System

Abstract

A system is provided.SOLUTION: The system includes an input means for collecting schedule information of a couple and routine information of a child, a generation means for generating an optimal task schedule on the basis of the collected information, a display means for displaying the generated task schedule, a monitoring means for monitoring a progress status of a task and confirming a completion status of the task, and a notification means for transmitting a reminder of the task to a user.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] While there is a wealth of information available about child-rearing, there is little information about daily housework and how to spend time outside of child-rearing. While cooperation between spouses is important in raising children, the current situation is that managing individual schedules and dividing up tasks can be difficult. This can lead to poor cooperation between spouses and an increased burden of child-rearing. The present invention aims to reduce the burden of child-rearing by enabling couples to comfortably manage the tasks required for child-rearing and efficiently adjust schedules, thereby enabling parents to enjoy raising their children without stress. [Means for solving the problem]

[0005] In order to solve the above problems, the present invention provides the following means: a system including an input means for collecting schedule information for a couple and information about a child's routine, a generation means for generating an optimal task schedule based on the collected information, a display means for displaying the generated task schedule, a monitoring means for monitoring the progress of tasks and confirming their completion status, and a notification means for sending task reminders to the user. The system also includes a storage means for saving the generated schedule in a database. Furthermore, the system includes an update means for updating the information in the database after the user completes a task. This allows couples to efficiently share tasks and raise their children without stress.

[0006] "Schedule information" is information about the couple's daily plans, working hours, holidays, individual tasks, and other timetable information.

[0007] "Routine information" is information about regular activities such as feeding a child, changing diapers, and going to bed.

[0008] "Input means" refers to an interface or device for a user to input information, and specifically includes a keyboard, mouse, touch panel, or equivalent input device.

[0009] "Generation means" refers to a program or algorithm for creating an optimal task schedule based on input schedule information and routine information.

[0010] "Display means" refers to a device or interface for visually showing the generated task schedule to the user, and specifically includes a display or smartphone screen.

[0011] "Monitoring means" refers to the functionality for tracking the progress of a task in real time and determining whether the task has been completed.

[0012] "Notification means" refers to a method or device for sending task reminders or alerts to a user, and specifically includes pop-up notifications, audio notifications, or email notifications.

[0013] "Storage means" refers to a function or device for storing the generated schedule and task progress status in a database.

[0014] "Update means" refers to a function or device that records information about a user's completed task in a database and keeps the schedule up to date. [Brief explanation of the drawings]

[0015] [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

[0016] 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.

[0017] First, the terms used in the following description will be explained.

[0018] 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).

[0019] 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.

[0020] 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.

[0021] 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.

[0022] 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."

[0023] [First embodiment]

[0024] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0025] 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.

[0026] 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).

[0027] 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.

[0028] 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.

[0029] 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.

[0030] 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.

[0031] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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."

[0036] This invention is a system that allows couples to manage the tasks necessary for child-rearing comfortably and adjust schedules efficiently. This system collects information on the couple's schedules and the child's routines, generates and displays an optimal task schedule, monitors the progress of tasks, and sends reminders.

[0037] System Overview

[0038] The system has the following main features:

[0039] 1. User data input function

[0040] 2. Schedule generation function

[0041] 3. Task management function

[0042] 4. Notification function

[0043] 1. User data input function

[0044] After logging in to the application, users enter information about their spouse's schedule and their child's routine, including each spouse's working hours and vacations, baby feeding and diaper changing times, etc. The server collects this information and stores it in a database.

[0045] 2. Schedule generation function

[0046] The server retrieves user data stored in the database and uses a generative AI model to generate an optimal task schedule. This schedule takes into account the couple's schedules, assigning tasks to the wife when the husband is at work, and vice versa. The generated schedule is then saved in the database.

[0047] 3. Task management function

[0048] The terminal displays a list of tasks for each user based on the acquired schedule. The progress of tasks is monitored in real time, allowing the user to check the tasks in progress. When the user notifies the terminal of completed tasks, the server updates the database and adjusts the next tasks.

[0049] 4. Notification function

[0050] The device will send reminder notifications at the necessary times based on the set schedule, which can be in the form of pop-ups, voice, email, etc. When a task reminder is triggered, the user can check the notification and start working on the task.

[0051] Specific examples

[0052] For example, in a household where the husband works from 9am to 6pm and the wife works from 11am to 8pm, tasks might be managed as follows:

[0053] 1. 9:00 AM - Husband starts work.

[0054] 2. 10:00 AM - My wife feeds and changes the baby.

[0055] 3. 11:00 AM - My wife starts work.

[0056] 4. 1:00 PM - Husband feeds and changes baby during his lunch break.

[0057] 5. 4:00 PM - My wife does the evening feeding and diaper change.

[0058] 6. 6pm - Husband finishes work and starts preparing dinner.

[0059] In this way, couples can adjust their schedules and children's routines, and share tasks comfortably. The system sends reminder notifications and supports task management in real time, reducing the burden of child-rearing and providing an environment where parents can enjoy raising their children without stress.

[0060] The processing flow will be explained below.

[0061] Step 1: Collect user data

[0062] 1. The user logs in to the application.

[0063] 2. The server displays a form to the logged-in user to enter information about the couple's individual schedules and children's routines.

[0064] 3. Users enter their own schedule (work hours and break times), their partner's schedule, and their child's routine (feeding and diaper changing times) into the form.

[0065] 4. The server collects the entered information and stores it in a database.

[0066] Step 2: Generate a schedule

[0067] 1. The server retrieves the schedule information of the couple and their children from the database.

[0068] 2. The server inputs the acquired data into the generative AI model and instructs it to generate an optimal task schedule.

[0069] 3. Based on the schedule information, the generative AI model generates an efficient schedule that takes into account the convenience of each couple and the needs of their children.

[0070] 4. The server retrieves the generated schedule and stores it in the database.

[0071] Step 3: Managing tasks

[0072] 1. The server sends the generated schedule to each terminal.

[0073] 2. Based on the received schedule, the device visually displays the current and next tasks to be done to the user.

[0074] 3. The user checks the displayed tasks and begins working on each one.

[0075] 4. The device monitors the progress of the task and provides a form where completed tasks can be recorded.

[0076] 5. When the user completes the task, the information is entered on the terminal and sent to the server.

[0077] 6. The server receives the completed task information and updates the database.

[0078] Step 4: Sending notifications

[0079] 1. The device will display reminders for each task at the appropriate time based on the schedule you set.

[0080] 2. When the time comes for a reminder, the device will send a pop-up notification, a sound notification, or an email notification to the user.

[0081] 3. The user sees the notification and begins the task.

[0082] 4. The server saves the notification sending history in the database and updates the next notification schedule.

[0083] Example 1

[0084] 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."

[0085] In modern households, couples face challenges in managing child-rearing tasks comfortably and efficiently. Creating and managing an optimal schedule requires taking into account various factors, such as each spouse's working hours, holidays, and children's routines. However, doing this manually can be difficult and stressful. In these circumstances, a system that provides efficient task management and timely reminder notifications is needed.

[0086] 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.

[0087] In this invention, the server includes an input means for collecting the couple's schedule information and the child's regular routine information, a generation means for generating an optimal task schedule based on the collected information, and a display means for displaying the schedule generated by using the generation AI model as the generation means, thereby enabling couples to efficiently manage the tasks necessary for child-rearing without strain and easily adjust their schedules.

[0088] "Married couple schedule information" is information about the schedules of the husband and wife, such as their working hours and holidays.

[0089] "Child routine information" refers to information about a child's daily activities and habits, such as feeding times and diaper changing times.

[0090] The "input means" is a means by which a user inputs information about the couple's schedule and information about the children's regular schedule into the application.

[0091] The "generation means" is a means for generating an optimal task schedule based on collected information, and in this invention, this is the part that uses the generative AI model.

[0092] A "generative AI model" is an artificial intelligence model that generates an optimal task schedule based on a specific prompt sentence.

[0093] The "display means" is a means for displaying the generated task schedule to the user.

[0094] The "monitoring means" is a means for monitoring the progress of a task and checking the completion state of the task.

[0095] A "notification means" is a means for sending task reminders to a user.

[0096] The "storage means" is a means for storing the generated schedule in a database.

[0097] The "update means" is a means for updating the information in the database after the user completes a task.

[0098] A "database" is a system for storing collected information, generated schedules, task progress, etc.

[0099] A "terminal" is a device that allows a user to check task schedules and update progress.

[0100] A "server" is a central computer system that collects user data, generates schedules, stores and updates data, and sends reminder notifications.

[0101] A "user" is an individual who uses the system to input, confirm, and report completion of tasks.

[0102] The present invention is a system for enabling couples to manage tasks necessary for raising children without straining themselves and to adjust schedules efficiently. Specific embodiments of this system will be described below.

[0103] This system consists of a server, terminals, and users, and has the following main functions:

[0104] 1. User data input function

[0105] 2. Schedule generation function

[0106] 3. Task management function

[0107] 4. Notification function

[0108] User data input function

[0109] After logging in to the application, the user enters the couple's schedule information and the child's regular schedule information. For example, the husband's working hours (9:00-18:00), the wife's working hours (11:00-20:00), and the child's feeding times (10:00, 13:00, 16:00). This information is sent to the server and stored in the database.

[0110] Schedule generation function

[0111] The server retrieves user information collected from the database and provides prompts to the generative AI model to generate an optimal task schedule. For example, the prompt might be, "Consider the couple's schedule and the child's routine, and generate an optimal childcare schedule." The generated schedule is then stored in the database.

[0112] Task management function

[0113] The terminal retrieves schedule information from the database and displays a list of tasks to the user. When the user completes a task, they enter their progress into the terminal, which then sends the information to the server. The server receives this information and updates the database.

[0114] Notification function

[0115] The device calculates the timing of the reminder notification based on the schedule and sends the reminder to the user at the appropriate time. The reminder is sent in the form of a pop-up, voice, email, etc. The user can check the reminder and start working on the task.

[0116] Specific examples

[0117] For example, in a household where the husband works from 9am to 6pm and the wife works from 11am to 8pm, tasks might be managed as follows:

[0118] 1. 9:00 AM - My husband starts work.

[0119] 2. 10:00 AM - My wife feeds and changes the baby.

[0120] 3. 11:00 AM - My wife starts work.

[0121] 4. 1:00 PM - Husband feeds and changes baby during his lunch break.

[0122] 5. 4:00 PM - My wife does the evening feeding and diaper change.

[0123] 6. 6 PM - Husband finishes work and starts preparing dinner.

[0124] In this way, couples can efficiently coordinate their schedules and children's routines, allowing them to share tasks comfortably and reducing the burden of child-rearing.

[0125] Prompt Sentence Examples

[0126] "Generate the optimal childcare schedule, taking into account the couple's schedules and the child's routines."

[0127] This system provides an environment for couples to efficiently manage child-rearing tasks and reduce stress.

[0128] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0129] Step 1:

[0130] A user logs in to the application by entering their user ID and password. This information is sent to the server, which authenticates the user. If authentication is successful, the dashboard is displayed.

[0131] Step 2:

[0132] The user inputs the couple's schedule information and the child's regular schedule information. Specifically, the husband's working hours, the wife's working hours, the child's breastfeeding times, etc. The server receives this input data and stores it in a database. Examples of input data include the husband's working hours "9:00-18:00", the wife's working hours "11:00-20:00", and the child's breastfeeding times "10:00, 13:00, 16:00".

[0133] Step 3:

[0134] The server retrieves user data collected from the database. Based on this information, it provides prompts to the generative AI model. As a specific example, the prompt is "Generate the optimal childcare schedule, taking into account the couple's schedule and the child's routine." Based on this prompt, the generative AI model generates the optimal task schedule. The generated schedule is returned to the server and saved in the database again.

[0135] Step 4:

[0136] The device retrieves schedule information related to the user from the database. The device displays the retrieved schedule to the user. For example, at 10:00 AM, the device displays information such as "The wife will breastfeed and change diapers," and at 1:00 PM, the device displays information such as "The husband will breastfeed and change diapers during his lunch break."

[0137] Step 5:

[0138] The user inputs the progress of the task into the terminal. For example, if the task at 10:00 AM is completed, the user inputs "Task completed at 10:00 AM." This information is sent to the server via the terminal.

[0139] Step 6:

[0140] The server receives the task completion information sent by the user and updates the database. Specifically, it changes the status of the corresponding task to "Completed."

[0141] Step 7:

[0142] The device calculates the timing of the reminder based on the schedule, for example, setting a reminder 10 minutes before the task starts, and the reminder can be in the form of a pop-up, sound notification, email, or other notification.

[0143] Step 8:

[0144] The device will send reminder notifications to the user at the set times. For example, at 9:50 a.m., a reminder to "feed and change diapers at 10 a.m." The user can confirm the reminder and get to work on the task.

[0145] Through these steps, the system efficiently performs a series of processes from collecting user data to generating schedules, managing tasks, and sending reminder notifications.

[0146] (Application example 1)

[0147] 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."

[0148] While existing systems allow couples to comfortably manage the tasks required for child-rearing and efficiently adjust schedules, there is a lack of a general-purpose system that can handle shift management and task allocation for store staff. This makes it difficult to manage tasks among staff and reduce the burden on each staff member.

[0149] 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.

[0150] In this invention, the server includes input means for collecting couple schedule information and child routine information, generation means for generating an optimal task schedule based on the collected information, display means for displaying the generated task schedule, monitoring means for monitoring task progress and confirming task completion status, notification means for sending task reminders to users, input means for collecting store staff shift information and work details, generation means for generating an optimal store staff shift schedule based on the collected information, and notification means for reminding store staff of the generated shift schedule, thereby enabling effective task management and real-time shift schedule management.

[0151] "Married couple schedule information" is information about the time schedules of the husband and wife, such as their working hours, holidays, and daily routines.

[0152] "Child routine information" is information about a child's daily activities and the times of care required (such as feeding times and diaper changes).

[0153] "Input means" refers to the interface through which a user inputs schedule and routine information into the application, and includes smartphone apps and web applications.

[0154] "Generators" are algorithms or systems that automatically create optimal task schedules based on collected information. This includes schedule generation using generative AI models.

[0155] The "display means" is an interface for visually presenting the generated task schedule to the user, such as a smartphone screen or a computer monitor.

[0156] The "monitoring means" is a system for checking the progress of tasks in real time and tracking the user's progress. This includes sensing technology and real-time data processing technology.

[0157] "Notification means" refers to a means for notifying users of task reminders and important events. This means conveying information to users in the form of pop-up notifications, audio notifications, emails, etc.

[0158] "Store staff" refers to employees who work in brick-and-mortar stores such as restaurants and retailers. Their work shifts and tasks need to be managed.

[0159] "Shift information" is information about the schedule of store staff, such as working hours, holidays, and shift changes.

[0160] "Job Description" refers to the specific tasks and roles that restaurant staff must perform (e.g., setting tables, cleaning, taking orders).

[0161] A "prompt sentence" is a text sentence of a specific format that the system inputs to the generative AI model to generate an optimal schedule.

[0162] The "generated shift schedule" refers to an optimal work schedule for store staff generated by the generation means.

[0163] "Real time" means that data processing occurs virtually immediately, within a very short time frame.

[0164] This invention is a system that efficiently manages the schedules and tasks of couples and store staff. It collects the working status and routines of couples and store staff, generates optimal schedules, and sends reminders. This system is effectively operated using a cloud server and smartphone application.

[0165] System configuration

[0166] The system mainly consists of the following hardware and software:

[0167] Server: Collects data, generates schedules, and manages the database.

[0168] Database: PostgreSQL is used to store user and staff schedule information, as well as generated schedule information.

[0169] Backend: Server-side processing is performed using the Django framework using Python.

[0170] Front-end: Develop a smartphone application using React Native.

[0171] Notification system: Uses Firebase Cloud Messaging to send reminders and notifications.

[0172] Generative AI models: Use models such as OpenAI's GPT-3 to generate optimal schedules.

[0173] Processing flow and roles

[0174] Data entry and collection

[0175] Users (couples or store staff) log in to the smartphone app and enter their work shift and routine information. This data is sent in real time to a cloud server and stored in a database.

[0176] Generate a schedule

[0177] The server uses a generative AI model to generate an optimal schedule based on the information stored in the database. This model receives schedule information and prompts entered by users and staff. For example, the following prompts can be input into the generative AI model:

[0178] Example prompt sentence:

[0179] "Generate the optimal shift schedule and task assignments for store staff based on the following data: Data: Staff A (Work: 9:00-17:00, Break: 12:00-13:00), Staff B (Work: 10:00-18:00, Break: 13:00-14:00). Store tasks: Prepare breakfast, clean the store, set tables, take orders, prepare dinner."

[0180] Viewing and Monitoring Schedules

[0181] The generated schedule is visually displayed to each user and staff member on a smartphone app. Users and staff members can check the progress of their assigned tasks in real time, and the database is updated when they report completed tasks.

[0182] Reminders

[0183] Use the notification system to send reminders to users and staff via pop-up and audio notifications sent via Firebase Cloud Messaging, helping users and staff remember to complete tasks.

[0184] Specific examples

[0185] For example, the family restaurant "Smile Diner" uses the system as follows:

[0186] 9:00 AM - The restaurant opens and Staff A begins preparing breakfast in the kitchen.

[0187] 10:00 AM - The app sends a reminder notification and Staff B begins cleaning the store.

[0188] 12:00 noon - Staff A goes on break and Staff C transitions to setting tables and taking orders.

[0189] 3:00 PM - Staff member A returns and takes on the task of preparing dinner.

[0190] This allows for efficient division of labor among staff members, ensuring smooth operation.

[0191] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0192] Step 1:

[0193] The user logs into the smartphone app and enters frequent schedule and routine information. The server saves this input information in a database on the cloud. The input for this step is the working hours and task information of couples and store staff, and the output is user data saved in the database. Specifically, the user enters information into the input fields on the screen and presses the send button, which sends the data to the server.

[0194] Step 2:

[0195] The server retrieves the information stored in the database and inputs prompt statements to the generative AI model to generate an optimal schedule. The input for this step is the user data stored in the database and the generative AI model, and the output is the generated schedule. The server runs a Python script to extract information from the database, pass it to the generative AI model, and receive a response.

[0196] Step 3:

[0197] The generated schedule is saved in the database again and transferred to the smartphone app. The input of this step is the generated schedule, and the output is the schedule saved in the database and transferred to the smartphone app. The server adds the response from the generative AI model to the database and sends the data to the device via WebSocket or API to notify the user in real time.

[0198] Step 4:

[0199] The user checks the generated schedule through the smartphone app and updates the progress of each task. The input of this step is the user's task completion information, and the output is updated database information. The user marks the task as completed on the smartphone app screen, and the information is immediately sent to the server.

[0200] Step 5:

[0201] The server periodically monitors the progress of the task and sends reminders and notifications as needed. The input for this step is the current time and the schedule stored in the database, and the output is a reminder notification to the user. The server sends the reminder at the set time via Firebase Cloud Messaging and provides the notification to the user.

[0202] Through these steps, the system can efficiently manage the schedules and tasks of users and store staff, and provide notifications at the appropriate times.

[0203] 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.

[0204] This invention is a system that allows couples to comfortably manage the tasks necessary for child-rearing and efficiently adjust schedules, and its effectiveness is enhanced by combining it with an emotion engine that recognizes the user's emotions. This system collects information about the couple's schedule and the child's routine, generates and displays an optimal task schedule, monitors task progress, notifies reminders, and adjusts tasks and notifications appropriately based on the recognized emotions.

[0205] System Overview

[0206] The system has the following main features:

[0207] 1. User data input function

[0208] 2. Schedule generation function

[0209] 3. Task management function

[0210] 4. Notification function

[0211] 5. Emotion recognition function

[0212] 1. User data input function

[0213] After logging in to the application, users enter information about their spouse's schedule and their child's routine, including each spouse's working hours and vacations, baby feeding and diaper changing times, etc. The server collects this information and stores it in a database.

[0214] 2. Schedule generation function

[0215] The server retrieves user data stored in the database and uses a generative AI model to generate an optimal task schedule. This schedule takes into account the couple's schedules, assigning tasks to the wife when the husband is at work, and vice versa. The generated schedule is then saved in the database.

