system

Abstract

We provide the system. [Solution] An information processing device that collects user information and creates individual profiles, An information processing device that optimally assigns household chores based on collected information and adjusts the assignment information, A communication device that transmits notifications of assigned household chores to an output device, An input processing device that processes voice input and makes changes to business processes, An information processing device that collects information on the status of work completion and reflects it in the next work assignment, A system including mechanical devices that assist in physical work.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In many modern families, dual-income households are becoming common, but there is often an unequal distribution of housework, with a particular family member being burdened disproportionately. Also, housework scheduling management is cumbersome, and a systematic management method for efficiently performing tasks is required. This problem has led to an increase in the stress level within the family, resulting in a decline in the quality of life of all family members.

Means for Solving the Problems

[0005] This invention collects user plans, task progress, preferences, and evaluations via a server, and assigns optimized household tasks to each individual user based on this data. Furthermore, it includes a function to notify the user's terminal of reminders for assigned tasks. The system also includes terminal means that receive voice instructions and adjust tasks, and server means that collect task completion status and reflect it in the next scheduling, thereby realizing efficient and fair household management. This makes it possible to eliminate the imbalance in the burden of household chores, promote harmony within the family, and improve the quality of life for all family members.

[0006] A "server system" is a computer system that collects and analyzes data from users within a home network to perform optimized task assignments.

[0007] A "terminal device" is a device that has the function of notifying the user of a reminder and receives voice commands and transmits them to the server.

[0008] "User plans" refer to information about the activities and tasks that a user plans on a daily basis.

[0009] "Task progress" refers to information indicating the current status of household tasks.

[0010] "Preferences and ratings" refer to users' personal preferences regarding household chores and feedback from users regarding past tasks.

[0011] "Optimized household task assignment" refers to a method of distributing household tasks efficiently and fairly based on each user's circumstances.

[0012] A "reminder" is a notification that prompts a user to complete a pre-assigned task.

[0013] "Voice commands" are commands or requests that a user gives to a device via voice.

[0014] "Task adjustment" is the process of changing or modifying already assigned tasks and schedules based on the user's voice commands.

[0015] "Task completion status" refers to information indicating the extent to which a specific task has been carried out and completed. [Brief explanation of the drawing]

[0016] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when combined with an emotion engine. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when combined with an emotion engine.

Mode for Carrying Out the Invention

[0017] Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0018] First, the terms used in the following description will be explained.

[0019] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), etc.

[0020] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0021] In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0022] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0024] [First Embodiment]

[0025] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0026] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0027] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0028] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0029] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0030] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0031] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0032] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0034] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0035] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0036] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0037] This invention is a system for efficiently managing the division of household chores in dual-income households, aiming to optimally schedule tasks by exchanging information among a server, terminal, and user. The embodiments of this system are described below.

[0038] First, the server collects various information from the household members. This includes each member's schedule, history of past household tasks, preferences, and feedback. Based on this data, the server creates user profiles and plans for the efficient distribution of household tasks.

[0039] The server then uses an optimization algorithm to assign household tasks to each member. This algorithm takes into account task priorities and each user's available time to generate a manageable schedule. Finally, it notifies each user via their device of the assigned tasks, thereby promoting that household chores are completed according to plan.

[0040] Users receive notifications when tasks are assigned during their daily lives and begin taking action to complete them. Furthermore, if users wish to adjust tasks, they can give voice commands via their device. These voice commands are interpreted by the device and transmitted to the server. The server receives the voice commands, readjusts the schedule, and sends the new schedule to the device.

[0041] Once a task is completed, the user reports its progress on their device. The information reported from the device is sent to the server and used for scheduling future tasks. The server uses the feedback information to update the user profile and optimize the system for more accurate task assignment.

[0042] As a concrete example, suppose a household schedules are set up so that user A is responsible for preparing dinner on weekends, and user B is responsible for cleaning during the week. User A receives a reminder on their device to "prepare dinner on Saturday afternoon," and if that day is inconvenient, they can give a voice command to "change it to Sunday." Based on this command, the server updates the schedule and notifies user A of the new appointment.

[0043] In this way, the system aims to improve overall family harmony and quality of life by efficiently distributing household tasks and ensuring fairness in the burden of housework.

[0044] The following describes the processing flow.

[0045] Step 1:

[0046] The server collects and analyzes the user's schedule, past task history, preferences, and feedback. This creates a user profile that includes the tasks the user excels at, tasks they want to avoid, and their time constraints.

[0047] Step 2:

[0048] The server lists all necessary household tasks, including common chores like cooking, cleaning, laundry, and shopping. Each task is assigned a priority and a deadline.

[0049] Step 3:

[0050] The server uses an optimization algorithm to optimally distribute household tasks based on each user's profile. This takes into account each user's free time, the urgency of the tasks, and their individual strengths in task allocation.

[0051] Step 4:

[0052] The server sends the allocation results to the terminal. This prepares the terminal to notify the user of the household tasks assigned to it and their schedules.

[0053] Step 5:

[0054] The device displays a task reminder to the user at a specified time. For example, it might send a message saying, "Please prepare dinner at 6 PM today."

[0055] Step 6:

[0056] Users can give voice commands to their devices. For example, if they want to change the time of a task, they can say, "Change the time for preparing dinner to 7 PM."

[0057] Step 7:

[0058] The terminal interprets the voice command and sends the content to the server. The server then readjusts the schedule based on this information.

[0059] Step 8:

[0060] The server sends the updated schedule back to the terminal and sets up new reminders as needed.

[0061] Step 9:

[0062] Users report their progress using their device after completing a task. This might involve simple reports such as, "I've finished preparing dinner."

[0063] Step 10:

[0064] The terminal sends a report to the server, which then updates the user profile based on this information. This improves scheduling accuracy by providing useful information for future task assignments.

[0065] (Example 1)

[0066] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0067] In dual-income households, the division of household chores tends to be uneven, resulting in an excessive burden on certain members. Furthermore, a lack of flexibility to respond to daily schedules and unexpected changes can make time management difficult. The purpose of this invention is to solve these problems and realize efficient and fair management of household chores.

[0068] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0069] In this invention, the server includes an information processing device that collects users' schedules, work progress, preferences, and evaluations; an information processing device that assigns home-based tasks optimized for each individual user based on the collected information; and an information device that transmits notifications regarding the assigned tasks to the user's information device. This enables efficient and fair assignment of home-based tasks to each member, as well as flexible responses to schedule changes and feedback.

[0070] "Users" refers to individual household members who utilize a system designed to efficiently manage household tasks.

[0071] An "information processing device" refers to a computer system that has the function of assigning tasks based on data collected from users and updating records based on feedback.

[0072] "Information equipment" refers to devices that have the function of sending work notifications to users and receiving voice instructions, and includes smartphones and tablets.

[0073] "Work" refers to household chores and other tasks performed within the home, and signifies a unit of action assigned by the system.

[0074] "Notification" refers to information that information devices transmit to users to inform them of the start time of work or other important matters.

[0075] "Voice support function" refers to technology that allows users to give voice instructions to the system, and includes a function that analyzes voice input and converts the instructions into text.

[0076] This invention is a system for achieving efficient division and management of household tasks in dual-income households. This system consists of an information processing device (hereinafter referred to as a server), information devices (hereinafter referred to as terminals), and household members (hereinafter referred to as users).

[0077] The server collects various information from each member of the household. This information includes the user's schedule, past work history, work preferences, and feedback. The collected data is used to create optimized profiles for each user. A database management system (e.g., SQL database) is used for data processing to efficiently manage the information.

[0078] Next, the server uses a linear programming algorithm to plan the optimal distribution of household tasks based on the collected data. This plan takes into account task priorities and user availability to generate a reasonable schedule. This ensures that tasks are distributed to each member in a manageable manner.

