are stored in a list.

[0096] "Reminder" refers to a function or notification that notifies a user when a task deadline is approaching.

[0097] "Confirmation message" refers to a notification that informs the user that the task was successfully added.

[0098] "List format" refers to a format in which each task or reminder is displayed in order.

[0099] "Notification" refers to a means of communicating information from the system to the user.

[0100] "Means" refers to any process, function, or combination thereof necessary for carrying out the invention.

[0101] The present invention relates to a system for efficiently managing user tasks and generating reminders. This system has the functions of generating tasks based on user input, saving them in a database, and generating and notifying reminders when the task deadline approaches.

[0102] Hardware and software used

[0103] Server: Uses hardware suitable for high-performance processing (e.g., AWS EC2, Microsoft Azure, etc.) and a database for managing and storing data (e.g., MySQL, MongoDB, etc.).

[0104] Terminal: A user device such as a smartphone, tablet, or PC. These devices include an interface through which the user enters task information.

[0105] software:

[0106] Front-end: Building the user interface using React, Vue.js, etc.

[0107] Backend: Build the API using Node.js, Python (Flask, Django, etc.).

[0108] Database Management: SQL (MySQL, PostgreSQL, etc.) or NoSQL (MongoDB, etc.) databases.

[0109] Adding a task

[0110] When a user adds a new task, they enter the task name and deadline date. The device receives this and sends the task information to the server. The server analyzes the received information and creates a new task. The created task is saved in the database. The server sends a message to the device confirming that the task was successfully added, notifying the user.

[0111] Examples:

[0112] When a user wants to add a new task, they enter the task name and due date into the terminal and send it to the server. The server receives this information, creates a new task, and saves it in the schedule. Example: Task name "Meeting", due date "October 15, 2023"

[0113] Generate reminders

[0114] When a user requests a reminder to be generated, the device sends a reminder generation request to the server. The server retrieves all tasks from the user's schedule and generates a reminder for each task. The reminder date is set to a random date between 1 and 3 days before the task's due date. The generated reminder is notified to the user and displayed on the device.

[0115] Examples:

[0116] When a user wants to create a reminder, they send a request to the server from their device. The server retrieves all tasks and sets a random date for each task. Example: Set a "Meeting" reminder for October 12, 2023

[0117] Get schedule

[0118] When a user wants to check his / her entire schedule, the terminal sends a schedule acquisition request to the server. The server acquires all the user's tasks and returns them to the terminal in a list format. The terminal displays this list to the user, allowing the user to easily check the schedule.

[0119] Examples:

[0120] When a user wants to check the entire schedule, they send a schedule request from their device to the server. The server retrieves all tasks and returns a list. For example, details of "meetings" and "presentations" are displayed.

[0121] This allows the system of the present invention to support users in efficiently managing tasks and ensuring that deadlines are not forgotten. Specifically, the system automates the processes of task creation, saving, reminder creation and notification, and schedule acquisition and display, thereby reducing the burden on users.

[0122] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0123] Adding a task

[0124] Step 1:

[0125] The user enters the task name and due date.

[0126] Input: The user enters the "task name" and "due date" into the terminal.

[0127] Output: The task name and due date will be displayed on the terminal.

[0128] Step 2:

[0129] The terminal acquires the input task information and sends it to the server. Specifically, it sends the data as an HTTP request.

[0130] Input: The terminal obtains task information input by the user.

[0131] Output: The HTTP request to send to the server.

[0132] Step 3:

[0133] The server analyzes the received task information and creates a new task. It parses the JSON format data and creates a task object.

[0134] Input: HTTP request for task information sent from the device.

[0135] Output: The created task object.

[0136] Step 4:

[0137] The server stores the created task objects in a database, either SQL or NoSQL.

[0138] Input: The created task object.

[0139] Output: Task data stored in a database.

[0140] Step 5:

[0141] The server generates and returns to the terminal a confirmation message indicating that the task was successfully added.

[0142] Input: Database saved results of the task.

[0143] Output: A confirmation message.

[0144] Step 6:

[0145] The terminal displays to the user the confirmation message received from the server.

[0146] Input: The confirmation message sent by the server.

[0147] Output: The confirmation message displayed to the user.

[0148] Generate reminders

[0149] Step 1:

[0150] The user presses a button to request the creation of a reminder.

[0151] Input: A user request to create a reminder.

[0152] Output: Triggers a request by the device to generate a reminder.

[0153] Step 2:

[0154] The device sends a reminder generation request to the server as an HTTP request.

[0155] Input: A request from the user to create a reminder.

[0156] Output: The HTTP request to send to the server.

[0157] Step 3:

[0158] The server retrieves all tasks for the user from the database, using an SQL query to retrieve all tasks associated with the user ID.

[0159] Input: Reminder generation request and user ID.

[0160] Output: All task data for the user.

[0161] Step 4:

[0162] The server sets a random reminder for each task, 1-3 days before the due date, using an algorithm to generate the random date.

[0163] Input: The user's task data.

[0164] Output: The set reminder information.

[0165] Step 5:

[0166] The server generates the generated reminder as a notification object and sends a notification to the user.

[0167] Input: The set reminder information.

[0168] Output: A notification object.

[0169] Step 6:

[0170] The notification received by the terminal is displayed on the user's screen.

[0171] Input: The notification object sent by the server.

[0172] Output: The reminder notification shown to the user.

[0173] Get schedule

[0174] Step 1:

[0175] The user presses the schedule display button.

[0176] Input: A user request to view a schedule.

[0177] Output: Triggers a request to view the schedule by the terminal.

[0178] Step 2:

[0179] The terminal sends a schedule acquisition request to the server as an HTTP request.

[0180] Input: Schedule retrieval request from user.

[0181] Output: The HTTP request to send to the server.

[0182] Step 3:

[0183] The server retrieves all tasks for the user from the database and executes an SQL query to retrieve all tasks.

[0184] Input: Schedule retrieval request and user ID.

[0185] Output: All task data for the user.

[0186] Step 4:

[0187] The server formats the acquired task information into a list and returns it to the terminal as a JSON response.

[0188] Input: The user's task data.

[0189] Output: Task information formatted as a list.

[0190] Step 5:

[0191] The device parses the received JSON data and displays it in list format on the user's screen.

[0192] Input: Task information in list format sent from the server.

[0193] Output: The schedule list displayed to the user.

[0194] (Application example 1)

[0195] 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."

[0196] Efficient task management and reminder notifications are needed in the field. In particular, in work environments such as factories, it is important for workers to quickly enter task information, check progress, and receive reminders for important tasks. However, existing systems make it difficult to achieve these tasks without hassle, resulting in a decrease in work efficiency.

[0197] 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.

[0198] In this invention, the server includes means for receiving task information from a user, means for generating tasks based on the task information, means for saving the generated tasks as a schedule, means for generating reminders based on the schedule, means for notifying the user of the generated reminders, means for transmitting task information to the server by a computer device, means for receiving voice input from a smart device, and means for displaying task information and reminders on a display of the smart device, thereby enabling a worker to quickly add tasks through voice input and check task information and reminders in real time on the display of the smart device.

[0199] A "user" is an individual or entity that uses the system to manage tasks and receive reminder notifications.

[0200] "Task information" is detailed information such as the name and deadline of a task added by a user.

[0201] The term "means" refers to a device, a program, or a method for realizing a specific function or process.

[0202] The "server" is a computer system that processes task information sent by users, generates tasks, saves schedules, and generates and notifies reminders.

[0203] A "schedule" is a list or plan by which generated tasks are managed over time.

[0204] A "reminder" is a warning or alert that notifies a user when a task is about to expire.

[0205] A "computing device" is an electronic device that a user uses to send task information to a server.

[0206] A "smart device" is an electronic device that has the ability to interact with a user through voice input and a display.

[0207] "Voice input" is an operation means for recognizing the user's voice and processing it as text information.

[0208] A "display" is a display device that allows a user to visually confirm information.

[0209] The present invention relates to a system that enables factory workers to efficiently manage tasks and receive reminder notifications using smart devices. Hereinafter, embodiments of the present invention will be described in detail.

[0210] System Overview

[0211] The system of the present invention allows users (workers) to input task information using their smart devices, generates tasks based on that information, and saves them as a schedule. Furthermore, when a task deadline approaches, the system generates a reminder and notifies the worker. This system consists of a server, a computer, and a smart device.

[0212] Hardware and software used

[0213] 1. Server

[0214] The server is a computer system that generates tasks based on task information sent by users, saves them as schedules, and generates and notifies reminders. For example, a program written in Python runs on the server.

[0215] 2. Computer equipment

[0216] The computing device is an electronic device that the user uses to send task information to the server, such as a smartphone or tablet.

[0217] 3. Smart Devices

[0218] A smart device is an electronic device that has the ability to interact with a user through voice input or a display, such as Google Glass or other smart glasses.

[0219] Program processing

[0220] Adding a task

[0221] When a user adds a new task, they specify the task name and due date using voice input or touch operation on their smart device. This information is displayed on the display and can be confirmed. The smart device then sends the task information to the server via a computer. The server uses this information to create a new task and adds it to the schedule list. For example, if a user sets a task called "Parts Inspection" for October 15, 2023, the server uses this information to create a task and saves it in the schedule.

[0222] Generate reminders

[0223] When a task deadline approaches, the server retrieves all tasks from the schedule and generates a reminder for each task. The reminder date is set to a random date 1 to 3 days before the task deadline. For example, a reminder for "Parts Inspection" may be set for October 13, 2023. The server notifies the smart device of the generated reminder, and the worker receives the reminder on the display.

[0224] Get schedule

[0225] When a user wants to check their entire schedule, they send a schedule acquisition request from their smart device to the server. The server acquires all of the user's tasks and returns them as a list to the smart device. The smart device displays this list on its display, allowing the user to easily check their schedule.

[0226] Specific examples

[0227] Example prompts to input to a generative AI model:

[0228] "Add task: 'Quality Check', due date: October 16, 2023"

[0229] "Generate a reminder"

[0230] View schedule

[0231] When Worker A at a factory uses smart glasses and gives voice instructions such as "Add the following task: 'Parts inspection', Deadline: October 20, 2023," the task is added to the server and a reminder is sent to the smart glasses.

[0232] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0233] Step 1:

[0234] The user inputs task information (task name and due date) using a smart device by voice or touch operation. The input information is converted into digital data by the smart device and displayed for confirmation.

[0235] Input: Task name and due date entered by the user via voice or touch

[0236] Output: Digital task information (task name and due date)

[0237] Step 2:

[0238] The smart device sends the input task information to the server via the computer, and the task information arrives at the server via a network connection.

[0239] Input: Digital data (task information) converted by smart device

[0240] Output: Task information sent to the server

[0241] Step 3:

[0242] The server creates a new task based on the received task information and adds it to the user's schedule list. The task information is saved in the database.

[0243] Input: Task information sent to the server

[0244] Output: Tasks saved in the database (task name, due date, status)

[0245] Step 4:

[0246] When a user requests that a reminder be generated, the smart device sends the request to the server via the computing device.

[0247] Input: User request to create a reminder

[0248] Output: Reminder generation request sent to the server

[0249] Step 5:

[0250] The server retrieves all tasks from the schedule list and sets a reminder date based on the due date of each task, which is set to a random date between 1 and 3 days before the due date.

[0251] Input: Task information stored in the schedule list (task name, due date, status)

[0252] Output: Generated reminder information (reminder date, task name)

[0253] Step 6:

[0254] The server notifies the smart device of the generated reminder information, which is then displayed on the smart device's display, visually informing the user of the reminder content.

[0255] Input: Generated reminder information

[0256] Output: Reminder content displayed on smart device

[0257] Step 7:

[0258] When a user makes a request to view the entire schedule, the smart device sends the request to the server via the computing device.

[0259] Input: User request to retrieve schedule

[0260] Output: Schedule retrieval request sent to the server

[0261] Step 8:

[0262] The server retrieves all tasks from the user's schedule list, returns them to the smart device in a list format, and the smart device displays the retrieved task list on its display, providing a visual representation to the user.

[0263] Input: All task information stored in the user's schedule list

[0264] Output: Task list displayed on a smart device

[0265] 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.

[0266] The present invention relates to a system that efficiently manages users' tasks and generates reminders by combining an emotion engine with the system to enable appropriate notifications and task management based on the user's emotions. The system of the present invention has the functions of generating tasks based on user input and saving them as a schedule, as well as generating and notifying reminders when task deadlines approach. It also includes a function that recognizes the user's emotions using the emotion engine and adjusts task management and reminder notifications based on those emotions.

[0267] Adding a task

[0268] When a user wants to add a new task, they enter the task name and deadline. The device receives this and sends the task information to the server. The server creates a new task based on the received information and adds it to the user's schedule list. For example, if a user sets a task called "Meeting" for October 15, 2023, the system will create a task based on this information and save it in the schedule. If the task is added successfully, the server will return a confirmation message to the device.

[0269] Generate reminders

[0270] When a user requests to generate a reminder, the device sends a reminder generation request to the server. The server retrieves all tasks from the user's schedule and generates a reminder for each task. The reminder date is set to a random date 1 to 3 days before the task's due date. For example, for a "Meeting" on October 15, 2023, a reminder is set for October 12, 2023. The generated reminder is notified to the user and displayed on the device.

[0271] Use of emotion engine

[0272] The system also includes an emotion engine that recognizes the user's emotions. The emotion engine uses technologies such as voice recognition and facial expression analysis to determine the user's current emotional state. For example, if the server detects that the user is feeling stressed, it will adjust the content of the reminder notification and deliver it in a gentler tone. If the user is relaxed, it will deliver a normal notification.

[0273] Task Priority Adjustment

[0274] Based on emotion recognition by the emotion engine, the server can automatically adjust the importance and priority of the user's tasks. For example, if the user feels tired, it will postpone less important tasks.

[0275] Get schedule

[0276] When a user wants to check their entire schedule, the terminal sends a schedule retrieval request to the server. The server retrieves all of the user's tasks and returns them to the terminal as a list. The terminal displays the list to the user, allowing the user to easily check their schedule. For example, if the user's schedule includes a "meeting" and a "presentation," the details of these will be displayed on the terminal. In this way, by realizing appropriate task management and reminder notifications based on the user's emotions, the invention can improve the user's convenience and quality of life.

[0277] The processing flow will be explained below.

[0278] Adding a task

[0279] Step 1:

[0280] The user inputs the task name and deadline date into the terminal.

[0281] Step 2:

[0282] The terminal receives input from the user and requests the add_task method from the server.

[0283] Step 3:

[0284] The server creates a new task based on the received task name and due date. Specifically, it constructs the task information in a dictionary format (e.g., {"task_name": "Meeting", "due_date": datetime(2023, 10, 15)}).

[0285] Step 4:

[0286] The server adds the generated task information to the user's schedule list.

[0287] Step 5:

[0288] The server will send a confirmation message back to the terminal indicating that the task was added successfully.

[0289] Step 6:

[0290] The terminal displays a confirmation message to the user.

[0291] Generate reminders

[0292] Step 1:

[0293] The user requests that a reminder be created.

[0294] Step 2:

[0295] The device calls the generate_reminders method to send a reminder generation request to the server.

[0296] Step 3:

[0297] The server retrieves all tasks from the user's schedule.

[0298] Step 4:

[0299] For each task, the server randomly selects a date between 1 and 3 days before the due date and generates a reminder. For example, if the due date for a "Meeting" is October 15, 2023, the server sets the reminder for October 12, 13, or 14, 2023.

[0300] Step 5:

[0301] The server stores the generated reminders in a list, keeping only tasks beyond the current date.

[0302] Step 6:

[0303] The server returns the reminder list to the terminal.

[0304] Step 7:

[0305] The terminal displays the received reminder list to the user.

[0306] Use of emotion engine

[0307] Step 1:

[0308] The user expresses his / her emotions to the terminal by voice input or facial expression analysis.

[0309] Step 2:

[0310] The terminal invokes the emotion engine to send an emotion recognition request to the server.

[0311] Step 3:

[0312] The server uses an emotion engine to analyze the user's current emotions from their voice patterns and facial expressions.

[0313] Step 4:

[0314] The server then adjusts the content and style of the reminder notification based on the emotion recognition results. For example, if the user is feeling stressed, the server will notify them in a gentle tone.

[0315] Step 5:

[0316] The server automatically adjusts the importance and priority of tasks based on the emotion recognition results. For example, if the user feels tired, it postpones less important tasks.

[0317] Get schedule

[0318] Step 1:

[0319] The user requests confirmation of the entire schedule.

[0320] Step 2:

[0321] The terminal calls the get_schedule method to send a schedule acquisition request to the server.

[0322] Step 3:

[0323] The server gets all the user's tasks from the schedule list.

[0324] Step 4:

[0325] The server returns the acquired schedule list to the terminal.

[0326] Step 5:

[0327] The terminal displays the received schedule list to the user. For example, if the schedule includes "meeting" and "presentation," the details of these are displayed.

[0328] Example 2

[0329] 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."

[0330] Conventional task management systems did not take into account the user's emotional state when it came to notifications or adjusting task priorities. As a result, even during stressful or fatigued times, they only sent the same reminder notifications, lacking appropriate support tailored to the user's state. Furthermore, the reminder date settings were fixed, making it difficult to respond to situations requiring flexible management. This could have a negative impact on users' work efficiency and quality of life.

[0331] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0332] In this invention, the server includes means for receiving task information from a user, means for generating tasks based on the task information, means for saving the generated tasks as a schedule, means for generating reminders based on the schedule, means for notifying the user of the generated reminders, means for determining the user's emotions based on emotion analysis technology, and means for adjusting notification content and task priority based on the user's emotions. This enables appropriate notifications and task management according to the user's emotional state, thereby improving the user's work efficiency and quality of life.

[0333] "Task information" is the name of the task and related information such as the deadline entered by the user.

[0334] A "task" is an operation or plan that a user must perform, and is an element that is managed based on a schedule.

[0335] A "schedule" is a chronological list or calendar for managing a user's tasks.