[0216] 3. Task management function

[0217] Based on the schedule, the device visually displays the current and next tasks to be done to the user. The progress of tasks is monitored in real time, allowing the user to check the tasks in progress. The user can notify the server of completed tasks on the device, and the server updates the database and adjusts the next tasks.

[0218] 4. Notification function

[0219] The device will send reminder notifications at the necessary times based on the set schedule, which can be in the form of pop-ups, voice, email, etc. When a task reminder is triggered, the user can check the notification and start working on the task.

[0220] 5. Emotion recognition function

[0221] The device is equipped with an emotion engine that recognizes emotions from the user's facial expressions and voice. This allows the device to grasp the user's stress level and motivation in real time. The recognized emotions are sent to a server, which automatically adjusts tasks and schedules.

[0222] Specific examples

[0223] For example, in a household where the husband works from 9am to 6pm and the wife works from 11am to 8pm, tasks might be managed as follows:

[0224] 1. 9 AM - Husband starts work. The emotion engine recognizes his stress level and sends reminders to his wife as needed.

[0225] 2. 10:00 AM - Wife feeds and changes the baby. The emotion engine recognizes her stress level and adjusts the division of tasks.

[0226] 3. 11:00 AM - Wife starts work. System assigns task to husband during lunch break.

[0227] 4. 1 PM - Husband feeds and changes baby during his lunch break. The Emotion Engine reassessed his stress level.

[0228] 5. 4 PM - Wife does evening feeding and diaper change. Emotion Engine adjusts notifications based on wife's feedback.

[0229] 6. 6 PM - Husband finishes work and starts preparing dinner. The system confirms the task completion and notifies him of the next scheduled event.

[0230] In this way, the couple can adjust their schedules and their children's routines, and flexibly change task allocation and notification methods based on their emotional state, allowing them to raise their children comfortably.The introduction of an emotion engine makes it possible to reduce user stress and provide an environment where users can complete tasks efficiently.

[0231] The processing flow will be explained below.

[0232] Step 1: Collect user data

[0233] 1. The user logs in to the application.

[0234] 2. The server displays a form to the logged-in user to enter the couple's schedule information and the children's routine information.

[0235] 3. The user enters their own and their partner's schedules (e.g., working hours, break times) and their child's routines (e.g., feeding times, diaper changing times).

[0236] 4. The server collects the entered information and stores it in a database.

[0237] Step 2: Collecting emotion data

[0238] 1. The emotion engine installed in the device recognizes emotions from the user's facial expressions and voice.

[0239] 2. The device sends the recognized emotion data to the server.

[0240] 3. The server stores the emotion data in a database and records the user's emotional state.

[0241] Step 3: Generate a schedule

[0242] 1. The server retrieves schedule information and emotional data of the couple and their children from the database.

[0243] 2. The server inputs the acquired data into the generative AI model and instructs it to generate an optimal task schedule.

[0244] 3. The generative AI model generates an efficient schedule that takes into account the user's emotional state based on schedule information and emotional data.

[0245] 4. The server retrieves the generated schedule and stores it in the database.

[0246] Step 4: Managing tasks

[0247] 1. The server sends the generated schedule to each terminal.

[0248] 2. Based on the received schedule, the device visually displays the current and next tasks to be done to the user.

[0249] 3. The user checks the displayed tasks and begins working on each one.

[0250] 4. The device monitors the progress of the task and provides a form where completed tasks can be recorded.

[0251] 5. When the user completes the task, the information is entered on the device and sent to the server.

[0252] 6. The server receives the completed task information and updates the database.

[0253] Step 5: Sending notifications

[0254] 1. The device will display reminders for each task at the appropriate time based on the schedule you set.

[0255] 2. When the time comes for a reminder, the device will send a pop-up notification, a sound notification, or an email notification to the user.

[0256] 3. The user sees the notification and begins the task.

[0257] 4. The server saves the notification sending history in the database and updates the next notification schedule.

[0258] Specific examples

[0259] Step 1: Collect user data

[0260] A user logs into the application and enters the husband and wife's schedules and the children's routines. For example, the husband works from 9am to 6pm and the wife works from 11am to 8pm.

[0261] Step 2: Collecting emotion data

[0262] The device's built-in emotion engine recognizes the user's current emotional state from their facial expressions and voice, collecting data such as "high stress" or "relaxed." The device then sends this information to a server, which stores it in a database.

[0263] Step 3: Generate a schedule

[0264] The server uses a generative AI model to generate an optimal task schedule based on the user's schedule information and emotional data. For example, if the emotional data indicates "high stress," the generative AI model generates a schedule that reduces the workload.

[0265] Step 4: Managing tasks

[0266] The device displays the optimal schedule to the user and monitors the progress of the tasks in real time. When the user completes a task, the information is sent to the server and the database is updated.

[0267] Step 5: Sending notifications

[0268] The device will send reminders based on the schedule, such as notifications like "It's time for the next feeding." The notification method will also be adjusted based on the emotional data, so if the user is feeling stressed, a gentle tone will be sent.

[0269] In this way, combining the emotion engine enables flexible schedule management and task notifications that take into account the user's emotional state, facilitating cooperation between spouses and reducing the burden of raising children.

[0270] Example 2

[0271] 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."

[0272] Modern couples are faced with the need to efficiently manage childcare tasks and reduce stress amid their busy lives. However, there are no systems in place that can schedule tasks while taking into account individual circumstances and emotions. Therefore, there is a need for a system that allows couples to share and execute childcare tasks comfortably and effectively.

[0273] 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.

[0274] In this invention, the server includes input means for collecting time information of the couple and information on the child's daily routine, generation means for generating an optimal task timetable based on the collected information, display means for displaying the generated task timetable, monitoring means for monitoring task progress and confirming task completion status, notification means for sending task reminders to the user, emotion recognition means for analyzing the user's facial expressions and voice and recognizing their emotional state, and adjustment means for adjusting tasks and notifications based on the recognized emotion. This enables optimal management and sharing of childcare tasks while taking into account the couple's schedules and emotional state.

[0275] "Married couple time information" is data that indicates the husband or wife's working hours, vacation time, and their schedules.

[0276] "Children's daily routine information" is data that represents a child's daily routines and schedules, such as feeding times, diaper changing times, and sleeping times.

[0277] "Input means" refers to the interface and software that allows users to input their schedules and children's daily routines.

[0278] "Generation means" refers to the algorithm and generative AI model that creates an optimal task schedule based on input information.

[0279] The "display means" refers to a display device or application interface for visually presenting the generated task timetable to the user.

[0280] "Monitoring tools" are software and hardware used to view and track the progress and completion of tasks in real time.

[0281] "Notification means" refers to the system and method for sending reminders and task notifications to users.

[0282] The "emotion recognition means" refers to software and hardware for analyzing the user's facial expressions and voice to recognize the user's emotional state.

[0283] "Adjustment" refers to algorithms and systems for dynamically modifying and adjusting the content and timing of tasks and notifications based on perceived emotions.

[0284] The "data repository" is a database and storage device for storing collected data and generated task timetables.

[0285] "Users" refers to individuals who use the system, primarily couples.

[0286] This invention is a system that collects information on couples' time and children's daily routines, generates and displays an optimal task schedule, monitors task progress, and sends reminder notifications.It also has the ability to recognize the user's emotions and adjust tasks and notifications appropriately based on their emotions.

[0287] System Overview

[0288] The system consists of the following main hardware and software:

[0289] Server: Database (e.g. MySQL), generative AI model (e.g. GPT-4)

[0290] Device (smartphone or tablet): Input form, display screen, emotion recognition engine (e.g., Microsoft Azure Emotion API)

[0291] Users: A married couple who use this system

[0292] User data input function

[0293] Users log in to the application and enter schedule information such as husband and wife's working hours, vacation time, baby feeding and diaper changing times, etc. This information is collected by the server and stored in a database. OAuth 2.0 is used for login, and HTML forms and JavaScript are used for data entry.

[0294] Schedule generation function

[0295] The server retrieves the user data stored in the database and generates an optimal task timetable using a generative AI model (e.g., GPT-4). Example prompt: "Generate the optimal task schedule based on the husband and wife's schedules and children's routine information." The generated timetable is then saved back to the database.

[0296] Task management function

[0297] The device visually displays the current and upcoming tasks to the user based on a schedule retrieved from the database. Task progress is monitored in real time, and as the user completes a task, the server updates the database with that information. This display is done using HTML and JavaScript.

[0298] Notification function

[0299] The device will send reminder notifications based on the schedule you set, in the form of pop-ups, sounds, emails, etc., using the JavaScript timer function.

[0300] Emotion recognition function

[0301] The device uses the built-in camera and microphone to capture the user's facial expressions and voice, and sends them to an emotion recognition engine (e.g., Microsoft Azure's Emotion API) for analysis. The emotion data is sent to a server, which dynamically adjusts tasks and notifications.

[0302] Specific examples

[0303] For example, in a household where the husband works from 9am to 6pm and the wife works from 11am to 8pm, tasks might be managed as follows:

[0304] 1. 9 AM - Husband starts work, emotion engine recognizes husband's stress level, and sends wife a reminder if necessary.

[0305] 2. 10:00 AM - Wife feeds and changes the baby. The emotion engine recognizes her stress level and the system adjusts the distribution of tasks.

[0306] 3. 11:00 AM - Wife starts work. System assigns husband a task during his lunch break.

[0307] 4. 1 PM - Husband feeds and changes baby during his lunch break. The Emotion Engine reassessed his stress level.

[0308] 5. 4 PM - Wife does evening feeding and diaper change. Emotion engine adjusts notifications based on wife's feedback.

[0309] 6. 6 PM - Husband finishes work and starts preparing dinner. The system confirms task completion and notifies him of his next scheduled appointment.

[0310] This system allows parents to smoothly raise their children by adjusting their schedules and the children's daily routines, and flexibly changing task allocation and notification methods based on their emotional state.The introduction of an emotion recognition engine can reduce user stress and provide an environment in which tasks can be completed efficiently.

[0311] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0312] Step 1: User data input

[0313] A user logs in to an application. First, they enter their login information and send it to the authentication server. The authentication server authenticates the user using OAuth 2.0 and, if successful, generates and returns an authentication token. The device stores this token and uses it for subsequent operations.

[0314] Input: Username and Password

[0315] Output: Authentication token

[0316] Users enter schedule information such as husband and wife working hours, vacation time, baby feeding and diaper changing times, etc. The input information is collected using an HTML form and JavaScript and sent to the server in JSON format.

[0317] Input: Schedule information (working hours, holidays, breastfeeding time, diaper changing time, etc.)

[0318] Output: Schedule information in JSON format

[0319] The server parses the received JSON data and saves it to a MySQL database using an INSERT query. The database stores the schedule information for each husband, wife, and child.

[0320] Input: Schedule information in JSON format

[0321] Output: Schedule data stored in the database

[0322] Step 2: Schedule generation

[0323] The server retrieves user data from the database using a SQL "SELECT" query, which is then converted into a Python data frame (e.g., Pandas) for internal processing.

[0324] Input: Schedule data stored in the database

[0325] Output: Data frame for internal processing

[0326] The server inputs a prompt into a generative AI model (e.g., GPT-4) to generate an optimal task timetable. An example prompt is "Please generate an optimal task schedule based on the husband and wife's schedules and children's routine information." The generative AI model generates a task timetable based on the received prompt and returns it in JSON format.

[0327] Input: User data and prompt statements

[0328] Output: Task timetable in JSON format

[0329] The server saves the generated task timetable to the database using an "INSERT" query. The database stores the schedule ID, task details, start time, end time, etc.

[0330] Input: Task timetable in JSON format

[0331] Output: Task timetable saved in the database

[0332] Step 3: Task Management

[0333] The device retrieves the current schedule from the database with a "GET" request. The server receives the request, retrieves the data using an SQL "SELECT" query, and returns it to the device in JSON format.

[0334] Input: Task timetable stored in the database

[0335] Output: Task information in JSON format

[0336] The device parses the received JSON data and displays a list of tasks using HTML and JavaScript. The user interface displays the current and next tasks.

[0337] Input: Task information in JSON format

[0338] Output: Task list display screen

[0339] When a user completes a task, they tap the task on their device to send a completion notification, which then sends the completion notification data in JSON format to the server.

[0340] Input: Completion notification (task ID, completion status, etc.)

[0341] Output: JSON format completion notification

[0342] The server receives the completion notification and updates the database using an "UPDATE" query, changing the status of the completed task to "completed" and coordinating the next task.

[0343] Input: JSON format completion notification

[0344] Output: Updated database

[0345] Step 4: Notification

[0346] The device uses a JavaScript timer function to set reminders for each task based on the schedule data, and the timer will trigger an alert when the task's start time approaches.

[0347] Input: Task start time

[0348] Output: Set timer

[0349] When the timer triggers an alert, the device sends the user a reminder notification in the form of a pop-up, voice, email, or other format.

[0350] Input: Timer alert

[0351] Output: Reminder notification

[0352] Step 5: Emotion Recognition

[0353] The device captures the user's facial expressions and voice using the device's built-in camera and microphone, and this captured data is obtained in real time using WebRTC.

[0354] Input: facial expression data, voice data

[0355] Output: Captured data

[0356] The device sends the captured data to an emotion recognition engine (e.g., Microsoft Azure's Emotion API) for analysis, and the emotion engine returns the emotional state in JSON format.

[0357] Input: Captured data

[0358] Output: Emotion data in JSON format

[0359] The server dynamically adjusts the task order and notification method based on the emotion data received from the emotion engine, and updates the database contents using the "UPDATE" query to reflect the changes in real time.

[0360] Input: Emotion data in JSON format

[0361] Output: Adjusted task schedule and notification method

[0362] (Application example 2)

[0363] 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."

[0364] In modern society, the number of dual-income households is increasing, making it a major challenge to raise children efficiently and comfortably. In particular, couples raising children face the complexities of managing their daily schedules, making it difficult to keep track of task progress in real time. Furthermore, the impact of stress and emotional changes on child-rearing cannot be ignored. Therefore, in order for couples to raise children smoothly, they need support not only through task management but also through emotional recognition. Appropriate support is also needed when purchasing childcare products or seeking advice in physical stores.

[0365] 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 input means for collecting schedule information of the couple and information about the child's routine, generation means for generating an optimal task schedule based on the collected information, display means for displaying the generated task schedule, monitoring means for monitoring the progress of tasks and confirming their completion status, notification means for sending task reminders to the user, recognition means for recognizing emotions from the user's facial expressions and voice, adjustment means for appropriately adjusting tasks and notification methods based on the recognized emotions, guidance means for navigating to specific areas within the store, and conversation means for receiving childcare consultations from the user. This enables couples to raise their children efficiently and flexibly adjust tasks based on their emotional state, making it easier to purchase childcare products and receive childcare consultations in physical stores.

[0366] "Input means" refers to a device or method for collecting information on the couple's schedule and the children's routines.

[0367] A "generation means" is a device or method that generates an optimal task schedule based on collected information.

[0368] The "display means" is a device or method that visually presents the generated task schedule to the user.

[0369] A "monitoring means" is a device or method that tracks the progress of a task and verifies its completion.

[0370] A "notifier" is a device or method that sends task reminders to a user.

[0371] The "recognition means" is a device or method for analyzing emotions from the user's facial expressions and voice.

[0372] An "adjustment means" is a device or method that changes tasks or notification methods based on recognized emotions.

[0373] "Guidance means" refers to a device or method that provides directions or navigation to a specific area within a store.

[0374] The "conversation means" is an interactive device or method for receiving advice from the user regarding child rearing.

[0375] This invention provides a system that mainly comprises the following means. Specifically, it is a system that collects information on couples' schedules and children's routines, and generates, displays, monitors, notifies, and adjusts an optimal task schedule. It also has a conversation means that recognizes emotions from the user's facial expressions and voice, and receives consultations about child-rearing from the user.

[0376] System Configuration

[0377] 1. Input method:

[0378] The server uses devices such as smartphones and tablets to input information about the couple's schedule and the child's routine. The user inputs this information through an application and sends it to the server.

[0379] 2. Generation means:

[0380] The server uses a generative AI model to generate an optimal task schedule based on the collected information on the couple's schedule and the child's routine. This task schedule is automatically calculated, taking into account the user's working hours and the child's daily rhythm.

[0381] 3. Display means:

[0382] The terminal visually displays the generated task schedule to the user, who can then check the schedule via a dedicated application.

[0383] 4. Monitoring measures:

[0384] The device monitors the progress of the task in real time, and when the user completes the task, the device sends the information to the server and updates the database.

[0385] 5. Means of notification:

[0386] The device will send reminders to the user for scheduled tasks in the form of push notifications, emails, audio alerts, etc.

[0387] 6. Emotion recognition means:

[0388] The device captures the user's facial expressions and voice and uses an emotion engine to recognize the user's emotional state. For example, it uses a facial recognition library (such as face-api.js) to analyze the facial expression data and evaluate the user's stress level.

[0389] 7. Adjustment means:

[0390] The server then adjusts tasks and notifications accordingly based on the recognized emotions, for example, changing task priorities or making notifications more gentle if the user indicates a high stress level.

[0391] 8. Guidance means:

[0392] The device provides navigation when users are searching for specific areas within a physical store, such as directions to childcare products and breastfeeding areas.

[0393] 9. Means of communication:

[0394] The device accepts user inquiries about childcare via an AI chatbot. When a user inputs a question about childcare, the chatbot provides appropriate advice.

[0395] Specific examples

[0396] For example, if the system is used in a household where the husband works from 9:00 a.m. to 6:00 p.m. and the wife works from 11:00 a.m. to 8:00 p.m., the process will proceed as follows:

[0397] 1. 9:00 AM: The server notices that the husband has started work and sends a reminder notification to the wife.

[0398] 2. 10 AM: The device displays tasks for the wife to breastfeed and change the diaper. The emotion engine recognizes her stress level and readjusts the tasks as needed.

[0399] 3. 11:00 AM: The wife starts work, the server updates this information, and generates a schedule so that the task is assigned during the husband's lunch break.

[0400] 4. 1 PM: The device sends feeding and diaper change reminders to her husband, and uses facial recognition technology to reassess his stress level.

[0401] 5. 4 PM: My wife does the evening feeding and diaper change while the device monitors the progress.

[0402] 6. 6 PM: The server recognizes that my husband has finished work and notifies him of the upcoming dinner preparation task.

[0403] An example of a prompt might be, "Sir, it seems you're feeling stressed right now. Here's the nearest diaper changing area. Also, if you have any childcare concerns, please ask our childcare consultation chatbot."

[0404] This system allows couples to raise their children efficiently, flexibly manage tasks based on their emotional state, and provides comprehensive support within physical stores.

[0405] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0406] Step 1:

[0407] The server collects information about the couple's schedule and the child's routine entered by the user using input methods, including input from a smartphone or tablet. The input data includes the couple's working hours, the timing of the child's feeding and diaper changes, etc. This data is sent to the server and stored in a database.

[0408] Step 2:

[0409] The server acquires the collected schedule and routine information and generates an optimal task schedule using a generative AI model. This generation involves implementing an algorithm to allocate tasks appropriately, taking into account the user's working hours and children's daily routines. The output is saved in a database as the generated task schedule.

[0410] Step 3:

[0411] The terminal uses a display means to visually display the task schedule obtained from the server to the user. Specifically, the user can check the current and next tasks to be performed through a dedicated application. The input in this process is the task schedule obtained from the server, and the output is the schedule displayed on the user's terminal screen.

[0412] Step 4:

[0413] The terminal monitors the progress of the task in real time using a monitoring means. When the user completes the task, the terminal sends the information to the server, which updates the database. The input to this process is the user's notification of task completion, and the output is the updated task information in the database.

[0414] Step 5:

[0415] The device uses a notification mechanism to send task reminders to the user, which can take the form of real-time push notifications, emails, voice alerts, etc. The input is the time information of the scheduled task, and the output is the reminder notification to the user.

[0416] Step 6:

[0417] The device uses a recognition means to recognize emotions from the user's facial expressions and voice. Specifically, it uses a facial expression recognition library (such as face-api.js) to analyze the video captured by the camera and generate emotion data. The input is the camera video and audio data, and the output is the analyzed emotion data.