[0079] The generated schedule is notified to each user via a device. The device is a common computing device such as a smartphone or tablet, which sends reminders to users using push notifications or voice assistants. The device also receives voice commands (e.g., using "voice assistance") and transmits instructions to the server.

[0080] Users initiate actions based on notifications they receive from their devices during their daily lives. If they wish to change their schedule, they can request adjustments via voice input. This allows for flexible responses tailored to the user's needs.

[0081] As a concrete example, a schedule is created in a household to efficiently divide the tasks of "preparing dinner" and "cleaning the house." If the user gives a voice command saying, "I want to change the time for preparing dinner from Saturday to Sunday," the server receives this command and readjusts the schedule. The new, adjusted schedule is then notified to the user again via the terminal.

[0082] An example of a prompt message is: "I would like to design a system to optimally manage the division of household chores in dual-income households. Please specify how the server, terminal, and user will cooperate, and what algorithms and technologies (e.g., optimization algorithms, speech recognition technology) will be used to efficiently distribute the work."

[0083] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0084] Step 1:

[0085] The server collects information such as the user's schedule, past work history, preferences, and ratings. This information is obtained from home calendar applications and task management tools. Input data includes the user's schedule and feedback, and the server uses this to create a user profile. Specific data processing involves converting the acquired schedule into a standardized format and saving it to a database. The output is a detailed profile for each user.

[0086] Step 2:

[0087] The server assigns home-based tasks based on collected user profiles. At this stage, a linear programming algorithm is used to generate an optimal schedule, considering task priorities and user availability. The inputs are user profiles and task lists, and the schedule is created through calculations based on these. The generated schedule is output, determining the tasks assigned to each user.

[0088] Step 3:

[0089] The terminal notifies the user of schedule information received from the server. Notifications are primarily sent via smartphone push notifications or reminder apps. The input is schedule data from the server, and based on this, the terminal sets reminders to inform the user of information such as the start time and duration of the task. The output is the schedule notification that has been confirmed by the user.

[0090] Step 4:

[0091] The user begins work based on the received notification. If a change to the schedule is needed, they send a voice command via the terminal. The input is the user's voice instruction, which the terminal converts to text using speech recognition technology. The converted text instruction is sent to the server. The output is a schedule change request.

[0092] Step 5:

[0093] The server receives a schedule change request from the user and re-optimizes the schedule. It recalculates based on the new conditions and outputs an adjusted result with minimal impact. The input data is the user's change request and the current schedule. The output is the adjusted new schedule.

[0094] Step 6:

[0095] Users report the completion of a task via their terminal. The terminal sends the completion data to the server, providing feedback information that will be used for future task assignments. The input is the task completion status, and based on this, the server reflects the feedback in the user profile, generating an updated profile as output.

[0096] (Application Example 1)

[0097] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0098] In dual-income families, efficiently managing and fairly dividing household chores can be challenging, often leading to an uneven distribution of time and effort. Furthermore, tracking the progress of chores and adjusting tasks as needed is a time-consuming process. Maintaining harmony within the household through intuitive voice-activated operation and feedback is also a challenge.

[0099] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0100] In this invention, the server includes an information processing device that collects user information and creates individual profiles; an information processing device that optimally assigns household chores based on the collected information and adjusts the assignment information; a communication device that transmits notifications of assigned household chores to an output device; an input processing device that processes voice input and makes changes to the tasks; an information processing device that collects the status of the work performed and reflects it in the next task assignment; and a mechanical device that supports physical work. This enables the efficient and fair distribution of household chores.

[0101] "User" refers to the individual person who manages and performs household chore tasks within the home.

[0102] An "information processing device" is a device that acquires and analyzes data and performs calculations to optimize the schedule of household chores.

[0103] A "communication device" is a device used to transmit task information output from an information processing device to the user's terminal.

[0104] An "input processing device" is a device that receives voice commands from a user, analyzes them, and performs further processing.

[0105] A "mechanical device" is a device that physically performs assigned household tasks and assists or automates household work.

[0106] This invention is a system for efficiently managing and performing household chores within the home, and consists of a server, terminals, and users. The main hardware necessary for carrying out the invention includes an information processing device, a communication device, an input processing device, and a mechanical device.

[0107] The server collects information from users to generate individual profiles. This involves using devices such as smartphones and tablets to obtain schedules and preferences from users through a database. The information processing unit then analyzes this data and assigns household chores optimized for each individual user. An optimization algorithm is used for this assignment.

[0108] The device is responsible for notifying the user of assigned household chores. Notifications are provided as voice and visual reminders to encourage actions within the home. The device also utilizes voice recognition software (e.g., Google® Cloud Speech-to-Text API) to receive voice commands. The received voice commands are analyzed by an input processing unit, and the necessary processing is performed.

[0109] Users utilize a home assistant robot to manage the progress of assigned tasks and adjust them via voice as needed. The server updates the work plan based on this information and improves future task assignments based on the feedback.

[0110] A concrete example is a scenario where a user gives a voice command such as "Do this week's cleaning on Saturday," and the robot incorporates this into its regular cleaning schedule, automating the task. The following are examples of prompts used for the generated AI model:

[0111] "Design a feature that allows a home robot to create a cleaning schedule based on voice commands and notify users of the optimal time according to their own schedule."

[0112] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0113] Step 1:

[0114] The server collects information from each user within the home network, including schedules, preferences, and past task execution history. Input is data sent from users via their devices, and output is individual user profiles. To analyze this data, a database management system is used to organize the information and generate profiles.

[0115] Step 2:

[0116] The server uses an optimization algorithm to assign household chores based on collected user profile data. Inputs are user profiles and imported work tasks, while output is an individually optimized task schedule. Optimization techniques and scheduling algorithms are used for data processing.

[0117] Step 3:

[0118] The device receives schedules and notifies the user of household chore reminders. Inputs are assigned tasks from the server, and outputs are visual or audio reminders to the user. The device's notification functions and interface are used for notifications.

[0119] Step 4:

[0120] Users give voice commands and make change requests through their devices. Input is the user's voice commands, and output is converted speech-to-text data. Google Cloud Speech-to-Text API is used for speech recognition.

[0121] Step 5:

[0122] The server receives change requests from users and adjusts tasks accordingly. Input is text data converted from speech, and output is an updated task schedule. Natural language processing techniques and scheduling algorithms are used for data processing.

[0123] Step 6:

[0124] Users monitor task progress and report completion status via their terminal. Input is progress report data, and output is feedback information sent to the server. A dedicated user interface is used for reporting.

[0125] Step 7:

[0126] The server uses the received feedback information to update user profiles and utilize this information for future task assignments. The input is progress feedback data, and the output is updated profile information. Machine learning algorithms may be used for the updates.

[0127] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0128] This invention relates to a system that recognizes a user's emotional state and enables the scheduling of household tasks accordingly. This system consists of a server, a terminal, a user, and an emotion engine. The following describes its embodiments in detail.

[0129] First, the emotion engine is built into the device and analyzes the user's voice, facial expressions, and other biometric information in real time to recognize the user's emotional state. This emotional data indicates the user's stress, fatigue, and happiness levels, and is important information that can be used to assign tasks at home.

[0130] The server collects emotional data from the emotion engine, along with the user's schedule, past task history, preferences, and feedback. This data is integrated into a profile and used to assign household tasks optimized for the user. When assigning tasks, the user's emotional state is taken into consideration; for example, users who are highly stressed are assigned less burdensome tasks.

[0131] The server uses this information to generate an optimal household task schedule and sends it to the device. The device then sends reminders to the user based on this schedule, prompting them to complete tasks. This allows the user to perform tasks at the appropriate time according to their emotional state.