[0336] A "reminder" is a message that notifies the user not to forget a particular task or event.

[0337] "Emotion analysis technology" is a technology that determines a user's current emotional state using technologies such as voice recognition and facial expression analysis.

[0338] "Notifications" are messages or alerts that the system sends to inform the user.

[0339] "Priority adjustment" is an operation that changes the importance and processing order of tasks based on the user's emotional state and other conditions.

[0340] "User State" refers to the user's current mental and emotional state.

[0341] The present invention relates to a system that combines an emotion engine with a system that efficiently manages user tasks and generates reminders, enabling appropriate notifications and task management based on the user's emotions. The system of the present invention uses specific hardware and software to perform a series of data processing.

[0342] The main components of the system include a user terminal, a server, and an emotion engine. The user terminal accepts input from the user and sends it to the server. The server processes the data based on the received information and generates and manages tasks and reminders. The emotion engine uses voice recognition and facial expression analysis technology to determine the user's emotions and uses this information to adjust notification content and task priority.

[0343] The specific processing procedure is as follows.

[0344] Adding a task

[0345] To add a new task, the user enters the task name and deadline. For example, the user enters "Meeting" and "October 15, 2023" into the terminal. The terminal receives this and sends the task information to the server. The server generates a new task based on the received information and adds it to the user's schedule list. After the task is successfully added, the server returns a confirmation message to the terminal and displays it to the user.

[0346] Generate reminders

[0347] The user presses the "Generate Reminder" button on the device to request a reminder. For example, select "Generate Reminder." The device sends the request to the server, which retrieves all tasks from the user's schedule and generates a reminder. The reminder date is set to a random date 1 to 3 days before the task's due date. The generated reminder is notified to the user and displayed on the device.

[0348] Use of emotion engine

[0349] The server uses an emotion engine to determine the user's emotional state. It uses emotion analysis technology to identify emotions through voice recognition and facial expression analysis. For example, if a user types, "I'm stressed today," the server's emotion engine analyzes it and determines that stress is high. Based on this, the server adjusts the content of the reminder notification and sends a gentle message such as, "Tomorrow is a meeting day. Please stay calm and proceed."

[0350] Task Priority Adjustment

[0351] Based on emotion recognition by the emotion engine, the server automatically adjusts the importance and priority of tasks. For example, if the user reports that they are "tired," the server will postpone the "organizing documents" task until the next day. The device then notifies the user of the adjustment results.

[0352] Get schedule

[0353] To check the overall status of their schedule, a user makes a schedule acquisition request on the terminal. For example, they select "Check Schedule." The terminal sends the request to the server, which acquires all of the user's tasks and generates a list. The list is sent to the terminal and displayed to the user.

[0354] Prompt Sentence Examples

[0355] 1. Add task prompt: "Schedule a meeting for October 15, 2023."

[0356] 2. Reminder generation prompt: "Set a reminder"

[0357] 3. Emotion-aware prompt: "Change the notification content to a gentler tone when the user feels stressed."

[0358] 4. Task Priority Adjustment Prompt: "If the user feels fatigued, postpone less important tasks."

[0359] 5. Schedule retrieval prompt: "Show the entire schedule"

[0360] The present invention realizes appropriate task management and notification functions according to the user's emotional state, thereby improving the user's work efficiency and quality of life.

[0361] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0362] Step 1:

[0363] To add a new task, a user enters the task name and deadline into the terminal. Specifically, the user enters "Meeting" and "October 15, 2023" into the input form on the terminal and presses the "Add" button. Input: Task name, deadline. Output: Task addition request.

[0364] Step 2:

[0365] The device receives the entered task information and sends it to the server. Specifically, the device sends the task name and deadline entered by the user to the server as an HTTP request. Input: Task addition request. Output: Request data containing task information.

[0366] Step 3:

[0367] The server receives the information and creates a new task. Specifically, the server saves the received task name and deadline date in the database and creates a new task entry. Input: Request data containing task information. Output: New task entry.

[0368] Step 4:

[0369] The server adds the created task to the user's schedule list. As a concrete action, it associates the task entry stored in the database with the user's schedule list. Input: New task entry. Output: Updated schedule list.

[0370] Step 5:

[0371] After the task is successfully added, the server returns a confirmation message to the terminal. Specifically, the server generates a message saying "Task successfully added" and sends it to the terminal. Input: Updated schedule list. Output: Confirmation message.

[0372] Step 6:

[0373] The terminal displays a confirmation message to the user. Specifically, the terminal displays the confirmation message received from the server in a dialog or grid to notify the user. Input: Confirmation message. Output: Notification to the user.

[0374] Step 7:

[0375] The user presses the "Create reminder" button on the device to request the creation of a reminder. Specifically, the "Create reminder" button is selected and a request is sent to the server. Input: Reminder creation request. Output: Reminder creation request.

[0376] Step 8:

[0377] The device sends a reminder creation request to the server. Specifically, it sends the request data to the server as an HTTP request. Input: Reminder creation request. Output: Request data.

[0378] Step 9:

[0379] The server retrieves all tasks from the user's schedule and generates reminders for each task. Specifically, the server queries the user's schedule list from the database and sets reminders for each task 1-3 days before its due date. Input: User's schedule list. Output: Reminder setting list.

[0380] Step 10:

[0381] The server notifies the user of the created reminder. Specifically, it generates a reminder notification message and sends it to the device. Input: Reminder setting list. Output: Notification message.

[0382] Step 11:

[0383] The device displays the generated reminder information to the user. Specific actions include displaying the reminder information in a popup or notification bar on the device. Input: Notification message. Output: Displaying the reminder to the user.

[0384] Step 12:

[0385] The server uses an emotion engine to determine the user's emotional state. Specifically, the server analyzes the user's input using voice recognition and facial expression analysis technology to identify the user's emotional state. Input: User's voice or facial expression data. Output: Emotional state data.

[0386] Step 13:

[0387] The server adjusts the content of the reminder notification based on the emotion determined by the emotion engine. Specifically, it selects a message template according to the emotional state and generates the notification content. Input: Emotional state data. Output: Emotion-based notification message.

[0388] Step 14:

[0389] The server sends a reminder notification based on the emotion to the device, which then displays it to the user. Specifically, the server sends a notification message based on the emotion to the device, which then displays it. Input: A notification message based on the emotion. Output: Display to the user.

[0390] Step 15:

[0391] The server automatically adjusts the importance and priority of tasks based on emotion recognition by the emotion engine. Specifically, it recalculates task priorities and updates the schedule based on the emotional state. Input: Emotional state data. Output: Updated task list.

[0392] Step 16:

[0393] The server sends the adjusted task information to the terminal, which displays it to the user. Specifically, the server sends the updated task list to the terminal, which displays it. Input: Updated task list. Output: Display to the user.

[0394] Step 17:

[0395] To check the entire schedule, the user makes a schedule acquisition request on the terminal. Specifically, the user presses the "Check Schedule" button on the terminal. Input: Schedule acquisition request. Output: Schedule acquisition request.

[0396] Step 18:

[0397] The terminal sends the request to the server, which retrieves all tasks from the user's schedule. Specifically, the schedule retrieval request is sent to the server as an HTTP request, and the server retrieves the schedule data from the database. Input: Schedule retrieval request. Output: Retrieved schedule data.

[0398] Step 19:

[0399] The server returns the acquired schedule data to the terminal as a list. Specifically, it formats the schedule data and sends it to the terminal in list format. Input: Acquired schedule data. Output: Schedule list data.

[0400] Step 20:

[0401] The terminal displays the acquired schedule information to the user. Specifically, the schedule information is displayed to the user in list format. Input: Schedule list data. Output: Schedule displayed to the user.

[0402] (Application example 2)

[0403] 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."

[0404] Conventional task management systems and reminder generation systems simply set task information and reminders without considering the user's emotional state. As a result, notifications are sent without considering the user's mental state and emotions, which can easily cause stress and discomfort. In particular, in virtual stores, customers' emotional state has a significant impact on their purchasing motivation and experience, so appropriate emotional responses are required. Furthermore, existing systems lacked the ability to adjust task priorities based on the user's emotions, which placed a heavy burden on users.

[0405] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving task information from a user, means for generating tasks based on the task information, means for saving the generated tasks as a schedule, means for generating reminders based on the schedule, means for notifying the user of the generated reminders, means for recognizing the user's emotional state, and means for adjusting notification content and task management based on the emotional state. This enables appropriate task management and reminder notifications based on the user's emotional state. In particular, in a virtual store, it becomes possible to monitor customers' emotional states in real time and take appropriate measures to improve their experience.

[0406] "Task information" is information about work or schedule that a user wants to manage or execute.

[0407] A "task" is an action or activity that a user must perform to achieve a particular purpose or goal.

[0408] A "schedule" refers to managing a user's tasks and plans and organizing them in terms of time.

[0409] A "reminder" is a record or information that notifies a user to perform a specific task or schedule and urges the user not to forget.

[0410] "Emotional state" refers to the user's current state of mind or mood, including stress, relaxation, excitement, fatigue, etc.

[0411] "Emotion recognition" is the process of determining a user's current emotional state using technologies such as voice recognition and facial expression analysis.

[0412] "Notification content" is information displayed or communicated to the user, including reminders and important messages.

[0413] "Task management" refers to a series of tasks that a user sets up, such as creating, saving, organizing, prioritizing, and generating reminders for tasks.

[0414] A "virtual store" is an e-commerce store operated on the Internet, where users can browse and purchase products online.

[0415] The present invention relates to a system for efficiently managing a user's tasks and generating reminders based on the user's emotional state. The system is configured as follows.

[0416] System Configuration

[0417] The system mainly consists of a server and a terminal. The server contains a database, an emotion recognition engine, and a reminder generation function. The terminal acts as a user interface, allowing users to input task information, display reminders, and acquire emotional states.

[0418] Hardware

[0419] Devices: Smartphones, tablets, computers, etc.

[0420] Server: High-performance data processing server

[0421] software

[0422] Database Management: Firebase Firestore

[0423] Emotion recognition: Google Cloud Natural Language API

[0424] Notification system: Firebase Cloud Messaging (FCM)

[0425] Program Description

[0426] 1. Add a task:

[0427] The user uses the device to input task information, including the task name and due date. In addition, the device also accepts free text input from the user (e.g., "I'm a little excited today because I want to buy this present."). The device then sends this information to the server.

[0428] 2. Emotion recognition:

[0429] The server analyzes the text using the Google Cloud Natural Language API to determine the user's emotional state. Based on the emotion recognition results, the server determines the priority of the task. For example, if the user is feeling stressed, the task will be assigned a low priority.

[0430] 3. Task creation and saving:

[0431] The server generates tasks based on the received information and saves them as schedules in Firebase Firestore, including task name, due date, sentiment score, priority, etc.

[0432] 4. Reminder generation:

[0433] When a task is about to expire, the server generates a reminder and sends a notification to the user's device using Firebase Cloud Messaging. The reminder date is set to a random date between 1 and 3 days before the task's due date, and the content of the notification is also adjusted based on the user's emotional state.

[0434] Specific examples

[0435] For example, if a user enters the task "I want to find a new gift" in a virtual store and comments, "I'm a little nervous today," the server will use an emotion recognition engine to recognize the emotion of "nervous." As a result, the server will assign a low priority to the task and send a gentle reminder message to the user. For example, a message such as, "Take your time looking. I'm sure you'll find a nice gift" will be sent to the user's device.

[0436] Example prompts to input to a generative AI model:

[0437] "If users express negative emotions, provide a supportive message to ease those feelings."

[0438] "If they're feeling stressed while searching for a gift, recommend a product that will help them relax."

[0439] This system will enable users to manage tasks and receive reminder notifications appropriately according to their emotions, making daily life and online shopping more comfortable.

[0440] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0441] Step 1:

[0442] The user inputs task information using a terminal. The input includes the task name and deadline date. In addition, free text input (e.g., "I'm a little excited because I want to buy this present today") is also accepted to grasp the emotional state. Here, the input data is the task name, deadline date, and emotional text, and the terminal sends this data to the server.

[0443] Step 2:

[0444] The server processes the received task information and emotion text. Specifically, it sends the emotion text to the Google Cloud Natural Language API and analyzes the user's emotional state. This analysis outputs an emotion score. For example, a positive emotion score is obtained from the text "I'm feeling a little excited today."

[0445] Step 3:

[0446] The server prioritizes the task based on the sentiment score: for a positive sentiment score, it sets the priority as "high" and for a negative sentiment score, it sets the priority as "low." It then creates a task with this priority and stores it in Firebase Firestore.

[0447] Step 4:

[0448] The server generates reminders based on the schedule. The reminder date is set to a random date between 1 and 3 days before the task's due date. This reminder information is sent to the user's device via Firebase Cloud Messaging. The due date and sentiment score are input data to generate the reminder, and the reminder information is output.

[0449] Step 5:

[0450] The server adjusts the content of the reminder notification based on the user's emotional state. If the emotional score is low, a gentle reminder notification is generated, and if the emotional score is high, a normal notification is generated. Specifically, the message content of the reminder notification changes depending on the emotional state. For example, if the emotional score is negative, the message generated is, "Take your time and look around. I'm sure you'll find a pleasant gift."

[0451] Step 6:

[0452] The generated reminders and notifications are displayed on the user's device, allowing the user to receive timely reminders and support tailored to their emotional state.

[0453] These steps will enable appropriate task management and reminder notifications based on the user's emotional state, providing a pleasant user experience.

[0454] 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.

[0455] 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.

[0456] 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.

[0457] [Second embodiment]

[0458] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0459] 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.

[0460] 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).

[0461] 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.

[0462] 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.

[0463] 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).

[0464] 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.

[0465] 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.

[0466] 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.

[0467] 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.

[0468] 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.

[0469] 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."

[0470] The present invention relates to a system for efficiently managing user tasks and generating reminders. The system of the present invention has the functions of generating tasks based on user input, saving them as schedules, and generating and notifying reminders when task deadlines approach.

[0471] Adding a task

[0472] When a user wants to add a new task, they enter the task name and deadline. The device receives this and sends the task information to the server. The server creates a new task based on the received information and adds it to the user's schedule list. For example, if a user sets a task called "Meeting" for October 15, 2023, the system will create a task based on this information and save it in the schedule. If the task is added successfully, the server will return a confirmation message to the device.

[0473] Generate reminders

[0474] When a user requests to create a reminder, the device sends a reminder creation request to the server. The server retrieves all tasks from the user's schedule and creates a reminder for each task. The reminder date is set to a random date 1 to 3 days before the task's due date. For example, a "Meeting" reminder is set for October 12, 2023. The generated reminder is notified to the user and displayed on the device.

[0475] Get schedule

[0476] When a user wants to check their entire schedule, the device sends a schedule retrieval request to the server. The server retrieves all of the user's tasks and returns them to the device as a list. The device displays this list to the user, allowing the user to easily check the schedule. For example, if the user's schedule includes a "meeting" and a "presentation," the details will be displayed on the device.

[0477] In this way, the system of the present invention supports users in efficiently managing tasks and ensuring that deadlines are not forgotten. Specifically, it automates the processes of task creation, saving, reminder creation and notification, and schedule acquisition and display, thereby reducing the burden on users.

[0478] The processing flow will be explained below.

[0479] Adding a task

[0480] Step 1:

[0481] The user inputs the task name and deadline date into the terminal.

[0482] Step 2:

[0483] The terminal receives input from the user and requests the add_task method from the server.

[0484] Step 3:

[0485] The server creates a new task based on the received task name and due date. Specifically, it constructs the task information in a dictionary format (e.g., {"task_name": "Meeting", "due_date": datetime(2023, 10, 15)}).

[0486] Step 4:

[0487] The server adds the generated task information to the user's schedule list.

[0488] Step 5:

[0489] The server will send a confirmation message back to the terminal indicating that the task was added successfully.

[0490] Step 6:

[0491] The terminal displays a confirmation message to the user.

[0492] Generate reminders

[0493] Step 1:

[0494] The user requests that a reminder be created.

[0495] Step 2:

[0496] The device calls the generate_reminders method to send a reminder generation request to the server.

[0497] Step 3:

[0498] The server retrieves all tasks from the user's schedule.

[0499] Step 4:

[0500] For each task, the server randomly selects a date between 1 and 3 days before the due date and generates a reminder. For example, if the due date for a "Meeting" is October 15, 2023, the server sets the reminder for October 12, 13, or 14, 2023.

[0501] Step 5:

[0502] The server stores the generated reminders in a list, keeping only tasks beyond the current date.

[0503] Step 6:

[0504] The server returns the reminder list to the terminal.

[0505] Step 7:

[0506] The terminal displays the received reminder list to the user.

[0507] Get schedule

[0508] Step 1:

[0509] The user requests confirmation of the entire schedule.

[0510] Step 2:

[0511] The terminal calls the get_schedule method to send a schedule acquisition request to the server.

[0512] Step 3:

[0513] The server gets all the user's tasks from the schedule list.

[0514] Step 4:

[0515] The server returns the acquired schedule list to the terminal.

[0516] Step 5:

[0517] The terminal displays the received schedule list to the user. For example, if the schedule includes "meeting" and "presentation," the details of these are displayed.

[0518] Example 1

[0519] 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."

[0520] Conventional task management systems have the drawback of requiring users to manually add tasks and set reminders, and the fixed reminder dates limit flexible notification options. Furthermore, they lack the functionality to easily check the entire schedule, making it difficult for users to efficiently manage tasks.

[0521] 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.

[0522] In this invention, the server includes a means for receiving task information from a user, a means for generating a task based on the task information, a means for storing the generated task in a database, a means for generating a message confirming that the task has been successfully added and notifying the user, a means for generating a reminder based on the schedule, and a means for notifying the user of the generated reminder. This allows the user to efficiently manage tasks and receive flexible reminder notifications. It also allows the user to easily check the entire schedule in list format.

[0523] "User" refers to an individual or organization that uses the system.

[0524] "Task information" refers to information such as task name and deadline date that a user enters into the system.

[0525] A "task" refers to a schedule or work item that a user registers in the system.