[0418] Step 7:

[0419] The server adjusts tasks and notification methods accordingly based on the recognized emotion data. For example, if the stress level is high, it may change the priority of the task or change the notification method to a softer tone. The input is emotion data, and the output is the adjusted task schedule and notification method.

[0420] Step 8:

[0421] The device uses the guidance means to navigate to a specific area within a physical store, indicating the location of childcare products and equipment that the user has searched for in the application. The input is a search request from the user, and the output is navigation information.

[0422] Step 9:

[0423] The device uses a conversational means to receive childcare-related consultations from the user via an AI chatbot. When the user inputs a childcare-related question through the application, the chatbot uses a generative AI model to provide appropriate advice. The input is the user's question, and the output is advice from the chatbot.

[0424] 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.

[0425] 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.

[0426] 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.

[0427] [Second embodiment]

[0428] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0429] 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.

[0430] 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).

[0431] 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.

[0432] 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.

[0433] 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).

[0434] 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. 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.

[0435] 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.

[0436] 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.

[0437] 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.

[0438] In the smart glasses 214, 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.

[0439] 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."

[0440] This invention is a system that allows couples to manage the tasks necessary for child-rearing comfortably and adjust schedules efficiently. This system collects information on the couple's schedules and the child's routines, generates and displays an optimal task schedule, monitors the progress of tasks, and sends reminders.

[0441] System Overview

[0442] The system has the following main features:

[0443] 1. User data input function

[0444] 2. Schedule generation function

[0445] 3. Task management function

[0446] 4. Notification function

[0447] 1. User data input function

[0448] After logging in to the application, users enter information about their spouse's schedule and their child's routine, including each spouse's working hours and vacations, baby feeding and diaper changing times, etc. The server collects this information and stores it in a database.

[0449] 2. Schedule generation function

[0450] The server retrieves user data stored in the database and uses a generative AI model to generate an optimal task schedule. This schedule takes into account the couple's schedules, assigning tasks to the wife when the husband is at work, and vice versa. The generated schedule is saved in the database.

[0451] 3. Task management function

[0452] The terminal displays a list of tasks for each user based on the acquired schedule. The progress of tasks is monitored in real time, allowing the user to check the tasks in progress. When the user notifies the terminal of completed tasks, the server updates the database and adjusts the next tasks.

[0453] 4. Notification function

[0454] The device will send reminder notifications at the necessary times based on the set schedule, which can be in the form of pop-ups, voice, email, etc. When a task reminder is triggered, the user can check the notification and start working on the task.

[0455] Specific examples

[0456] For example, in a household where the husband works from 9am to 6pm and the wife works from 11am to 8pm, tasks might be managed as follows:

[0457] 1. 9:00 AM - Husband starts work.

[0458] 2. 10:00 AM - My wife feeds and changes the baby.

[0459] 3. 11:00 AM - My wife starts work.

[0460] 4. 1:00 PM - Husband feeds and changes baby during his lunch break.

[0461] 5. 4:00 PM - My wife does the evening feeding and diaper change.

[0462] 6. 6pm - Husband finishes work and starts preparing dinner.

[0463] In this way, couples can adjust their schedules and children's routines, and share tasks comfortably. The system sends reminder notifications and supports task management in real time, reducing the burden of child-rearing and providing an environment where parents can enjoy raising their children without stress.

[0464] The processing flow will be explained below.

[0465] Step 1: Collect user data

[0466] 1. The user logs in to the application.

[0467] 2. The server displays a form to the logged-in user to enter information about the couple's individual schedules and children's routines.

[0468] 3. Users enter their own schedule (work hours and break times), their partner's schedule, and their child's routine (feeding and diaper changing times) into the form.

[0469] 4. The server collects the entered information and stores it in a database.

[0470] Step 2: Generate a schedule

[0471] 1. The server retrieves the schedule information of the couple and their children from the database.

[0472] 2. The server inputs the acquired data into the generative AI model and instructs it to generate an optimal task schedule.

[0473] 3. Based on the schedule information, the generative AI model generates an efficient schedule that takes into account the convenience of each couple and the needs of their children.

[0474] 4. The server retrieves the generated schedule and stores it in the database.

[0475] Step 3: Managing tasks

[0476] 1. The server sends the generated schedule to each terminal.

[0477] 2. Based on the received schedule, the device visually displays the current and next tasks to be done to the user.

[0478] 3. The user checks the displayed tasks and begins working on each one.

[0479] 4. The device monitors the progress of the task and provides a form where completed tasks can be recorded.

[0480] 5. When the user completes the task, the information is entered on the terminal and sent to the server.

[0481] 6. The server receives the completed task information and updates the database.

[0482] Step 4: Sending notifications

[0483] 1. The device will display reminders for each task at the appropriate time based on the schedule you set.

[0484] 2. When the time comes for a reminder, the device will send a pop-up notification, a sound notification, or an email notification to the user.

[0485] 3. The user sees the notification and begins the task.

[0486] 4. The server saves the notification sending history in the database and updates the next notification schedule.

[0487] Example 1

[0488] 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."

[0489] In modern households, couples face challenges in managing child-rearing tasks comfortably and efficiently. Creating and managing an optimal schedule requires taking into account various factors, such as each spouse's working hours, holidays, and children's routines. However, doing this manually can be difficult and stressful. In these circumstances, a system that provides efficient task management and timely reminder notifications is needed.

[0490] 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.

[0491] In this invention, the server includes an input means for collecting the couple's schedule information and the child's regular routine information, a generation means for generating an optimal task schedule based on the collected information, and a display means for displaying the schedule generated by using the generation AI model as the generation means, thereby enabling couples to efficiently manage the tasks necessary for child-rearing without strain and easily adjust their schedules.

[0492] "Married couple schedule information" is information about the schedules of the husband and wife, such as their working hours and holidays.

[0493] "Child routine information" refers to information about a child's daily activities and habits, such as feeding times and diaper changing times.

[0494] The "input means" is a means by which a user inputs information about the couple's schedule and information about the children's regular schedule into the application.

[0495] The "generation means" is a means for generating an optimal task schedule based on collected information, and in this invention, this is the part that uses the generative AI model.

[0496] A "generative AI model" is an artificial intelligence model that generates an optimal task schedule based on a specific prompt sentence.

[0497] The "display means" is a means for displaying the generated task schedule to the user.

[0498] The "monitoring means" is a means for monitoring the progress of a task and checking the completion state of the task.

[0499] A "notification means" is a means for sending task reminders to a user.

[0500] The "storage means" is a means for storing the generated schedule in a database.

[0501] The "update means" is a means for updating the information in the database after the user completes a task.

[0502] A "database" is a system for storing collected information, generated schedules, task progress, etc.

[0503] A "terminal" is a device that allows a user to check task schedules and update progress.

[0504] A "server" is a central computer system that collects user data, generates schedules, stores and updates data, and sends reminder notifications.

[0505] A "user" is an individual who uses the system to input, confirm, and report completion of tasks.

[0506] The present invention is a system for enabling couples to manage tasks necessary for raising children without straining themselves and to adjust schedules efficiently. Specific embodiments of this system will be described below.

[0507] This system consists of a server, terminals, and users, and has the following main functions:

[0508] 1. User data input function

[0509] 2. Schedule generation function

[0510] 3. Task management function

[0511] 4. Notification function

[0512] User data input function

[0513] After logging in to the application, the user enters the couple's schedule information and the child's regular schedule information. For example, the husband's working hours (9:00-18:00), the wife's working hours (11:00-20:00), and the child's feeding times (10:00, 13:00, 16:00). This information is sent to the server and stored in the database.

[0514] Schedule generation function

[0515] The server retrieves user information collected from the database and provides prompts to the generative AI model to generate an optimal task schedule. For example, the prompt might be, "Consider the couple's schedule and the child's routine, and generate an optimal childcare schedule." The generated schedule is then stored in the database.

[0516] Task management function

[0517] The terminal retrieves schedule information from the database and displays a list of tasks to the user. When the user completes a task, they enter their progress into the terminal, which then sends the information to the server. The server receives this information and updates the database.

[0518] Notification function

[0519] The device calculates the timing of the reminder notification based on the schedule and sends the reminder to the user at the appropriate time. The reminder is sent in the form of a pop-up, voice, email, etc. The user can check the reminder and start working on the task.

[0520] Specific examples

[0521] For example, in a household where the husband works from 9am to 6pm and the wife works from 11am to 8pm, tasks might be managed as follows:

[0522] 1. 9:00 AM - My husband starts work.

[0523] 2. 10:00 AM - My wife feeds and changes the baby.

[0524] 3. 11:00 AM - My wife starts work.

[0525] 4. 1:00 PM - Husband feeds and changes baby during his lunch break.

[0526] 5. 4:00 PM - My wife does the evening feeding and diaper change.

[0527] 6. 6 PM - Husband finishes work and starts preparing dinner.

[0528] In this way, couples can efficiently coordinate their schedules and children's routines, allowing them to share tasks comfortably and reducing the burden of child-rearing.

[0529] Prompt Sentence Examples

[0530] "Generate the optimal childcare schedule, taking into account the couple's schedules and the child's routines."

[0531] This system provides an environment for couples to efficiently manage child-rearing tasks and reduce stress.

[0532] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0533] Step 1:

[0534] A user logs in to the application by entering their user ID and password. This information is sent to the server, which authenticates the user. If authentication is successful, the dashboard is displayed.

[0535] Step 2:

[0536] The user inputs the couple's schedule information and the child's regular schedule information. Specifically, the husband's working hours, the wife's working hours, the child's breastfeeding times, etc. The server receives this input data and stores it in a database. Examples of input data include the husband's working hours "9:00-18:00", the wife's working hours "11:00-20:00", and the child's breastfeeding times "10:00, 13:00, 16:00".

[0537] Step 3:

[0538] The server retrieves user data collected from the database. Based on this information, it provides prompts to the generative AI model. As a specific example, the prompt is "Generate the optimal childcare schedule, taking into account the couple's schedule and the child's routine." Based on this prompt, the generative AI model generates the optimal task schedule. The generated schedule is returned to the server and saved in the database again.

[0539] Step 4:

[0540] The device retrieves schedule information related to the user from the database. The device displays the retrieved schedule to the user. For example, at 10:00 AM, the device displays information such as "The wife will breastfeed and change diapers," and at 1:00 PM, the device displays information such as "The husband will breastfeed and change diapers during his lunch break."

[0541] Step 5:

[0542] The user inputs the progress of the task into the terminal. For example, if the task at 10:00 AM is completed, the user inputs "Task completed at 10:00 AM." This information is sent to the server via the terminal.

[0543] Step 6:

[0544] The server receives the task completion information sent by the user and updates the database. Specifically, it changes the status of the corresponding task to "Completed."

[0545] Step 7:

[0546] The device calculates the timing of the reminder based on the schedule, for example, setting a reminder 10 minutes before the task starts, and the reminder can be in the form of a pop-up, sound notification, email, or other notification.

[0547] Step 8:

[0548] The device will send reminder notifications to the user at the set times. For example, at 9:50 a.m., a reminder to "feed and change diapers at 10 a.m." The user can confirm the reminder and get to work on the task.

[0549] Through these steps, the system efficiently performs a series of processes from collecting user data to generating schedules, managing tasks, and sending reminder notifications.

[0550] (Application example 1)

[0551] 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."

[0552] While existing systems allow couples to comfortably manage the tasks required for child-rearing and efficiently adjust schedules, there is a lack of a general-purpose system that can handle shift management and task allocation for store staff. This makes it difficult to manage tasks among staff and reduce the burden on each staff member.

[0553] 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.

[0554] In this invention, the server includes input means for collecting couple schedule information and child routine information, generation means for generating an optimal task schedule based on the collected information, display means for displaying the generated task schedule, monitoring means for monitoring task progress and confirming task completion status, notification means for sending task reminders to users, input means for collecting store staff shift information and work details, generation means for generating an optimal store staff shift schedule based on the collected information, and notification means for reminding store staff of the generated shift schedule, thereby enabling effective task management and real-time shift schedule management.

[0555] "Married couple schedule information" is information about the time schedules of the husband and wife, such as their working hours, holidays, and daily routines.

[0556] "Child routine information" is information about a child's daily activities and the times of care required (such as feeding times and diaper changes).

[0557] "Input means" refers to the interface through which a user inputs schedule and routine information into the application, and includes smartphone apps and web applications.

[0558] "Generators" are algorithms or systems that automatically create optimal task schedules based on collected information. This includes schedule generation using generative AI models.

[0559] The "display means" is an interface for visually presenting the generated task schedule to the user, such as a smartphone screen or a computer monitor.

[0560] The "monitoring means" is a system for checking the progress of tasks in real time and tracking the user's progress. This includes sensing technology and real-time data processing technology.

[0561] "Notification means" refers to a means for notifying users of task reminders and important events. This means conveying information to users in the form of pop-up notifications, audio notifications, emails, etc.

[0562] "Store staff" refers to employees who work in brick-and-mortar stores such as restaurants and retailers. Their work shifts and tasks need to be managed.

[0563] "Shift information" is information about the schedule of store staff, such as working hours, holidays, and shift changes.

[0564] "Job Description" refers to the specific tasks and roles that restaurant staff must perform (e.g., setting tables, cleaning, taking orders).

[0565] A "prompt sentence" is a text sentence of a specific format that the system inputs to the generative AI model to generate an optimal schedule.

[0566] The "generated shift schedule" refers to an optimal work schedule for store staff generated by the generation means.

[0567] "Real time" means that data processing occurs virtually immediately, within a very short time frame.

[0568] This invention is a system that efficiently manages the schedules and tasks of couples and store staff. It collects the working status and routines of couples and store staff, generates optimal schedules, and sends reminders. This system is effectively operated using a cloud server and smartphone application.

[0569] System configuration

[0570] The system mainly consists of the following hardware and software:

[0571] Server: Collects data, generates schedules, and manages the database.

[0572] Database: PostgreSQL is used to store user and staff schedule information, as well as generated schedule information.

[0573] Backend: Server-side processing is performed using the Django framework using Python.

[0574] Front-end: Develop a smartphone application using React Native.

[0575] Notification system: Uses Firebase Cloud Messaging to send reminders and notifications.

[0576] Generative AI models: Use models such as OpenAI's GPT-3 to generate optimal schedules.

[0577] Processing flow and roles

[0578] Data entry and collection

[0579] Users (couples or store staff) log in to the smartphone app and enter their work shift and routine information. This data is sent in real time to a cloud server and stored in a database.

[0580] Generate a schedule

[0581] The server uses a generative AI model to generate an optimal schedule based on the information stored in the database. This model receives schedule information and prompts entered by users and staff. For example, the following prompts can be input into the generative AI model:

[0582] Example prompt sentence:

[0583] "Generate the optimal shift schedule and task assignments for store staff based on the following data: Data: Staff A (Work: 9:00-17:00, Break: 12:00-13:00), Staff B (Work: 10:00-18:00, Break: 13:00-14:00). Store tasks: Prepare breakfast, clean the store, set tables, take orders, prepare dinner."

[0584] Viewing and Monitoring Schedules

[0585] The generated schedule is visually displayed to each user and staff member on a smartphone app. Users and staff members can check the progress of their assigned tasks in real time, and the database is updated when they report completed tasks.

[0586] Reminders

[0587] Use the notification system to send reminders to users and staff via pop-up and audio notifications sent via Firebase Cloud Messaging, helping users and staff remember to complete tasks.

[0588] Specific examples

[0589] For example, the family restaurant "Smile Diner" uses the system as follows:

[0590] 9:00 AM - The restaurant opens and Staff A begins preparing breakfast in the kitchen.

[0591] 10:00 AM - The app sends a reminder notification and Staff B begins cleaning the store.

[0592] 12:00 noon - Staff A goes on break and Staff C transitions to setting tables and taking orders.

[0593] 3:00 PM - Staff member A returns and takes on the task of preparing dinner.

[0594] This allows for efficient division of labor among staff members, ensuring smooth operation.

[0595] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0596] Step 1:

[0597] The user logs into the smartphone app and enters frequent schedule and routine information. The server saves this input information in a database on the cloud. The input for this step is the working hours and task information of couples and store staff, and the output is user data saved in the database. Specifically, the user enters information into the input fields on the screen and presses the send button, which sends the data to the server.

[0598] Step 2:

[0599] The server retrieves the information stored in the database and inputs prompt statements to the generative AI model to generate an optimal schedule. The input for this step is the user data stored in the database and the generative AI model, and the output is the generated schedule. The server runs a Python script to extract information from the database, pass it to the generative AI model, and receive a response.

[0600] Step 3:

[0601] The generated schedule is saved in the database again and transferred to the smartphone app. The input of this step is the generated schedule, and the output is the schedule saved in the database and transferred to the smartphone app. The server adds the response from the generative AI model to the database and sends the data to the device via WebSocket or API to notify the user in real time.

[0602] Step 4:

[0603] The user checks the generated schedule through the smartphone app and updates the progress of each task. The input of this step is the user's task completion information, and the output is updated database information. The user marks the task as completed on the smartphone app screen, and the information is immediately sent to the server.

[0604] Step 5:

[0605] The server periodically monitors the progress of the task and sends reminders and notifications as needed. The input for this step is the current time and the schedule stored in the database, and the output is a reminder notification to the user. The server sends the reminder at the set time via Firebase Cloud Messaging and provides the notification to the user.

[0606] Through these steps, the system can efficiently manage the schedules and tasks of users and store staff, and provide notifications at the appropriate times.

[0607] 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.

[0608] This invention is a system that allows couples to comfortably manage the tasks necessary for child-rearing and efficiently adjust schedules, and its effectiveness is enhanced by combining it with an emotion engine that recognizes the user's emotions. This system collects information about the couple's schedule and the child's routine, generates and displays an optimal task schedule, monitors task progress, notifies reminders, and adjusts tasks and notifications appropriately based on the recognized emotions.

[0609] System Overview

[0610] The system has the following main features:

[0611] 1. User data input function

[0612] 2. Schedule generation function

[0613] 3. Task management function

[0614] 4. Notification function

[0615] 5. Emotion recognition function

[0616] 1. User data input function

[0617] After logging in to the application, users enter information about their spouse's schedule and their child's routine, including each spouse's working hours and vacations, baby feeding and diaper changing times, etc. The server collects this information and stores it in a database.

[0618] 2. Schedule generation function

[0619] The server retrieves user data stored in the database and uses a generative AI model to generate an optimal task schedule. This schedule takes into account the couple's schedules, assigning tasks to the wife when the husband is at work, and vice versa. The generated schedule is saved in the database.

[0620] 3. Task management function

[0621] Based on the schedule, the device visually displays the current and next tasks to be done to the user. The progress of tasks is monitored in real time, allowing the user to check the tasks in progress. The user can notify the server of completed tasks on the device, and the server updates the database and adjusts the next tasks.

[0622] 4. Notification function

[0623] The device will send reminder notifications at the necessary times based on the set schedule, which can be in the form of a pop-up, voice, email, etc. When a task reminder is triggered, the user can check the notification and start working on the task.

[0624] 5. Emotion recognition function

[0625] The device is equipped with an emotion engine that recognizes emotions from the user's facial expressions and voice. This allows the device to grasp the user's stress level and motivation in real time. The recognized emotions are sent to a server, which automatically adjusts tasks and schedules.

[0626] Specific examples

[0627] For example, in a household where the husband works from 9am to 6pm and the wife works from 11am to 8pm, tasks might be managed as follows:

[0628] 1. 9 AM - Husband starts work. The emotion engine recognizes his stress level and sends reminders to his wife as needed.

[0629] 2. 10:00 AM - Wife feeds and changes the baby. The emotion engine recognizes her stress level and adjusts the division of tasks.

[0630] 3. 11:00 AM - Wife starts work. System assigns task to husband during lunch break.

[0631] 4. 1 PM - Husband feeds and changes baby during his lunch break. The Emotion Engine reassessed his stress level.

[0632] 5. 4 PM - Wife does evening feeding and diaper change. Emotion Engine adjusts notifications based on wife's feedback.

[0633] 6. 6 PM - Husband finishes work and starts preparing dinner. The system confirms the task completion and notifies him of the next scheduled event.

[0634] In this way, the couple can adjust their schedules and their children's routines, and flexibly change task allocation and notification methods based on their emotional state, allowing them to raise their children comfortably.The introduction of an emotion engine makes it possible to reduce user stress and provide an environment where users can complete tasks efficiently.