[0132] To give a specific example, if the emotion engine sends information to the server indicating that user A is tired one morning, the server will decide to postpone the demanding cleaning task scheduled for that afternoon until the next day and assign a lighter task instead. Based on this decision, the terminal will remind user A of the task change and notify them of the new schedule.

[0133] Once a task is completed, the user reports its progress. Later, the server dynamically updates the user's profile using emotional feedback provided by the emotion engine, improving scheduling accuracy for future tasks.

[0134] This system enables flexible and efficient task management tailored to the user's emotional state, which is expected to reduce the uneven distribution of household chores and improve the overall quality of life for the family.

[0135] The following describes the processing flow.

[0136] Step 1:

[0137] The device collects biometric information such as the user's voice, facial expressions, and heart rate. Based on this, an emotion engine analyzes the user's emotions and recognizes their current emotional state. This information is evaluated in categories such as stress, fatigue, and happiness.

[0138] Step 2:

[0139] The device sends emotional data, analyzed by the emotion engine, to the server. This allows the server to understand the user's emotional state in real time.

[0140] Step 3:

[0141] The server integrates emotional data along with the user's schedule, past task history, preferences, and feedback to update their profile. This profile contains detailed information about each user and forms the basis for optimal task assignment.

[0142] Step 4:

[0143] The server lists the household chores needed and optimizes task scheduling, taking into account the user's profile. This process includes adjustments based on the user's emotional state, such as prioritizing low-stress tasks based on emotional data.

[0144] Step 5:

[0145] Once the task schedule is determined, the server sends that information to the terminal. The terminal then prepares to notify the user of the task reminder according to this schedule.

[0146] Step 6:

[0147] The device displays a task reminder to the user at a specified time. For example, the notification might say, "You need to relax, so take a 20-minute walk."

[0148] Step 7:

[0149] Users can give voice commands to the device as needed. These commands can include requests to change or reschedule tasks.

[0150] Step 8:

[0151] The terminal interprets the voice commands from the user and sends the content to the server. Based on this, the server readjusts the task schedule.

[0152] Step 9:

[0153] The server sends the rescheduled schedule to the device, and the device updates the reminder based on the new information.

[0154] Step 10:

[0155] After completing a task, the user reports its progress on their device. This report includes the task's progress and their sense of accomplishment.

[0156] Step 11:

[0157] The device continuously monitors the user's emotional state and sends this information to the server. This allows the server to understand the user's long-term trends and incorporate them into future task assignments.

[0158] This series of processes is expected to enable household chore management that takes users' emotions into consideration, thereby improving harmony and efficiency within the home.

[0159] (Example 2)

[0160] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0161] In household task management, assigning tasks uniformly without considering the user's emotional state can increase user stress and workload. Furthermore, a lack of task assignments optimized for individual users leads to decreased overall efficiency and a decline in users' quality of life.

[0162] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0163] In this invention, the server includes analysis means for analyzing the user's emotional state, data means for collecting the user's plans, task progress, preferences, and evaluations, and assignment means for assigning tasks optimized for each individual user based on the collected data and emotional state. This enables flexible and efficient task management that takes the user's emotional state into account, and is expected to improve the quality of life.

[0164] "Analysis means" refers to a device or method that analyzes and quantifies a user's emotional state from voice, facial expressions, biometric information, etc.

[0165] "Data means" refers to a device or method for collecting, storing, and managing information such as a user's plans, task progress, preferences, and evaluations.

[0166] "Assignment means" refers to a device or method for determining and allocating tasks optimized for individual users based on collected data and emotional states.

[0167] "Notification means" refers to a device or method for sending information about an assigned task to the user's device and informing the user.

[0168] "Adjustment means" refers to a device or method for receiving voice instructions and changing or adjusting the content or schedule of assigned tasks.

[0169] An "update mechanism" is a device or method for updating a user's profile based on the completion status of tasks, thereby improving the accuracy of task scheduling for future tasks.

[0170] "Transmission means" refers to a device or method for transmitting user input received via a voice assistant to a data means.

[0171] This invention is a system that analyzes a user's emotional state and optimizes task management within the home. This system consists of multiple devices and programs, with the server, terminals, and users each playing their respective roles.

[0172] The device is equipped with an emotion recognition engine that acquires biometric information such as the user's voice, facial expressions, and heart rate from sensors. This data is analyzed in real time, and the user's emotional state, such as stress, fatigue, and happiness, is quantified. The emotion recognition engine utilizes commercially available facial recognition software and voice analysis software, for example.

[0173] The server receives emotional data provided by the terminal and stores it in a database. Furthermore, the server integrates this data with other information such as the user's schedule, past task history, preferences, and ratings. At this time, a generative AI model is used to assign optimal tasks based on the emotional state and preferences. The data processing performed by the server includes a database management system and predictive algorithms.

[0174] For example, if the device detects user B's stress level in the morning, the server will replace a heavy afternoon task, such as "heavy cleaning," with a lighter task like "organizing books," to alleviate the burden. This new schedule is sent to the device, and the device notifies the user.

[0175] After receiving a notification from their device, the user performs the task. Once the task is completed, they report the completion status via their device. The server receives these reports, updates the profile with new sentiment data, and improves the accuracy of future task scheduling.

[0176] This system enables flexible and efficient task management, reducing the workload within the home. It is expected to improve users' quality of life.

[0177] Example prompt: "Reschedule afternoon tasks based on the user's current emotional state."

[0178] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0179] Step 1:

[0180] The device acquires biometric information such as the user's voice, facial expressions, and heart rate from sensors. An emotion recognition engine analyzes this input data in real time, quantifying emotional data such as stress, fatigue, and happiness. This emotional data is then generated as output. Specifically, voice analysis software analyzes voice tone, and facial recognition software evaluates facial expressions.

[0181] Step 2:

[0182] The terminal sends the generated sentiment data to the server. The server receives the transmitted sentiment data and stores it in a database. The input sentiment data is integrated into the relevant user profile within the server. As output, the sentiment data is integrated with existing user data (schedule, history, ratings, etc.). This is where the database management system comes into play.

[0183] Step 3:

[0184] The server uses a generative AI model based on integrated data to generate optimal task schedules for individual users. Inputs include sentiment data and the entire user profile. Outputs include a task list optimized based on emotional state. This generative AI model uses a predictive algorithm to assign tasks.

[0185] Step 4:

[0186] The server sends the generated task schedule to the terminal. This becomes the input for the notification system, and the terminal notifies the user of the received schedule. The output is a task list displayed to the user. Specifically, the terminal uses alarms and pop-up notifications to inform the user.

[0187] Step 5:

[0188] The user receives notifications from their device, performs tasks, and reports their progress via the device upon completion. The input is the task progress information reported by the user. The output is the server receiving updated user data for the next time. Specific actions performed within this process include the user clicking a completion button.

[0189] Step 6:

[0190] The server receives a task completion report and dynamically updates the user profile based on the new sentiment data. Inputs include task completion status and sentiment feedback. Based on this, an updated profile is generated as output for use in future scheduling. Specifically, the data is then fed back into the generating AI model.

[0191] (Application Example 2)

[0192] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0193] In modern households, the management and adjustment of household tasks in accordance with users' emotions are often insufficient, creating a need for a system that can perform tasks efficiently and appropriately. Task management that does not consider users' emotional states can lead to stress and dissatisfaction, potentially lowering the quality of life within the home. The goal is to solve this problem by achieving flexible and appropriate task management that takes users' emotions into consideration, thereby improving the overall quality of life for the family.

[0194] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0195] In this invention, the server includes information processing means for collecting user plans, task progress, preferences, and evaluations; information processing means for assigning household tasks optimized for each individual user based on the collected data; and analysis means for recognizing the user's emotional state using an emotion analysis engine and dynamically adjusting task assignments using that information. This enables flexible task management that responds to the user's emotional state.