[0526] "Database" refers to the storage device within the system that stores and manages data such as generated tasks and reminders.

[0527] "Schedule" refers to list or calendar-style data in which a user's tasks are stored in a list.

[0528] "Reminder" refers to a function or notification that notifies a user when a task deadline is approaching.

[0529] "Confirmation message" refers to a notification that informs the user that the task was successfully added.

[0530] "List format" refers to a format in which each task or reminder is displayed in order.

[0531] "Notification" refers to a means of communicating information from the system to the user.

[0532] "Means" refers to any process, function, or combination thereof necessary for carrying out the invention.

[0533] The present invention relates to a system for efficiently managing user tasks and generating reminders. This system has the functions of generating tasks based on user input, saving them in a database, and generating and notifying reminders when the task deadline approaches.

[0534] Hardware and software used

[0535] Server: Uses hardware suitable for high-performance processing (e.g., AWS EC2, Microsoft Azure, etc.) and a database for managing and storing data (e.g., MySQL, MongoDB, etc.).

[0536] Terminal: A user device such as a smartphone, tablet, or PC. These devices include an interface through which the user enters task information.

[0537] software:

[0538] Front-end: Building the user interface using React, Vue.js, etc.

[0539] Backend: Build the API using Node.js, Python (Flask, Django, etc.).

[0540] Database Management: SQL (MySQL, PostgreSQL, etc.) or NoSQL (MongoDB, etc.) databases.

[0541] Adding a task

[0542] When a user adds a new task, they enter the task name and deadline date. The device receives this and sends the task information to the server. The server analyzes the received information and creates a new task. The created task is saved in the database. The server sends a message to the device confirming that the task was successfully added, notifying the user.

[0543] Examples:

[0544] When a user wants to add a new task, they enter the task name and due date into the terminal and send it to the server. The server receives this information, creates a new task, and saves it in the schedule. Example: Task name "Meeting", due date "October 15, 2023"

[0545] Generate reminders

[0546] When a user requests a reminder to be generated, the device sends a reminder generation request to the server. The server retrieves all tasks from the user's schedule and generates a reminder for each task. The reminder date is set to a random date between 1 and 3 days before the task's due date. The generated reminder is notified to the user and displayed on the device.

[0547] Examples:

[0548] When a user wants to create a reminder, they send a request to the server from their device. The server retrieves all tasks and sets a random date for each task. Example: Set a "Meeting" reminder for October 12, 2023

[0549] Get schedule

[0550] When a user wants to check his / her entire schedule, the terminal sends a schedule acquisition request to the server. The server acquires all the user's tasks and returns them to the terminal in a list format. The terminal displays this list to the user, allowing the user to easily check the schedule.

[0551] Examples:

[0552] When a user wants to check the entire schedule, they send a schedule request from their device to the server. The server retrieves all tasks and returns a list. For example, details of "meetings" and "presentations" are displayed.

[0553] This allows the system of the present invention to support users in efficiently managing tasks and ensuring that deadlines are not forgotten. Specifically, the system automates the processes of task creation, saving, reminder creation and notification, and schedule acquisition and display, thereby reducing the burden on users.

[0554] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0555] Adding a task

[0556] Step 1:

[0557] The user enters the task name and due date.

[0558] Input: The user enters the "task name" and "due date" into the terminal.

[0559] Output: The task name and due date will be displayed on the terminal.

[0560] Step 2:

[0561] The terminal acquires the input task information and sends it to the server. Specifically, it sends the data as an HTTP request.

[0562] Input: The terminal obtains task information input by the user.

[0563] Output: The HTTP request to send to the server.

[0564] Step 3:

[0565] The server analyzes the received task information and creates a new task. It parses the JSON format data and creates a task object.

[0566] Input: HTTP request for task information sent from the device.

[0567] Output: The created task object.

[0568] Step 4:

[0569] The server stores the created task objects in a database, either SQL or NoSQL.

[0570] Input: The created task object.

[0571] Output: Task data stored in a database.

[0572] Step 5:

[0573] The server generates and returns to the terminal a confirmation message indicating that the task was successfully added.

[0574] Input: Database saved results of the task.

[0575] Output: A confirmation message.

[0576] Step 6:

[0577] The terminal displays to the user the confirmation message received from the server.

[0578] Input: The confirmation message sent by the server.

[0579] Output: The confirmation message displayed to the user.

[0580] Generate reminders

[0581] Step 1:

[0582] The user presses a button to request the creation of a reminder.

[0583] Input: A user request to create a reminder.

[0584] Output: Triggers a request by the device to generate a reminder.

[0585] Step 2:

[0586] The device sends a reminder generation request to the server as an HTTP request.

[0587] Input: A request from the user to create a reminder.

[0588] Output: The HTTP request to send to the server.

[0589] Step 3:

[0590] The server retrieves all tasks for the user from the database, using an SQL query to retrieve all tasks associated with the user ID.

[0591] Input: Reminder generation request and user ID.

[0592] Output: All task data for the user.

[0593] Step 4:

[0594] The server sets a random reminder for each task, 1-3 days before the due date, using an algorithm to generate the random date.

[0595] Input: The user's task data.

[0596] Output: The set reminder information.

[0597] Step 5:

[0598] The server generates the generated reminder as a notification object and sends a notification to the user.

[0599] Input: The set reminder information.

[0600] Output: A notification object.

[0601] Step 6:

[0602] The notification received by the terminal is displayed on the user's screen.

[0603] Input: The notification object sent by the server.

[0604] Output: The reminder notification shown to the user.

[0605] Get schedule

[0606] Step 1:

[0607] The user presses the schedule display button.

[0608] Input: A user request to view a schedule.

[0609] Output: Triggers a request to view the schedule by the terminal.

[0610] Step 2:

[0611] The terminal sends a schedule acquisition request to the server as an HTTP request.

[0612] Input: Schedule retrieval request from user.

[0613] Output: The HTTP request to send to the server.

[0614] Step 3:

[0615] The server retrieves all tasks for the user from the database and executes an SQL query to retrieve all tasks.

[0616] Input: Schedule retrieval request and user ID.

[0617] Output: All task data for the user.

[0618] Step 4:

[0619] The server formats the acquired task information into a list and returns it to the terminal as a JSON response.

[0620] Input: The user's task data.

[0621] Output: Task information formatted as a list.

[0622] Step 5:

[0623] The device parses the received JSON data and displays it in list format on the user's screen.

[0624] Input: Task information in list format sent from the server.

[0625] Output: The schedule list displayed to the user.

[0626] (Application example 1)

[0627] 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."

[0628] Efficient task management and reminder notifications are needed in the field. In particular, in work environments such as factories, it is important for workers to quickly enter task information, check progress, and receive reminders for important tasks. However, existing systems make it difficult to achieve these tasks without hassle, resulting in a decrease in work efficiency.

[0629] 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.

[0630] In this invention, the server includes means for receiving task information from a user, means for generating tasks based on the task information, means for saving the generated tasks as a schedule, means for generating reminders based on the schedule, means for notifying the user of the generated reminders, means for transmitting task information to the server by a computer device, means for receiving voice input from a smart device, and means for displaying task information and reminders on a display of the smart device, thereby enabling a worker to quickly add tasks through voice input and check task information and reminders in real time on the display of the smart device.

[0631] A "user" is an individual or entity that uses the system to manage tasks and receive reminder notifications.

[0632] "Task information" is detailed information such as the name and deadline of a task added by a user.

[0633] The term "means" refers to a device, a program, or a method for realizing a specific function or process.

[0634] The "server" is a computer system that processes task information sent by users, generates tasks, saves schedules, and generates and notifies reminders.

[0635] A "schedule" is a list or plan by which generated tasks are managed over time.

[0636] A "reminder" is a warning or alert that notifies a user when a task is about to expire.

[0637] A "computing device" is an electronic device that a user uses to send task information to a server.

[0638] A "smart device" is an electronic device that has the ability to interact with a user through voice input and a display.

[0639] "Voice input" is an operation means for recognizing the user's voice and processing it as text information.

[0640] A "display" is a display device that allows a user to visually confirm information.

[0641] The present invention relates to a system that enables factory workers to efficiently manage tasks and receive reminder notifications using smart devices. Hereinafter, embodiments of the present invention will be described in detail.

[0642] System Overview

[0643] The system of the present invention allows users (workers) to input task information using their smart devices, generates tasks based on that information, and saves them as a schedule. Furthermore, when a task deadline approaches, the system generates a reminder and notifies the worker. This system consists of a server, a computer, and a smart device.

[0644] Hardware and software used

[0645] 1. Server

[0646] The server is a computer system that generates tasks based on task information sent by users, saves them as schedules, and generates and notifies reminders. For example, a program written in Python runs on the server.

[0647] 2. Computer equipment

[0648] The computing device is an electronic device that the user uses to send task information to the server, such as a smartphone or tablet.

[0649] 3. Smart Devices

[0650] A smart device is an electronic device that has the ability to interact with a user through voice input or a display, such as Google Glass or other smart glasses.

[0651] Program processing

[0652] Adding a task

[0653] When a user adds a new task, they specify the task name and due date using voice input or touch operation on their smart device. This information is displayed on the display and can be confirmed. The smart device then sends the task information to the server via a computer. The server uses this information to create a new task and adds it to the schedule list. For example, if a user sets a task called "Parts Inspection" for October 15, 2023, the server uses this information to create a task and saves it in the schedule.

[0654] Generate reminders

[0655] When a task deadline approaches, the server retrieves all tasks from the schedule and generates a reminder for each task. The reminder date is set to a random date 1 to 3 days before the task deadline. For example, a reminder for "Parts Inspection" may be set for October 13, 2023. The server notifies the smart device of the generated reminder, and the worker receives the reminder on the display.

[0656] Get schedule

[0657] When a user wants to check their entire schedule, they send a schedule acquisition request from their smart device to the server. The server acquires all of the user's tasks and returns them as a list to the smart device. The smart device displays this list on its display, allowing the user to easily check their schedule.

[0658] Specific examples

[0659] Example prompts to input to a generative AI model:

[0660] "Add task: 'Quality Check', due date: October 16, 2023"

[0661] "Generate a reminder"

[0662] View schedule

[0663] When Worker A at a factory uses smart glasses and gives voice instructions such as "Add the following task: 'Parts inspection', Deadline: October 20, 2023," the task is added to the server and a reminder is sent to the smart glasses.

[0664] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0665] Step 1:

[0666] The user inputs task information (task name and due date) using a smart device by voice or touch operation. The input information is converted into digital data by the smart device and displayed for confirmation.

[0667] Input: Task name and due date entered by the user via voice or touch

[0668] Output: Digital task information (task name and due date)

[0669] Step 2:

[0670] The smart device sends the input task information to the server via the computer, and the task information arrives at the server via a network connection.

[0671] Input: Digital data (task information) converted by smart device

[0672] Output: Task information sent to the server

[0673] Step 3:

[0674] The server creates a new task based on the received task information and adds it to the user's schedule list. The task information is saved in the database.

[0675] Input: Task information sent to the server

[0676] Output: Tasks saved in the database (task name, due date, status)

[0677] Step 4:

[0678] When a user requests that a reminder be generated, the smart device sends the request to the server via the computing device.

[0679] Input: User request to create a reminder

[0680] Output: Reminder generation request sent to the server

[0681] Step 5:

[0682] The server retrieves all tasks from the schedule list and sets a reminder date based on the due date of each task, which is set to a random date between 1 and 3 days before the due date.

[0683] Input: Task information stored in the schedule list (task name, due date, status)

[0684] Output: Generated reminder information (reminder date, task name)

[0685] Step 6:

[0686] The server notifies the smart device of the generated reminder information, which is then displayed on the smart device's display, visually informing the user of the reminder content.

[0687] Input: Generated reminder information

[0688] Output: Reminder content displayed on smart device

[0689] Step 7:

[0690] When a user makes a request to view the entire schedule, the smart device sends the request to the server via the computing device.

[0691] Input: User request to retrieve schedule

[0692] Output: Schedule retrieval request sent to the server

[0693] Step 8:

[0694] The server retrieves all tasks from the user's schedule list, returns them to the smart device in a list format, and the smart device displays the retrieved task list on its display, providing a visual representation to the user.

[0695] Input: All task information stored in the user's schedule list

[0696] Output: Task list displayed on a smart device

[0697] 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.

[0698] The present invention relates to a system that efficiently manages users' tasks and generates reminders by combining an emotion engine with the system to enable appropriate notifications and task management based on the user's emotions. The system of the present invention has the functions of generating tasks based on user input and saving them as a schedule, as well as generating and notifying reminders when task deadlines approach. It also includes a function that recognizes the user's emotions using the emotion engine and adjusts task management and reminder notifications based on those emotions.

[0699] Adding a task

[0700] When a user wants to add a new task, they enter the task name and deadline. The device receives this and sends the task information to the server. The server creates a new task based on the received information and adds it to the user's schedule list. For example, if a user sets a task called "Meeting" for October 15, 2023, the system will create a task based on this information and save it in the schedule. If the task is added successfully, the server will return a confirmation message to the device.

[0701] Generate reminders

[0702] When a user requests to generate a reminder, the device sends a reminder generation request to the server. The server retrieves all tasks from the user's schedule and generates a reminder for each task. The reminder date is set to a random date 1 to 3 days before the task's due date. For example, for a "Meeting" on October 15, 2023, a reminder is set for October 12, 2023. The generated reminder is notified to the user and displayed on the device.

[0703] Use of emotion engine

[0704] The system also includes an emotion engine that recognizes the user's emotions. The emotion engine uses technologies such as voice recognition and facial expression analysis to determine the user's current emotional state. For example, if the server detects that the user is feeling stressed, it will adjust the content of the reminder notification and deliver it in a gentler tone. If the user is relaxed, it will deliver a normal notification.

[0705] Task Priority Adjustment

[0706] Based on emotion recognition by the emotion engine, the server can automatically adjust the importance and priority of the user's tasks. For example, if the user feels tired, it will postpone less important tasks.

[0707] Get schedule

[0708] When a user wants to check their entire schedule, the terminal sends a schedule retrieval request to the server. The server retrieves all of the user's tasks and returns them to the terminal as a list. The terminal displays the list to the user, allowing the user to easily check their schedule. For example, if the user's schedule includes a "meeting" and a "presentation," the details of these will be displayed on the terminal. In this way, by realizing appropriate task management and reminder notifications based on the user's emotions, the invention can improve the user's convenience and quality of life.

[0709] The processing flow will be explained below.

[0710] Adding a task

[0711] Step 1:

[0712] The user inputs the task name and deadline date into the terminal.

[0713] Step 2:

[0714] The terminal receives input from the user and requests the add_task method from the server.

[0715] Step 3:

[0716] The server creates a new task based on the received task name and due date. Specifically, it constructs the task information in a dictionary format (e.g., {"task_name": "Meeting", "due_date": datetime(2023, 10, 15)}).

[0717] Step 4:

[0718] The server adds the generated task information to the user's schedule list.

[0719] Step 5:

[0720] The server will send a confirmation message back to the terminal indicating that the task was added successfully.

[0721] Step 6:

[0722] The terminal displays a confirmation message to the user.

[0723] Generate reminders

[0724] Step 1:

[0725] The user requests that a reminder be created.

[0726] Step 2:

[0727] The device calls the generate_reminders method to send a reminder generation request to the server.

[0728] Step 3:

[0729] The server retrieves all tasks from the user's schedule.

[0730] Step 4:

[0731] For each task, the server randomly selects a date between 1 and 3 days before the due date and generates a reminder. For example, if the due date for a "Meeting" is October 15, 2023, the server sets the reminder for October 12, 13, or 14, 2023.

[0732] Step 5:

[0733] The server stores the generated reminders in a list, keeping only tasks beyond the current date.

[0734] Step 6:

[0735] The server returns the reminder list to the terminal.

[0736] Step 7:

[0737] The terminal displays the received reminder list to the user.

[0738] Use of emotion engine

[0739] Step 1:

[0740] The user expresses his / her emotions to the terminal by voice input or facial expression analysis.

[0741] Step 2:

[0742] The terminal invokes the emotion engine to send an emotion recognition request to the server.

[0743] Step 3:

[0744] The server uses an emotion engine to analyze the user's current emotions from their voice patterns and facial expressions.

[0745] Step 4:

[0746] The server then adjusts the content and style of the reminder notification based on the emotion recognition results. For example, if the user is feeling stressed, the server will notify them in a gentle tone.

[0747] Step 5:

[0748] The server automatically adjusts the importance and priority of tasks based on the emotion recognition results. For example, if the user feels tired, it postpones less important tasks.

[0749] Get schedule

[0750] Step 1:

[0751] The user requests confirmation of the entire schedule.

[0752] Step 2:

[0753] The terminal calls the get_schedule method to send a schedule acquisition request to the server.

[0754] Step 3:

[0755] The server gets all the user's tasks from the schedule list.

[0756] Step 4:

[0757] The server returns the acquired schedule list to the terminal.

[0758] Step 5:

[0759] The terminal displays the received schedule list to the user. For example, if the schedule includes "meeting" and "presentation," the details of these are displayed.

[0760] Example 2

[0761] 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."

[0762] Conventional task management systems did not take into account the user's emotional state when it came to notifications or adjusting task priorities. As a result, even during stressful or fatigued times, they only sent the same reminder notifications, lacking appropriate support tailored to the user's state. Furthermore, the reminder date settings were fixed, making it difficult to respond to situations requiring flexible management. This could have a negative impact on users' work efficiency and quality of life.

[0763] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0764] In this invention, the server includes means for receiving task information from a user, means for generating tasks based on the task information, means for saving the generated tasks as a schedule, means for generating reminders based on the schedule, means for notifying the user of the generated reminders, means for determining the user's emotions based on emotion analysis technology, and means for adjusting notification content and task priority based on the user's emotions. This enables appropriate notifications and task management according to the user's emotional state, thereby improving the user's work efficiency and quality of life.

[0765] "Task information" is the name of the task and related information such as the deadline entered by the user.

[0766] A "task" is an operation or plan that a user must perform, and is an element that is managed based on a schedule.