[0635] The processing flow will be explained below.

[0636] Step 1: Collect user data

[0637] 1. The user logs in to the application.

[0638] 2. The server displays a form to the logged-in user to enter the couple's schedule information and the children's routine information.

[0639] 3. The user enters their own and their partner's schedules (e.g., working hours, break times) and their child's routines (e.g., feeding times, diaper changing times).

[0640] 4. The server collects the entered information and stores it in a database.

[0641] Step 2: Collecting emotion data

[0642] 1. The emotion engine installed in the device recognizes emotions from the user's facial expressions and voice.

[0643] 2. The device sends the recognized emotion data to the server.

[0644] 3. The server stores the emotion data in a database and records the user's emotional state.

[0645] Step 3: Generate a schedule

[0646] 1. The server retrieves schedule information and emotional data of the couple and their children from the database.

[0647] 2. The server inputs the acquired data into the generative AI model and instructs it to generate an optimal task schedule.

[0648] 3. The generative AI model generates an efficient schedule that takes into account the user's emotional state based on schedule information and emotional data.

[0649] 4. The server retrieves the generated schedule and stores it in the database.

[0650] Step 4: Managing tasks

[0651] 1. The server sends the generated schedule to each terminal.

[0652] 2. Based on the received schedule, the device visually displays the current and next tasks to be done to the user.

[0653] 3. The user checks the displayed tasks and begins working on each one.

[0654] 4. The device monitors the progress of the task and provides a form where completed tasks can be recorded.

[0655] 5. When the user completes the task, the information is entered on the device and sent to the server.

[0656] 6. The server receives the completed task information and updates the database.

[0657] Step 5: Sending notifications

[0658] 1. The device will display reminders for each task at the appropriate time based on the schedule you set.

[0659] 2. When the time comes for a reminder, the device will send a pop-up notification, a sound notification, or an email notification to the user.

[0660] 3. The user sees the notification and begins the task.

[0661] 4. The server saves the notification sending history in the database and updates the next notification schedule.

[0662] Specific examples

[0663] Step 1: Collect user data

[0664] A user logs into the application and enters the husband and wife's schedules and the children's routines. For example, the husband works from 9am to 6pm and the wife works from 11am to 8pm.

[0665] Step 2: Collecting emotion data

[0666] The device's built-in emotion engine recognizes the user's current emotional state from their facial expressions and voice, collecting data such as "high stress" or "relaxed." The device then sends this information to a server, which stores it in a database.

[0667] Step 3: Generate a schedule

[0668] The server uses a generative AI model to generate an optimal task schedule based on the user's schedule information and emotional data. For example, if the emotional data indicates "high stress," the generative AI model generates a schedule that reduces the workload.

[0669] Step 4: Managing tasks

[0670] The device displays the optimal schedule to the user and monitors the progress of the tasks in real time. When the user completes a task, the information is sent to the server and the database is updated.

[0671] Step 5: Sending notifications

[0672] The device will send reminders based on the schedule, such as notifications like "It's time for the next feeding." The notification method will also be adjusted based on the emotional data, so if the user is feeling stressed, a gentle tone will be sent.

[0673] In this way, combining the emotion engine enables flexible schedule management and task notifications that take into account the user's emotional state, facilitating cooperation between spouses and reducing the burden of raising children.

[0674] Example 2

[0675] 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."

[0676] Modern couples are faced with the need to efficiently manage childcare tasks and reduce stress amid their busy lives. However, there are no systems in place that can schedule tasks while taking into account individual circumstances and emotions. Therefore, there is a need for a system that allows couples to share and execute childcare tasks comfortably and effectively.

[0677] 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.

[0678] In this invention, the server includes input means for collecting time information of the couple and information on the child's daily routine, generation means for generating an optimal task timetable based on the collected information, display means for displaying the generated task timetable, monitoring means for monitoring task progress and confirming task completion status, notification means for sending task reminders to the user, emotion recognition means for analyzing the user's facial expressions and voice and recognizing their emotional state, and adjustment means for adjusting tasks and notifications based on the recognized emotion. This enables optimal management and sharing of childcare tasks while taking into account the couple's schedules and emotional state.

[0679] "Married couple time information" is data that indicates the husband or wife's working hours, vacation time, and their schedules.

[0680] "Children's daily routine information" is data that represents a child's daily routines and schedules, such as feeding times, diaper changing times, and sleeping times.

[0681] "Input means" refers to the interface and software that allows users to input their schedules and children's daily routines.

[0682] "Generation means" refers to the algorithm and generative AI model that creates an optimal task schedule based on input information.

[0683] The "display means" refers to a display device or application interface for visually presenting the generated task timetable to the user.

[0684] "Monitoring tools" are software and hardware used to view and track the progress and completion of tasks in real time.

[0685] "Notification means" refers to the system and method for sending reminders and task notifications to users.

[0686] The "emotion recognition means" refers to software and hardware for analyzing the user's facial expressions and voice to recognize the user's emotional state.

[0687] "Adjustment" refers to algorithms and systems for dynamically modifying and adjusting the content and timing of tasks and notifications based on perceived emotions.

[0688] The "data repository" is a database and storage device for storing collected data and generated task timetables.

[0689] "Users" refers to individuals who use the system, primarily couples.

[0690] This invention is a system that collects information on couples' time and children's daily routines, generates and displays an optimal task schedule, monitors task progress, and sends reminder notifications.It also has the ability to recognize the user's emotions and adjust tasks and notifications appropriately based on their emotions.

[0691] System Overview

[0692] The system consists of the following main hardware and software:

[0693] Server: Database (e.g. MySQL), generative AI model (e.g. GPT-4)

[0694] Device (smartphone or tablet): Input form, display screen, emotion recognition engine (e.g., Microsoft Azure Emotion API)

[0695] Users: A married couple who use this system

[0696] User data input function

[0697] Users log in to the application and enter schedule information such as husband and wife's working hours, vacation time, baby feeding and diaper changing times, etc. This information is collected by the server and stored in a database. OAuth 2.0 is used for login, and HTML forms and JavaScript are used for data entry.

[0698] Schedule generation function

[0699] The server retrieves the user data stored in the database and generates an optimal task timetable using a generative AI model (e.g., GPT-4). Example prompt: "Generate the optimal task schedule based on the husband and wife's schedules and children's routine information." The generated timetable is then saved back to the database.

[0700] Task management function

[0701] The device visually displays the current and upcoming tasks to the user based on a schedule retrieved from the database. Task progress is monitored in real time, and as the user completes a task, the server updates the database with that information. This display is done using HTML and JavaScript.

[0702] Notification function

[0703] The device will send reminder notifications based on the schedule you set, in the form of pop-ups, sounds, emails, etc., using the JavaScript timer function.

[0704] Emotion recognition function

[0705] The device uses the built-in camera and microphone to capture the user's facial expressions and voice, and sends them to an emotion recognition engine (e.g., Microsoft Azure's Emotion API) for analysis. The emotion data is sent to a server, which dynamically adjusts tasks and notifications.

[0706] Specific examples

[0707] For example, in a household where the husband works from 9am to 6pm and the wife works from 11am to 8pm, tasks might be managed as follows:

[0708] 1. 9 AM - Husband starts work, emotion engine recognizes husband's stress level, and sends wife a reminder if necessary.

[0709] 2. 10:00 AM - Wife feeds and changes the baby. The emotion engine recognizes her stress level and the system adjusts the distribution of tasks.

[0710] 3. 11:00 AM - Wife starts work. System assigns husband a task during his lunch break.

[0711] 4. 1 PM - Husband feeds and changes baby during his lunch break. The Emotion Engine reassessed his stress level.

[0712] 5. 4 PM - Wife does evening feeding and diaper change. Emotion engine adjusts notifications based on wife's feedback.

[0713] 6. 6 PM - Husband finishes work and starts preparing dinner. The system confirms task completion and notifies him of his next scheduled appointment.

[0714] This system allows parents to smoothly raise their children by adjusting their schedules and the children's daily routines, and flexibly changing task allocation and notification methods based on their emotional state.The introduction of an emotion recognition engine can reduce user stress and provide an environment in which tasks can be completed efficiently.

[0715] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0716] Step 1: User data input

[0717] A user logs in to an application. First, they enter their login information and send it to the authentication server. The authentication server authenticates the user using OAuth 2.0 and, if successful, generates and returns an authentication token. The device stores this token and uses it for subsequent operations.

[0718] Input: Username and Password

[0719] Output: Authentication token

[0720] Users enter schedule information such as husband and wife working hours, vacation time, baby feeding and diaper changing times, etc. The input information is collected using an HTML form and JavaScript and sent to the server in JSON format.

[0721] Input: Schedule information (working hours, holidays, breastfeeding time, diaper changing time, etc.)

[0722] Output: Schedule information in JSON format

[0723] The server parses the received JSON data and saves it to a MySQL database using an INSERT query. The database stores the schedule information for each husband, wife, and child.

[0724] Input: Schedule information in JSON format

[0725] Output: Schedule data stored in the database

[0726] Step 2: Schedule generation

[0727] The server retrieves user data from the database using a SQL "SELECT" query, which is then converted into a Python data frame (e.g., Pandas) for internal processing.

[0728] Input: Schedule data stored in the database

[0729] Output: Data frame for internal processing

[0730] The server inputs a prompt into a generative AI model (e.g., GPT-4) to generate an optimal task timetable. An example prompt is "Please generate an optimal task schedule based on the husband and wife's schedules and children's routine information." The generative AI model generates a task timetable based on the received prompt and returns it in JSON format.

[0731] Input: User data and prompt statements

[0732] Output: Task timetable in JSON format

[0733] The server saves the generated task timetable to the database using an "INSERT" query. The database stores the schedule ID, task details, start time, end time, etc.

[0734] Input: Task timetable in JSON format

[0735] Output: Task timetable saved in the database

[0736] Step 3: Task Management

[0737] The device retrieves the current schedule from the database with a "GET" request. The server receives the request, retrieves the data using an SQL "SELECT" query, and returns it to the device in JSON format.

[0738] Input: Task timetable stored in the database

[0739] Output: Task information in JSON format

[0740] The device parses the received JSON data and displays a list of tasks using HTML and JavaScript. The user interface displays the current and next tasks.

[0741] Input: Task information in JSON format

[0742] Output: Task list display screen

[0743] When a user completes a task, they tap the task on their device to send a completion notification, which then sends the completion notification data in JSON format to the server.

[0744] Input: Completion notification (task ID, completion status, etc.)

[0745] Output: JSON format completion notification

[0746] The server receives the completion notification and updates the database using an "UPDATE" query, changing the status of the completed task to "completed" and coordinating the next task.

[0747] Input: JSON format completion notification

[0748] Output: Updated database

[0749] Step 4: Notification

[0750] The device uses a JavaScript timer function to set reminders for each task based on the schedule data, and the timer will trigger an alert when the task's start time approaches.

[0751] Input: Task start time

[0752] Output: Set timer

[0753] When the timer triggers an alert, the device sends the user a reminder notification in the form of a pop-up, voice, email, or other format.

[0754] Input: Timer alert

[0755] Output: Reminder notification

[0756] Step 5: Emotion Recognition

[0757] The device captures the user's facial expressions and voice using the device's built-in camera and microphone, and this captured data is obtained in real time using WebRTC.

[0758] Input: facial expression data, voice data

[0759] Output: Captured data

[0760] The device sends the captured data to an emotion recognition engine (e.g., Microsoft Azure's Emotion API) for analysis, and the emotion engine returns the emotional state in JSON format.

[0761] Input: Captured data

[0762] Output: Emotion data in JSON format

[0763] The server dynamically adjusts the task order and notification method based on the emotion data received from the emotion engine, and updates the database contents using the "UPDATE" query to reflect the changes in real time.

[0764] Input: Emotion data in JSON format

[0765] Output: Adjusted task schedule and notification method

[0766] (Application example 2)

[0767] 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."

[0768] In modern society, the number of dual-income households is increasing, making it a major challenge to raise children efficiently and comfortably. In particular, couples raising children face the complexities of managing their daily schedules, making it difficult to keep track of task progress in real time. Furthermore, the impact of stress and emotional changes on child-rearing cannot be ignored. Therefore, in order for couples to raise children smoothly, they need support not only through task management but also through emotional recognition. Appropriate support is also needed when purchasing childcare products or seeking advice in physical stores.

[0769] 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 input means for collecting schedule information of the couple and information about the child's routine, generation means for generating an optimal task schedule based on the collected information, display means for displaying the generated task schedule, monitoring means for monitoring the progress of tasks and confirming their completion status, notification means for sending task reminders to the user, recognition means for recognizing emotions from the user's facial expressions and voice, adjustment means for appropriately adjusting tasks and notification methods based on the recognized emotions, guidance means for navigating to specific areas within the store, and conversation means for receiving childcare consultations from the user. This enables couples to raise their children efficiently and flexibly adjust tasks based on their emotional state, making it easier to purchase childcare products and receive childcare consultations in physical stores.

[0770] "Input means" refers to a device or method for collecting information on the couple's schedule and the children's routines.

[0771] A "generation means" is a device or method that generates an optimal task schedule based on collected information.

[0772] The "display means" is a device or method that visually presents the generated task schedule to the user.

[0773] A "monitoring means" is a device or method that tracks the progress of a task and verifies its completion.

[0774] A "notifier" is a device or method that sends task reminders to a user.

[0775] The "recognition means" is a device or method for analyzing emotions from the user's facial expressions and voice.

[0776] An "adjustment means" is a device or method that changes tasks or notification methods based on recognized emotions.

[0777] "Guidance means" refers to a device or method that provides directions or navigation to a specific area within a store.

[0778] The "conversation means" is an interactive device or method for receiving advice from the user regarding child rearing.

[0779] This invention provides a system that mainly comprises the following means. Specifically, it is a system that collects information on couples' schedules and children's routines, and generates, displays, monitors, notifies, and adjusts an optimal task schedule. It also has a conversation means that recognizes emotions from the user's facial expressions and voice, and receives consultations about child-rearing from the user.

[0780] System Configuration

[0781] 1. Input method:

[0782] The server uses devices such as smartphones and tablets to input information about the couple's schedule and the child's routine. The user inputs this information through an application and sends it to the server.

[0783] 2. Generation means:

[0784] The server uses a generative AI model to generate an optimal task schedule based on the collected information on the couple's schedule and the child's routine. This task schedule is automatically calculated, taking into account the user's working hours and the child's daily rhythm.

[0785] 3. Display means:

[0786] The terminal visually displays the generated task schedule to the user, who can then check the schedule via a dedicated application.

[0787] 4. Monitoring measures:

[0788] The device monitors the progress of the task in real time, and when the user completes the task, the device sends the information to the server and updates the database.

[0789] 5. Means of notification:

[0790] The device will send reminders to the user for scheduled tasks in the form of push notifications, emails, audio alerts, etc.

[0791] 6. Emotion recognition means:

[0792] The device captures the user's facial expressions and voice and uses an emotion engine to recognize the user's emotional state. For example, it uses a facial recognition library (such as face-api.js) to analyze the facial expression data and evaluate the user's stress level.

[0793] 7. Adjustment means:

[0794] The server then adjusts tasks and notifications accordingly based on the recognized emotions, for example, changing task priorities or making notifications more gentle if the user indicates a high stress level.

[0795] 8. Guidance means:

[0796] The device provides navigation when users are searching for specific areas within a physical store, such as directions to childcare products and breastfeeding areas.

[0797] 9. Means of communication:

[0798] The device accepts user inquiries about childcare via an AI chatbot. When a user inputs a question about childcare, the chatbot provides appropriate advice.

[0799] Specific examples

[0800] For example, if the system is used in a household where the husband works from 9:00 a.m. to 6:00 p.m. and the wife works from 11:00 a.m. to 8:00 p.m., the process will proceed as follows:

[0801] 1. 9:00 AM: The server notices that the husband has started work and sends a reminder notification to the wife.

[0802] 2. 10 AM: The device displays tasks for the wife to breastfeed and change the diaper. The emotion engine recognizes her stress level and readjusts the tasks as needed.

[0803] 3. 11:00 AM: The wife starts work, the server updates this information, and generates a schedule so that the task is assigned during the husband's lunch break.

[0804] 4. 1 PM: The device sends feeding and diaper change reminders to her husband, and uses facial recognition technology to reassess his stress level.

[0805] 5. 4 PM: My wife does the evening feeding and diaper change while the device monitors the progress.

[0806] 6. 6 PM: The server recognizes that my husband has finished work and notifies him of the upcoming dinner preparation task.

[0807] An example of a prompt might be, "Sir, it seems you're feeling stressed right now. Here's the nearest diaper changing area. Also, if you have any childcare concerns, please ask our childcare consultation chatbot."

[0808] This system allows couples to raise their children efficiently, flexibly manage tasks based on their emotional state, and provides comprehensive support within physical stores.

[0809] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0810] Step 1:

[0811] The server collects information about the couple's schedule and the child's routine entered by the user using input methods, including input from a smartphone or tablet. The input data includes the couple's working hours, the timing of the child's feeding and diaper changes, etc. This data is sent to the server and stored in a database.

[0812] Step 2:

[0813] The server acquires the collected schedule and routine information and generates an optimal task schedule using a generative AI model. This generation involves implementing an algorithm to allocate tasks appropriately, taking into account the user's working hours and children's daily routines. The output is saved in a database as the generated task schedule.

[0814] Step 3:

[0815] The terminal uses a display means to visually display the task schedule obtained from the server to the user. Specifically, the user can check the current and next tasks to be performed through a dedicated application. The input in this process is the task schedule obtained from the server, and the output is the schedule displayed on the user's terminal screen.

[0816] Step 4:

[0817] The terminal monitors the progress of the task in real time using a monitoring means. When the user completes the task, the terminal sends the information to the server, which updates the database. The input to this process is the user's notification of task completion, and the output is the updated task information in the database.

[0818] Step 5:

[0819] The device uses a notification mechanism to send task reminders to the user, which can take the form of real-time push notifications, emails, voice alerts, etc. The input is the time information of the scheduled task, and the output is the reminder notification to the user.

[0820] Step 6:

[0821] The device uses a recognition means to recognize emotions from the user's facial expressions and voice. Specifically, it uses a facial expression recognition library (such as face-api.js) to analyze the video captured by the camera and generate emotion data. The input is the camera video and audio data, and the output is the analyzed emotion data.

[0822] Step 7:

[0823] The server adjusts tasks and notification methods accordingly based on the recognized emotion data. For example, if the stress level is high, it may change the priority of the task or change the notification method to a softer tone. The input is emotion data, and the output is the adjusted task schedule and notification method.

[0824] Step 8:

[0825] The device uses the guidance means to navigate to a specific area within a physical store, indicating the location of childcare products and equipment that the user has searched for in the application. The input is a search request from the user, and the output is navigation information.

[0826] Step 9:

[0827] The device uses a conversational means to receive childcare-related consultations from the user via an AI chatbot. When the user inputs a childcare-related question through the application, the chatbot uses a generative AI model to provide appropriate advice. The input is the user's question, and the output is advice from the chatbot.

[0828] 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.

[0829] 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.

[0830] 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.

[0831] [Third embodiment]

[0832] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0833] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0834] 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).

[0835] 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.

[0836] 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.

[0837] 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).

[0838] 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.

[0839] 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.

[0840] 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.

[0841] 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.

[0842] 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.

[0843] 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."

[0844] This invention is a system that allows couples to manage the tasks necessary for child-rearing comfortably and adjust schedules efficiently. This system collects information on the couple's schedules and the child's routines, generates and displays an optimal task schedule, monitors the progress of tasks, and sends reminders.

[0845] System Overview

[0846] The system has the following main features:

[0847] 1. User data input function

[0848] 2. Schedule generation function

[0849] 3. Task management function

[0850] 4. Notification function

[0851] 1. User data input function

[0852] After logging in to the application, users enter information about their spouse's schedule and their child's routine, including each spouse's working hours and vacations, baby feeding and diaper changing times, etc. The server collects this information and stores it in a database.

[0853] 2. Schedule generation function

[0854] The server retrieves user data stored in the database and uses a generative AI model to generate an optimal task schedule. This schedule takes into account the couple's schedules, assigning tasks to the wife when the husband is at work, and vice versa. The generated schedule is saved in the database.