[0196] "User plans" refer to information that shows the activities and schedules that a user has planned for the future.

[0197] "Task progress" refers to status information that indicates the extent to which an assigned task has been completed.

[0198] "Preferences and ratings" refers to information that indicates a user's personal preferences and evaluations of past tasks.

[0199] "Information processing means" refers to a device or system that has the function of collecting and analyzing data and providing information necessary for task management.

[0200] "Display means" refers to devices or systems used to present information to users visually or audibly.

[0201] "Communication means" refers to technologies or systems for sending and receiving data between other devices or systems.

[0202] "Analysis means" refers to a device or system that has the function of analyzing data and extracting useful information.

[0203] A "mobile device" is a terminal or device that can provide information to users while being carried around.

[0204] An "emotion analysis engine" is a technology or system that analyzes a user's voice, facial expressions, and other biometric information to recognize their emotional state.

[0205] The system for realizing this invention flexibly manages household tasks based on the user's emotions and consists of several main components.

[0206] The server collects information on the user's plans, task progress, preferences, and ratings, and assigns household tasks optimized for each individual user. It can recognize the user's emotional state from their voice and facial expressions, and analyze this information using an emotion analysis engine. For example, if the server determines that the user is tired, it will prioritize assigning less demanding tasks.

[0207] The device serves to notify the user's mobile device of assigned tasks. Through voice assistants and display methods, it can inform the user of task schedules and allow for adjustments as needed. Specifically, it provides voice reminders at user-specified times, such as, "You have laundry scheduled for today, would you like to do it at a different time?"

[0208] Users report the progress of their tasks through the system interface. This allows the system to receive the necessary feedback to improve the accuracy of future task scheduling.

[0209] As an example of a prompt, the question "What household chores would you recommend when the user is not under heavy load?" is input to the generating AI model. This allows the system to obtain information to make appropriate task suggestions. This information is used for dynamic task assignment, helping to streamline household task management.

[0210] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0211] Step 1:

[0212] The server collects user plans, task progress, preferences, and evaluations. It uses the user's past scheduling data and feedback as input to build foundational data for optimal task allocation. This data is referenced in the subsequent task assignment process.

[0213] Step 2:

[0214] The device analyzes the user's voice and facial expressions through an emotion analysis engine to recognize their emotional state. The input is real-time collected audio and video data, which is then analyzed to generate an output representing the user's emotional state (e.g., fatigue, stress, happiness). This analysis result is then sent to a server.

[0215] Step 3:

[0216] The server assigns optimized household tasks based on collected emotional data. It uses emotional data and user profiles collected in the previous step as input. This dynamically generates task schedules, resulting in output task lists with varying execution orders and content.

[0217] Step 4:

[0218] The device notifies the user of the generated task schedule. The input is a task list sent from the server, which is then communicated to the user using a voice assistant or notification function. Specifically, notifications such as, "You seem tired today, so let's do the cleaning tomorrow?" are sent.

[0219] Step 5:

[0220] Users report the completion status of tasks via their terminal. The input consists of completion reports for tasks displayed on the terminal, and the results are sent to the server. The output is updated data including the task completion status.

[0221] Step 6:

[0222] The server updates the profile to improve scheduling accuracy for the next task based on user feedback and completion status. Inputs include completion reports and sentiment feedback, and the server outputs an improved profile to provide the optimal task schedule.

[0223] Through this series of steps, the system supports a comfortable living environment for the user.

[0224] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0225] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0226] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0227] [Second Embodiment]

[0228] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0229] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0230] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0231] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0232] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0233] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0234] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0235] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0236] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0237] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0238] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0239] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0240] This invention is a system for efficiently managing the division of household chores in dual-income households, aiming to optimally schedule tasks by exchanging information among a server, terminal, and user. The embodiments of this system are described below.

[0241] First, the server collects various information from the household members. This includes each member's schedule, history of past household tasks, preferences, and feedback. Based on this data, the server creates user profiles and plans for the efficient distribution of household tasks.

[0242] The server then uses an optimization algorithm to assign household tasks to each member. This algorithm takes into account task priorities and each user's available time to generate a manageable schedule. Finally, it notifies each user via their device of the assigned tasks, thereby promoting that household chores are completed according to plan.

[0243] Users receive notifications when tasks are assigned during their daily lives and begin taking action to complete them. Furthermore, if users wish to adjust tasks, they can give voice commands via their device. These voice commands are interpreted by the device and transmitted to the server. The server receives the voice commands, readjusts the schedule, and sends the new schedule to the device.

[0244] Once a task is completed, the user reports its progress on their device. The information reported from the device is sent to the server and used for scheduling future tasks. The server uses the feedback information to update the user profile and optimize the system for more accurate task assignment.

[0245] As a concrete example, suppose a household schedules are set up so that user A is responsible for preparing dinner on weekends, and user B is responsible for cleaning during the week. User A receives a reminder on their device to "prepare dinner on Saturday afternoon," and if that day is inconvenient, they can give a voice command to "change it to Sunday." Based on this command, the server updates the schedule and notifies user A of the new appointment.

[0246] In this way, the system aims to improve overall family harmony and quality of life by efficiently distributing household tasks and ensuring fairness in the burden of housework.

[0247] The following describes the processing flow.

[0248] Step 1:

[0249] The server collects and analyzes the user's schedule, past task history, preferences, and feedback. This creates a user profile that includes the tasks the user excels at, tasks they want to avoid, and their time constraints.

[0250] Step 2:

[0251] The server lists all necessary household tasks, including common chores like cooking, cleaning, laundry, and shopping. Each task is assigned a priority and a deadline.

[0252] Step 3:

[0253] The server uses an optimization algorithm to optimally distribute household tasks based on each user's profile. This takes into account each user's free time, the urgency of the tasks, and their individual strengths in task allocation.

[0254] Step 4:

[0255] The server sends the allocation results to the terminal. This prepares the terminal to notify the user of the household tasks assigned to it and their schedules.

[0256] Step 5:

[0257] The device displays a task reminder to the user at a specified time. For example, it might send a message saying, "Please prepare dinner at 6 PM today."

[0258] Step 6:

[0259] Users can give voice commands to their devices. For example, if they want to change the time of a task, they can say, "Change the time for preparing dinner to 7 PM."

[0260] Step 7:

[0261] The terminal interprets the voice command and sends the content to the server. The server then readjusts the schedule based on this information.

[0262] Step 8:

[0263] The server sends the updated schedule back to the terminal and sets up new reminders as needed.

[0264] Step 9:

[0265] Users report their progress using their device after completing a task. This might involve simple reports such as, "I've finished preparing dinner."

[0266] Step 10:

[0267] The terminal sends a report to the server, which then updates the user profile based on this information. This improves scheduling accuracy by providing useful information for future task assignments.

[0268] (Example 1)

[0269] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0270] In dual-income households, the division of household chores tends to be uneven, resulting in an excessive burden on certain members. Furthermore, a lack of flexibility to respond to daily schedules and unexpected changes can make time management difficult. The purpose of this invention is to solve these problems and realize efficient and fair management of household chores.

[0271] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0272] In this invention, the server includes an information processing device that collects users' schedules, work progress, preferences, and evaluations; an information processing device that assigns home-based tasks optimized for each individual user based on the collected information; and an information device that transmits notifications regarding the assigned tasks to the user's information device. This enables efficient and fair assignment of home-based tasks to each member, as well as flexible responses to schedule changes and feedback.

[0273] "Users" refers to individual household members who utilize a system designed to efficiently manage household tasks.

[0274] An "information processing device" refers to a computer system that has the function of assigning tasks based on data collected from users and updating records based on feedback.

[0275] "Information equipment" refers to devices that have the function of sending work notifications to users and receiving voice instructions, and includes smartphones and tablets.