[0767] A "schedule" is a chronological list or calendar for managing a user's tasks.

[0768] A "reminder" is a message that notifies the user not to forget a particular task or event.

[0769] "Emotion analysis technology" is a technology that determines a user's current emotional state using technologies such as voice recognition and facial expression analysis.

[0770] "Notifications" are messages or alerts that the system sends to inform the user.

[0771] "Priority adjustment" is an operation that changes the importance and processing order of tasks based on the user's emotional state and other conditions.

[0772] "User State" refers to the user's current mental and emotional state.

[0773] The present invention relates to a system that combines an emotion engine with a system that efficiently manages user tasks and generates reminders, enabling appropriate notifications and task management based on the user's emotions. The system of the present invention uses specific hardware and software to perform a series of data processing.

[0774] The main components of the system include a user terminal, a server, and an emotion engine. The user terminal accepts input from the user and sends it to the server. The server processes the data based on the received information and generates and manages tasks and reminders. The emotion engine uses voice recognition and facial expression analysis technology to determine the user's emotions and uses this information to adjust notification content and task priority.

[0775] The specific processing procedure is as follows.

[0776] Adding a task

[0777] To add a new task, the user enters the task name and deadline. For example, the user enters "Meeting" and "October 15, 2023" into the terminal. The terminal receives this and sends the task information to the server. The server generates a new task based on the received information and adds it to the user's schedule list. After the task is successfully added, the server returns a confirmation message to the terminal and displays it to the user.

[0778] Generate reminders

[0779] The user presses the "Generate Reminder" button on the device to request a reminder. For example, select "Generate Reminder." The device sends the request to the server, which retrieves all tasks from the user's schedule and generates a reminder. The reminder date is set to a random date 1 to 3 days before the task's due date. The generated reminder is notified to the user and displayed on the device.

[0780] Use of emotion engine

[0781] The server uses an emotion engine to determine the user's emotional state. It uses emotion analysis technology to identify emotions through voice recognition and facial expression analysis. For example, if a user types, "I'm stressed today," the server's emotion engine analyzes it and determines that stress is high. Based on this, the server adjusts the content of the reminder notification and sends a gentle message such as, "Tomorrow is a meeting day. Please stay calm and proceed."

[0782] Task Priority Adjustment

[0783] Based on emotion recognition by the emotion engine, the server automatically adjusts the importance and priority of tasks. For example, if the user reports that they are "tired," the server will postpone the "organizing documents" task until the next day. The device then notifies the user of the adjustment results.

[0784] Get schedule

[0785] To check the overall status of their schedule, a user makes a schedule acquisition request on the terminal. For example, they select "Check Schedule." The terminal sends the request to the server, which acquires all of the user's tasks and generates a list. The list is sent to the terminal and displayed to the user.

[0786] Prompt Sentence Examples

[0787] 1. Add task prompt: "Schedule a meeting for October 15, 2023."

[0788] 2. Reminder generation prompt: "Set a reminder"

[0789] 3. Emotion-aware prompt: "Change the notification content to a gentler tone when the user feels stressed."

[0790] 4. Task Priority Adjustment Prompt: "If the user feels fatigued, postpone less important tasks."

[0791] 5. Schedule retrieval prompt: "Show the entire schedule"

[0792] The present invention realizes appropriate task management and notification functions according to the user's emotional state, thereby improving the user's work efficiency and quality of life.

[0793] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0794] Step 1:

[0795] To add a new task, a user enters the task name and deadline into the terminal. Specifically, the user enters "Meeting" and "October 15, 2023" into the input form on the terminal and presses the "Add" button. Input: Task name, deadline. Output: Task addition request.

[0796] Step 2:

[0797] The device receives the entered task information and sends it to the server. Specifically, the device sends the task name and deadline entered by the user to the server as an HTTP request. Input: Task addition request. Output: Request data containing task information.

[0798] Step 3:

[0799] The server receives the information and creates a new task. Specifically, the server saves the received task name and deadline date in the database and creates a new task entry. Input: Request data containing task information. Output: New task entry.

[0800] Step 4:

[0801] The server adds the created task to the user's schedule list. As a concrete action, it associates the task entry stored in the database with the user's schedule list. Input: New task entry. Output: Updated schedule list.

[0802] Step 5:

[0803] After the task is successfully added, the server returns a confirmation message to the terminal. Specifically, the server generates a message saying "Task successfully added" and sends it to the terminal. Input: Updated schedule list. Output: Confirmation message.

[0804] Step 6:

[0805] The terminal displays a confirmation message to the user. Specifically, the terminal displays the confirmation message received from the server in a dialog or grid to notify the user. Input: Confirmation message. Output: Notification to the user.

[0806] Step 7:

[0807] The user presses the "Create reminder" button on the device to request the creation of a reminder. Specifically, the "Create reminder" button is selected and a request is sent to the server. Input: Reminder creation request. Output: Reminder creation request.

[0808] Step 8:

[0809] The device sends a reminder creation request to the server. Specifically, it sends the request data to the server as an HTTP request. Input: Reminder creation request. Output: Request data.

[0810] Step 9:

[0811] The server retrieves all tasks from the user's schedule and generates reminders for each task. Specifically, the server queries the user's schedule list from the database and sets reminders for each task 1-3 days before its due date. Input: User's schedule list. Output: Reminder setting list.

[0812] Step 10:

[0813] The server notifies the user of the created reminder. Specifically, it generates a reminder notification message and sends it to the device. Input: Reminder setting list. Output: Notification message.

[0814] Step 11:

[0815] The device displays the generated reminder information to the user. Specific actions include displaying the reminder information in a popup or notification bar on the device. Input: Notification message. Output: Displaying the reminder to the user.

[0816] Step 12:

[0817] The server uses an emotion engine to determine the user's emotional state. Specifically, the server analyzes the user's input using voice recognition and facial expression analysis technology to identify the user's emotional state. Input: User's voice or facial expression data. Output: Emotional state data.

[0818] Step 13:

[0819] The server adjusts the content of the reminder notification based on the emotion determined by the emotion engine. Specifically, it selects a message template according to the emotional state and generates the notification content. Input: Emotional state data. Output: Emotion-based notification message.

[0820] Step 14:

[0821] The server sends a reminder notification based on the emotion to the device, which then displays it to the user. Specifically, the server sends a notification message based on the emotion to the device, which then displays it. Input: A notification message based on the emotion. Output: Display to the user.

[0822] Step 15:

[0823] The server automatically adjusts the importance and priority of tasks based on emotion recognition by the emotion engine. Specifically, it recalculates task priorities and updates the schedule based on the emotional state. Input: Emotional state data. Output: Updated task list.

[0824] Step 16:

[0825] The server sends the adjusted task information to the terminal, which displays it to the user. Specifically, the server sends the updated task list to the terminal, which displays it. Input: Updated task list. Output: Display to the user.

[0826] Step 17:

[0827] To check the entire schedule, the user makes a schedule acquisition request on the terminal. Specifically, the user presses the "Check Schedule" button on the terminal. Input: Schedule acquisition request. Output: Schedule acquisition request.

[0828] Step 18:

[0829] The terminal sends the request to the server, which retrieves all tasks from the user's schedule. Specifically, the schedule retrieval request is sent to the server as an HTTP request, and the server retrieves the schedule data from the database. Input: Schedule retrieval request. Output: Retrieved schedule data.

[0830] Step 19:

[0831] The server returns the acquired schedule data to the terminal as a list. Specifically, it formats the schedule data and sends it to the terminal in list format. Input: Acquired schedule data. Output: Schedule list data.

[0832] Step 20:

[0833] The terminal displays the acquired schedule information to the user. Specifically, the schedule information is displayed to the user in list format. Input: Schedule list data. Output: Schedule displayed to the user.

[0834] (Application example 2)

[0835] 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."

[0836] Conventional task management systems and reminder generation systems simply set task information and reminders without considering the user's emotional state. As a result, notifications are sent without considering the user's mental state and emotions, which can easily cause stress and discomfort. In particular, in virtual stores, customers' emotional state has a significant impact on their purchasing motivation and experience, so appropriate emotional responses are required. Furthermore, existing systems lacked the ability to adjust task priorities based on the user's emotions, which placed a heavy burden on users.

[0837] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving task information from a user, means for generating tasks based on the task information, means for saving the generated tasks as a schedule, means for generating reminders based on the schedule, means for notifying the user of the generated reminders, means for recognizing the user's emotional state, and means for adjusting notification content and task management based on the emotional state. This enables appropriate task management and reminder notifications based on the user's emotional state. In particular, in a virtual store, it becomes possible to monitor customers' emotional states in real time and take appropriate measures to improve their experience.

[0838] "Task information" is information about work or schedule that a user wants to manage or execute.

[0839] A "task" is an action or activity that a user must perform to achieve a particular purpose or goal.

[0840] A "schedule" refers to managing a user's tasks and plans and organizing them in terms of time.

[0841] A "reminder" is a record or information that notifies a user to perform a specific task or schedule and urges the user not to forget.

[0842] "Emotional state" refers to the user's current state of mind or mood, including stress, relaxation, excitement, fatigue, etc.

[0843] "Emotion recognition" is the process of determining a user's current emotional state using technologies such as voice recognition and facial expression analysis.

[0844] "Notification content" is information displayed or communicated to the user, including reminders and important messages.

[0845] "Task management" refers to a series of tasks that a user sets up, such as creating, saving, organizing, prioritizing, and generating reminders for tasks.

[0846] A "virtual store" is an e-commerce store operated on the Internet, where users can browse and purchase products online.

[0847] The present invention relates to a system for efficiently managing a user's tasks and generating reminders based on the user's emotional state. The system is configured as follows.

[0848] System Configuration

[0849] The system mainly consists of a server and a terminal. The server contains a database, an emotion recognition engine, and a reminder generation function. The terminal acts as a user interface, allowing users to input task information, display reminders, and acquire emotional states.

[0850] Hardware

[0851] Devices: Smartphones, tablets, computers, etc.

[0852] Server: High-performance data processing server

[0853] software

[0854] Database Management: Firebase Firestore

[0855] Emotion recognition: Google Cloud Natural Language API

[0856] Notification system: Firebase Cloud Messaging (FCM)

[0857] Program Description

[0858] 1. Add a task:

[0859] The user uses the device to input task information, including the task name and due date. In addition, the device also accepts free text input from the user (e.g., "I'm a little excited today because I want to buy this present."). The device then sends this information to the server.

[0860] 2. Emotion recognition:

[0861] The server analyzes the text using the Google Cloud Natural Language API to determine the user's emotional state. Based on the emotion recognition results, the server determines the priority of the task. For example, if the user is feeling stressed, the task will be assigned a low priority.

[0862] 3. Task creation and saving:

[0863] The server generates tasks based on the received information and saves them as schedules in Firebase Firestore, including task name, due date, sentiment score, priority, etc.

[0864] 4. Reminder generation:

[0865] When a task is about to expire, the server generates a reminder and sends a notification to the user's device using Firebase Cloud Messaging. The reminder date is set to a random date between 1 and 3 days before the task's due date, and the content of the notification is also adjusted based on the user's emotional state.

[0866] Specific examples

[0867] For example, if a user enters the task "I want to find a new gift" in a virtual store and comments, "I'm a little nervous today," the server will use an emotion recognition engine to recognize the emotion of "nervous." As a result, the server will assign a low priority to the task and send a gentle reminder message to the user. For example, a message such as, "Take your time looking. I'm sure you'll find a nice gift" will be sent to the user's device.

[0868] Example prompts to input to a generative AI model:

[0869] "If users express negative emotions, provide a supportive message to ease those feelings."

[0870] "If they're feeling stressed while searching for a gift, recommend a product that will help them relax."

[0871] This system will enable users to manage tasks and receive reminder notifications appropriately according to their emotions, making daily life and online shopping more comfortable.

[0872] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0873] Step 1:

[0874] The user inputs task information using a terminal. The input includes the task name and deadline date. In addition, free text input (e.g., "I'm a little excited because I want to buy this present today") is also accepted to grasp the emotional state. Here, the input data is the task name, deadline date, and emotional text, and the terminal sends this data to the server.

[0875] Step 2:

[0876] The server processes the received task information and emotion text. Specifically, it sends the emotion text to the Google Cloud Natural Language API and analyzes the user's emotional state. This analysis outputs an emotion score. For example, a positive emotion score is obtained from the text "I'm feeling a little excited today."

[0877] Step 3:

[0878] The server prioritizes the task based on the sentiment score: for a positive sentiment score, it sets the priority as "high" and for a negative sentiment score, it sets the priority as "low." It then creates a task with this priority and stores it in Firebase Firestore.

[0879] Step 4:

[0880] The server generates reminders based on the schedule. The reminder date is set to a random date between 1 and 3 days before the task's due date. This reminder information is sent to the user's device via Firebase Cloud Messaging. The due date and sentiment score are input data to generate the reminder, and the reminder information is output.

[0881] Step 5:

[0882] The server adjusts the content of the reminder notification based on the user's emotional state. If the emotional score is low, a gentle reminder notification is generated, and if the emotional score is high, a normal notification is generated. Specifically, the message content of the reminder notification changes depending on the emotional state. For example, if the emotional score is negative, the message generated is, "Take your time and look around. I'm sure you'll find a pleasant gift."

[0883] Step 6:

[0884] The generated reminders and notifications are displayed on the user's device, allowing the user to receive timely reminders and support tailored to their emotional state.

[0885] These steps will enable appropriate task management and reminder notifications based on the user's emotional state, providing a pleasant user experience.

[0886] 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.

[0887] 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.

[0888] 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.

[0889] [Third embodiment]

[0890] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0891] 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.

[0892] 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).

[0893] 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.

[0894] 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.

[0895] 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).

[0896] 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.

[0897] 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.

[0898] 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.

[0899] 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.

[0900] 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.

[0901] 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."

[0902] The present invention relates to a system for efficiently managing user tasks and generating reminders. The system of the present invention has the functions of generating tasks based on user input, saving them as schedules, and generating and notifying reminders when task deadlines approach.

[0903] Adding a task

[0904] When a user wants to add a new task, they enter the task name and deadline. The device receives this and sends the task information to the server. The server creates a new task based on the received information and adds it to the user's schedule list. For example, if a user sets a task called "Meeting" for October 15, 2023, the system will create a task based on this information and save it in the schedule. If the task is added successfully, the server will return a confirmation message to the device.

[0905] Generate reminders

[0906] When a user requests to create a reminder, the device sends a reminder creation request to the server. The server retrieves all tasks from the user's schedule and creates a reminder for each task. The reminder date is set to a random date 1 to 3 days before the task's due date. For example, a "Meeting" reminder is set for October 12, 2023. The generated reminder is notified to the user and displayed on the device.

[0907] Get schedule

[0908] When a user wants to check their entire schedule, the device sends a schedule retrieval request to the server. The server retrieves all of the user's tasks and returns them to the device as a list. The device displays this list to the user, allowing the user to easily check the schedule. For example, if the user's schedule includes a "meeting" and a "presentation," the details will be displayed on the device.

[0909] In this way, the system of the present invention supports users in efficiently managing tasks and ensuring that deadlines are not forgotten. Specifically, it automates the processes of task creation, saving, reminder creation and notification, and schedule acquisition and display, thereby reducing the burden on users.

[0910] The processing flow will be explained below.

[0911] Adding a task

[0912] Step 1:

[0913] The user inputs the task name and deadline date into the terminal.

[0914] Step 2:

[0915] The terminal receives input from the user and requests the add_task method from the server.

[0916] Step 3:

[0917] The server creates a new task based on the received task name and due date. Specifically, it constructs the task information in a dictionary format (e.g., {"task_name": "Meeting", "due_date": datetime(2023, 10, 15)}).

[0918] Step 4:

[0919] The server adds the generated task information to the user's schedule list.

[0920] Step 5:

[0921] The server will send a confirmation message back to the terminal indicating that the task was added successfully.

[0922] Step 6:

[0923] The terminal displays a confirmation message to the user.

[0924] Generate reminders

[0925] Step 1:

[0926] The user requests that a reminder be created.

[0927] Step 2:

[0928] The device calls the generate_reminders method to send a reminder generation request to the server.

[0929] Step 3:

[0930] The server retrieves all tasks from the user's schedule.

[0931] Step 4:

[0932] For each task, the server randomly selects a date between 1 and 3 days before the due date and generates a reminder. For example, if the due date for a "Meeting" is October 15, 2023, the server sets the reminder for October 12, 13, or 14, 2023.

[0933] Step 5:

[0934] The server stores the generated reminders in a list, keeping only tasks beyond the current date.

[0935] Step 6:

[0936] The server returns the reminder list to the terminal.

[0937] Step 7:

[0938] The terminal displays the received reminder list to the user.

[0939] Get schedule

[0940] Step 1:

[0941] The user requests confirmation of the entire schedule.

[0942] Step 2:

[0943] The terminal calls the get_schedule method to send a schedule acquisition request to the server.

[0944] Step 3:

[0945] The server gets all the user's tasks from the schedule list.

[0946] Step 4:

[0947] The server returns the acquired schedule list to the terminal.

[0948] Step 5:

[0949] The terminal displays the received schedule list to the user. For example, if the schedule includes "meeting" and "presentation," the details of these are displayed.

[0950] Example 1

[0951] 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."

[0952] Conventional task management systems have the drawback of requiring users to manually add tasks and set reminders, and the fixed reminder dates limit flexible notification options. Furthermore, they lack the functionality to easily check the entire schedule, making it difficult for users to efficiently manage tasks.

[0953] 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.

[0954] In this invention, the server includes a means for receiving task information from a user, a means for generating a task based on the task information, a means for storing the generated task in a database, a means for generating a message confirming that the task has been successfully added and notifying the user, a means for generating a reminder based on the schedule, and a means for notifying the user of the generated reminder. This allows the user to efficiently manage tasks and receive flexible reminder notifications. It also allows the user to easily check the entire schedule in list format.

[0955] "User" refers to an individual or organization that uses the system.