[0855] 3. Task management function

[0856] The terminal displays a list of tasks for each user based on the acquired schedule. The progress of tasks is monitored in real time, allowing the user to check the tasks in progress. When the user notifies the terminal of completed tasks, the server updates the database and adjusts the next tasks.

[0857] 4. Notification function

[0858] The device will send reminder notifications at the necessary times based on the set schedule, which can be in the form of a pop-up, voice, email, etc. When a task reminder is triggered, the user can check the notification and start working on the task.

[0859] Specific examples

[0860] For example, in a household where the husband works from 9am to 6pm and the wife works from 11am to 8pm, tasks might be managed as follows:

[0861] 1. 9:00 AM - Husband starts work.

[0862] 2. 10:00 AM - My wife feeds and changes the baby.

[0863] 3. 11:00 AM - My wife starts work.

[0864] 4. 1:00 PM - Husband feeds and changes baby during his lunch break.

[0865] 5. 4:00 PM - My wife does the evening feeding and diaper change.

[0866] 6. 6pm - Husband finishes work and starts preparing dinner.

[0867] In this way, couples can adjust their schedules and children's routines, and share tasks comfortably. The system sends reminder notifications and supports task management in real time, reducing the burden of child-rearing and providing an environment where parents can enjoy raising their children without stress.

[0868] The processing flow will be explained below.

[0869] Step 1: Collect user data

[0870] 1. The user logs in to the application.

[0871] 2. The server displays a form to the logged-in user to enter information about the couple's individual schedules and children's routines.

[0872] 3. Users enter their own schedule (work hours and break times), their partner's schedule, and their child's routine (feeding and diaper changing times) into the form.

[0873] 4. The server collects the entered information and stores it in a database.

[0874] Step 2: Generate a schedule

[0875] 1. The server retrieves the schedule information of the couple and their children from the database.

[0876] 2. The server inputs the acquired data into the generative AI model and instructs it to generate an optimal task schedule.

[0877] 3. Based on the schedule information, the generative AI model generates an efficient schedule that takes into account the convenience of each couple and the needs of their children.

[0878] 4. The server retrieves the generated schedule and stores it in the database.

[0879] Step 3: Managing tasks

[0880] 1. The server sends the generated schedule to each terminal.

[0881] 2. Based on the received schedule, the device visually displays the current and next tasks to be done to the user.

[0882] 3. The user checks the displayed tasks and begins working on each one.

[0883] 4. The device monitors the progress of the task and provides a form where completed tasks can be recorded.

[0884] 5. When the user completes the task, the information is entered on the terminal and sent to the server.

[0885] 6. The server receives the completed task information and updates the database.

[0886] Step 4: Sending notifications

[0887] 1. The device will display reminders for each task at the appropriate time based on the schedule you set.

[0888] 2. When the time comes for a reminder, the device will send a pop-up notification, a sound notification, or an email notification to the user.

[0889] 3. The user sees the notification and begins the task.

[0890] 4. The server saves the notification sending history in the database and updates the next notification schedule.

[0891] Example 1

[0892] 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."

[0893] In modern households, couples face challenges in managing child-rearing tasks comfortably and efficiently. Creating and managing an optimal schedule requires taking into account various factors, such as each spouse's working hours, holidays, and children's routines. However, doing this manually can be difficult and stressful. In these circumstances, a system that provides efficient task management and timely reminder notifications is needed.

[0894] 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.

[0895] In this invention, the server includes an input means for collecting the couple's schedule information and the child's regular routine information, a generation means for generating an optimal task schedule based on the collected information, and a display means for displaying the schedule generated by using the generation AI model as the generation means, thereby enabling couples to efficiently manage the tasks necessary for child-rearing without strain and easily adjust their schedules.

[0896] "Married couple schedule information" is information about the schedules of the husband and wife, such as their working hours and holidays.

[0897] "Child routine information" refers to information about a child's daily activities and habits, such as feeding times and diaper changing times.

[0898] The "input means" is a means by which a user inputs information about the couple's schedule and information about the children's regular schedule into the application.

[0899] The "generation means" is a means for generating an optimal task schedule based on collected information, and in this invention, this is the part that uses the generative AI model.

[0900] A "generative AI model" is an artificial intelligence model that generates an optimal task schedule based on a specific prompt sentence.

[0901] The "display means" is a means for displaying the generated task schedule to the user.

[0902] The "monitoring means" is a means for monitoring the progress of a task and checking the completion state of the task.

[0903] A "notification means" is a means for sending task reminders to a user.

[0904] The "storage means" is a means for storing the generated schedule in a database.

[0905] The "update means" is a means for updating the information in the database after the user completes a task.

[0906] A "database" is a system for storing collected information, generated schedules, task progress, etc.

[0907] A "terminal" is a device that allows a user to check task schedules and update progress.

[0908] A "server" is a central computer system that collects user data, generates schedules, stores and updates data, and sends reminder notifications.

[0909] A "user" is an individual who uses the system to input, confirm, and report completion of tasks.

[0910] The present invention is a system for enabling couples to manage tasks necessary for raising children without straining themselves and to adjust schedules efficiently. Specific embodiments of this system will be described below.

[0911] This system consists of a server, terminals, and users, and has the following main functions:

[0912] 1. User data input function

[0913] 2. Schedule generation function

[0914] 3. Task management function

[0915] 4. Notification function

[0916] User data input function

[0917] After logging in to the application, the user enters the couple's schedule information and the child's regular schedule information. For example, the husband's working hours (9:00-18:00), the wife's working hours (11:00-20:00), and the child's feeding times (10:00, 13:00, 16:00). This information is sent to the server and stored in the database.

[0918] Schedule generation function

[0919] The server retrieves user information collected from the database and provides prompts to the generative AI model to generate an optimal task schedule. For example, the prompt might be, "Consider the couple's schedule and the child's routine, and generate an optimal childcare schedule." The generated schedule is then stored in the database.

[0920] Task management function

[0921] The terminal retrieves schedule information from the database and displays a list of tasks to the user. When the user completes a task, they enter their progress into the terminal, which then sends the information to the server. The server receives this information and updates the database.

[0922] Notification function

[0923] The device calculates the timing of the reminder notification based on the schedule and sends the reminder to the user at the appropriate time. The reminder is sent in the form of a pop-up, voice, email, etc. The user can check the reminder and start working on the task.

[0924] Specific examples

[0925] For example, in a household where the husband works from 9am to 6pm and the wife works from 11am to 8pm, tasks might be managed as follows:

[0926] 1. 9:00 AM - My husband starts work.

[0927] 2. 10:00 AM - My wife feeds and changes the baby.

[0928] 3. 11:00 AM - My wife starts work.

[0929] 4. 1:00 PM - Husband feeds and changes baby during his lunch break.

[0930] 5. 4:00 PM - My wife does the evening feeding and diaper change.

[0931] 6. 6 PM - Husband finishes work and starts preparing dinner.

[0932] In this way, couples can efficiently coordinate their schedules and children's routines, allowing them to share tasks comfortably and reducing the burden of child-rearing.

[0933] Prompt Sentence Examples

[0934] "Generate the optimal childcare schedule, taking into account the couple's schedules and the child's routines."

[0935] This system provides an environment for couples to efficiently manage child-rearing tasks and reduce stress.

[0936] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0937] Step 1:

[0938] A user logs in to the application by entering their user ID and password. This information is sent to the server, which authenticates the user. If authentication is successful, the dashboard is displayed.

[0939] Step 2:

[0940] The user inputs the couple's schedule information and the child's regular schedule information. Specifically, the husband's working hours, the wife's working hours, the child's breastfeeding times, etc. The server receives this input data and stores it in a database. Examples of input data include the husband's working hours "9:00-18:00", the wife's working hours "11:00-20:00", and the child's breastfeeding times "10:00, 13:00, 16:00".

[0941] Step 3:

[0942] The server retrieves user data collected from the database. Based on this information, it provides prompts to the generative AI model. As a specific example, the prompt is "Generate the optimal childcare schedule, taking into account the couple's schedule and the child's routine." Based on this prompt, the generative AI model generates the optimal task schedule. The generated schedule is returned to the server and saved in the database again.

[0943] Step 4:

[0944] The device retrieves schedule information related to the user from the database. The device displays the retrieved schedule to the user. For example, at 10:00 AM, the device displays information such as "The wife will breastfeed and change diapers," and at 1:00 PM, the device displays information such as "The husband will breastfeed and change diapers during his lunch break."

[0945] Step 5:

[0946] The user inputs the progress of the task into the terminal. For example, if the task at 10:00 AM is completed, the user inputs "Task completed at 10:00 AM." This information is sent to the server via the terminal.

[0947] Step 6:

[0948] The server receives the task completion information sent by the user and updates the database. Specifically, it changes the status of the corresponding task to "Completed."

[0949] Step 7:

[0950] The device calculates the timing of the reminder based on the schedule, for example, setting a reminder 10 minutes before the task starts, and the reminder can be in the form of a pop-up, sound notification, email, or other notification.

[0951] Step 8:

[0952] The device will send reminder notifications to the user at the set times. For example, at 9:50 a.m., a reminder to "feed and change diapers at 10 a.m." The user can confirm the reminder and get to work on the task.

[0953] Through these steps, the system efficiently performs a series of processes from collecting user data to generating schedules, managing tasks, and sending reminder notifications.

[0954] (Application example 1)

[0955] 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."

[0956] While existing systems allow couples to comfortably manage the tasks required for child-rearing and efficiently adjust schedules, there is a lack of a general-purpose system that can handle shift management and task allocation for store staff. This makes it difficult to manage tasks among staff and reduce the burden on each staff member.

[0957] 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.

[0958] In this invention, the server includes input means for collecting couple schedule information and child routine information, generation means for generating an optimal task schedule based on the collected information, display means for displaying the generated task schedule, monitoring means for monitoring task progress and confirming task completion status, notification means for sending task reminders to users, input means for collecting store staff shift information and work details, generation means for generating an optimal store staff shift schedule based on the collected information, and notification means for reminding store staff of the generated shift schedule, thereby enabling effective task management and real-time shift schedule management.

[0959] "Married couple schedule information" is information about the time schedules of the husband and wife, such as their working hours, holidays, and daily routines.

[0960] "Child routine information" is information about a child's daily activities and the times of care required (such as feeding times and diaper changes).

[0961] "Input means" refers to the interface through which a user inputs schedule and routine information into the application, and includes smartphone apps and web applications.

[0962] "Generators" are algorithms or systems that automatically create optimal task schedules based on collected information. This includes schedule generation using generative AI models.

[0963] The "display means" is an interface for visually presenting the generated task schedule to the user, such as a smartphone screen or a computer monitor.

[0964] The "monitoring means" is a system for checking the progress of tasks in real time and tracking the user's progress. This includes sensing technology and real-time data processing technology.

[0965] "Notification means" refers to a means for notifying users of task reminders and important events. This means conveying information to users in the form of pop-up notifications, audio notifications, emails, etc.

[0966] "Store staff" refers to employees who work in brick-and-mortar stores such as restaurants and retailers. Their work shifts and tasks need to be managed.

[0967] "Shift information" is information about the schedule of store staff, such as working hours, holidays, and shift changes.

[0968] "Job Description" refers to the specific tasks and roles that restaurant staff must perform (e.g., setting tables, cleaning, taking orders).

[0969] A "prompt sentence" is a text sentence of a specific format that the system inputs to the generative AI model to generate an optimal schedule.

[0970] The "generated shift schedule" refers to an optimal work schedule for store staff generated by the generation means.

[0971] "Real time" means that data processing occurs virtually immediately, within a very short time frame.

[0972] This invention is a system that efficiently manages the schedules and tasks of couples and store staff. It collects the working status and routines of couples and store staff, generates optimal schedules, and sends reminders. This system is effectively operated using a cloud server and smartphone application.

[0973] System configuration

[0974] The system mainly consists of the following hardware and software:

[0975] Server: Collects data, generates schedules, and manages the database.

[0976] Database: PostgreSQL is used to store user and staff schedule information, as well as generated schedule information.

[0977] Backend: Server-side processing is performed using the Django framework using Python.

[0978] Front-end: Develop a smartphone application using React Native.

[0979] Notification system: Uses Firebase Cloud Messaging to send reminders and notifications.

[0980] Generative AI models: Use models such as OpenAI's GPT-3 to generate optimal schedules.

[0981] Processing flow and roles

[0982] Data entry and collection

[0983] Users (couples or store staff) log in to the smartphone app and enter their work shift and routine information. This data is sent in real time to a cloud server and stored in a database.

[0984] Generate a schedule

[0985] The server uses a generative AI model to generate an optimal schedule based on the information stored in the database. This model receives schedule information and prompts entered by users and staff. For example, the following prompts can be input into the generative AI model:

[0986] Example prompt sentence:

[0987] "Generate the optimal shift schedule and task assignments for store staff based on the following data: Data: Staff A (Work: 9:00-17:00, Break: 12:00-13:00), Staff B (Work: 10:00-18:00, Break: 13:00-14:00). Store tasks: Prepare breakfast, clean the store, set tables, take orders, prepare dinner."

[0988] Viewing and Monitoring Schedules

[0989] The generated schedule is visually displayed to each user and staff member on a smartphone app. Users and staff members can check the progress of their assigned tasks in real time, and the database is updated when they report completed tasks.

[0990] Reminders

[0991] Use the notification system to send reminders to users and staff via pop-up and audio notifications sent via Firebase Cloud Messaging, helping users and staff remember to complete tasks.

[0992] Specific examples

[0993] For example, the family restaurant "Smile Diner" uses the system as follows:

[0994] 9:00 AM - The restaurant opens and Staff A begins preparing breakfast in the kitchen.

[0995] 10:00 AM - The app sends a reminder notification and Staff B begins cleaning the store.

[0996] 12:00 noon - Staff A goes on break and Staff C transitions to setting tables and taking orders.

[0997] 3:00 PM - Staff member A returns and takes on the task of preparing dinner.

[0998] This allows for efficient division of labor among staff members, ensuring smooth operation.

[0999] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1000] Step 1:

[1001] The user logs into the smartphone app and enters frequent schedule and routine information. The server saves this input information in a database on the cloud. The input for this step is the working hours and task information of couples and store staff, and the output is user data saved in the database. Specifically, the user enters information into the input fields on the screen and presses the send button, which sends the data to the server.

[1002] Step 2:

[1003] The server retrieves the information stored in the database and inputs prompt statements to the generative AI model to generate an optimal schedule. The input for this step is the user data stored in the database and the generative AI model, and the output is the generated schedule. The server runs a Python script to extract information from the database, pass it to the generative AI model, and receive a response.

[1004] Step 3:

[1005] The generated schedule is saved in the database again and transferred to the smartphone app. The input of this step is the generated schedule, and the output is the schedule saved in the database and transferred to the smartphone app. The server adds the response from the generative AI model to the database and sends the data to the device via WebSocket or API to notify the user in real time.

[1006] Step 4:

[1007] The user checks the generated schedule through the smartphone app and updates the progress of each task. The input of this step is the user's task completion information, and the output is updated database information. The user marks the task as completed on the smartphone app screen, and the information is immediately sent to the server.

[1008] Step 5:

[1009] The server periodically monitors the progress of the task and sends reminders and notifications as needed. The input for this step is the current time and the schedule stored in the database, and the output is a reminder notification to the user. The server sends the reminder at the set time via Firebase Cloud Messaging and provides the notification to the user.

[1010] Through these steps, the system can efficiently manage the schedules and tasks of users and store staff, and provide notifications at the appropriate times.

[1011] 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.

[1012] This invention is a system that allows couples to comfortably manage the tasks necessary for child-rearing and efficiently adjust schedules, and its effectiveness is enhanced by combining it with an emotion engine that recognizes the user's emotions. This system collects information about the couple's schedule and the child's routine, generates and displays an optimal task schedule, monitors task progress, notifies reminders, and adjusts tasks and notifications appropriately based on the recognized emotions.

[1013] System Overview

[1014] The system has the following main features:

[1015] 1. User data input function

[1016] 2. Schedule generation function

[1017] 3. Task management function

[1018] 4. Notification function

[1019] 5. Emotion recognition function

[1020] 1. User data input function

[1021] After logging in to the application, users enter information about their spouse's schedule and their child's routine, including each spouse's working hours and vacations, baby feeding and diaper changing times, etc. The server collects this information and stores it in a database.

[1022] 2. Schedule generation function

[1023] The server retrieves user data stored in the database and uses a generative AI model to generate an optimal task schedule. This schedule takes into account the couple's schedules, assigning tasks to the wife when the husband is at work, and vice versa. The generated schedule is saved in the database.

[1024] 3. Task management function

[1025] Based on the schedule, the device visually displays the current and next tasks to be done to the user. The progress of tasks is monitored in real time, allowing the user to check the tasks in progress. The user can notify the server of completed tasks on the device, and the server updates the database and adjusts the next tasks.

[1026] 4. Notification function

[1027] The device will send reminder notifications at the necessary times based on the set schedule, which can be in the form of a pop-up, voice, email, etc. When a task reminder is triggered, the user can check the notification and start working on the task.

[1028] 5. Emotion recognition function

[1029] The device is equipped with an emotion engine that recognizes emotions from the user's facial expressions and voice. This allows the device to grasp the user's stress level and motivation in real time. The recognized emotions are sent to a server, which automatically adjusts tasks and schedules.

[1030] Specific examples

[1031] For example, in a household where the husband works from 9am to 6pm and the wife works from 11am to 8pm, tasks might be managed as follows:

[1032] 1. 9 AM - Husband starts work. The emotion engine recognizes his stress level and sends reminders to his wife as needed.

[1033] 2. 10:00 AM - Wife feeds and changes the baby. The emotion engine recognizes her stress level and adjusts the division of tasks.

[1034] 3. 11:00 AM - Wife starts work. System assigns task to husband during lunch break.

[1035] 4. 1 PM - Husband feeds and changes baby during his lunch break. The Emotion Engine reassessed his stress level.

[1036] 5. 4 PM - Wife does evening feeding and diaper change. Emotion Engine adjusts notifications based on wife's feedback.

[1037] 6. 6 PM - Husband finishes work and starts preparing dinner. The system confirms the task completion and notifies him of the next scheduled event.

[1038] In this way, the couple can adjust their schedules and their children's routines, and flexibly change task allocation and notification methods based on their emotional state, allowing them to raise their children comfortably.The introduction of an emotion engine makes it possible to reduce user stress and provide an environment where users can complete tasks efficiently.

[1039] The processing flow will be explained below.

[1040] Step 1: Collect user data

[1041] 1. The user logs in to the application.

[1042] 2. The server displays a form to the logged-in user to enter the couple's schedule information and the children's routine information.

[1043] 3. The user enters their own and their partner's schedules (e.g., working hours, break times) and their child's routines (e.g., feeding times, diaper changing times).

[1044] 4. The server collects the entered information and stores it in a database.

[1045] Step 2: Collecting emotion data

[1046] 1. The emotion engine installed in the device recognizes emotions from the user's facial expressions and voice.

[1047] 2. The device sends the recognized emotion data to the server.

[1048] 3. The server stores the emotion data in a database and records the user's emotional state.

[1049] Step 3: Generate a schedule

[1050] 1. The server retrieves schedule information and emotional data of the couple and their children from the database.

[1051] 2. The server inputs the acquired data into the generative AI model and instructs it to generate an optimal task schedule.

[1052] 3. The generative AI model generates an efficient schedule that takes into account the user's emotional state based on schedule information and emotional data.

[1053] 4. The server retrieves the generated schedule and stores it in the database.

[1054] Step 4: Managing tasks

[1055] 1. The server sends the generated schedule to each terminal.

[1056] 2. Based on the received schedule, the device visually displays the current and next tasks to be done to the user.

[1057] 3. The user checks the displayed tasks and begins working on each one.

[1058] 4. The device monitors the progress of the task and provides a form where completed tasks can be recorded.

[1059] 5. When the user completes the task, the information is entered on the device and sent to the server.

[1060] 6. The server receives the completed task information and updates the database.

[1061] Step 5: Sending notifications

[1062] 1. The device will display reminders for each task at the appropriate time based on the schedule you set.

[1063] 2. When the time comes for a reminder, the device will send a pop-up notification, a sound notification, or an email notification to the user.