[0276] "Work" refers to household chores and other tasks performed within the home, and signifies a unit of action assigned by the system.

[0277] "Notification" refers to information that information devices transmit to users to inform them of the start time of work or other important matters.

[0278] "Voice support function" refers to technology that allows users to give voice instructions to the system, and includes a function that analyzes voice input and converts the instructions into text.

[0279] This invention is a system for achieving efficient division and management of household tasks in dual-income households. This system consists of an information processing device (hereinafter referred to as a server), information devices (hereinafter referred to as terminals), and household members (hereinafter referred to as users).

[0280] The server collects various information from each member within the household. This information includes the user's schedule, past work history, preferences and feedback regarding work. The collected data is used to create a profile optimized for each user. For data processing, a database management system (e.g., SQL database) is used to manage information efficiently.

[0281] Next, the server uses a linear programming algorithm to plan an optimal division of household chores based on the collected data. In this plan, the priority of the chores and the user's free time are considered to generate a reasonable schedule. As a result, the chores are distributed to each member in a reasonable manner.

[0282] The generated schedule is notified to each user via the terminal. The terminal is a general computing device such as a smartphone or tablet, and uses push notifications and voice assistants to send reminders to the user. The terminal also receives voice commands (e.g., using the "voice assistance function") and conveys instructions to the server.

[0283] The user starts to act based on the notifications received from the terminal in daily life. If the user wishes to change the schedule, an adjustment request can be made through voice input. This enables flexible response according to the user's convenience.

[0284] As a specific example, in a certain household, a schedule is arranged to efficiently divide the tasks of "preparing dinner" and "cleaning the house". At this time, if the user gives a voice instruction saying "I want to change the preparation of dinner from Saturday to Sunday", the server receives this instruction and readjusts the schedule. The new schedule after adjustment is notified to the user again via the terminal.

[0285] As an example of a prompt sentence, there is "I want to devise a system for optimally managing housework sharing in a dual-income family. Please specifically show how the server, terminal, and users cooperate and what algorithms and technologies (e.g., optimization algorithms, speech recognition technology) are used to efficiently distribute the work."

[0286] The flow of the specific process in Example 1 will be described using FIG. 11.

[0287] Step 1:

[0288] The server collects information such as the user's schedule, past work history, preferences, and evaluations. This information is obtained from the calendar application and task management tool within the home. As input data, there is the user's schedule and feedback, and based on these, the server creates a user profile. As specific data processing, operations such as converting the acquired schedule into a standardized format and storing it in the database are performed. The output is a detailed profile for each user.

[0289] Step 2:

[0290] Based on the collected user profile, the server assigns housework. At this stage, a linear programming algorithm is utilized to consider the task priorities and the user's available time to generate an optimal schedule. The input is the user profile and the work list, and based on the arithmetic processing using these, a schedule is created. The generated schedule is output, and the work assigned to each user is determined.

[0291] Step 3:

[0292] The terminal notifies the user of schedule information received from the server. Notifications are primarily sent via smartphone push notifications or reminder apps. The input is schedule data from the server, and based on this, the terminal sets reminders to inform the user of information such as the start time and duration of the task. The output is the schedule notification that has been confirmed by the user.

[0293] Step 4:

[0294] The user begins work based on the received notification. If a change to the schedule is needed, they send a voice command via the terminal. The input is the user's voice instruction, which the terminal converts to text using speech recognition technology. The converted text instruction is sent to the server. The output is a schedule change request.

[0295] Step 5:

[0296] The server receives a schedule change request from the user and re-optimizes the schedule. It recalculates based on the new conditions and outputs an adjusted result with minimal impact. The input data is the user's change request and the current schedule. The output is the adjusted new schedule.

[0297] Step 6:

[0298] Users report the completion of a task via their terminal. The terminal sends the completion data to the server, providing feedback information that will be used for future task assignments. The input is the task completion status, and based on this, the server reflects the feedback in the user profile, generating an updated profile as output.

[0299] (Application Example 1)

[0300] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0301] In a dual-income family, it is difficult to efficiently manage and fairly share household chores, and the burden of time and labor may be unevenly distributed. Additionally, tracking the progress of household chores and adjusting tasks as needed is a time-consuming task. Furthermore, it is also a challenge to continuously maintain harmony within the family through intuitive voice operations and feedback.

[0302] The specific processing by the specific processing unit 290 of the data processing apparatus 12 in Application Example 1 is realized by the following respective means.

[0303] In this invention, the server includes an information processing apparatus that collects user information and creates individual profiles, an information processing apparatus that optimally assigns household chores based on the collected information and adjusts the assignment information, a communication apparatus that transmits notifications of the assigned household chores to an output device, an input processing apparatus that processes voice input and changes the tasks, an information processing apparatus that collects the implementation status of the tasks and reflects it in the next task assignment, and a mechanical apparatus that supports physical work. As a result, efficient and fair sharing of household chores becomes possible.

[0304] "User" refers to an individual person who manages and executes tasks of household chores within the family.

[0305] "Information processing apparatus" is an apparatus that acquires data, analyzes it, and performs computational operations to optimize the schedule of household chores.

[0306] "Communication apparatus" is an apparatus for transmitting task information output from the information processing apparatus to the user's terminal.

[0307] "Input processing apparatus" is an apparatus that receives voice instructions from the user, analyzes them, and performs further processing.

[0308] "Mechanical apparatus" is an apparatus that physically executes the assigned household chores and assists or automates in-house work.

[0309] This invention is a system for efficiently managing and performing household chores within the home, and consists of a server, terminals, and users. The main hardware necessary for carrying out the invention includes an information processing device, a communication device, an input processing device, and a mechanical device.

[0310] The server collects information from users to generate individual profiles. This involves using devices such as smartphones and tablets to obtain schedules and preferences from users through a database. The information processing unit then analyzes this data and assigns household chores optimized for each individual user. An optimization algorithm is used for this assignment.

[0311] The device is responsible for notifying the user of assigned household chores. Notifications are provided as voice and visual reminders to encourage actions within the home. The device also utilizes speech recognition software (e.g., Google Cloud Speech-to-Text API) to receive voice commands. The received voice commands are analyzed by an input processing unit, and the necessary processing is performed.

[0312] Users utilize a home assistant robot to manage the progress of assigned tasks and adjust them via voice as needed. The server updates the work plan based on this information and improves future task assignments based on the feedback.

[0313] A concrete example is a scenario where a user gives a voice command such as "Do this week's cleaning on Saturday," and the robot incorporates this into its regular cleaning schedule, automating the task. The following are examples of prompts used for the generated AI model:

[0314] "Design a feature that allows a home robot to create a cleaning schedule based on voice commands and notify users of the optimal time according to their own schedule."

[0315] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0316] Step 1:

[0317] The server collects information from each user within the home network, including schedules, preferences, and past task execution history. Input is data sent from users via their devices, and output is individual user profiles. To analyze this data, a database management system is used to organize the information and generate profiles.

[0318] Step 2:

[0319] The server uses an optimization algorithm to assign household chores based on collected user profile data. Inputs are user profiles and imported work tasks, while output is an individually optimized task schedule. Optimization techniques and scheduling algorithms are used for data processing.

[0320] Step 3:

[0321] The device receives schedules and notifies the user of household chore reminders. Inputs are assigned tasks from the server, and outputs are visual or audio reminders to the user. The device's notification functions and interface are used for notifications.

[0322] Step 4:

[0323] Users give voice commands and make change requests through their devices. Input is the user's voice commands, and output is converted speech-to-text data. Google Cloud Speech-to-Text API is used for speech recognition.