[0956] "Task information" refers to information such as task name and deadline date that a user enters into the system.

[0957] A "task" refers to a schedule or work item that a user registers in the system.

[0958] "Database" refers to the storage device within the system that stores and manages data such as generated tasks and reminders.

[0959] "Schedule" refers to list or calendar-style data in which a user's tasks are stored in a list.

[0960] "Reminder" refers to a function or notification that notifies a user when a task deadline is approaching.

[0961] "Confirmation message" refers to a notification that informs the user that the task was successfully added.

[0962] "List format" refers to a format in which each task or reminder is displayed in order.

[0963] "Notification" refers to a means of communicating information from the system to the user.

[0964] "Means" refers to any process, function, or combination thereof necessary for carrying out the invention.

[0965] The present invention relates to a system for efficiently managing user tasks and generating reminders. This system has the functions of generating tasks based on user input, saving them in a database, and generating and notifying reminders when the task deadline approaches.

[0966] Hardware and software used

[0967] Server: Uses hardware suitable for high-performance processing (e.g., AWS EC2, Microsoft Azure, etc.) and a database for managing and storing data (e.g., MySQL, MongoDB, etc.).

[0968] Terminal: A user device such as a smartphone, tablet, or PC. These devices include an interface through which the user enters task information.

[0969] software:

[0970] Front-end: Building the user interface using React, Vue.js, etc.

[0971] Backend: Build the API using Node.js, Python (Flask, Django, etc.).

[0972] Database Management: SQL (MySQL, PostgreSQL, etc.) or NoSQL (MongoDB, etc.) databases.

[0973] Adding a task

[0974] When a user adds a new task, they enter the task name and deadline date. The device receives this and sends the task information to the server. The server analyzes the received information and creates a new task. The created task is saved in the database. The server sends a message to the device confirming that the task was successfully added, notifying the user.

[0975] Examples:

[0976] When a user wants to add a new task, they enter the task name and due date into the terminal and send it to the server. The server receives this information, creates a new task, and saves it in the schedule. Example: Task name "Meeting", due date "October 15, 2023"

[0977] Generate reminders

[0978] When a user requests a reminder to be generated, the device sends a reminder generation request to the server. The server retrieves all tasks from the user's schedule and generates a reminder for each task. The reminder date is set to a random date between 1 and 3 days before the task's due date. The generated reminder is notified to the user and displayed on the device.

[0979] Examples:

[0980] When a user wants to create a reminder, they send a request to the server from their device. The server retrieves all tasks and sets a random date for each task. Example: Set a "Meeting" reminder for October 12, 2023

[0981] Get schedule

[0982] When a user wants to check his / her entire schedule, the terminal sends a schedule acquisition request to the server. The server acquires all the user's tasks and returns them to the terminal in a list format. The terminal displays this list to the user, allowing the user to easily check the schedule.

[0983] Examples:

[0984] When a user wants to check the entire schedule, they send a schedule request from their device to the server. The server retrieves all tasks and returns a list. For example, details of "meetings" and "presentations" are displayed.

[0985] This allows the system of the present invention to support users in efficiently managing tasks and ensuring that deadlines are not forgotten. Specifically, the system automates the processes of task creation, saving, reminder creation and notification, and schedule acquisition and display, thereby reducing the burden on users.

[0986] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0987] Adding a task

[0988] Step 1:

[0989] The user enters the task name and due date.

[0990] Input: The user enters the "task name" and "due date" into the terminal.

[0991] Output: The task name and due date will be displayed on the terminal.

[0992] Step 2:

[0993] The terminal acquires the input task information and sends it to the server. Specifically, it sends the data as an HTTP request.

[0994] Input: The terminal obtains task information input by the user.

[0995] Output: The HTTP request to send to the server.

[0996] Step 3:

[0997] The server analyzes the received task information and creates a new task. It parses the JSON format data and creates a task object.

[0998] Input: HTTP request for task information sent from the device.

[0999] Output: The created task object.

[1000] Step 4:

[1001] The server stores the created task objects in a database, either SQL or NoSQL.

[1002] Input: The created task object.

[1003] Output: Task data stored in a database.

[1004] Step 5:

[1005] The server generates and returns to the terminal a confirmation message indicating that the task was successfully added.

[1006] Input: Database saved results of the task.

[1007] Output: A confirmation message.

[1008] Step 6:

[1009] The terminal displays to the user the confirmation message received from the server.

[1010] Input: The confirmation message sent by the server.

[1011] Output: The confirmation message displayed to the user.

[1012] Generate reminders

[1013] Step 1:

[1014] The user presses a button to request the creation of a reminder.

[1015] Input: A user request to create a reminder.

[1016] Output: Triggers a request by the device to generate a reminder.

[1017] Step 2:

[1018] The device sends a reminder generation request to the server as an HTTP request.

[1019] Input: A request from the user to create a reminder.

[1020] Output: The HTTP request to send to the server.

[1021] Step 3:

[1022] The server retrieves all tasks for the user from the database, using an SQL query to retrieve all tasks associated with the user ID.

[1023] Input: Reminder generation request and user ID.

[1024] Output: All task data for the user.

[1025] Step 4:

[1026] The server sets a random reminder for each task, 1-3 days before the due date, using an algorithm to generate the random date.

[1027] Input: The user's task data.

[1028] Output: The set reminder information.

[1029] Step 5:

[1030] The server generates the generated reminder as a notification object and sends a notification to the user.

[1031] Input: The set reminder information.

[1032] Output: A notification object.

[1033] Step 6:

[1034] The notification received by the terminal is displayed on the user's screen.

[1035] Input: The notification object sent by the server.

[1036] Output: The reminder notification shown to the user.

[1037] Get schedule

[1038] Step 1:

[1039] The user presses the schedule display button.

[1040] Input: A user request to view a schedule.

[1041] Output: Triggers a request to view the schedule by the terminal.

[1042] Step 2:

[1043] The terminal sends a schedule acquisition request to the server as an HTTP request.

[1044] Input: Schedule retrieval request from user.

[1045] Output: The HTTP request to send to the server.

[1046] Step 3:

[1047] The server retrieves all tasks for the user from the database and executes an SQL query to retrieve all tasks.

[1048] Input: Schedule retrieval request and user ID.

[1049] Output: All task data for the user.

[1050] Step 4:

[1051] The server formats the acquired task information into a list and returns it to the terminal as a JSON response.

[1052] Input: The user's task data.

[1053] Output: Task information formatted as a list.

[1054] Step 5:

[1055] The device parses the received JSON data and displays it in list format on the user's screen.

[1056] Input: Task information in list format sent from the server.

[1057] Output: The schedule list displayed to the user.

[1058] (Application example 1)

[1059] 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."

[1060] Efficient task management and reminder notifications are needed in the field. In particular, in work environments such as factories, it is important for workers to quickly enter task information, check progress, and receive reminders for important tasks. However, existing systems make it difficult to achieve these tasks without hassle, resulting in a decrease in work efficiency.

[1061] 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.

[1062] In this invention, the server includes means for receiving task information from a user, means for generating tasks based on the task information, means for saving the generated tasks as a schedule, means for generating reminders based on the schedule, means for notifying the user of the generated reminders, means for transmitting task information to the server by a computer device, means for receiving voice input from a smart device, and means for displaying task information and reminders on a display of the smart device, thereby enabling a worker to quickly add tasks through voice input and check task information and reminders in real time on the display of the smart device.

[1063] A "user" is an individual or entity that uses the system to manage tasks and receive reminder notifications.

[1064] "Task information" is detailed information such as the name and deadline of a task added by a user.

[1065] The term "means" refers to a device, a program, or a method for realizing a specific function or process.

[1066] The "server" is a computer system that processes task information sent by users, generates tasks, saves schedules, and generates and notifies reminders.

[1067] A "schedule" is a list or plan by which generated tasks are managed over time.

[1068] A "reminder" is a warning or alert that notifies a user when a task is about to expire.

[1069] A "computing device" is an electronic device that a user uses to send task information to a server.

[1070] A "smart device" is an electronic device that has the ability to interact with a user through voice input and a display.

[1071] "Voice input" is an operation means for recognizing the user's voice and processing it as text information.

[1072] A "display" is a display device that allows a user to visually confirm information.

[1073] The present invention relates to a system that enables factory workers to efficiently manage tasks and receive reminder notifications using smart devices. Hereinafter, embodiments of the present invention will be described in detail.

[1074] System Overview

[1075] The system of the present invention allows users (workers) to input task information using their smart devices, generates tasks based on that information, and saves them as a schedule. Furthermore, when a task deadline approaches, the system generates a reminder and notifies the worker. This system consists of a server, a computer, and a smart device.

[1076] Hardware and software used

[1077] 1. Server

[1078] The server is a computer system that generates tasks based on task information sent by users, saves them as schedules, and generates and notifies reminders. For example, a program written in Python runs on the server.

[1079] 2. Computer equipment

[1080] The computing device is an electronic device that the user uses to send task information to the server, such as a smartphone or tablet.

[1081] 3. Smart Devices

[1082] A smart device is an electronic device that has the ability to interact with a user through voice input or a display, such as Google Glass or other smart glasses.

[1083] Program processing

[1084] Adding a task

[1085] When a user adds a new task, they specify the task name and due date using voice input or touch operation on their smart device. This information is displayed on the display and can be confirmed. The smart device then sends the task information to the server via a computer. The server uses this information to create a new task and adds it to the schedule list. For example, if a user sets a task called "Parts Inspection" for October 15, 2023, the server uses this information to create a task and saves it in the schedule.

[1086] Generate reminders

[1087] When a task deadline approaches, the server retrieves all tasks from the schedule and generates a reminder for each task. The reminder date is set to a random date 1 to 3 days before the task deadline. For example, a reminder for "Parts Inspection" may be set for October 13, 2023. The server notifies the smart device of the generated reminder, and the worker receives the reminder on the display.

[1088] Get schedule

[1089] When a user wants to check their entire schedule, they send a schedule acquisition request from their smart device to the server. The server acquires all of the user's tasks and returns them as a list to the smart device. The smart device displays this list on its display, allowing the user to easily check their schedule.

[1090] Specific examples

[1091] Example prompts to input to a generative AI model:

[1092] "Add task: 'Quality Check', due date: October 16, 2023"

[1093] "Generate a reminder"

[1094] View schedule

[1095] When Worker A at a factory uses smart glasses and gives voice instructions such as "Add the following task: 'Parts inspection', Deadline: October 20, 2023," the task is added to the server and a reminder is sent to the smart glasses.

[1096] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1097] Step 1:

[1098] The user inputs task information (task name and due date) using a smart device by voice or touch operation. The input information is converted into digital data by the smart device and displayed for confirmation.

[1099] Input: Task name and due date entered by the user via voice or touch

[1100] Output: Digital task information (task name and due date)

[1101] Step 2:

[1102] The smart device sends the input task information to the server via the computer, and the task information arrives at the server via a network connection.

[1103] Input: Digital data (task information) converted by smart device

[1104] Output: Task information sent to the server

[1105] Step 3:

[1106] The server creates a new task based on the received task information and adds it to the user's schedule list. The task information is saved in the database.

[1107] Input: Task information sent to the server

[1108] Output: Tasks saved in the database (task name, due date, status)

[1109] Step 4:

[1110] When a user requests that a reminder be generated, the smart device sends the request to the server via the computing device.

[1111] Input: User request to create a reminder

[1112] Output: Reminder generation request sent to the server

[1113] Step 5:

[1114] The server retrieves all tasks from the schedule list and sets a reminder date based on the due date of each task, which is set to a random date between 1 and 3 days before the due date.

[1115] Input: Task information stored in the schedule list (task name, due date, status)

[1116] Output: Generated reminder information (reminder date, task name)

[1117] Step 6:

[1118] The server notifies the smart device of the generated reminder information, which is then displayed on the smart device's display, visually informing the user of the reminder content.

[1119] Input: Generated reminder information

[1120] Output: Reminder content displayed on smart device

[1121] Step 7:

[1122] When a user makes a request to view the entire schedule, the smart device sends the request to the server via the computing device.

[1123] Input: User request to retrieve schedule

[1124] Output: Schedule retrieval request sent to the server

[1125] Step 8:

[1126] The server retrieves all tasks from the user's schedule list, returns them to the smart device in a list format, and the smart device displays the retrieved task list on its display, providing a visual representation to the user.

[1127] Input: All task information stored in the user's schedule list

[1128] Output: Task list displayed on a smart device

[1129] 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.

[1130] The present invention relates to a system that efficiently manages users' tasks and generates reminders by combining an emotion engine with the system to enable appropriate notifications and task management based on the user's emotions. The system of the present invention has the functions of generating tasks based on user input and saving them as a schedule, as well as generating and notifying reminders when task deadlines approach. It also includes a function that recognizes the user's emotions using the emotion engine and adjusts task management and reminder notifications based on those emotions.

[1131] Adding a task

[1132] When a user wants to add a new task, they enter the task name and deadline. The device receives this and sends the task information to the server. The server creates a new task based on the received information and adds it to the user's schedule list. For example, if a user sets a task called "Meeting" for October 15, 2023, the system will create a task based on this information and save it in the schedule. If the task is added successfully, the server will return a confirmation message to the device.

[1133] Generate reminders

[1134] When a user requests to generate a reminder, the device sends a reminder generation request to the server. The server retrieves all tasks from the user's schedule and generates a reminder for each task. The reminder date is set to a random date 1 to 3 days before the task's due date. For example, for a "Meeting" on October 15, 2023, a reminder is set for October 12, 2023. The generated reminder is notified to the user and displayed on the device.

[1135] Use of emotion engine

[1136] The system also includes an emotion engine that recognizes the user's emotions. The emotion engine uses technologies such as voice recognition and facial expression analysis to determine the user's current emotional state. For example, if the server detects that the user is feeling stressed, it will adjust the content of the reminder notification and deliver it in a gentler tone. If the user is relaxed, it will deliver a normal notification.

[1137] Task Priority Adjustment

[1138] Based on emotion recognition by the emotion engine, the server can automatically adjust the importance and priority of the user's tasks. For example, if the user feels tired, it will postpone less important tasks.

[1139] Get schedule

[1140] When a user wants to check their entire schedule, the terminal sends a schedule retrieval request to the server. The server retrieves all of the user's tasks and returns them to the terminal as a list. The terminal displays the list to the user, allowing the user to easily check their schedule. For example, if the user's schedule includes a "meeting" and a "presentation," the details of these will be displayed on the terminal. In this way, by realizing appropriate task management and reminder notifications based on the user's emotions, the invention can improve the user's convenience and quality of life.

[1141] The processing flow will be explained below.

[1142] Adding a task

[1143] Step 1:

[1144] The user inputs the task name and deadline date into the terminal.

[1145] Step 2:

[1146] The terminal receives input from the user and requests the add_task method from the server.

[1147] Step 3:

[1148] The server creates a new task based on the received task name and due date. Specifically, it constructs the task information in a dictionary format (e.g., {"task_name": "Meeting", "due_date": datetime(2023, 10, 15)}).

[1149] Step 4:

[1150] The server adds the generated task information to the user's schedule list.

[1151] Step 5:

[1152] The server will send a confirmation message back to the terminal indicating that the task was added successfully.

[1153] Step 6:

[1154] The terminal displays a confirmation message to the user.

[1155] Generate reminders

[1156] Step 1:

[1157] The user requests that a reminder be created.

[1158] Step 2:

[1159] The device calls the generate_reminders method to send a reminder generation request to the server.

[1160] Step 3:

[1161] The server retrieves all tasks from the user's schedule.

[1162] Step 4:

[1163] For each task, the server randomly selects a date between 1 and 3 days before the due date and generates a reminder. For example, if the due date for a "Meeting" is October 15, 2023, the server sets the reminder for October 12, 13, or 14, 2023.

[1164] Step 5:

[1165] The server stores the generated reminders in a list, keeping only tasks beyond the current date.

[1166] Step 6:

[1167] The server returns the reminder list to the terminal.

[1168] Step 7:

[1169] The terminal displays the received reminder list to the user.

[1170] Use of emotion engine

[1171] Step 1:

[1172] The user expresses his / her emotions to the terminal by voice input or facial expression analysis.

[1173] Step 2:

[1174] The terminal invokes the emotion engine to send an emotion recognition request to the server.

[1175] Step 3:

[1176] The server uses an emotion engine to analyze the user's current emotions from their voice patterns and facial expressions.

[1177] Step 4:

[1178] The server then adjusts the content and style of the reminder notification based on the emotion recognition results. For example, if the user is feeling stressed, the server will notify them in a gentle tone.

[1179] Step 5:

[1180] The server automatically adjusts the importance and priority of tasks based on the emotion recognition results. For example, if the user feels tired, it postpones less important tasks.

[1181] Get schedule

[1182] Step 1:

[1183] The user requests confirmation of the entire schedule.

[1184] Step 2:

[1185] The terminal calls the get_schedule method to send a schedule acquisition request to the server.

[1186] Step 3:

[1187] The server gets all the user's tasks from the schedule list.

[1188] Step 4:

[1189] The server returns the acquired schedule list to the terminal.

[1190] Step 5:

[1191] The terminal displays the received schedule list to the user. For example, if the schedule includes "meeting" and "presentation," the details of these are displayed.

[1192] Example 2

[1193] 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."

[1194] Conventional task management systems did not take into account the user's emotional state when it came to notifications or adjusting task priorities. As a result, even during stressful or fatigued times, they only sent the same reminder notifications, lacking appropriate support tailored to the user's state. Furthermore, the reminder date settings were fixed, making it difficult to respond to situations requiring flexible management. This could have a negative impact on users' work efficiency and quality of life.

[1195] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1196] In this invention, the server includes means for receiving task information from a user, means for generating tasks based on the task information, means for saving the generated tasks as a schedule, means for generating reminders based on the schedule, means for notifying the user of the generated reminders, means for determining the user's emotions based on emotion analysis technology, and means for adjusting notification content and task priority based on the user's emotions. This enables appropriate notifications and task management according to the user's emotional state, thereby improving the user's work efficiency and quality of life.