[1064] 3. The user sees the notification and begins the task.

[1065] 4. The server saves the notification sending history in the database and updates the next notification schedule.

[1066] Specific examples

[1067] Step 1: Collect user data

[1068] A user logs into the application and enters the husband and wife's schedules and the children's routines. For example, the husband works from 9am to 6pm and the wife works from 11am to 8pm.

[1069] Step 2: Collecting emotion data

[1070] The device's built-in emotion engine recognizes the user's current emotional state from their facial expressions and voice, collecting data such as "high stress" or "relaxed." The device then sends this information to a server, which stores it in a database.

[1071] Step 3: Generate a schedule

[1072] The server uses a generative AI model to generate an optimal task schedule based on the user's schedule information and emotional data. For example, if the emotional data indicates "high stress," the generative AI model generates a schedule that reduces the workload.

[1073] Step 4: Managing tasks

[1074] The device displays the optimal schedule to the user and monitors the progress of the tasks in real time. When the user completes a task, the information is sent to the server and the database is updated.

[1075] Step 5: Sending notifications

[1076] The device will send reminders based on the schedule, such as notifications like "It's time for the next feeding." The notification method will also be adjusted based on the emotional data, so if the user is feeling stressed, a gentle tone will be sent.

[1077] In this way, combining the emotion engine enables flexible schedule management and task notifications that take into account the user's emotional state, facilitating cooperation between spouses and reducing the burden of raising children.

[1078] Example 2

[1079] 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."

[1080] Modern couples are faced with the need to efficiently manage childcare tasks and reduce stress amid their busy lives. However, there are no systems in place that can schedule tasks while taking into account individual circumstances and emotions. Therefore, there is a need for a system that allows couples to share and execute childcare tasks comfortably and effectively.

[1081] 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.

[1082] In this invention, the server includes input means for collecting time information of the couple and information on the child's daily routine, generation means for generating an optimal task timetable based on the collected information, display means for displaying the generated task timetable, monitoring means for monitoring task progress and confirming task completion status, notification means for sending task reminders to the user, emotion recognition means for analyzing the user's facial expressions and voice and recognizing their emotional state, and adjustment means for adjusting tasks and notifications based on the recognized emotion. This enables optimal management and sharing of childcare tasks while taking into account the couple's schedules and emotional state.

[1083] "Married couple time information" is data that indicates the husband or wife's working hours, vacation time, and their schedules.

[1084] "Children's daily routine information" is data that represents a child's daily routines and schedules, such as feeding times, diaper changing times, and sleeping times.

[1085] "Input means" refers to the interface and software that allows users to input their schedules and children's daily routines.

[1086] "Generation means" refers to the algorithm and generative AI model that creates an optimal task schedule based on input information.

[1087] The "display means" refers to a display device or application interface for visually presenting the generated task timetable to the user.

[1088] "Monitoring tools" are software and hardware used to view and track the progress and completion of tasks in real time.

[1089] "Notification means" refers to the system and method for sending reminders and task notifications to users.

[1090] The "emotion recognition means" refers to software and hardware for analyzing the user's facial expressions and voice to recognize the user's emotional state.

[1091] "Adjustment" refers to algorithms and systems for dynamically modifying and adjusting the content and timing of tasks and notifications based on perceived emotions.

[1092] The "data repository" is a database and storage device for storing collected data and generated task timetables.

[1093] "Users" refers to individuals who use the system, primarily couples.

[1094] This invention is a system that collects information on couples' time and children's daily routines, generates and displays an optimal task schedule, monitors task progress, and sends reminder notifications.It also has the ability to recognize the user's emotions and adjust tasks and notifications appropriately based on their emotions.

[1095] System Overview

[1096] The system consists of the following main hardware and software:

[1097] Server: Database (e.g. MySQL), generative AI model (e.g. GPT-4)

[1098] Device (smartphone or tablet): Input form, display screen, emotion recognition engine (e.g., Microsoft Azure Emotion API)

[1099] Users: A married couple who use this system

[1100] User data input function

[1101] Users log in to the application and enter schedule information such as husband and wife's working hours, vacation time, baby feeding and diaper changing times, etc. This information is collected by the server and stored in a database. OAuth 2.0 is used for login, and HTML forms and JavaScript are used for data entry.

[1102] Schedule generation function

[1103] The server retrieves the user data stored in the database and generates an optimal task timetable using a generative AI model (e.g., GPT-4). Example prompt: "Generate the optimal task schedule based on the husband and wife's schedules and children's routine information." The generated timetable is then saved back to the database.

[1104] Task management function

[1105] The device visually displays the current and upcoming tasks to the user based on a schedule retrieved from the database. Task progress is monitored in real time, and as the user completes a task, the server updates the database with that information. This display is done using HTML and JavaScript.

[1106] Notification function

[1107] The device will send reminder notifications based on the schedule you set, in the form of pop-ups, sounds, emails, etc., using the JavaScript timer function.

[1108] Emotion recognition function

[1109] The device uses the built-in camera and microphone to capture the user's facial expressions and voice, and sends them to an emotion recognition engine (e.g., Microsoft Azure's Emotion API) for analysis. The emotion data is sent to a server, which dynamically adjusts tasks and notifications.

[1110] Specific examples

[1111] For example, in a household where the husband works from 9am to 6pm and the wife works from 11am to 8pm, tasks might be managed as follows:

[1112] 1. 9 AM - Husband starts work, emotion engine recognizes husband's stress level, and sends wife a reminder if necessary.

[1113] 2. 10:00 AM - Wife feeds and changes the baby. The emotion engine recognizes her stress level and the system adjusts the distribution of tasks.

[1114] 3. 11:00 AM - Wife starts work. System assigns husband a task during his lunch break.

[1115] 4. 1 PM - Husband feeds and changes baby during his lunch break. The Emotion Engine reassessed his stress level.

[1116] 5. 4 PM - Wife does evening feeding and diaper change. Emotion engine adjusts notifications based on wife's feedback.

[1117] 6. 6 PM - Husband finishes work and starts preparing dinner. The system confirms task completion and notifies him of his next scheduled appointment.

[1118] This system allows parents to smoothly raise their children by adjusting their schedules and the children's daily routines, and flexibly changing task allocation and notification methods based on their emotional state.The introduction of an emotion recognition engine can reduce user stress and provide an environment in which tasks can be completed efficiently.

[1119] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1120] Step 1: User data input

[1121] A user logs in to an application. First, they enter their login information and send it to the authentication server. The authentication server authenticates the user using OAuth 2.0 and, if successful, generates and returns an authentication token. The device stores this token and uses it for subsequent operations.

[1122] Input: Username and Password

[1123] Output: Authentication token

[1124] Users enter schedule information such as husband and wife working hours, vacation time, baby feeding and diaper changing times, etc. The input information is collected using an HTML form and JavaScript and sent to the server in JSON format.

[1125] Input: Schedule information (working hours, holidays, breastfeeding time, diaper changing time, etc.)

[1126] Output: Schedule information in JSON format

[1127] The server parses the received JSON data and saves it to a MySQL database using an INSERT query. The database stores the schedule information for each husband, wife, and child.

[1128] Input: Schedule information in JSON format

[1129] Output: Schedule data stored in the database

[1130] Step 2: Schedule generation

[1131] The server retrieves user data from the database using a SQL "SELECT" query, which is then converted into a Python data frame (e.g., Pandas) for internal processing.

[1132] Input: Schedule data stored in the database

[1133] Output: Data frame for internal processing

[1134] The server inputs a prompt into a generative AI model (e.g., GPT-4) to generate an optimal task timetable. An example prompt is "Please generate an optimal task schedule based on the husband and wife's schedules and children's routine information." The generative AI model generates a task timetable based on the received prompt and returns it in JSON format.

[1135] Input: User data and prompt statements

[1136] Output: Task timetable in JSON format

[1137] The server saves the generated task timetable to the database using an "INSERT" query. The database stores the schedule ID, task details, start time, end time, etc.

[1138] Input: Task timetable in JSON format

[1139] Output: Task timetable saved in the database

[1140] Step 3: Task Management

[1141] The device retrieves the current schedule from the database with a "GET" request. The server receives the request, retrieves the data using an SQL "SELECT" query, and returns it to the device in JSON format.

[1142] Input: Task timetable stored in the database

[1143] Output: Task information in JSON format

[1144] The device parses the received JSON data and displays a list of tasks using HTML and JavaScript. The user interface displays the current and next tasks.

[1145] Input: Task information in JSON format

[1146] Output: Task list display screen

[1147] When a user completes a task, they tap the task on their device to send a completion notification, which then sends the completion notification data in JSON format to the server.

[1148] Input: Completion notification (task ID, completion status, etc.)

[1149] Output: JSON format completion notification

[1150] The server receives the completion notification and updates the database using an "UPDATE" query, changing the status of the completed task to "completed" and coordinating the next task.

[1151] Input: JSON format completion notification

[1152] Output: Updated database

[1153] Step 4: Notification

[1154] The device uses a JavaScript timer function to set reminders for each task based on the schedule data, and the timer will trigger an alert when the task's start time approaches.

[1155] Input: Task start time

[1156] Output: Set timer

[1157] When the timer triggers an alert, the device sends the user a reminder notification in the form of a pop-up, voice, email, or other format.

[1158] Input: Timer alert

[1159] Output: Reminder notification

[1160] Step 5: Emotion Recognition

[1161] The device captures the user's facial expressions and voice using the device's built-in camera and microphone, and this captured data is obtained in real time using WebRTC.

[1162] Input: facial expression data, voice data

[1163] Output: Captured data

[1164] The device sends the captured data to an emotion recognition engine (e.g., Microsoft Azure's Emotion API) for analysis, and the emotion engine returns the emotional state in JSON format.

[1165] Input: Captured data

[1166] Output: Emotion data in JSON format

[1167] The server dynamically adjusts the task order and notification method based on the emotion data received from the emotion engine, and updates the database contents using the "UPDATE" query to reflect the changes in real time.

[1168] Input: Emotion data in JSON format

[1169] Output: Adjusted task schedule and notification method

[1170] (Application example 2)

[1171] 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."

[1172] In modern society, the number of dual-income households is increasing, making it a major challenge to raise children efficiently and comfortably. In particular, couples raising children face the complexities of managing their daily schedules, making it difficult to keep track of task progress in real time. Furthermore, the impact of stress and emotional changes on child-rearing cannot be ignored. Therefore, in order for couples to raise children smoothly, they need support not only through task management but also through emotional recognition. Appropriate support is also needed when purchasing childcare products or seeking advice in physical stores.

[1173] 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 input means for collecting schedule information of the couple and information about the child's routine, generation means for generating an optimal task schedule based on the collected information, display means for displaying the generated task schedule, monitoring means for monitoring the progress of tasks and confirming their completion status, notification means for sending task reminders to the user, recognition means for recognizing emotions from the user's facial expressions and voice, adjustment means for appropriately adjusting tasks and notification methods based on the recognized emotions, guidance means for navigating to specific areas within the store, and conversation means for receiving childcare consultations from the user. This enables couples to raise their children efficiently and flexibly adjust tasks based on their emotional state, making it easier to purchase childcare products and receive childcare consultations in physical stores.

[1174] "Input means" refers to a device or method for collecting information on the couple's schedule and the children's routines.

[1175] A "generation means" is a device or method that generates an optimal task schedule based on collected information.

[1176] The "display means" is a device or method that visually presents the generated task schedule to the user.

[1177] A "monitoring means" is a device or method that tracks the progress of a task and verifies its completion.

[1178] A "notifier" is a device or method that sends task reminders to a user.

[1179] The "recognition means" is a device or method for analyzing emotions from the user's facial expressions and voice.

[1180] An "adjustment means" is a device or method that changes tasks or notification methods based on recognized emotions.

[1181] "Guidance means" refers to a device or method that provides directions or navigation to a specific area within a store.

[1182] The "conversation means" is an interactive device or method for receiving advice from the user regarding child rearing.

[1183] This invention provides a system that mainly comprises the following means. Specifically, it is a system that collects information on couples' schedules and children's routines, and generates, displays, monitors, notifies, and adjusts an optimal task schedule. It also has a conversation means that recognizes emotions from the user's facial expressions and voice, and receives consultations about child-rearing from the user.

[1184] System Configuration

[1185] 1. Input method:

[1186] The server uses devices such as smartphones and tablets to input information about the couple's schedule and the child's routine. The user inputs this information through an application and sends it to the server.

[1187] 2. Generation means:

[1188] The server uses a generative AI model to generate an optimal task schedule based on the collected information on the couple's schedule and the child's routine. This task schedule is automatically calculated, taking into account the user's working hours and the child's daily rhythm.

[1189] 3. Display means:

[1190] The terminal visually displays the generated task schedule to the user, who can then check the schedule via a dedicated application.

[1191] 4. Monitoring measures:

[1192] The device monitors the progress of the task in real time, and when the user completes the task, the device sends the information to the server and updates the database.

[1193] 5. Means of notification:

[1194] The device will send reminders to the user for scheduled tasks in the form of push notifications, emails, audio alerts, etc.

[1195] 6. Emotion recognition means:

[1196] The device captures the user's facial expressions and voice and uses an emotion engine to recognize the user's emotional state. For example, it uses a facial recognition library (such as face-api.js) to analyze the facial expression data and evaluate the user's stress level.

[1197] 7. Adjustment means:

[1198] The server then adjusts tasks and notifications accordingly based on the recognized emotions, for example, changing task priorities or making notifications more gentle if the user indicates a high stress level.

[1199] 8. Guidance means:

[1200] The device provides navigation when users are searching for specific areas within a physical store, such as directions to childcare products and breastfeeding areas.

[1201] 9. Means of communication:

[1202] The device accepts user inquiries about childcare via an AI chatbot. When a user inputs a question about childcare, the chatbot provides appropriate advice.

[1203] Specific examples

[1204] For example, if the system is used in a household where the husband works from 9:00 a.m. to 6:00 p.m. and the wife works from 11:00 a.m. to 8:00 p.m., the process will proceed as follows:

[1205] 1. 9:00 AM: The server notices that the husband has started work and sends a reminder notification to the wife.

[1206] 2. 10 AM: The device displays tasks for the wife to breastfeed and change the diaper. The emotion engine recognizes her stress level and readjusts the tasks as needed.

[1207] 3. 11:00 AM: The wife starts work, the server updates this information, and generates a schedule so that the task is assigned during the husband's lunch break.

[1208] 4. 1 PM: The device sends feeding and diaper change reminders to her husband, and uses facial recognition technology to reassess his stress level.

[1209] 5. 4 PM: My wife does the evening feeding and diaper change while the device monitors the progress.

[1210] 6. 6 PM: The server recognizes that my husband has finished work and notifies him of the upcoming dinner preparation task.

[1211] An example of a prompt might be, "Sir, it seems you're feeling stressed right now. Here's the nearest diaper changing area. Also, if you have any childcare concerns, please ask our childcare consultation chatbot."

[1212] This system allows couples to raise their children efficiently, flexibly manage tasks based on their emotional state, and provides comprehensive support within physical stores.

[1213] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1214] Step 1:

[1215] The server collects information about the couple's schedule and the child's routine entered by the user using input methods, including input from a smartphone or tablet. The input data includes the couple's working hours, the timing of the child's feeding and diaper changes, etc. This data is sent to the server and stored in a database.

[1216] Step 2:

[1217] The server acquires the collected schedule and routine information and generates an optimal task schedule using a generative AI model. This generation involves implementing an algorithm to allocate tasks appropriately, taking into account the user's working hours and children's daily routines. The output is saved in a database as the generated task schedule.

[1218] Step 3:

[1219] The terminal uses a display means to visually display the task schedule obtained from the server to the user. Specifically, the user can check the current and next tasks to be performed through a dedicated application. The input in this process is the task schedule obtained from the server, and the output is the schedule displayed on the user's terminal screen.

[1220] Step 4:

[1221] The terminal monitors the progress of the task in real time using a monitoring means. When the user completes the task, the terminal sends the information to the server, which updates the database. The input to this process is the user's notification of task completion, and the output is the updated task information in the database.

[1222] Step 5:

[1223] The device uses a notification mechanism to send task reminders to the user, which can take the form of real-time push notifications, emails, voice alerts, etc. The input is the time information of the scheduled task, and the output is the reminder notification to the user.

[1224] Step 6:

[1225] The device uses a recognition means to recognize emotions from the user's facial expressions and voice. Specifically, it uses a facial expression recognition library (such as face-api.js) to analyze the video captured by the camera and generate emotion data. The input is the camera video and audio data, and the output is the analyzed emotion data.

[1226] Step 7:

[1227] The server adjusts tasks and notification methods accordingly based on the recognized emotion data. For example, if the stress level is high, it may change the priority of the task or change the notification method to a softer tone. The input is emotion data, and the output is the adjusted task schedule and notification method.

[1228] Step 8:

[1229] The device uses the guidance means to navigate to a specific area within a physical store, indicating the location of childcare products and equipment that the user has searched for in the application. The input is a search request from the user, and the output is navigation information.

[1230] Step 9:

[1231] The device uses a conversational means to receive childcare-related consultations from the user via an AI chatbot. When the user inputs a childcare-related question through the application, the chatbot uses a generative AI model to provide appropriate advice. The input is the user's question, and the output is advice from the chatbot.

[1232] 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.

[1233] 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.

[1234] 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.

[1235] [Fourth embodiment]

[1236] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1237] 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.

[1238] 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).

[1239] 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.

[1240] 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.

[1241] 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).

[1242] 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. 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.

[1243] 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.

[1244] 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.

[1245] 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.

[1246] 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.

[1247] 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.

[1248] 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."

[1249] This invention is a system that allows couples to manage the tasks necessary for child-rearing comfortably and adjust schedules efficiently. This system collects information on the couple's schedules and the child's routines, generates and displays an optimal task schedule, monitors the progress of tasks, and sends reminders.

[1250] System Overview

[1251] The system has the following main features:

[1252] 1. User data input function

[1253] 2. Schedule generation function

[1254] 3. Task management function

[1255] 4. Notification function

[1256] 1. User data input function

[1257] After logging in to the application, users enter information about their spouse's schedule and their child's routine, including each spouse's working hours and vacations, baby feeding and diaper changing times, etc. The server collects this information and stores it in a database.

[1258] 2. Schedule generation function

[1259] The server retrieves user data stored in the database and uses a generative AI model to generate an optimal task schedule. This schedule takes into account the couple's schedules, assigning tasks to the wife when the husband is at work, and vice versa. The generated schedule is saved in the database.

[1260] 3. Task management function

[1261] The terminal displays a list of tasks for each user based on the acquired schedule. The progress of tasks is monitored in real time, allowing the user to check the tasks in progress. When the user notifies the terminal of completed tasks, the server updates the database and adjusts the next tasks.

[1262] 4. Notification function

[1263] The device will send reminder notifications at the necessary times based on the set schedule, which can be in the form of a pop-up, voice, email, etc. When a task reminder is triggered, the user can check the notification and start working on the task.

[1264] Specific examples

[1265] For example, in a household where the husband works from 9am to 6pm and the wife works from 11am to 8pm, tasks might be managed as follows:

[1266] 1. 9:00 AM - Husband starts work.

[1267] 2. 10:00 AM - My wife feeds and changes the baby.

[1268] 3. 11:00 AM - My wife starts work.

[1269] 4. 1:00 PM - Husband feeds and changes baby during his lunch break.

[1270] 5. 4:00 PM - My wife does the evening feeding and diaper change.

[1271] 6. 6pm - Husband finishes work and starts preparing dinner.

[1272] In this way, couples can adjust their schedules and children's routines, and share tasks comfortably. The system sends reminder notifications and supports task management in real time, reducing the burden of child-rearing and providing an environment where parents can enjoy raising their children without stress.

[1273] The processing flow will be explained below.

[1274] Step 1: Collect user data

[1275] 1. The user logs in to the application.

[1276] 2. The server displays a form to the logged-in user to enter information about the couple's individual schedules and children's routines.

[1277] 3. Users enter their own schedule (work hours and break times), their partner's schedule, and their child's routine (feeding and diaper changing times) into the form.

[1278] 4. The server collects the entered information and stores it in a database.

[1279] Step 2: Generate a schedule

[1280] 1. The server retrieves the schedule information of the couple and their children from the database.