[0324] Step 5:

[0325] The server receives change requests from users and adjusts tasks accordingly. Input is text data converted from speech, and output is an updated task schedule. Natural language processing techniques and scheduling algorithms are used for data processing.

[0326] Step 6:

[0327] Users monitor task progress and report completion status via their terminal. Input is progress report data, and output is feedback information sent to the server. A dedicated user interface is used for reporting.

[0328] Step 7:

[0329] The server uses the received feedback information to update user profiles and utilize this information for future task assignments. The input is progress feedback data, and the output is updated profile information. Machine learning algorithms may be used for the updates.

[0330] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0331] This invention relates to a system that recognizes a user's emotional state and enables the scheduling of household tasks accordingly. This system consists of a server, a terminal, a user, and an emotion engine. The following describes its embodiments in detail.

[0332] First, the emotion engine is built into the device and analyzes the user's voice, facial expressions, and other biometric information in real time to recognize the user's emotional state. This emotional data indicates the user's stress, fatigue, and happiness levels, and is important information that can be used to assign tasks at home.

[0333] The server collects emotional data from the emotion engine, along with the user's schedule, past task history, preferences, and feedback. This data is integrated into a profile and used to assign household tasks optimized for the user. When assigning tasks, the user's emotional state is taken into consideration; for example, users who are highly stressed are assigned less burdensome tasks.

[0334] The server uses this information to generate an optimal household task schedule and sends it to the device. The device then sends reminders to the user based on this schedule, prompting them to complete tasks. This allows the user to perform tasks at the appropriate time according to their emotional state.

[0335] To give a specific example, if the emotion engine sends information to the server indicating that user A is tired one morning, the server will decide to postpone the demanding cleaning task scheduled for that afternoon until the next day and assign a lighter task instead. Based on this decision, the terminal will remind user A of the task change and notify them of the new schedule.

[0336] Once a task is completed, the user reports its progress. Later, the server dynamically updates the user's profile using emotional feedback provided by the emotion engine, improving scheduling accuracy for future tasks.

[0337] This system enables flexible and efficient task management tailored to the user's emotional state, which is expected to reduce the uneven distribution of household chores and improve the overall quality of life for the family.

[0338] The following describes the processing flow.

[0339] Step 1:

[0340] The device collects biometric information such as the user's voice, facial expressions, and heart rate. Based on this, an emotion engine analyzes the user's emotions and recognizes their current emotional state. This information is evaluated in categories such as stress, fatigue, and happiness.

[0341] Step 2:

[0342] The device sends emotional data, analyzed by the emotion engine, to the server. This allows the server to understand the user's emotional state in real time.

[0343] Step 3:

[0344] The server integrates emotional data along with the user's schedule, past task history, preferences, and feedback to update their profile. This profile contains detailed information about each user and forms the basis for optimal task assignment.

[0345] Step 4:

[0346] The server lists the household chores needed and optimizes task scheduling, taking into account the user's profile. This process includes adjustments based on the user's emotional state, such as prioritizing low-stress tasks based on emotional data.

[0347] Step 5:

[0348] Once the task schedule is determined, the server sends that information to the terminal. The terminal then prepares to notify the user of the task reminder according to this schedule.

[0349] Step 6:

[0350] The device displays a task reminder to the user at a specified time. For example, the notification might say, "You need to relax, so take a 20-minute walk."

[0351] Step 7:

[0352] Users can give voice commands to the device as needed. These commands can include requests to change or reschedule tasks.

[0353] Step 8:

[0354] The terminal interprets the voice commands from the user and sends the content to the server. Based on this, the server readjusts the task schedule.

[0355] Step 9:

[0356] The server sends the rescheduled schedule to the device, and the device updates the reminder based on the new information.

[0357] Step 10:

[0358] After completing a task, the user reports its progress on their device. This report includes the task's progress and their sense of accomplishment.

[0359] Step 11:

[0360] The device continuously monitors the user's emotional state and sends this information to the server. This allows the server to understand the user's long-term trends and incorporate them into future task assignments.

[0361] This series of processes is expected to enable household chore management that takes users' emotions into consideration, thereby improving harmony and efficiency within the home.

[0362] (Example 2)

[0363] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0364] In household task management, assigning tasks uniformly without considering the user's emotional state can increase user stress and workload. Furthermore, a lack of task assignments optimized for individual users leads to decreased overall efficiency and a decline in users' quality of life.

[0365] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0366] In this invention, the server includes analysis means for analyzing the user's emotional state, data means for collecting the user's plans, task progress, preferences, and evaluations, and assignment means for assigning tasks optimized for each individual user based on the collected data and emotional state. This enables flexible and efficient task management that takes the user's emotional state into account, and is expected to improve the quality of life.

[0367] "Analysis means" refers to a device or method that analyzes and quantifies a user's emotional state from voice, facial expressions, biometric information, etc.

[0368] "Data means" refers to a device or method for collecting, storing, and managing information such as a user's plans, task progress, preferences, and evaluations.

[0369] "Assignment means" refers to a device or method for determining and allocating tasks optimized for individual users based on collected data and emotional states.

[0370] "Notification means" refers to a device or method for sending information about an assigned task to the user's device and informing the user.

[0371] "Adjustment means" refers to a device or method for receiving voice instructions and changing or adjusting the content or schedule of assigned tasks.

[0372] An "update mechanism" is a device or method for updating a user's profile based on the completion status of tasks, thereby improving the accuracy of task scheduling for future tasks.

[0373] "Transmission means" refers to a device or method for transmitting user input received via a voice assistant to a data means.

[0374] This invention is a system that analyzes a user's emotional state and optimizes task management within the home. This system consists of multiple devices and programs, with the server, terminals, and users each playing their respective roles.

[0375] The device is equipped with an emotion recognition engine that acquires biometric information such as the user's voice, facial expressions, and heart rate from sensors. This data is analyzed in real time, and the user's emotional state, such as stress, fatigue, and happiness, is quantified. The emotion recognition engine utilizes commercially available facial recognition software and voice analysis software, for example.

[0376] The server receives emotional data provided by the terminal and stores it in a database. Furthermore, the server integrates this data with other information such as the user's schedule, past task history, preferences, and ratings. At this time, a generative AI model is used to assign optimal tasks based on the emotional state and preferences. The data processing performed by the server includes a database management system and predictive algorithms.

[0377] For example, if the device detects user B's stress level in the morning, the server will replace a heavy afternoon task, such as "heavy cleaning," with a lighter task like "organizing books," to alleviate the burden. This new schedule is sent to the device, and the device notifies the user.

[0378] After receiving a notification from their device, the user performs the task. Once the task is completed, they report the completion status via their device. The server receives these reports, updates the profile with new sentiment data, and improves the accuracy of future task scheduling.

[0379] This system enables flexible and efficient task management, reducing the workload within the home. It is expected to improve users' quality of life.

[0380] Example prompt: "Reschedule afternoon tasks based on the user's current emotional state."

[0381] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0382] Step 1:

[0383] The device acquires biometric information such as the user's voice, facial expressions, and heart rate from sensors. An emotion recognition engine analyzes this input data in real time, quantifying emotional data such as stress, fatigue, and happiness. This emotional data is then generated as output. Specifically, voice analysis software analyzes voice tone, and facial recognition software evaluates facial expressions.

[0384] Step 2:

[0385] The terminal sends the generated sentiment data to the server. The server receives the transmitted sentiment data and stores it in a database. The input sentiment data is integrated into the relevant user profile within the server. As output, the sentiment data is integrated with existing user data (schedule, history, ratings, etc.). This is where the database management system comes into play.

[0386] Step 3:

[0387] The server uses a generative AI model based on integrated data to generate optimal task schedules for individual users. Inputs include sentiment data and the entire user profile. Outputs include a task list optimized based on emotional state. This generative AI model uses a predictive algorithm to assign tasks.