[1197] "Task information" is the name of the task and related information such as the deadline entered by the user.

[1198] A "task" is an operation or plan that a user must perform, and is an element that is managed based on a schedule.

[1199] A "schedule" is a chronological list or calendar for managing a user's tasks.

[1200] A "reminder" is a message that notifies the user not to forget a particular task or event.

[1201] "Emotion analysis technology" is a technology that determines a user's current emotional state using technologies such as voice recognition and facial expression analysis.

[1202] "Notifications" are messages or alerts that the system sends to inform the user.

[1203] "Priority adjustment" is an operation that changes the importance and processing order of tasks based on the user's emotional state and other conditions.

[1204] "User State" refers to the user's current mental and emotional state.

[1205] The present invention relates to a system that combines an emotion engine with a system that efficiently manages user tasks and generates reminders, enabling appropriate notifications and task management based on the user's emotions. The system of the present invention uses specific hardware and software to perform a series of data processing.

[1206] The main components of the system include a user terminal, a server, and an emotion engine. The user terminal accepts input from the user and sends it to the server. The server processes the data based on the received information and generates and manages tasks and reminders. The emotion engine uses voice recognition and facial expression analysis technology to determine the user's emotions and uses this information to adjust notification content and task priority.

[1207] The specific processing procedure is as follows.

[1208] Adding a task

[1209] To add a new task, the user enters the task name and deadline. For example, the user enters "Meeting" and "October 15, 2023" into the terminal. The terminal receives this and sends the task information to the server. The server generates a new task based on the received information and adds it to the user's schedule list. After the task is successfully added, the server returns a confirmation message to the terminal and displays it to the user.

[1210] Generate reminders

[1211] The user presses the "Generate Reminder" button on the device to request a reminder. For example, select "Generate Reminder." The device sends the request to the server, which retrieves all tasks from the user's schedule and generates a reminder. The reminder date is set to a random date 1 to 3 days before the task's due date. The generated reminder is notified to the user and displayed on the device.

[1212] Use of emotion engine

[1213] The server uses an emotion engine to determine the user's emotional state. It uses emotion analysis technology to identify emotions through voice recognition and facial expression analysis. For example, if a user types, "I'm stressed today," the server's emotion engine analyzes it and determines that stress is high. Based on this, the server adjusts the content of the reminder notification and sends a gentle message such as, "Tomorrow is a meeting day. Please stay calm and proceed."

[1214] Task Priority Adjustment

[1215] Based on emotion recognition by the emotion engine, the server automatically adjusts the importance and priority of tasks. For example, if the user reports that they are "tired," the server will postpone the "organizing documents" task until the next day. The device then notifies the user of the adjustment results.

[1216] Get schedule

[1217] To check the overall status of their schedule, a user makes a schedule acquisition request on the terminal. For example, they select "Check Schedule." The terminal sends the request to the server, which acquires all of the user's tasks and generates a list. The list is sent to the terminal and displayed to the user.

[1218] Prompt Sentence Examples

[1219] 1. Add task prompt: "Schedule a meeting for October 15, 2023."

[1220] 2. Reminder generation prompt: "Set a reminder"

[1221] 3. Emotion-aware prompt: "Change the notification content to a gentler tone when the user feels stressed."

[1222] 4. Task Priority Adjustment Prompt: "If the user feels fatigued, postpone less important tasks."

[1223] 5. Schedule retrieval prompt: "Show the entire schedule"

[1224] The present invention realizes appropriate task management and notification functions according to the user's emotional state, thereby improving the user's work efficiency and quality of life.

[1225] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1226] Step 1:

[1227] To add a new task, a user enters the task name and deadline into the terminal. Specifically, the user enters "Meeting" and "October 15, 2023" into the input form on the terminal and presses the "Add" button. Input: Task name, deadline. Output: Task addition request.

[1228] Step 2:

[1229] The device receives the entered task information and sends it to the server. Specifically, the device sends the task name and deadline entered by the user to the server as an HTTP request. Input: Task addition request. Output: Request data containing task information.

[1230] Step 3:

[1231] The server receives the information and creates a new task. Specifically, the server saves the received task name and deadline date in the database and creates a new task entry. Input: Request data containing task information. Output: New task entry.

[1232] Step 4:

[1233] The server adds the created task to the user's schedule list. As a concrete action, it associates the task entry stored in the database with the user's schedule list. Input: New task entry. Output: Updated schedule list.

[1234] Step 5:

[1235] After the task is successfully added, the server returns a confirmation message to the terminal. Specifically, the server generates a message saying "Task successfully added" and sends it to the terminal. Input: Updated schedule list. Output: Confirmation message.

[1236] Step 6:

[1237] The terminal displays a confirmation message to the user. Specifically, the terminal displays the confirmation message received from the server in a dialog or grid to notify the user. Input: Confirmation message. Output: Notification to the user.

[1238] Step 7:

[1239] The user presses the "Create reminder" button on the device to request the creation of a reminder. Specifically, the "Create reminder" button is selected and a request is sent to the server. Input: Reminder creation request. Output: Reminder creation request.

[1240] Step 8:

[1241] The device sends a reminder creation request to the server. Specifically, it sends the request data to the server as an HTTP request. Input: Reminder creation request. Output: Request data.

[1242] Step 9:

[1243] The server retrieves all tasks from the user's schedule and generates reminders for each task. Specifically, the server queries the user's schedule list from the database and sets reminders for each task 1-3 days before its due date. Input: User's schedule list. Output: Reminder setting list.

[1244] Step 10:

[1245] The server notifies the user of the created reminder. Specifically, it generates a reminder notification message and sends it to the device. Input: Reminder setting list. Output: Notification message.

[1246] Step 11:

[1247] The device displays the generated reminder information to the user. Specific actions include displaying the reminder information in a popup or notification bar on the device. Input: Notification message. Output: Displaying the reminder to the user.

[1248] Step 12:

[1249] The server uses an emotion engine to determine the user's emotional state. Specifically, the server analyzes the user's input using voice recognition and facial expression analysis technology to identify the user's emotional state. Input: User's voice or facial expression data. Output: Emotional state data.

[1250] Step 13:

[1251] The server adjusts the content of the reminder notification based on the emotion determined by the emotion engine. Specifically, it selects a message template according to the emotional state and generates the notification content. Input: Emotional state data. Output: Emotion-based notification message.

[1252] Step 14:

[1253] The server sends a reminder notification based on the emotion to the device, which then displays it to the user. Specifically, the server sends a notification message based on the emotion to the device, which then displays it. Input: A notification message based on the emotion. Output: Display to the user.

[1254] Step 15:

[1255] The server automatically adjusts the importance and priority of tasks based on emotion recognition by the emotion engine. Specifically, it recalculates task priorities and updates the schedule based on the emotional state. Input: Emotional state data. Output: Updated task list.

[1256] Step 16:

[1257] The server sends the adjusted task information to the terminal, which displays it to the user. Specifically, the server sends the updated task list to the terminal, which displays it. Input: Updated task list. Output: Display to the user.

[1258] Step 17:

[1259] To check the entire schedule, the user makes a schedule acquisition request on the terminal. Specifically, the user presses the "Check Schedule" button on the terminal. Input: Schedule acquisition request. Output: Schedule acquisition request.

[1260] Step 18:

[1261] The terminal sends the request to the server, which retrieves all tasks from the user's schedule. Specifically, the schedule retrieval request is sent to the server as an HTTP request, and the server retrieves the schedule data from the database. Input: Schedule retrieval request. Output: Retrieved schedule data.

[1262] Step 19:

[1263] The server returns the acquired schedule data to the terminal as a list. Specifically, it formats the schedule data and sends it to the terminal in list format. Input: Acquired schedule data. Output: Schedule list data.

[1264] Step 20:

[1265] The terminal displays the acquired schedule information to the user. Specifically, the schedule information is displayed to the user in list format. Input: Schedule list data. Output: Schedule displayed to the user.

[1266] (Application example 2)

[1267] 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."

[1268] Conventional task management systems and reminder generation systems simply set task information and reminders without considering the user's emotional state. As a result, notifications are sent without considering the user's mental state and emotions, which can easily cause stress and discomfort. In particular, in virtual stores, customers' emotional state has a significant impact on their purchasing motivation and experience, so appropriate emotional responses are required. Furthermore, existing systems lacked the ability to adjust task priorities based on the user's emotions, which placed a heavy burden on users.

[1269] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving task information from a user, means for generating tasks based on the task information, means for saving the generated tasks as a schedule, means for generating reminders based on the schedule, means for notifying the user of the generated reminders, means for recognizing the user's emotional state, and means for adjusting notification content and task management based on the emotional state. This enables appropriate task management and reminder notifications based on the user's emotional state. In particular, in a virtual store, it becomes possible to monitor customers' emotional states in real time and take appropriate measures to improve their experience.

[1270] "Task information" is information about work or schedule that a user wants to manage or execute.

[1271] A "task" is an action or activity that a user must perform to achieve a particular purpose or goal.

[1272] A "schedule" refers to managing a user's tasks and plans and organizing them in terms of time.

[1273] A "reminder" is a record or information that notifies a user to perform a specific task or schedule and urges the user not to forget.

[1274] "Emotional state" refers to the user's current state of mind or mood, including stress, relaxation, excitement, fatigue, etc.

[1275] "Emotion recognition" is the process of determining a user's current emotional state using technologies such as voice recognition and facial expression analysis.

[1276] "Notification content" is information displayed or communicated to the user, including reminders and important messages.

[1277] "Task management" refers to a series of tasks that a user sets up, such as creating, saving, organizing, prioritizing, and generating reminders for tasks.

[1278] A "virtual store" is an e-commerce store operated on the Internet, where users can browse and purchase products online.

[1279] The present invention relates to a system for efficiently managing a user's tasks and generating reminders based on the user's emotional state. The system is configured as follows.

[1280] System Configuration

[1281] The system mainly consists of a server and a terminal. The server contains a database, an emotion recognition engine, and a reminder generation function. The terminal acts as a user interface, allowing users to input task information, display reminders, and acquire emotional states.

[1282] Hardware

[1283] Devices: Smartphones, tablets, computers, etc.

[1284] Server: High-performance data processing server

[1285] software

[1286] Database Management: Firebase Firestore

[1287] Emotion recognition: Google Cloud Natural Language API

[1288] Notification system: Firebase Cloud Messaging (FCM)

[1289] Program Description

[1290] 1. Add a task:

[1291] The user uses the device to input task information, including the task name and due date. In addition, the device also accepts free text input from the user (e.g., "I'm a little excited today because I want to buy this present."). The device then sends this information to the server.

[1292] 2. Emotion recognition:

[1293] The server analyzes the text using the Google Cloud Natural Language API to determine the user's emotional state. Based on the emotion recognition results, the server determines the priority of the task. For example, if the user is feeling stressed, the task will be assigned a low priority.

[1294] 3. Task creation and saving:

[1295] The server generates tasks based on the received information and saves them as schedules in Firebase Firestore, including task name, due date, sentiment score, priority, etc.

[1296] 4. Reminder generation:

[1297] When a task is about to expire, the server generates a reminder and sends a notification to the user's device using Firebase Cloud Messaging. The reminder date is set to a random date between 1 and 3 days before the task's due date, and the content of the notification is also adjusted based on the user's emotional state.

[1298] Specific examples

[1299] For example, if a user enters the task "I want to find a new gift" in a virtual store and comments, "I'm a little nervous today," the server will use an emotion recognition engine to recognize the emotion of "nervous." As a result, the server will assign a low priority to the task and send a gentle reminder message to the user. For example, a message such as, "Take your time looking. I'm sure you'll find a nice gift" will be sent to the user's device.

[1300] Example prompts to input to a generative AI model:

[1301] "If users express negative emotions, provide a supportive message to ease those feelings."

[1302] "If they're feeling stressed while searching for a gift, recommend a product that will help them relax."

[1303] This system will enable users to manage tasks and receive reminder notifications appropriately according to their emotions, making daily life and online shopping more comfortable.

[1304] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1305] Step 1:

[1306] The user inputs task information using a terminal. The input includes the task name and deadline date. In addition, free text input (e.g., "I'm a little excited because I want to buy this present today") is also accepted to grasp the emotional state. Here, the input data is the task name, deadline date, and emotional text, and the terminal sends this data to the server.

[1307] Step 2:

[1308] The server processes the received task information and emotion text. Specifically, it sends the emotion text to the Google Cloud Natural Language API and analyzes the user's emotional state. This analysis outputs an emotion score. For example, a positive emotion score is obtained from the text "I'm feeling a little excited today."

[1309] Step 3:

[1310] The server prioritizes the task based on the sentiment score: for a positive sentiment score, it sets the priority as "high" and for a negative sentiment score, it sets the priority as "low." It then creates a task with this priority and stores it in Firebase Firestore.

[1311] Step 4:

[1312] The server generates reminders based on the schedule. The reminder date is set to a random date between 1 and 3 days before the task's due date. This reminder information is sent to the user's device via Firebase Cloud Messaging. The due date and sentiment score are input data to generate the reminder, and the reminder information is output.

[1313] Step 5:

[1314] The server adjusts the content of the reminder notification based on the user's emotional state. If the emotional score is low, a gentle reminder notification is generated, and if the emotional score is high, a normal notification is generated. Specifically, the message content of the reminder notification changes depending on the emotional state. For example, if the emotional score is negative, the message generated is, "Take your time and look around. I'm sure you'll find a pleasant gift."

[1315] Step 6:

[1316] The generated reminders and notifications are displayed on the user's device, allowing the user to receive timely reminders and support tailored to their emotional state.

[1317] These steps will enable appropriate task management and reminder notifications based on the user's emotional state, providing a pleasant user experience.

[1318] 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.

[1319] 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.

[1320] 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.

[1321] [Fourth embodiment]

[1322] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1323] 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.

[1324] 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).

[1325] 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.

[1326] 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.

[1327] 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).

[1328] 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.

[1329] 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.

[1330] 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.

[1331] 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.

[1332] 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.

[1333] 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.

[1334] 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."

[1335] The present invention relates to a system for efficiently managing user tasks and generating reminders. The system of the present invention has the functions of generating tasks based on user input, saving them as schedules, and generating and notifying reminders when task deadlines approach.

[1336] Adding a task

[1337] When a user wants to add a new task, they enter the task name and deadline. The device receives this and sends the task information to the server. The server creates a new task based on the received information and adds it to the user's schedule list. For example, if a user sets a task called "Meeting" for October 15, 2023, the system will create a task based on this information and save it in the schedule. If the task is added successfully, the server will return a confirmation message to the device.

[1338] Generate reminders

[1339] When a user requests to create a reminder, the device sends a reminder creation request to the server. The server retrieves all tasks from the user's schedule and creates a reminder for each task. The reminder date is set to a random date 1 to 3 days before the task's due date. For example, a "Meeting" reminder is set for October 12, 2023. The generated reminder is notified to the user and displayed on the device.

[1340] Get schedule

[1341] When a user wants to check their entire schedule, the device sends a schedule retrieval request to the server. The server retrieves all of the user's tasks and returns them to the device as a list. The device displays this list to the user, allowing the user to easily check the schedule. For example, if the user's schedule includes a "meeting" and a "presentation," the details will be displayed on the device.

[1342] In this way, the system of the present invention supports users in efficiently managing tasks and ensuring that deadlines are not forgotten. Specifically, it automates the processes of task creation, saving, reminder creation and notification, and schedule acquisition and display, thereby reducing the burden on users.

[1343] The processing flow will be explained below.

[1344] Adding a task

[1345] Step 1:

[1346] The user inputs the task name and deadline date into the terminal.

[1347] Step 2:

[1348] The terminal receives input from the user and requests the add_task method from the server.

[1349] Step 3:

[1350] The server creates a new task based on the received task name and due date. Specifically, it constructs the task information in a dictionary format (e.g., {"task_name": "Meeting", "due_date": datetime(2023, 10, 15)}).

[1351] Step 4:

[1352] The server adds the generated task information to the user's schedule list.

[1353] Step 5:

[1354] The server will send a confirmation message back to the terminal indicating that the task was added successfully.

[1355] Step 6:

[1356] The terminal displays a confirmation message to the user.

[1357] Generate reminders

[1358] Step 1:

[1359] The user requests that a reminder be created.

[1360] Step 2:

[1361] The device calls the generate_reminders method to send a reminder generation request to the server.

[1362] Step 3:

[1363] The server retrieves all tasks from the user's schedule.

[1364] Step 4:

[1365] For each task, the server randomly selects a date between 1 and 3 days before the due date and generates a reminder. For example, if the due date for a "Meeting" is October 15, 2023, the server sets the reminder for October 12, 13, or 14, 2023.

[1366] Step 5:

[1367] The server stores the generated reminders in a list, keeping only tasks beyond the current date.

[1368] Step 6:

[1369] The server returns the reminder list to the terminal.

[1370] Step 7:

[1371] The terminal displays the received reminder list to the user.

[1372] Get schedule

[1373] Step 1:

[1374] The user requests confirmation of the entire schedule.

[1375] Step 2:

[1376] The terminal calls the get_schedule method to send a schedule acquisition request to the server.

[1377] Step 3:

[1378] The server gets all the user's tasks from the schedule list.

[1379] Step 4:

[1380] The server returns the acquired schedule list to the terminal.

[1381] Step 5:

[1382] The terminal displays the received schedule list to the user. For example, if the schedule includes "meeting" and "presentation," the details of these are displayed.

[1383] Example 1

[1384] 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."

[1385] Conventional task management systems have the drawback of requiring users to manually add tasks and set reminders, and the fixed reminder dates limit flexible notification options. Furthermore, they lack the functionality to easily check the entire schedule, making it difficult for users to efficiently manage tasks.

[1386] 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.

[1387] In this invention, the server includes a means for receiving task information from a user, a means for generating a task based on the task information, a means for storing the generated task in a database, a means for generating a message confirming that the task has been successfully added and notifying the user, a means for generating a reminder based on the schedule, and a means for notifying the user of the generated reminder. This allows the user to efficiently manage tasks and receive flexible reminder notifications. It also allows the user to easily check the entire schedule in list format.