[1281] 2. The server inputs the acquired data into the generative AI model and instructs it to generate an optimal task schedule.

[1282] 3. Based on the schedule information, the generative AI model generates an efficient schedule that takes into account the convenience of each couple and the needs of their children.

[1283] 4. The server retrieves the generated schedule and stores it in the database.

[1284] Step 3: Managing tasks

[1285] 1. The server sends the generated schedule to each terminal.

[1286] 2. Based on the received schedule, the device visually displays the current and next tasks to be done to the user.

[1287] 3. The user checks the displayed tasks and begins working on each one.

[1288] 4. The device monitors the progress of the task and provides a form where completed tasks can be recorded.

[1289] 5. When the user completes the task, the information is entered on the terminal and sent to the server.

[1290] 6. The server receives the completed task information and updates the database.

[1291] Step 4: Sending notifications

[1292] 1. The device will display reminders for each task at the appropriate time based on the schedule you set.

[1293] 2. When the time comes for a reminder, the device will send a pop-up notification, a sound notification, or an email notification to the user.

[1294] 3. The user sees the notification and begins the task.

[1295] 4. The server saves the notification sending history in the database and updates the next notification schedule.

[1296] Example 1

[1297] 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."

[1298] In modern households, couples face challenges in managing child-rearing tasks comfortably and efficiently. Creating and managing an optimal schedule requires taking into account various factors, such as each spouse's working hours, holidays, and children's routines. However, doing this manually can be difficult and stressful. In these circumstances, a system that provides efficient task management and timely reminder notifications is needed.

[1299] 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.

[1300] In this invention, the server includes an input means for collecting the couple's schedule information and the child's regular routine information, a generation means for generating an optimal task schedule based on the collected information, and a display means for displaying the schedule generated by using the generation AI model as the generation means, thereby enabling couples to efficiently manage the tasks necessary for child-rearing without strain and easily adjust their schedules.

[1301] "Married couple schedule information" is information about the schedules of the husband and wife, such as their working hours and holidays.

[1302] "Child routine information" refers to information about a child's daily activities and habits, such as feeding times and diaper changing times.

[1303] The "input means" is a means by which a user inputs information about the couple's schedule and information about the children's regular schedule into the application.

[1304] The "generation means" is a means for generating an optimal task schedule based on collected information, and in this invention, this is the part that uses the generative AI model.

[1305] A "generative AI model" is an artificial intelligence model that generates an optimal task schedule based on a specific prompt sentence.

[1306] The "display means" is a means for displaying the generated task schedule to the user.

[1307] The "monitoring means" is a means for monitoring the progress of a task and checking the completion state of the task.

[1308] A "notification means" is a means for sending task reminders to a user.

[1309] The "storage means" is a means for storing the generated schedule in a database.

[1310] The "update means" is a means for updating the information in the database after the user completes a task.

[1311] A "database" is a system for storing collected information, generated schedules, task progress, etc.

[1312] A "terminal" is a device that allows a user to check task schedules and update progress.

[1313] A "server" is a central computer system that collects user data, generates schedules, stores and updates data, and sends reminder notifications.

[1314] A "user" is an individual who uses the system to input, confirm, and report completion of tasks.

[1315] The present invention is a system for enabling couples to manage tasks necessary for raising children without straining themselves and to adjust schedules efficiently. Specific embodiments of this system will be described below.

[1316] This system consists of a server, terminals, and users, and has the following main functions:

[1317] 1. User data input function

[1318] 2. Schedule generation function

[1319] 3. Task management function

[1320] 4. Notification function

[1321] User data input function

[1322] After logging in to the application, the user enters the couple's schedule information and the child's regular schedule information. For example, the husband's working hours (9:00-18:00), the wife's working hours (11:00-20:00), and the child's feeding times (10:00, 13:00, 16:00). This information is sent to the server and stored in the database.

[1323] Schedule generation function

[1324] The server retrieves user information collected from the database and provides prompts to the generative AI model to generate an optimal task schedule. For example, the prompt might be, "Consider the couple's schedule and the child's routine, and generate an optimal childcare schedule." The generated schedule is then stored in the database.

[1325] Task management function

[1326] The terminal retrieves schedule information from the database and displays a list of tasks to the user. When the user completes a task, they enter their progress into the terminal, which then sends the information to the server. The server receives this information and updates the database.

[1327] Notification function

[1328] The device calculates the timing of the reminder notification based on the schedule and sends the reminder to the user at the appropriate time. The reminder is sent in the form of a pop-up, voice, email, etc. The user can check the reminder and start working on the task.

[1329] Specific examples

[1330] For example, in a household where the husband works from 9am to 6pm and the wife works from 11am to 8pm, tasks might be managed as follows:

[1331] 1. 9:00 AM - My husband starts work.

[1332] 2. 10:00 AM - My wife feeds and changes the baby.

[1333] 3. 11:00 AM - My wife starts work.

[1334] 4. 1:00 PM - Husband feeds and changes baby during his lunch break.

[1335] 5. 4:00 PM - My wife does the evening feeding and diaper change.

[1336] 6. 6 PM - Husband finishes work and starts preparing dinner.

[1337] In this way, couples can efficiently coordinate their schedules and children's routines, allowing them to share tasks comfortably and reducing the burden of child-rearing.

[1338] Prompt Sentence Examples

[1339] "Generate the optimal childcare schedule, taking into account the couple's schedules and the child's routines."

[1340] This system provides an environment for couples to efficiently manage child-rearing tasks and reduce stress.

[1341] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1342] Step 1:

[1343] A user logs in to the application by entering their user ID and password. This information is sent to the server, which authenticates the user. If authentication is successful, the dashboard is displayed.

[1344] Step 2:

[1345] The user inputs the couple's schedule information and the child's regular schedule information. Specifically, the husband's working hours, the wife's working hours, the child's breastfeeding times, etc. The server receives this input data and stores it in a database. Examples of input data include the husband's working hours "9:00-18:00", the wife's working hours "11:00-20:00", and the child's breastfeeding times "10:00, 13:00, 16:00".

[1346] Step 3:

[1347] The server retrieves user data collected from the database. Based on this information, it provides prompts to the generative AI model. As a specific example, the prompt is "Generate the optimal childcare schedule, taking into account the couple's schedule and the child's routine." Based on this prompt, the generative AI model generates the optimal task schedule. The generated schedule is returned to the server and saved in the database again.

[1348] Step 4:

[1349] The device retrieves schedule information related to the user from the database. The device displays the retrieved schedule to the user. For example, at 10:00 AM, the device displays information such as "The wife will breastfeed and change diapers," and at 1:00 PM, the device displays information such as "The husband will breastfeed and change diapers during his lunch break."

[1350] Step 5:

[1351] The user inputs the progress of the task into the terminal. For example, if the task at 10:00 AM is completed, the user inputs "Task completed at 10:00 AM." This information is sent to the server via the terminal.

[1352] Step 6:

[1353] The server receives the task completion information sent by the user and updates the database. Specifically, it changes the status of the corresponding task to "Completed."

[1354] Step 7:

[1355] The device calculates the timing of the reminder based on the schedule, for example, setting a reminder 10 minutes before the task starts, and the reminder can be in the form of a pop-up, a sound notification, or an email.

[1356] Step 8:

[1357] The device will send reminder notifications to the user at the set times. For example, at 9:50 a.m., a reminder to "feed and change diapers at 10 a.m." The user can confirm the reminder and get to work on the task.

[1358] Through these steps, the system efficiently performs a series of processes from collecting user data to generating schedules, managing tasks, and sending reminder notifications.

[1359] (Application example 1)

[1360] 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."

[1361] While existing systems allow couples to comfortably manage the tasks required for child-rearing and efficiently adjust schedules, there is a lack of a general-purpose system that can handle shift management and task allocation for store staff. This makes it difficult to manage tasks among staff and reduce the burden on each staff member.

[1362] 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.

[1363] In this invention, the server includes input means for collecting couple schedule information and child routine information, generation means for generating an optimal task schedule based on the collected information, display means for displaying the generated task schedule, monitoring means for monitoring task progress and confirming task completion status, notification means for sending task reminders to users, input means for collecting store staff shift information and work details, generation means for generating an optimal store staff shift schedule based on the collected information, and notification means for reminding store staff of the generated shift schedule, thereby enabling effective task management and real-time shift schedule management.

[1364] "Married couple schedule information" is information about the time schedules of the husband and wife, such as their working hours, holidays, and daily routines.

[1365] "Child routine information" is information about a child's daily activities and the times of care required (such as feeding times and diaper changes).

[1366] "Input means" refers to the interface through which a user inputs schedule and routine information into the application, and includes smartphone apps and web applications.

[1367] "Generators" are algorithms or systems that automatically create optimal task schedules based on collected information. This includes schedule generation using generative AI models.

[1368] The "display means" is an interface for visually presenting the generated task schedule to the user, such as a smartphone screen or a computer monitor.

[1369] The "monitoring means" is a system for checking the progress of tasks in real time and tracking the user's progress. This includes sensing technology and real-time data processing technology.

[1370] "Notification means" refers to a means for notifying users of task reminders and important events. This means conveying information to users in the form of pop-up notifications, audio notifications, emails, etc.

[1371] "Store staff" refers to employees who work in brick-and-mortar stores such as restaurants and retailers. Their work shifts and tasks need to be managed.

[1372] "Shift information" is information about the schedule of store staff, such as working hours, holidays, and shift changes.

[1373] "Job Description" refers to the specific tasks and roles that restaurant staff must perform (e.g., setting tables, cleaning, taking orders).

[1374] A "prompt sentence" is a text sentence of a specific format that the system inputs to the generative AI model to generate an optimal schedule.

[1375] The "generated shift schedule" refers to an optimal work schedule for store staff generated by the generation means.

[1376] "Real time" means that data processing occurs virtually immediately, within a very short time frame.

[1377] This invention is a system that efficiently manages the schedules and tasks of couples and store staff. It collects the working status and routines of couples and store staff, generates optimal schedules, and sends reminders. This system is effectively operated using a cloud server and smartphone application.

[1378] System configuration

[1379] The system mainly consists of the following hardware and software:

[1380] Server: Collects data, generates schedules, and manages the database.

[1381] Database: PostgreSQL is used to store user and staff schedule information, as well as generated schedule information.

[1382] Backend: Server-side processing is performed using the Django framework using Python.

[1383] Front-end: Develop a smartphone application using React Native.

[1384] Notification system: Uses Firebase Cloud Messaging to send reminders and notifications.

[1385] Generative AI models: Use models such as OpenAI's GPT-3 to generate optimal schedules.

[1386] Processing flow and roles

[1387] Data entry and collection

[1388] Users (couples or store staff) log in to the smartphone app and enter their work shift and routine information. This data is sent in real time to a cloud server and stored in a database.

[1389] Generate a schedule

[1390] The server uses a generative AI model to generate an optimal schedule based on the information stored in the database. This model receives schedule information and prompts entered by users and staff. For example, the following prompts can be input into the generative AI model:

[1391] Example prompt sentence:

[1392] "Generate the optimal shift schedule and task assignments for store staff based on the following data: Data: Staff A (Work: 9:00-17:00, Break: 12:00-13:00), Staff B (Work: 10:00-18:00, Break: 13:00-14:00). Store tasks: Prepare breakfast, clean the store, set tables, take orders, prepare dinner."

[1393] Viewing and Monitoring Schedules

[1394] The generated schedule is visually displayed to each user and staff member on a smartphone app. Users and staff members can check the progress of their assigned tasks in real time, and the database is updated when they report completed tasks.

[1395] Reminders

[1396] Use the notification system to send reminders to users and staff via pop-up and audio notifications sent via Firebase Cloud Messaging, helping users and staff remember to complete tasks.

[1397] Specific examples

[1398] For example, the family restaurant "Smile Diner" uses the system as follows:

[1399] 9:00 AM - The restaurant opens and Staff A begins preparing breakfast in the kitchen.

[1400] 10:00 AM - The app sends a reminder notification and Staff B begins cleaning the store.

[1401] 12:00 noon - Staff A goes on break and Staff C transitions to setting tables and taking orders.

[1402] 3:00 PM - Staff member A returns and takes on the task of preparing dinner.

[1403] This allows for efficient division of labor among staff members, ensuring smooth operation.

[1404] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1405] Step 1:

[1406] The user logs into the smartphone app and enters frequent schedule and routine information. The server saves this input information in a database on the cloud. The input for this step is the working hours and task information of couples and store staff, and the output is user data saved in the database. Specifically, the user enters information into the input fields on the screen and presses the send button, which sends the data to the server.

[1407] Step 2:

[1408] The server retrieves the information stored in the database and inputs prompt statements to the generative AI model to generate an optimal schedule. The input for this step is the user data stored in the database and the generative AI model, and the output is the generated schedule. The server runs a Python script to extract information from the database, pass it to the generative AI model, and receive a response.

[1409] Step 3:

[1410] The generated schedule is saved in the database again and transferred to the smartphone app. The input of this step is the generated schedule, and the output is the schedule saved in the database and transferred to the smartphone app. The server adds the response from the generative AI model to the database and sends the data to the device via WebSocket or API to notify the user in real time.

[1411] Step 4:

[1412] The user checks the generated schedule through the smartphone app and updates the progress of each task. The input of this step is the user's task completion information, and the output is updated database information. The user marks the task as completed on the smartphone app screen, and the information is immediately sent to the server.

[1413] Step 5:

[1414] The server periodically monitors the progress of the task and sends reminders and notifications as needed. The input for this step is the current time and the schedule stored in the database, and the output is a reminder notification to the user. The server sends the reminder at the set time via Firebase Cloud Messaging and provides the notification to the user.

[1415] Through these steps, the system can efficiently manage the schedules and tasks of users and store staff, and provide notifications at the appropriate times.

[1416] 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.

[1417] This invention is a system that allows couples to comfortably manage the tasks necessary for child-rearing and efficiently adjust schedules, and its effectiveness is enhanced by combining it with an emotion engine that recognizes the user's emotions. This system collects information about the couple's schedule and the child's routine, generates and displays an optimal task schedule, monitors task progress, notifies reminders, and adjusts tasks and notifications appropriately based on the recognized emotions.

[1418] System Overview

[1419] The system has the following main features:

[1420] 1. User data input function

[1421] 2. Schedule generation function

[1422] 3. Task management function

[1423] 4. Notification function

[1424] 5. Emotion recognition function

[1425] 1. User data input function

[1426] After logging in to the application, users enter information about their spouse's schedule and their child's routine, including each spouse's working hours and vacations, baby feeding and diaper changing times, etc. The server collects this information and stores it in a database.

[1427] 2. Schedule generation function

[1428] The server retrieves user data stored in the database and uses a generative AI model to generate an optimal task schedule. This schedule takes into account the couple's schedules, assigning tasks to the wife when the husband is at work, and vice versa. The generated schedule is saved in the database.

[1429] 3. Task management function

[1430] Based on the schedule, the device visually displays the current and next tasks to be done to the user. The progress of tasks is monitored in real time, allowing the user to check the tasks in progress. The user can notify the server of completed tasks on the device, and the server updates the database and adjusts the next tasks.

[1431] 4. Notification function

[1432] The device will send reminder notifications at the necessary times based on the set schedule, which can be in the form of a pop-up, voice, email, etc. When a task reminder is triggered, the user can check the notification and start working on the task.

[1433] 5. Emotion recognition function

[1434] The device is equipped with an emotion engine that recognizes emotions from the user's facial expressions and voice. This allows the device to grasp the user's stress level and motivation in real time. The recognized emotions are sent to a server, which automatically adjusts tasks and schedules.

[1435] Specific examples

[1436] For example, in a household where the husband works from 9am to 6pm and the wife works from 11am to 8pm, tasks might be managed as follows:

[1437] 1. 9 AM - Husband starts work. The emotion engine recognizes his stress level and sends reminders to his wife as needed.

[1438] 2. 10:00 AM - Wife feeds and changes the baby. The emotion engine recognizes her stress level and adjusts the division of tasks.

[1439] 3. 11:00 AM - Wife starts work. System assigns task to husband during lunch break.

[1440] 4. 1 PM - Husband feeds and changes baby during his lunch break. The Emotion Engine reassessed his stress level.

[1441] 5. 4 PM - Wife does evening feeding and diaper change. Emotion Engine adjusts notifications based on wife's feedback.

[1442] 6. 6 PM - Husband finishes work and starts preparing dinner. The system confirms the task completion and notifies him of the next scheduled event.

[1443] In this way, the couple can adjust their schedules and their children's routines, and flexibly change task allocation and notification methods based on their emotional state, allowing them to raise their children comfortably.The introduction of an emotion engine makes it possible to reduce user stress and provide an environment where users can complete tasks efficiently.

[1444] The processing flow will be explained below.

[1445] Step 1: Collect user data

[1446] 1. The user logs in to the application.

[1447] 2. The server displays a form to the logged-in user to enter the couple's schedule information and the children's routine information.

[1448] 3. The user enters their own and their partner's schedules (e.g., working hours, break times) and their child's routines (e.g., feeding times, diaper changing times).

[1449] 4. The server collects the entered information and stores it in a database.

[1450] Step 2: Collecting emotion data

[1451] 1. The emotion engine installed in the device recognizes emotions from the user's facial expressions and voice.

[1452] 2. The device sends the recognized emotion data to the server.

[1453] 3. The server stores the emotion data in a database and records the user's emotional state.

[1454] Step 3: Generate a schedule

[1455] 1. The server retrieves schedule information and emotional data of the couple and their children from the database.

[1456] 2. The server inputs the acquired data into the generative AI model and instructs it to generate an optimal task schedule.

[1457] 3. The generative AI model generates an efficient schedule that takes into account the user's emotional state based on schedule information and emotional data.

[1458] 4. The server retrieves the generated schedule and stores it in the database.

[1459] Step 4: Managing tasks

[1460] 1. The server sends the generated schedule to each terminal.

[1461] 2. Based on the received schedule, the device visually displays the current and next tasks to be done to the user.

[1462] 3. The user checks the displayed tasks and begins working on each one.

[1463] 4. The device monitors the progress of the task and provides a form where completed tasks can be recorded.

[1464] 5. When the user completes the task, the information is entered on the device and sent to the server.

[1465] 6. The server receives the completed task information and updates the database.

[1466] Step 5: Sending notifications

[1467] 1. The device will display reminders for each task at the appropriate time based on the schedule you set.

[1468] 2. When the time comes for a reminder, the device will send a pop-up notification, a sound notification, or an email notification to the user.

[1469] 3. The user sees the notification and begins the task.

[1470] 4. The server saves the notification sending history in the database and updates the next notification schedule.

[1471] Specific examples

[1472] Step 1: Collect user data

[1473] A user logs into the application and enters the husband and wife's schedules and the children's routines. For example, the husband works from 9am to 6pm and the wife works from 11am to 8pm.

[1474] Step 2: Collecting emotion data

[1475] The device's built-in emotion engine recognizes the user's current emotional state from their facial expressions and voice, collecting data such as "high stress" or "relaxed." The device then sends this information to a server, which stores it in a database.

[1476] Step 3: Generate a schedule

[1477] The server uses a generative AI model to generate an optimal task schedule based on the user's schedule information and emotional data. For example, if the emotional data indicates "high stress," the generative AI model generates a schedule that reduces the workload.

[1478] Step 4: Managing tasks

[1479] The device displays the optimal schedule to the user and monitors the progress of the tasks in real time. When the user completes a task, the information is sent to the server and the database is updated.

[1480] Step 5: Sending notifications

[1481] The device will send reminders based on the schedule, such as notifications like "It's time for the next feeding." The notification method will also be adjusted based on the emotional data, so if the user is feeling stressed, a gentle tone will be sent.

[1482] In this way, combining the emotion engine enables flexible schedule management and task notifications that take into account the user's emotional state, facilitating cooperation between spouses and reducing the burden of raising children.

[1483] Example 2

[1484] 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."

[1485] Modern couples are faced with the need to efficiently manage childcare tasks and reduce stress amid their busy lives. However, there are no systems in place that can schedule tasks while taking into account individual circumstances and emotions. Therefore, there is a need for a system that allows couples to share and execute childcare tasks comfortably and effectively.

[1486] 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.