[0388] Step 4:

[0389] The server sends the generated task schedule to the terminal. This becomes the input for the notification system, and the terminal notifies the user of the received schedule. The output is a task list displayed to the user. Specifically, the terminal uses alarms and pop-up notifications to inform the user.

[0390] Step 5:

[0391] The user receives notifications from their device, performs tasks, and reports their progress via the device upon completion. The input is the task progress information reported by the user. The output is the server receiving updated user data for the next time. Specific actions performed within this process include the user clicking a completion button.

[0392] Step 6:

[0393] The server receives a task completion report and dynamically updates the user profile based on the new sentiment data. Inputs include task completion status and sentiment feedback. Based on this, an updated profile is generated as output for use in future scheduling. Specifically, the data is then fed back into the generating AI model.

[0394] (Application Example 2)

[0395] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0396] In modern households, the management and adjustment of household tasks in accordance with users' emotions are often insufficient, creating a need for a system that can perform tasks efficiently and appropriately. Task management that does not consider users' emotional states can lead to stress and dissatisfaction, potentially lowering the quality of life within the home. The goal is to solve this problem by achieving flexible and appropriate task management that takes users' emotions into consideration, thereby improving the overall quality of life for the family.

[0397] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0398] In this invention, the server includes information processing means for collecting user plans, task progress, preferences, and evaluations; information processing means for assigning household tasks optimized for each individual user based on the collected data; and analysis means for recognizing the user's emotional state using an emotion analysis engine and dynamically adjusting task assignments using that information. This enables flexible task management that responds to the user's emotional state.

[0399] "User plans" refer to information that shows the activities and schedules that a user has planned for the future.

[0400] "Task progress" refers to status information that indicates the extent to which an assigned task has been completed.

[0401] "Preferences and ratings" refers to information that indicates a user's personal preferences and evaluations of past tasks.

[0402] "Information processing means" refers to a device or system that has the function of collecting and analyzing data and providing information necessary for task management.

[0403] "Display means" refers to devices or systems used to present information to users visually or audibly.

[0404] "Communication means" refers to technologies or systems for sending and receiving data between other devices or systems.

[0405] "Analysis means" refers to a device or system that has the function of analyzing data and extracting useful information.

[0406] A "mobile device" is a terminal or device that can provide information to users while being carried around.

[0407] An "emotion analysis engine" is a technology or system that analyzes a user's voice, facial expressions, and other biometric information to recognize their emotional state.

[0408] The system for realizing this invention flexibly manages household tasks based on the user's emotions and consists of several main components.

[0409] The server collects information on the user's plans, task progress, preferences, and ratings, and assigns household tasks optimized for each individual user. It can recognize the user's emotional state from their voice and facial expressions, and analyze this information using an emotion analysis engine. For example, if the server determines that the user is tired, it will prioritize assigning less demanding tasks.

[0410] The device serves to notify the user's mobile device of assigned tasks. Through voice assistants and display methods, it can inform the user of task schedules and allow for adjustments as needed. Specifically, it provides voice reminders at user-specified times, such as, "You have laundry scheduled for today, would you like to do it at a different time?"

[0411] Users report the progress of their tasks through the system interface. This allows the system to receive the necessary feedback to improve the accuracy of future task scheduling.

[0412] As an example of a prompt, the question "What household chores would you recommend when the user is not under heavy load?" is input to the generating AI model. This allows the system to obtain information to make appropriate task suggestions. This information is used for dynamic task assignment, helping to streamline household task management.

[0413] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0414] Step 1:

[0415] The server collects user plans, task progress, preferences, and evaluations. It uses the user's past scheduling data and feedback as input to build foundational data for optimal task allocation. This data is referenced in the subsequent task assignment process.

[0416] Step 2:

[0417] The device analyzes the user's voice and facial expressions through an emotion analysis engine to recognize their emotional state. The input is real-time collected audio and video data, which is then analyzed to generate an output representing the user's emotional state (e.g., fatigue, stress, happiness). This analysis result is then sent to a server.

[0418] Step 3:

[0419] The server assigns optimized household tasks based on collected emotional data. It uses emotional data and user profiles collected in the previous step as input. This dynamically generates task schedules, resulting in output task lists with varying execution orders and content.

[0420] Step 4:

[0421] The device notifies the user of the generated task schedule. The input is a task list sent from the server, which is then communicated to the user using a voice assistant or notification function. Specifically, notifications such as, "You seem tired today, so let's do the cleaning tomorrow?" are sent.

[0422] Step 5:

[0423] Users report the completion status of tasks via their terminal. The input consists of completion reports for tasks displayed on the terminal, and the results are sent to the server. The output is updated data including the task completion status.

[0424] Step 6:

[0425] The server updates the profile to improve scheduling accuracy for the next task based on user feedback and completion status. Inputs include completion reports and sentiment feedback, and the server outputs an improved profile to provide the optimal task schedule.

[0426] Through this series of steps, the system supports a comfortable living environment for the user.

[0427] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0428] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0429] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0430] [Third Embodiment]

[0431] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0432] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0433] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0434] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0435] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0436] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0437] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0438] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0439] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0440] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0441] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0442] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0443] This invention is a system for efficiently managing the division of household chores in dual-income households, aiming to optimally schedule tasks by exchanging information among a server, terminal, and user. The embodiments of this system are described below.

[0444] First, the server collects various information from the household members. This includes each member's schedule, history of past household tasks, preferences, and feedback. Based on this data, the server creates user profiles and plans for the efficient distribution of household tasks.

[0445] The server then uses an optimization algorithm to assign household tasks to each member. This algorithm takes into account task priorities and each user's available time to generate a manageable schedule. Finally, it notifies each user via their device of the assigned tasks, thereby promoting that household chores are completed according to plan.

[0446] Users receive notifications when tasks are assigned during their daily lives and begin taking action to complete them. Furthermore, if users wish to adjust tasks, they can give voice commands via their device. These voice commands are interpreted by the device and transmitted to the server. The server receives the voice commands, readjusts the schedule, and sends the new schedule to the device.

[0447] Once a task is completed, the user reports its progress on their device. The information reported from the device is sent to the server and used for scheduling future tasks. The server uses the feedback information to update the user profile and optimize the system for more accurate task assignment.

[0448] As a concrete example, suppose a household schedules are set up so that user A is responsible for preparing dinner on weekends, and user B is responsible for cleaning during the week. User A receives a reminder on their device to "prepare dinner on Saturday afternoon," and if that day is inconvenient, they can give a voice command to "change it to Sunday." Based on this command, the server updates the schedule and notifies user A of the new appointment.

[0449] In this way, the system aims to improve overall family harmony and quality of life by efficiently distributing household tasks and ensuring fairness in the burden of housework.

[0450] The following describes the processing flow.

[0451] Step 1:

[0452] The server collects and analyzes the user's schedule, past task history, preferences, and feedback. This creates a user profile that includes the tasks the user excels at, tasks they want to avoid, and their time constraints.

[0453] Step 2:

[0454] The server lists all necessary household tasks, including common chores like cooking, cleaning, laundry, and shopping. Each task is assigned a priority and a deadline.

[0455] Step 3:

[0456] The server uses an optimization algorithm to optimally distribute household tasks based on each user's profile. This takes into account each user's free time, the urgency of the tasks, and their individual strengths in task allocation.

[0457] Step 4:

[0458] The server sends the allocation results to the terminal. This prepares the terminal to notify the user of the household tasks assigned to it and their schedules.

[0459] Step 5:

[0460] The device displays a task reminder to the user at a specified time. For example, it might send a message saying, "Please prepare dinner at 6 PM today."

[0461] Step 6:

[0462] Users can give voice commands to their devices. For example, if they want to change the time of a task, they can say, "Change the time for preparing dinner to 7 PM."