[1388] "User" refers to an individual or organization that uses the system.

[1389] "Task information" refers to information such as task name and deadline date that a user enters into the system.

[1390] A "task" refers to a schedule or work item that a user registers in the system.

[1391] "Database" refers to the storage device within the system that stores and manages data such as generated tasks and reminders.

[1392] "Schedule" refers to list or calendar-style data in which a user's tasks are stored in a list.

[1393] "Reminder" refers to a function or notification that notifies a user when a task deadline is approaching.

[1394] "Confirmation message" refers to a notification that informs the user that the task was successfully added.

[1395] "List format" refers to a format in which each task or reminder is displayed in order.

[1396] "Notification" refers to a means of communicating information from the system to the user.

[1397] "Means" refers to any process, function, or combination thereof necessary for carrying out the invention.

[1398] The present invention relates to a system for efficiently managing user tasks and generating reminders. This system has the functions of generating tasks based on user input, saving them in a database, and generating and notifying reminders when the task deadline approaches.

[1399] Hardware and software used

[1400] Server: Uses hardware suitable for high-performance processing (e.g., AWS EC2, Microsoft Azure, etc.) and a database for managing and storing data (e.g., MySQL, MongoDB, etc.).

[1401] Terminal: A user device such as a smartphone, tablet, or PC. These devices include an interface through which the user enters task information.

[1402] software:

[1403] Front-end: Building the user interface using React, Vue.js, etc.

[1404] Backend: Build the API using Node.js, Python (Flask, Django, etc.).

[1405] Database Management: SQL (MySQL, PostgreSQL, etc.) or NoSQL (MongoDB, etc.) databases.

[1406] Adding a task

[1407] When a user adds a new task, they enter the task name and deadline date. The device receives this and sends the task information to the server. The server analyzes the received information and creates a new task. The created task is saved in the database. The server sends a message to the device confirming that the task was successfully added, notifying the user.

[1408] Examples:

[1409] When a user wants to add a new task, they enter the task name and due date into the terminal and send it to the server. The server receives this information, creates a new task, and saves it in the schedule. Example: Task name "Meeting", due date "October 15, 2023"

[1410] Generate reminders

[1411] When a user requests a reminder to be generated, the device sends a reminder generation request to the server. The server retrieves all tasks from the user's schedule and generates a reminder for each task. The reminder date is set to a random date between 1 and 3 days before the task's due date. The generated reminder is notified to the user and displayed on the device.

[1412] Examples:

[1413] When a user wants to create a reminder, they send a request to the server from their device. The server retrieves all tasks and sets a random date for each task. Example: Set a "Meeting" reminder for October 12, 2023

[1414] Get schedule

[1415] When a user wants to check his / her entire schedule, the terminal sends a schedule acquisition request to the server. The server acquires all the user's tasks and returns them to the terminal in a list format. The terminal displays this list to the user, allowing the user to easily check the schedule.

[1416] Examples:

[1417] When a user wants to check the entire schedule, they send a schedule request from their device to the server. The server retrieves all tasks and returns a list. For example, details of "meetings" and "presentations" are displayed.

[1418] This allows the system of the present invention to support users in efficiently managing tasks and ensuring that deadlines are not forgotten. Specifically, the system automates the processes of task creation, saving, reminder creation and notification, and schedule acquisition and display, thereby reducing the burden on users.

[1419] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1420] Adding a task

[1421] Step 1:

[1422] The user enters the task name and due date.

[1423] Input: The user enters the "task name" and "due date" into the terminal.

[1424] Output: The task name and due date will be displayed on the terminal.

[1425] Step 2:

[1426] The terminal acquires the input task information and sends it to the server. Specifically, it sends the data as an HTTP request.

[1427] Input: The terminal obtains task information input by the user.

[1428] Output: The HTTP request to send to the server.

[1429] Step 3:

[1430] The server analyzes the received task information and creates a new task. It parses the JSON format data and creates a task object.

[1431] Input: HTTP request for task information sent from the device.

[1432] Output: The created task object.

[1433] Step 4:

[1434] The server stores the created task objects in a database, either SQL or NoSQL.

[1435] Input: The created task object.

[1436] Output: Task data stored in a database.

[1437] Step 5:

[1438] The server generates and returns to the terminal a confirmation message indicating that the task was successfully added.

[1439] Input: Database saved results of the task.

[1440] Output: A confirmation message.

[1441] Step 6:

[1442] The terminal displays to the user the confirmation message received from the server.

[1443] Input: The confirmation message sent by the server.

[1444] Output: The confirmation message displayed to the user.

[1445] Generate reminders

[1446] Step 1:

[1447] The user presses a button to request the creation of a reminder.

[1448] Input: A user request to create a reminder.

[1449] Output: Triggers a request by the device to generate a reminder.

[1450] Step 2:

[1451] The device sends a reminder generation request to the server as an HTTP request.

[1452] Input: A request from the user to create a reminder.

[1453] Output: The HTTP request to send to the server.

[1454] Step 3:

[1455] The server retrieves all tasks for the user from the database, using an SQL query to retrieve all tasks associated with the user ID.

[1456] Input: Reminder generation request and user ID.

[1457] Output: All task data for the user.

[1458] Step 4:

[1459] The server sets a random reminder for each task, 1-3 days before the due date, using an algorithm to generate the random date.

[1460] Input: The user's task data.

[1461] Output: The set reminder information.

[1462] Step 5:

[1463] The server generates the generated reminder as a notification object and sends a notification to the user.

[1464] Input: The set reminder information.

[1465] Output: A notification object.

[1466] Step 6:

[1467] The notification received by the terminal is displayed on the user's screen.

[1468] Input: The notification object sent by the server.

[1469] Output: The reminder notification shown to the user.

[1470] Get schedule

[1471] Step 1:

[1472] The user presses the schedule display button.

[1473] Input: A user request to view a schedule.

[1474] Output: Triggers a request to view the schedule by the terminal.

[1475] Step 2:

[1476] The terminal sends a schedule acquisition request to the server as an HTTP request.

[1477] Input: Schedule retrieval request from user.

[1478] Output: The HTTP request to send to the server.

[1479] Step 3:

[1480] The server retrieves all tasks for the user from the database and executes an SQL query to retrieve all tasks.

[1481] Input: Schedule retrieval request and user ID.

[1482] Output: All task data for the user.

[1483] Step 4:

[1484] The server formats the acquired task information into a list and returns it to the terminal as a JSON response.

[1485] Input: The user's task data.

[1486] Output: Task information formatted as a list.

[1487] Step 5:

[1488] The device parses the received JSON data and displays it in list format on the user's screen.

[1489] Input: Task information in list format sent from the server.

[1490] Output: The schedule list displayed to the user.

[1491] (Application example 1)

[1492] 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."

[1493] Efficient task management and reminder notifications are needed in the field. In particular, in work environments such as factories, it is important for workers to quickly enter task information, check progress, and receive reminders for important tasks. However, existing systems make it difficult to achieve these tasks without hassle, resulting in a decrease in work efficiency.

[1494] 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.

[1495] In this invention, the server includes means for receiving task information from a user, means for generating tasks based on the task information, means for saving the generated tasks as a schedule, means for generating reminders based on the schedule, means for notifying the user of the generated reminders, means for transmitting task information to the server by a computer device, means for receiving voice input from a smart device, and means for displaying task information and reminders on a display of the smart device, thereby enabling a worker to quickly add tasks through voice input and check task information and reminders in real time on the display of the smart device.

[1496] A "user" is an individual or entity that uses the system to manage tasks and receive reminder notifications.

[1497] "Task information" is detailed information such as the name and deadline of a task added by a user.

[1498] The term "means" refers to a device, a program, or a method for realizing a specific function or process.

[1499] The "server" is a computer system that processes task information sent by users, generates tasks, saves schedules, and generates and notifies reminders.

[1500] A "schedule" is a list or plan by which generated tasks are managed over time.

[1501] A "reminder" is a warning or alert that notifies a user when a task is about to expire.

[1502] A "computing device" is an electronic device that a user uses to send task information to a server.

[1503] A "smart device" is an electronic device that has the ability to interact with a user through voice input and a display.

[1504] "Voice input" is an operation means for recognizing the user's voice and processing it as text information.

[1505] A "display" is a display device that allows a user to visually confirm information.

[1506] The present invention relates to a system that enables factory workers to efficiently manage tasks and receive reminder notifications using smart devices. Hereinafter, embodiments of the present invention will be described in detail.

[1507] System Overview

[1508] The system of the present invention allows users (workers) to input task information using their smart devices, generates tasks based on that information, and saves them as a schedule. Furthermore, when a task deadline approaches, the system generates a reminder and notifies the worker. This system consists of a server, a computer, and a smart device.

[1509] Hardware and software used

[1510] 1. Server

[1511] The server is a computer system that generates tasks based on task information sent by users, saves them as schedules, and generates and notifies reminders. For example, a program written in Python runs on the server.

[1512] 2. Computer equipment

[1513] The computing device is an electronic device that the user uses to send task information to the server, such as a smartphone or tablet.

[1514] 3. Smart Devices

[1515] A smart device is an electronic device that has the ability to interact with a user through voice input or a display, such as Google Glass or other smart glasses.

[1516] Program processing

[1517] Adding a task

[1518] When a user adds a new task, they specify the task name and due date using voice input or touch operation on their smart device. This information is displayed on the display and can be confirmed. The smart device then sends the task information to the server via a computer. The server uses this information to create a new task and adds it to the schedule list. For example, if a user sets a task called "Parts Inspection" for October 15, 2023, the server uses this information to create a task and saves it in the schedule.

[1519] Generate reminders

[1520] When a task deadline approaches, the server retrieves all tasks from the schedule and generates a reminder for each task. The reminder date is set to a random date 1 to 3 days before the task deadline. For example, a reminder for "Parts Inspection" may be set for October 13, 2023. The server notifies the smart device of the generated reminder, and the worker receives the reminder on the display.

[1521] Get schedule

[1522] When a user wants to check their entire schedule, they send a schedule acquisition request from their smart device to the server. The server acquires all of the user's tasks and returns them as a list to the smart device. The smart device displays this list on its display, allowing the user to easily check their schedule.

[1523] Specific examples

[1524] Example prompts to input to a generative AI model:

[1525] "Add task: 'Quality Check', due date: October 16, 2023"

[1526] "Generate a reminder"

[1527] View schedule

[1528] When Worker A at a factory uses smart glasses and gives voice instructions such as "Add the following task: 'Parts inspection', Deadline: October 20, 2023," the task is added to the server and a reminder is sent to the smart glasses.

[1529] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1530] Step 1:

[1531] The user inputs task information (task name and due date) using a smart device by voice or touch operation. The input information is converted into digital data by the smart device and displayed for confirmation.

[1532] Input: Task name and due date entered by the user via voice or touch

[1533] Output: Digital task information (task name and due date)

[1534] Step 2:

[1535] The smart device sends the input task information to the server via the computer, and the task information arrives at the server via a network connection.

[1536] Input: Digital data (task information) converted by smart device

[1537] Output: Task information sent to the server

[1538] Step 3:

[1539] The server creates a new task based on the received task information and adds it to the user's schedule list. The task information is saved in the database.

[1540] Input: Task information sent to the server

[1541] Output: Tasks saved in the database (task name, due date, status)

[1542] Step 4:

[1543] When a user requests that a reminder be generated, the smart device sends the request to the server via the computing device.

[1544] Input: User request to create a reminder

[1545] Output: Reminder generation request sent to the server

[1546] Step 5:

[1547] The server retrieves all tasks from the schedule list and sets a reminder date based on the due date of each task, which is set to a random date between 1 and 3 days before the due date.

[1548] Input: Task information stored in the schedule list (task name, due date, status)

[1549] Output: Generated reminder information (reminder date, task name)

[1550] Step 6:

[1551] The server notifies the smart device of the generated reminder information, which is then displayed on the smart device's display, visually informing the user of the reminder content.

[1552] Input: Generated reminder information

[1553] Output: Reminder content displayed on smart device

[1554] Step 7:

[1555] When a user makes a request to view the entire schedule, the smart device sends the request to the server via the computing device.

[1556] Input: User request to retrieve schedule

[1557] Output: Schedule retrieval request sent to the server

[1558] Step 8:

[1559] The server retrieves all tasks from the user's schedule list, returns them to the smart device in a list format, and the smart device displays the retrieved task list on its display, providing a visual representation to the user.

[1560] Input: All task information stored in the user's schedule list

[1561] Output: Task list displayed on a smart device

[1562] 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.

[1563] The present invention relates to a system that efficiently manages users' tasks and generates reminders by combining an emotion engine with the system to enable appropriate notifications and task management based on the user's emotions. The system of the present invention has the functions of generating tasks based on user input and saving them as a schedule, as well as generating and notifying reminders when task deadlines approach. It also includes a function that recognizes the user's emotions using the emotion engine and adjusts task management and reminder notifications based on those emotions.

[1564] Adding a task

[1565] When a user wants to add a new task, they enter the task name and deadline. The device receives this and sends the task information to the server. The server creates a new task based on the received information and adds it to the user's schedule list. For example, if a user sets a task called "Meeting" for October 15, 2023, the system will create a task based on this information and save it in the schedule. If the task is added successfully, the server will return a confirmation message to the device.

[1566] Generate reminders

[1567] When a user requests to generate a reminder, the device sends a reminder generation request to the server. The server retrieves all tasks from the user's schedule and generates a reminder for each task. The reminder date is set to a random date 1 to 3 days before the task's due date. For example, for a "Meeting" on October 15, 2023, a reminder is set for October 12, 2023. The generated reminder is notified to the user and displayed on the device.

[1568] Use of emotion engine

[1569] The system also includes an emotion engine that recognizes the user's emotions. The emotion engine uses technologies such as voice recognition and facial expression analysis to determine the user's current emotional state. For example, if the server detects that the user is feeling stressed, it will adjust the content of the reminder notification and deliver it in a gentler tone. If the user is relaxed, it will deliver a normal notification.

[1570] Task Priority Adjustment

[1571] Based on emotion recognition by the emotion engine, the server can automatically adjust the importance and priority of the user's tasks. For example, if the user feels tired, it will postpone less important tasks.

[1572] Get schedule

[1573] When a user wants to check their entire schedule, the terminal sends a schedule retrieval request to the server. The server retrieves all of the user's tasks and returns them to the terminal as a list. The terminal displays the list to the user, allowing the user to easily check their schedule. For example, if the user's schedule includes a "meeting" and a "presentation," the details of these will be displayed on the terminal. In this way, by realizing appropriate task management and reminder notifications based on the user's emotions, the invention can improve the user's convenience and quality of life.

[1574] The processing flow will be explained below.

[1575] Adding a task

[1576] Step 1:

[1577] The user inputs the task name and deadline date into the terminal.

[1578] Step 2:

[1579] The terminal receives input from the user and requests the add_task method from the server.

[1580] Step 3:

[1581] The server creates a new task based on the received task name and due date. Specifically, it constructs the task information in a dictionary format (e.g., {"task_name": "Meeting", "due_date": datetime(2023, 10, 15)}).

[1582] Step 4:

[1583] The server adds the generated task information to the user's schedule list.

[1584] Step 5:

[1585] The server will send a confirmation message back to the terminal indicating that the task was added successfully.

[1586] Step 6:

[1587] The terminal displays a confirmation message to the user.

[1588] Generate reminders

[1589] Step 1:

[1590] The user requests that a reminder be created.

[1591] Step 2:

[1592] The device calls the generate_reminders method to send a reminder generation request to the server.

[1593] Step 3:

[1594] The server retrieves all tasks from the user's schedule.

[1595] Step 4:

[1596] For each task, the server randomly selects a date between 1 and 3 days before the due date and generates a reminder. For example, if the due date for a "Meeting" is October 15, 2023, the server sets the reminder for October 12, 13, or 14, 2023.

[1597] Step 5:

[1598] The server stores the generated reminders in a list, keeping only tasks beyond the current date.

[1599] Step 6:

[1600] The server returns the reminder list to the terminal.

[1601] Step 7:

[1602] The terminal displays the received reminder list to the user.

[1603] Use of emotion engine

[1604] Step 1:

[1605] The user expresses his / her emotions to the terminal by voice input or facial expression analysis.

[1606] Step 2:

[1607] The terminal invokes the emotion engine to send an emotion recognition request to the server.

[1608] Step 3:

[1609] The server uses an emotion engine to analyze the user's current emotions from their voice patterns and facial expressions.

[1610] Step 4:

[1611] The server then adjusts the content and style of the reminder notification based on the emotion recognition results. For example, if the user is feeling stressed, the server will notify them in a gentle tone.

[1612] Step 5:

[1613] The server automatically adjusts the importance and priority of tasks based on the emotion recognition results. For example, if the user feels tired, it postpones less important tasks.

[1614] Get schedule

[1615] Step 1:

[1616] The user requests confirmation of the entire schedule.

[1617] Step 2:

[1618] The terminal calls the get_schedule method to send a schedule acquisition request to the server.

[1619] Step 3:

[1620] The server gets all the user's tasks from the schedule list.

[1621] Step 4:

[1622] The server returns the acquired schedule list to the terminal.

[1623] Step 5:

[1624] The terminal displays the received schedule list to the user. For example, if the schedule includes "meeting" and "presentation," the details of these are displayed.

[1625] Example 2

[1626] 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."

[1627] Conventional task management systems did not take into account the user's emotional state when it came to notifications or adjusting task priorities. As a result, even during stressful or fatigued times, they only sent the same reminder notifications, lacking appropriate support tailored to the user's state. Furthermore, the reminder date settings were fixed, making it difficult to respond to situations requiring flexible management. This could have a negative impact on users' work efficiency and quality of life.

[1628] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1629] In this invention, the server includes means for receiving task information from a user, means for generating tasks based on the task information, means for saving the generated tasks as a schedule, means for generating reminders based on the schedule, means for notifying the user of the generated reminders, means for determining the user's emotions based on emotion analysis technology, and means for adjusting notification content and task priority based on the user's emotions. This enables appropriate notifications and task management according to the user's emotional state, thereby improving the user's work efficiency and quality of life.