[1487] In this invention, the server includes input means for collecting time information of the couple and information on the child's daily routine, generation means for generating an optimal task timetable based on the collected information, display means for displaying the generated task timetable, monitoring means for monitoring task progress and confirming task completion status, notification means for sending task reminders to the user, emotion recognition means for analyzing the user's facial expressions and voice and recognizing their emotional state, and adjustment means for adjusting tasks and notifications based on the recognized emotion. This enables optimal management and sharing of childcare tasks while taking into account the couple's schedules and emotional state.

[1488] "Married couple time information" is data that indicates the husband or wife's working hours, vacation time, and their schedules.

[1489] "Children's daily routine information" is data that represents a child's daily routines and schedules, such as feeding times, diaper changing times, and sleeping times.

[1490] "Input means" refers to the interface and software that allows users to input their schedules and children's daily routines.

[1491] "Generation means" refers to the algorithm and generative AI model that creates an optimal task schedule based on input information.

[1492] The "display means" refers to a display device or application interface for visually presenting the generated task timetable to the user.

[1493] "Monitoring tools" are software and hardware used to view and track the progress and completion of tasks in real time.

[1494] "Notification means" refers to the system and method for sending reminders and task notifications to users.

[1495] The "emotion recognition means" refers to software and hardware for analyzing the user's facial expressions and voice to recognize the user's emotional state.

[1496] "Adjustment" refers to algorithms and systems for dynamically modifying and adjusting the content and timing of tasks and notifications based on perceived emotions.

[1497] The "data repository" is a database and storage device for storing collected data and generated task timetables.

[1498] "Users" refers to individuals who use the system, primarily couples.

[1499] This invention is a system that collects information on couples' time and children's daily routines, generates and displays an optimal task schedule, monitors task progress, and sends reminder notifications.It also has the ability to recognize the user's emotions and adjust tasks and notifications appropriately based on their emotions.

[1500] System Overview

[1501] The system consists of the following main hardware and software:

[1502] Server: Database (e.g. MySQL), generative AI model (e.g. GPT-4)

[1503] Device (smartphone or tablet): Input form, display screen, emotion recognition engine (e.g., Microsoft Azure Emotion API)

[1504] Users: A married couple who use this system

[1505] User data input function

[1506] Users log in to the application and enter schedule information such as husband and wife's working hours, vacation time, baby feeding and diaper changing times, etc. This information is collected by the server and stored in a database. OAuth 2.0 is used for login, and HTML forms and JavaScript are used for data entry.

[1507] Schedule generation function

[1508] The server retrieves the user data stored in the database and generates an optimal task timetable using a generative AI model (e.g., GPT-4). Example prompt: "Generate the optimal task schedule based on the husband and wife's schedules and children's routine information." The generated timetable is then saved back to the database.

[1509] Task management function

[1510] The device visually displays the current and upcoming tasks to the user based on a schedule retrieved from the database. Task progress is monitored in real time, and as the user completes a task, the server updates the database with that information. This display is done using HTML and JavaScript.

[1511] Notification function

[1512] The device will send reminder notifications based on the schedule you set, in the form of pop-ups, sounds, emails, etc., using the JavaScript timer function.

[1513] Emotion recognition function

[1514] The device uses the built-in camera and microphone to capture the user's facial expressions and voice, and sends them to an emotion recognition engine (e.g., Microsoft Azure's Emotion API) for analysis. The emotion data is sent to a server, which dynamically adjusts tasks and notifications.

[1515] Specific examples

[1516] For example, in a household where the husband works from 9am to 6pm and the wife works from 11am to 8pm, tasks might be managed as follows:

[1517] 1. 9 AM - Husband starts work, emotion engine recognizes husband's stress level, and sends wife a reminder if necessary.

[1518] 2. 10:00 AM - Wife feeds and changes the baby. The emotion engine recognizes her stress level and the system adjusts the distribution of tasks.

[1519] 3. 11:00 AM - Wife starts work. System assigns husband a task during his lunch break.

[1520] 4. 1 PM - Husband feeds and changes baby during his lunch break. The Emotion Engine reassessed his stress level.

[1521] 5. 4 PM - Wife does evening feeding and diaper change. Emotion engine adjusts notifications based on wife's feedback.

[1522] 6. 6 PM - Husband finishes work and starts preparing dinner. The system confirms task completion and notifies him of his next scheduled appointment.

[1523] This system allows parents to smoothly raise their children by adjusting their schedules and the children's daily routines, and flexibly changing task allocation and notification methods based on their emotional state.The introduction of an emotion recognition engine can reduce user stress and provide an environment in which tasks can be completed efficiently.

[1524] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1525] Step 1: User data input

[1526] A user logs in to an application. First, they enter their login information and send it to the authentication server. The authentication server authenticates the user using OAuth 2.0 and, if successful, generates and returns an authentication token. The device stores this token and uses it for subsequent operations.

[1527] Input: Username and Password

[1528] Output: Authentication token

[1529] Users enter schedule information such as husband and wife working hours, vacation time, baby feeding and diaper changing times, etc. The input information is collected using an HTML form and JavaScript and sent to the server in JSON format.

[1530] Input: Schedule information (working hours, holidays, breastfeeding time, diaper changing time, etc.)

[1531] Output: Schedule information in JSON format

[1532] The server parses the received JSON data and saves it to a MySQL database using an INSERT query. The database stores the schedule information for each husband, wife, and child.

[1533] Input: Schedule information in JSON format

[1534] Output: Schedule data stored in the database

[1535] Step 2: Schedule generation

[1536] The server retrieves user data from the database using a SQL "SELECT" query, which is then converted into a Python data frame (e.g., Pandas) for internal processing.

[1537] Input: Schedule data stored in the database

[1538] Output: Data frame for internal processing

[1539] The server inputs a prompt into a generative AI model (e.g., GPT-4) to generate an optimal task timetable. An example prompt is "Please generate an optimal task schedule based on the husband and wife's schedules and children's routine information." The generative AI model generates a task timetable based on the received prompt and returns it in JSON format.

[1540] Input: User data and prompt statements

[1541] Output: Task timetable in JSON format

[1542] The server saves the generated task timetable to the database using an "INSERT" query. The database stores the schedule ID, task details, start time, end time, etc.

[1543] Input: Task timetable in JSON format

[1544] Output: Task timetable saved in the database

[1545] Step 3: Task Management

[1546] The device retrieves the current schedule from the database with a "GET" request. The server receives the request, retrieves the data using an SQL "SELECT" query, and returns it to the device in JSON format.

[1547] Input: Task timetable stored in the database

[1548] Output: Task information in JSON format

[1549] The device parses the received JSON data and displays a list of tasks using HTML and JavaScript. The user interface displays the current and next tasks.

[1550] Input: Task information in JSON format

[1551] Output: Task list display screen

[1552] When a user completes a task, they tap the task on their device to send a completion notification, which then sends the completion notification data in JSON format to the server.

[1553] Input: Completion notification (task ID, completion status, etc.)

[1554] Output: JSON format completion notification

[1555] The server receives the completion notification and updates the database using an "UPDATE" query, changing the status of the completed task to "completed" and coordinating the next task.

[1556] Input: JSON format completion notification

[1557] Output: Updated database

[1558] Step 4: Notification

[1559] The device uses a JavaScript timer function to set reminders for each task based on the schedule data, and the timer will trigger an alert when the task's start time approaches.

[1560] Input: Task start time

[1561] Output: Set timer

[1562] When the timer triggers an alert, the device sends the user a reminder notification in the form of a pop-up, voice, email, or other format.

[1563] Input: Timer alert

[1564] Output: Reminder notification

[1565] Step 5: Emotion Recognition

[1566] The device captures the user's facial expressions and voice using the device's built-in camera and microphone, and this captured data is obtained in real time using WebRTC.

[1567] Input: facial expression data, voice data

[1568] Output: Captured data

[1569] The device sends the captured data to an emotion recognition engine (e.g., Microsoft Azure's Emotion API) for analysis, and the emotion engine returns the emotional state in JSON format.

[1570] Input: Captured data

[1571] Output: Emotion data in JSON format

[1572] The server dynamically adjusts the task order and notification method based on the emotion data received from the emotion engine, and updates the database contents using the "UPDATE" query to reflect the changes in real time.

[1573] Input: Emotion data in JSON format

[1574] Output: Adjusted task schedule and notification method

[1575] (Application example 2)

[1576] 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."

[1577] In modern society, the number of dual-income households is increasing, making it a major challenge to raise children efficiently and comfortably. In particular, couples raising children face the complexities of managing their daily schedules, making it difficult to keep track of task progress in real time. Furthermore, the impact of stress and emotional changes on child-rearing cannot be ignored. Therefore, in order for couples to raise children smoothly, they need support not only through task management but also through emotional recognition. Appropriate support is also needed when purchasing childcare products or seeking advice in physical stores.

[1578] 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 input means for collecting schedule information of the couple and information about the child's routine, generation means for generating an optimal task schedule based on the collected information, display means for displaying the generated task schedule, monitoring means for monitoring the progress of tasks and confirming their completion status, notification means for sending task reminders to the user, recognition means for recognizing emotions from the user's facial expressions and voice, adjustment means for appropriately adjusting tasks and notification methods based on the recognized emotions, guidance means for navigating to specific areas within the store, and conversation means for receiving childcare consultations from the user. This enables couples to raise their children efficiently and flexibly adjust tasks based on their emotional state, making it easier to purchase childcare products and receive childcare consultations in physical stores.

[1579] "Input means" refers to a device or method for collecting information on the couple's schedule and the children's routines.

[1580] A "generation means" is a device or method that generates an optimal task schedule based on collected information.

[1581] The "display means" is a device or method that visually presents the generated task schedule to the user.

[1582] A "monitoring means" is a device or method that tracks the progress of a task and verifies its completion.

[1583] A "notifier" is a device or method that sends task reminders to a user.

[1584] The "recognition means" is a device or method for analyzing emotions from the user's facial expressions and voice.

[1585] An "adjustment means" is a device or method that changes tasks or notification methods based on recognized emotions.

[1586] "Guidance means" refers to a device or method that provides directions or navigation to a specific area within a store.

[1587] The "conversation means" is an interactive device or method for receiving advice from the user regarding child rearing.

[1588] This invention provides a system that mainly comprises the following means. Specifically, it is a system that collects information on couples' schedules and children's routines, and generates, displays, monitors, notifies, and adjusts an optimal task schedule. It also has a conversation means that recognizes emotions from the user's facial expressions and voice, and receives consultations about child-rearing from the user.

[1589] System Configuration

[1590] 1. Input method:

[1591] The server uses devices such as smartphones and tablets to input information about the couple's schedule and the child's routine. The user inputs this information through an application and sends it to the server.

[1592] 2. Generation means:

[1593] The server uses a generative AI model to generate an optimal task schedule based on the collected information on the couple's schedule and the child's routine. This task schedule is automatically calculated, taking into account the user's working hours and the child's daily rhythm.

[1594] 3. Display means:

[1595] The terminal visually displays the generated task schedule to the user, who can then check the schedule via a dedicated application.

[1596] 4. Monitoring measures:

[1597] The device monitors the progress of the task in real time, and when the user completes the task, the device sends the information to the server and updates the database.

[1598] 5. Means of notification:

[1599] The device will send reminders to the user for scheduled tasks in the form of push notifications, emails, audio alerts, etc.

[1600] 6. Emotion recognition means:

[1601] The device captures the user's facial expressions and voice and uses an emotion engine to recognize the user's emotional state. For example, it uses a facial recognition library (such as face-api.js) to analyze the facial expression data and evaluate the user's stress level.

[1602] 7. Adjustment means:

[1603] The server then adjusts tasks and notifications accordingly based on the recognized emotions, for example, changing task priorities or making notifications more gentle if the user indicates a high stress level.

[1604] 8. Guidance means:

[1605] The device provides navigation when users are searching for specific areas within a physical store, such as directions to childcare products and breastfeeding areas.

[1606] 9. Means of communication:

[1607] The device accepts user inquiries about childcare via an AI chatbot. When a user inputs a question about childcare, the chatbot provides appropriate advice.

[1608] Specific examples

[1609] For example, if the system is used in a household where the husband works from 9:00 a.m. to 6:00 p.m. and the wife works from 11:00 a.m. to 8:00 p.m., the process will proceed as follows:

[1610] 1. 9:00 AM: The server notices that the husband has started work and sends a reminder notification to the wife.

[1611] 2. 10 AM: The device displays tasks for the wife to breastfeed and change the diaper. The emotion engine recognizes her stress level and readjusts the tasks as needed.

[1612] 3. 11:00 AM: The wife starts work, the server updates this information, and generates a schedule so that the task is assigned during the husband's lunch break.

[1613] 4. 1 PM: The device sends feeding and diaper change reminders to her husband, and uses facial recognition technology to reassess his stress level.

[1614] 5. 4 PM: My wife does the evening feeding and diaper change while the device monitors the progress.

[1615] 6. 6 PM: The server recognizes that my husband has finished work and notifies him of the upcoming dinner preparation task.

[1616] An example of a prompt might be, "Sir, it seems you're feeling stressed right now. Here's the nearest diaper changing area. Also, if you have any childcare concerns, please ask our childcare consultation chatbot."

[1617] This system allows couples to raise their children efficiently, flexibly manage tasks based on their emotional state, and provides comprehensive support within physical stores.

[1618] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1619] Step 1:

[1620] The server collects information about the couple's schedule and the child's routine entered by the user using input methods, including input from a smartphone or tablet. The input data includes the couple's working hours, the timing of the child's feeding and diaper changes, etc. This data is sent to the server and stored in a database.

[1621] Step 2:

[1622] The server acquires the collected schedule and routine information and generates an optimal task schedule using a generative AI model. This generation involves implementing an algorithm to allocate tasks appropriately, taking into account the user's working hours and children's daily routines. The output is saved in a database as the generated task schedule.

[1623] Step 3:

[1624] The terminal uses a display means to visually display the task schedule obtained from the server to the user. Specifically, the user can check the current and next tasks to be performed through a dedicated application. The input in this process is the task schedule obtained from the server, and the output is the schedule displayed on the user's terminal screen.

[1625] Step 4:

[1626] The terminal monitors the progress of the task in real time using a monitoring means. When the user completes the task, the terminal sends the information to the server, which updates the database. The input to this process is the user's notification of task completion, and the output is the updated task information in the database.

[1627] Step 5:

[1628] The device uses a notification mechanism to send task reminders to the user, which can take the form of real-time push notifications, emails, voice alerts, etc. The input is the time information of the scheduled task, and the output is the reminder notification to the user.

[1629] Step 6:

[1630] The device uses a recognition means to recognize emotions from the user's facial expressions and voice. Specifically, it uses a facial expression recognition library (such as face-api.js) to analyze the video captured by the camera and generate emotion data. The input is the camera video and audio data, and the output is the analyzed emotion data.

[1631] Step 7:

[1632] The server adjusts tasks and notification methods accordingly based on the recognized emotion data. For example, if the stress level is high, it may change the priority of the task or change the notification method to a softer tone. The input is emotion data, and the output is the adjusted task schedule and notification method.

[1633] Step 8:

[1634] The device uses the guidance means to navigate to a specific area within a physical store, indicating the location of childcare products and equipment that the user has searched for in the application. The input is a search request from the user, and the output is navigation information.

[1635] Step 9:

[1636] The device uses a conversational means to receive childcare-related consultations from the user via an AI chatbot. When the user inputs a childcare-related question through the application, the chatbot uses a generative AI model to provide appropriate advice. The input is the user's question, and the output is advice from the chatbot.

[1637] 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.

[1638] 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.

[1639] 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.

[1640] 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.

[1641] FIG. 9 is a diagram illustrating 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 actions 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.

[1642] 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.

[1643] 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).

[1644] 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.

[1645] 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."

[1646] 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.

[1647] 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).

[1648] 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.

[1649] 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.

[1650] 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.

[1651] 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.

[1652] 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.

[1653] 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.

[1654] 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.

[1655] 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.

[1656] 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.

[1657] 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.

[1658] The following is further disclosed regarding the above embodiment.

[1659] (Claim 1)

[1660] an input means for collecting information on the couple's schedule and the child's routine;

[1661] A generation means for generating an optimal task schedule based on the collected information;

[1662] a display means for displaying the generated task schedule;

[1663] monitoring means for monitoring the progress of the task and determining completion of the task;

[1664] A system including a notification mechanism for sending task reminders to a user.

[1665] (Claim 2)

[1666] 10. The system of claim 1, further comprising a storage means for storing the generated schedule in a database.

[1667] (Claim 3)

[1668] 10. The system of claim 1, further comprising an updating means for updating the information in the database after the user completes the task.

[1669] "Example 1"

[1670] (Claim 1)

[1671] input means for collecting the couple's schedule information and the children's regular schedule information;

[1672] A generation means for generating an optimal task schedule based on the collected information;

[1673] a display means for displaying the schedule generated using the generative AI model as the generation means;

[1674] monitoring means for monitoring the progress of the task and for determining the completion status of the task;

[1675] A system including a notification mechanism for sending task reminders to a user.

[1676] (Claim 2)

[1677] 10. The system of claim 1, further comprising a storage means for storing the generated schedule.

[1678] (Claim 3)

[1679] 10. The system of claim 1, further comprising an updating means for updating the information in the database after the user completes the task.

[1680] "Application Example 1"

[1681] (Claim 1)

[1682] an input means for collecting information on the couple's schedule and the child's routine;

[1683] A generation means for generating an optimal task schedule based on the collected information;

[1684] a display means for displaying the generated task schedule;

[1685] monitoring means for monitoring the progress of the task and determining completion of the task;

[1686] a notification means for sending task reminders to the user;

[1687] an input means for collecting store staff shift information and work content;

[1688] A generation means for generating an optimal shift schedule for store staff based on the collected information;

[1689] The system includes a notification means for reminding store staff of the generated shift schedule.

[1690] (Claim 2)

[1691] 10. The system of claim 1, further comprising a storage means for storing the generated schedule in a database.

[1692] (Claim 3)

[1693] 10. The system of claim 1, further comprising an updating means for updating the information in the database after the user completes the task.

[1694] "Example 2: Combining Emotion Engines"

[1695] (Claim 1)

[1696] an input means for collecting information on the couple's time and the child's daily routine;

[1697] A generation means for generating an optimal task timetable based on the collected information;

[1698] a display means for displaying the generated task timetable;

[1699] monitoring means for monitoring the progress of the task and determining completion of the task;

[1700] a notification means for sending task reminders to the user;

[1701] an emotion recognition means for analyzing a user's facial expression and voice and recognizing the user's emotional state;

[1702] The system includes an adjustment means for adjusting tasks and notifications based on the recognized emotions.

[1703] (Claim 2)

[1704] 10. The system of claim 1, further comprising storage means for storing the generated timetable in a repository.

[1705] (Claim 3)

[1706] 10. The system of claim 1, further comprising an updating means for updating the information in the information repository after the user completes the task.

[1707] "Application example 2 when combining emotion engines"

[1708] (Claim 1)

[1709] an input means for collecting information on the couple's schedule and the child's routine;

[1710] A generation means for generating an optimal task schedule based on the collected information;

[1711] a display means for displaying the generated task schedule;

[1712] monitoring means for monitoring the progress of the task and determining completion of the task;

[1713] a notification means for sending task reminders to the user;

[1714] A recognition means for recognizing emotions from a user's facial expression and voice;

[1715] an adjustment means for adjusting the task or notification method accordingly based on the recognized emotion;

[1716] a guidance means for navigating to a specific area within the store;

[1717] A conversation tool for receiving childcare-related advice from users

[1718] A system including:

[1719] (Claim 2)

[1720] 10. The system of claim 1, further comprising a storage means for storing the generated schedule in a database.

[1721] (Claim 3)

[1722] 10. The system of claim 1, further comprising an updating means for updating the information in the database after the user completes the task. [Explanation of symbols]

[1723] 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. an input means for collecting information on the couple's schedule and the child's routine; A generation means for generating an optimal task schedule based on the collected information; a display means for displaying the generated task schedule; monitoring means for monitoring the progress of the task and determining completion of the task; A system including a notification mechanism for sending task reminders to a user.

2. 2. The system of claim 1, further comprising a storage means for storing the generated schedule in a database.

3. 2. The system of claim 1, further comprising an updating means for updating the information in the database after the user completes the task.

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