[1630] "Task information" is the name of the task and related information such as the deadline entered by the user.

[1631] A "task" is an operation or plan that a user must perform, and is an element that is managed based on a schedule.

[1632] A "schedule" is a chronological list or calendar for managing a user's tasks.

[1633] A "reminder" is a message that notifies the user not to forget a particular task or event.

[1634] "Emotion analysis technology" is a technology that determines a user's current emotional state using technologies such as voice recognition and facial expression analysis.

[1635] "Notifications" are messages or alerts that the system sends to inform the user.

[1636] "Priority adjustment" is an operation that changes the importance and processing order of tasks based on the user's emotional state and other conditions.

[1637] "User State" refers to the user's current mental and emotional state.

[1638] The present invention relates to a system that combines an emotion engine with a system that efficiently manages user tasks and generates reminders, enabling appropriate notifications and task management based on the user's emotions. The system of the present invention uses specific hardware and software to perform a series of data processing.

[1639] The main components of the system include a user terminal, a server, and an emotion engine. The user terminal accepts input from the user and sends it to the server. The server processes the data based on the received information and generates and manages tasks and reminders. The emotion engine uses voice recognition and facial expression analysis technology to determine the user's emotions and uses this information to adjust notification content and task priority.

[1640] The specific processing procedure is as follows.

[1641] Adding a task

[1642] To add a new task, the user enters the task name and deadline. For example, the user enters "Meeting" and "October 15, 2023" into the terminal. The terminal receives this and sends the task information to the server. The server generates a new task based on the received information and adds it to the user's schedule list. After the task is successfully added, the server returns a confirmation message to the terminal and displays it to the user.

[1643] Generate reminders

[1644] The user presses the "Generate Reminder" button on the device to request a reminder. For example, select "Generate Reminder." The device sends the request to the server, which retrieves all tasks from the user's schedule and generates a reminder. The reminder date is set to a random date 1 to 3 days before the task's due date. The generated reminder is notified to the user and displayed on the device.

[1645] Use of emotion engine

[1646] The server uses an emotion engine to determine the user's emotional state. It uses emotion analysis technology to identify emotions through voice recognition and facial expression analysis. For example, if a user types, "I'm stressed today," the server's emotion engine analyzes it and determines that stress is high. Based on this, the server adjusts the content of the reminder notification and sends a gentle message such as, "Tomorrow is a meeting day. Please stay calm and proceed."

[1647] Task Priority Adjustment

[1648] Based on emotion recognition by the emotion engine, the server automatically adjusts the importance and priority of tasks. For example, if the user reports that they are "tired," the server will postpone the "organizing documents" task until the next day. The device then notifies the user of the adjustment results.

[1649] Get schedule

[1650] To check the overall status of their schedule, a user makes a schedule acquisition request on the terminal. For example, they select "Check Schedule." The terminal sends the request to the server, which acquires all of the user's tasks and generates a list. The list is sent to the terminal and displayed to the user.

[1651] Prompt Sentence Examples

[1652] 1. Add task prompt: "Schedule a meeting for October 15, 2023."

[1653] 2. Reminder generation prompt: "Set a reminder"

[1654] 3. Emotion-aware prompt: "Change the notification content to a gentler tone when the user feels stressed."

[1655] 4. Task Priority Adjustment Prompt: "If the user feels fatigued, postpone less important tasks."

[1656] 5. Schedule retrieval prompt: "Show the entire schedule"

[1657] The present invention realizes appropriate task management and notification functions according to the user's emotional state, thereby improving the user's work efficiency and quality of life.

[1658] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1659] Step 1:

[1660] To add a new task, a user enters the task name and deadline into the terminal. Specifically, the user enters "Meeting" and "October 15, 2023" into the input form on the terminal and presses the "Add" button. Input: Task name, deadline. Output: Task addition request.

[1661] Step 2:

[1662] The device receives the entered task information and sends it to the server. Specifically, the device sends the task name and deadline entered by the user to the server as an HTTP request. Input: Task addition request. Output: Request data containing task information.

[1663] Step 3:

[1664] The server receives the information and creates a new task. Specifically, the server saves the received task name and deadline date in the database and creates a new task entry. Input: Request data containing task information. Output: New task entry.

[1665] Step 4:

[1666] The server adds the created task to the user's schedule list. As a concrete action, it associates the task entry stored in the database with the user's schedule list. Input: New task entry. Output: Updated schedule list.

[1667] Step 5:

[1668] After the task is successfully added, the server returns a confirmation message to the terminal. Specifically, the server generates a message saying "Task successfully added" and sends it to the terminal. Input: Updated schedule list. Output: Confirmation message.

[1669] Step 6:

[1670] The terminal displays a confirmation message to the user. Specifically, the terminal displays the confirmation message received from the server in a dialog or grid to notify the user. Input: Confirmation message. Output: Notification to the user.

[1671] Step 7:

[1672] The user presses the "Create reminder" button on the device to request the creation of a reminder. Specifically, the "Create reminder" button is selected and a request is sent to the server. Input: Reminder creation request. Output: Reminder creation request.

[1673] Step 8:

[1674] The device sends a reminder creation request to the server. Specifically, it sends the request data to the server as an HTTP request. Input: Reminder creation request. Output: Request data.

[1675] Step 9:

[1676] The server retrieves all tasks from the user's schedule and generates reminders for each task. Specifically, the server queries the user's schedule list from the database and sets reminders for each task 1-3 days before its due date. Input: User's schedule list. Output: Reminder setting list.

[1677] Step 10:

[1678] The server notifies the user of the created reminder. Specifically, it generates a reminder notification message and sends it to the device. Input: Reminder setting list. Output: Notification message.

[1679] Step 11:

[1680] The device displays the generated reminder information to the user. Specific actions include displaying the reminder information in a popup or notification bar on the device. Input: Notification message. Output: Displaying the reminder to the user.

[1681] Step 12:

[1682] The server uses an emotion engine to determine the user's emotional state. Specifically, the server analyzes the user's input using voice recognition and facial expression analysis technology to identify the user's emotional state. Input: User's voice or facial expression data. Output: Emotional state data.

[1683] Step 13:

[1684] The server adjusts the content of the reminder notification based on the emotion determined by the emotion engine. Specifically, it selects a message template according to the emotional state and generates the notification content. Input: Emotional state data. Output: Emotion-based notification message.

[1685] Step 14:

[1686] The server sends a reminder notification based on the emotion to the device, which then displays it to the user. Specifically, the server sends a notification message based on the emotion to the device, which then displays it. Input: A notification message based on the emotion. Output: Display to the user.

[1687] Step 15:

[1688] The server automatically adjusts the importance and priority of tasks based on emotion recognition by the emotion engine. Specifically, it recalculates task priorities and updates the schedule based on the emotional state. Input: Emotional state data. Output: Updated task list.

[1689] Step 16:

[1690] The server sends the adjusted task information to the terminal, which displays it to the user. Specifically, the server sends the updated task list to the terminal, which displays it. Input: Updated task list. Output: Display to the user.

[1691] Step 17:

[1692] To check the entire schedule, the user makes a schedule acquisition request on the terminal. Specifically, the user presses the "Check Schedule" button on the terminal. Input: Schedule acquisition request. Output: Schedule acquisition request.

[1693] Step 18:

[1694] The terminal sends the request to the server, which retrieves all tasks from the user's schedule. Specifically, the schedule retrieval request is sent to the server as an HTTP request, and the server retrieves the schedule data from the database. Input: Schedule retrieval request. Output: Retrieved schedule data.

[1695] Step 19:

[1696] The server returns the acquired schedule data to the terminal as a list. Specifically, it formats the schedule data and sends it to the terminal in list format. Input: Acquired schedule data. Output: Schedule list data.

[1697] Step 20:

[1698] The terminal displays the acquired schedule information to the user. Specifically, the schedule information is displayed to the user in list format. Input: Schedule list data. Output: Schedule displayed to the user.

[1699] (Application example 2)

[1700] 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."

[1701] Conventional task management systems and reminder generation systems simply set task information and reminders without considering the user's emotional state. As a result, notifications are sent without considering the user's mental state and emotions, which can easily cause stress and discomfort. In particular, in virtual stores, customers' emotional state has a significant impact on their purchasing motivation and experience, so appropriate emotional responses are required. Furthermore, existing systems lacked the ability to adjust task priorities based on the user's emotions, which placed a heavy burden on users.

[1702] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving task information from a user, means for generating tasks based on the task information, means for saving the generated tasks as a schedule, means for generating reminders based on the schedule, means for notifying the user of the generated reminders, means for recognizing the user's emotional state, and means for adjusting notification content and task management based on the emotional state. This enables appropriate task management and reminder notifications based on the user's emotional state. In particular, in a virtual store, it becomes possible to monitor customers' emotional states in real time and take appropriate measures to improve their experience.

[1703] "Task information" is information about work or schedule that a user wants to manage or execute.

[1704] A "task" is an action or activity that a user must perform to achieve a particular purpose or goal.

[1705] A "schedule" refers to managing a user's tasks and plans and organizing them in terms of time.

[1706] A "reminder" is a record or information that notifies a user to perform a specific task or schedule and urges the user not to forget.

[1707] "Emotional state" refers to the user's current state of mind or mood, including stress, relaxation, excitement, fatigue, etc.

[1708] "Emotion recognition" is the process of determining a user's current emotional state using technologies such as voice recognition and facial expression analysis.

[1709] "Notification content" is information displayed or communicated to the user, including reminders and important messages.

[1710] "Task management" refers to a series of tasks that a user sets up, such as creating, saving, organizing, prioritizing, and generating reminders for tasks.

[1711] A "virtual store" is an e-commerce store operated on the Internet, where users can browse and purchase products online.

[1712] The present invention relates to a system for efficiently managing a user's tasks and generating reminders based on the user's emotional state. The system is configured as follows.

[1713] System Configuration

[1714] The system mainly consists of a server and a terminal. The server contains a database, an emotion recognition engine, and a reminder generation function. The terminal acts as a user interface, allowing users to input task information, display reminders, and acquire emotional states.

[1715] Hardware

[1716] Devices: Smartphones, tablets, computers, etc.

[1717] Server: High-performance data processing server

[1718] software

[1719] Database Management: Firebase Firestore

[1720] Emotion recognition: Google Cloud Natural Language API

[1721] Notification system: Firebase Cloud Messaging (FCM)

[1722] Program Description

[1723] 1. Add a task:

[1724] The user uses the device to input task information, including the task name and due date. In addition, the device also accepts free text input from the user (e.g., "I'm a little excited today because I want to buy this present."). The device then sends this information to the server.

[1725] 2. Emotion recognition:

[1726] The server analyzes the text using the Google Cloud Natural Language API to determine the user's emotional state. Based on the emotion recognition results, the server determines the priority of the task. For example, if the user is feeling stressed, the task will be assigned a low priority.

[1727] 3. Task creation and saving:

[1728] The server generates tasks based on the received information and saves them as schedules in Firebase Firestore, including task name, due date, sentiment score, priority, etc.

[1729] 4. Reminder generation:

[1730] When a task is about to expire, the server generates a reminder and sends a notification to the user's device using Firebase Cloud Messaging. The reminder date is set to a random date between 1 and 3 days before the task's due date, and the content of the notification is also adjusted based on the user's emotional state.

[1731] Specific examples

[1732] For example, if a user enters the task "I want to find a new gift" in a virtual store and comments, "I'm a little nervous today," the server will use an emotion recognition engine to recognize the emotion of "nervous." As a result, the server will assign a low priority to the task and send a gentle reminder message to the user. For example, a message such as, "Take your time looking. I'm sure you'll find a nice gift" will be sent to the user's device.

[1733] Example prompts to input to a generative AI model:

[1734] "If users express negative emotions, provide a supportive message to ease those feelings."

[1735] "If they're feeling stressed while searching for a gift, recommend a product that will help them relax."

[1736] This system will enable users to manage tasks and receive reminder notifications appropriately according to their emotions, making daily life and online shopping more comfortable.

[1737] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1738] Step 1:

[1739] The user inputs task information using a terminal. The input includes the task name and deadline date. In addition, free text input (e.g., "I'm a little excited because I want to buy this present today") is also accepted to grasp the emotional state. Here, the input data is the task name, deadline date, and emotional text, and the terminal sends this data to the server.

[1740] Step 2:

[1741] The server processes the received task information and emotion text. Specifically, it sends the emotion text to the Google Cloud Natural Language API and analyzes the user's emotional state. This analysis outputs an emotion score. For example, a positive emotion score is obtained from the text "I'm feeling a little excited today."

[1742] Step 3:

[1743] The server prioritizes the task based on the sentiment score: for a positive sentiment score, it sets the priority as "high" and for a negative sentiment score, it sets the priority as "low." It then creates a task with this priority and stores it in Firebase Firestore.

[1744] Step 4:

[1745] The server generates reminders based on the schedule. The reminder date is set to a random date between 1 and 3 days before the task's due date. This reminder information is sent to the user's device via Firebase Cloud Messaging. The due date and sentiment score are input data to generate the reminder, and the reminder information is output.

[1746] Step 5:

[1747] The server adjusts the content of the reminder notification based on the user's emotional state. If the emotional score is low, a gentle reminder notification is generated, and if the emotional score is high, a normal notification is generated. Specifically, the message content of the reminder notification changes depending on the emotional state. For example, if the emotional score is negative, the message generated is, "Take your time and look around. I'm sure you'll find a pleasant gift."

[1748] Step 6:

[1749] The generated reminders and notifications are displayed on the user's device, allowing the user to receive timely reminders and support tailored to their emotional state.

[1750] These steps will enable appropriate task management and reminder notifications based on the user's emotional state, providing a pleasant user experience.

[1751] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice 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 voice data.

[1752] 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.

[1753] 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 robot 414.

[1754] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1755] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1756] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1757] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1758] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1759] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1760] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1761] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1762] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1763] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1764] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1765] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1766] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1767] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1768] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1769] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1770] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1771] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1772] The following is further disclosed regarding the above embodiment.

[1773] (Claim 1)

[1774] means for receiving task information from a user;

[1775] means for generating a task based on the task information;

[1776] A means for saving the generated tasks as a schedule;

[1777] means for generating reminders based on the schedule;

[1778] The system includes a means for notifying a user of the generated reminder.

[1779] (Claim 2)

[1780] 10. The system of claim 1, further comprising means for setting the date of the generated reminder to a random date between 1 and 3 days before the due date of the task.

[1781] (Claim 3)

[1782] 10. The system of claim 1, further comprising means for obtaining and displaying the user's entire schedule.

[1783] "Example 1"

[1784] (Claim 1)

[1785] means for receiving task information from a user;

[1786] means for generating a task based on the task information;

[1787] a means for storing the generated tasks in a database;

[1788] means for generating and notifying a user of a message confirming that the task was successfully added;

[1789] means for generating reminders based on the schedule;

[1790] The system includes a means for notifying a user of the generated reminder.

[1791] (Claim 2)

[1792] 10. The system of claim 1, further comprising means for setting the date of the generated reminder to a random date between 1 and 3 days before the due date of the task.

[1793] (Claim 3)

[1794] 10. The system of claim 1, further comprising means for obtaining the user's entire schedule and displaying it in list form.

[1795] "Application Example 1"

[1796] (Claim 1)

[1797] means for receiving task information from a user;

[1798] means for generating a task based on the task information;

[1799] A means for saving the generated tasks as a schedule;

[1800] means for generating reminders based on the schedule;

[1801] means for notifying a user of the generated reminder;

[1802] means for transmitting task information to a server by a computer device;

[1803] a means for receiving voice input from the smart device;

[1804] A system including means for displaying task information and reminders on a display of a smart device.

[1805] (Claim 2)

[1806] 10. The system of claim 1, further comprising means for setting the date of the generated reminder to a random date between 1 and 3 days before the due date of the task.

[1807] (Claim 3)

[1808] 10. The system of claim 1, further comprising means for obtaining and displaying the user's entire schedule.

[1809] "Example 2: Combining Emotion Engines"

[1810] (Claim 1)

[1811] means for receiving task information from a user;

[1812] means for generating a task based on the task information;

[1813] A means for saving the generated tasks as a schedule;

[1814] means for generating reminders based on the schedule;

[1815] means for notifying a user of the generated reminder;

[1816] means for determining a user's emotion based on emotion analysis technology;

[1817] A means for adjusting notification content and task priority based on user emotions;

[1818] A system including:

[1819] (Claim 2)

[1820] 10. The system of claim 1, further comprising means for setting the date of the generated reminder to a random date between 1 and 3 days before the due date of the task.

[1821] (Claim 3)

[1822] 10. The system of claim 1, further comprising means for obtaining and displaying the user's entire schedule.

[1823] "Application example 2 when combining emotion engines"

[1824] (Claim 1)

[1825] means for receiving task information from a user;

[1826] means for generating a task based on the task information;

[1827] A means for saving the generated tasks as a schedule;

[1828] means for generating reminders based on the schedule;

[1829] means for notifying a user of the generated reminder;

[1830] means for recognizing the emotional state of a user;

[1831] The system includes means for adjusting notification content and task management based on said emotional state.

[1832] (Claim 2)

[1833] 10. The system of claim 1, further comprising means for setting the date of the generated reminder to a random date between 1 and 3 days before the due date of the task.

[1834] (Claim 3)

[1835] 10. The system of claim 1, further comprising means for obtaining and displaying the user's entire schedule. [Explanation of symbols]

[1836] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for receiving task information from a user; means for generating a task based on the task information; A means for saving the generated tasks as a schedule; means for generating reminders based on the schedule; The system includes a means for notifying a user of the generated reminder.

2. 10. The system of claim 1, further comprising means for setting the date of the generated reminder to a random date between 1 and 3 days before the due date of the task.

3. 10. The system of claim 1, further comprising means for obtaining and displaying the user's entire schedule.

Images