[0463] Step 7:

[0464] The terminal interprets the voice command and sends the content to the server. The server then readjusts the schedule based on this information.

[0465] Step 8:

[0466] The server sends the updated schedule back to the terminal and sets up new reminders as needed.

[0467] Step 9:

[0468] Users report their progress using their device after completing a task. This might involve simple reports such as, "I've finished preparing dinner."

[0469] Step 10:

[0470] The terminal sends a report to the server, which then updates the user profile based on this information. This improves scheduling accuracy by providing useful information for future task assignments.

[0471] (Example 1)

[0472] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0473] In dual-income households, the division of household chores tends to be uneven, resulting in an excessive burden on certain members. Furthermore, a lack of flexibility to respond to daily schedules and unexpected changes can make time management difficult. The purpose of this invention is to solve these problems and realize efficient and fair management of household chores.

[0474] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0475] In this invention, the server includes an information processing device that collects users' schedules, work progress, preferences, and evaluations; an information processing device that assigns home-based tasks optimized for each individual user based on the collected information; and an information device that transmits notifications regarding the assigned tasks to the user's information device. This enables efficient and fair assignment of home-based tasks to each member, as well as flexible responses to schedule changes and feedback.

[0476] "Users" refers to individual household members who utilize a system designed to efficiently manage household tasks.

[0477] An "information processing device" refers to a computer system that has the function of assigning tasks based on data collected from users and updating records based on feedback.

[0478] "Information equipment" refers to devices that have the function of sending work notifications to users and receiving voice instructions, and includes smartphones and tablets.

[0479] "Work" refers to household chores and other tasks performed within the home, and signifies a unit of action assigned by the system.

[0480] "Notification" refers to information that information devices transmit to users to inform them of the start time of work or other important matters.

[0481] "Voice support function" refers to technology that allows users to give voice instructions to the system, and includes a function that analyzes voice input and converts the instructions into text.

[0482] This invention is a system for achieving efficient division and management of household tasks in dual-income households. This system consists of an information processing device (hereinafter referred to as a server), information devices (hereinafter referred to as terminals), and household members (hereinafter referred to as users).

[0483] The server collects various information from each member of the household. This information includes the user's schedule, past work history, work preferences, and feedback. The collected data is used to create optimized profiles for each user. A database management system (e.g., SQL database) is used for data processing to efficiently manage the information.

[0484] Next, the server uses a linear programming algorithm to plan the optimal distribution of household tasks based on the collected data. This plan takes into account task priorities and user availability to generate a reasonable schedule. This ensures that tasks are distributed to each member in a manageable manner.

[0485] The generated schedule is notified to each user via a device. The device is a common computing device such as a smartphone or tablet, which sends reminders to users using push notifications or voice assistants. The device also receives voice commands (e.g., using "voice assistance") and transmits instructions to the server.

[0486] Users initiate actions based on notifications they receive from their devices during their daily lives. If they wish to change their schedule, they can request adjustments via voice input. This allows for flexible responses tailored to the user's needs.

[0487] As a concrete example, a schedule is created in a household to efficiently divide the tasks of "preparing dinner" and "cleaning the house." If the user gives a voice command saying, "I want to change the time for preparing dinner from Saturday to Sunday," the server receives this command and readjusts the schedule. The new, adjusted schedule is then notified to the user again via the terminal.

[0488] An example of a prompt message is: "I would like to design a system to optimally manage the division of household chores in dual-income households. Please specify how the server, terminal, and user will cooperate, and what algorithms and technologies (e.g., optimization algorithms, speech recognition technology) will be used to efficiently distribute the work."

[0489] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0490] Step 1:

[0491] The server collects information such as the user's schedule, past work history, preferences, and ratings. This information is obtained from home calendar applications and task management tools. Input data includes the user's schedule and feedback, and the server uses this to create a user profile. Specific data processing involves converting the acquired schedule into a standardized format and saving it to a database. The output is a detailed profile for each user.

[0492] Step 2:

[0493] The server assigns home-based tasks based on collected user profiles. At this stage, a linear programming algorithm is used to generate an optimal schedule, considering task priorities and user availability. The inputs are user profiles and task lists, and the schedule is created through calculations based on these. The generated schedule is output, determining the tasks assigned to each user.

[0494] Step 3:

[0495] The terminal notifies the user of schedule information received from the server. Notifications are primarily sent via smartphone push notifications or reminder apps. The input is schedule data from the server, and based on this, the terminal sets reminders to inform the user of information such as the start time and duration of the task. The output is the schedule notification that has been confirmed by the user.

[0496] Step 4:

[0497] The user begins work based on the received notification. If a change to the schedule is needed, they send a voice command via the terminal. The input is the user's voice instruction, which the terminal converts to text using speech recognition technology. The converted text instruction is sent to the server. The output is a schedule change request.

[0498] Step 5:

[0499] The server receives a schedule change request from the user and re-optimizes the schedule. It recalculates based on the new conditions and outputs an adjusted result with minimal impact. The input data is the user's change request and the current schedule. The output is the adjusted new schedule.

[0500] Step 6:

[0501] Users report the completion of a task via their terminal. The terminal sends the completion data to the server, providing feedback information that will be used for future task assignments. The input is the task completion status, and based on this, the server reflects the feedback in the user profile, generating an updated profile as output.

[0502] (Application Example 1)

[0503] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0504] In dual-income families, efficiently managing and fairly dividing household chores can be challenging, often leading to an uneven distribution of time and effort. Furthermore, tracking the progress of chores and adjusting tasks as needed is a time-consuming process. Maintaining harmony within the household through intuitive voice-activated operation and feedback is also a challenge.

[0505] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0506] In this invention, the server includes an information processing device that collects user information and creates individual profiles; an information processing device that optimally assigns household chores based on the collected information and adjusts the assignment information; a communication device that transmits notifications of assigned household chores to an output device; an input processing device that processes voice input and makes changes to the tasks; an information processing device that collects the status of the work performed and reflects it in the next task assignment; and a mechanical device that supports physical work. This enables the efficient and fair distribution of household chores.

[0507] "User" refers to the individual person who manages and performs household chore tasks within the home.

[0508] An "information processing device" is a device that acquires and analyzes data and performs calculations to optimize the schedule of household chores.

[0509] A "communication device" is a device used to transmit task information output from an information processing device to the user's terminal.

[0510] An "input processing device" is a device that receives voice commands from a user, analyzes them, and performs further processing.

[0511] A "mechanical device" is a device that physically performs assigned household tasks and assists or automates household work.

[0512] This invention is a system for efficiently managing and performing household chores within the home, and consists of a server, terminals, and users. The main hardware necessary for carrying out the invention includes an information processing device, a communication device, an input processing device, and a mechanical device.

[0513] The server collects information from users to generate individual profiles. This involves using devices such as smartphones and tablets to obtain schedules and preferences from users through a database. The information processing unit then analyzes this data and assigns household chores optimized for each individual user. An optimization algorithm is used for this assignment.

[0514] The device is responsible for notifying the user of assigned household chores. Notifications are provided as voice and visual reminders to encourage actions within the home. The device also utilizes speech recognition software (e.g., Google Cloud Speech-to-Text API) to receive voice commands. The received voice commands are analyzed by an input processing unit, and the necessary processing is performed.

[0515] Users utilize a home assistant robot to manage the progress of assigned tasks and adjust them via voice as needed. The server updates the work plan based on this information and improves future task assignments based on the feedback.

[0516] A concrete example is a scenario where a user gives a voice command such as "Do this week's cleaning on Saturday," and the robot incorporates this into its regular cleaning schedule, automating the task. The following are examples of prompts used for the generated AI model:

[0517] "Design a feature that allows a home robot to create a cleaning schedule based on voice commands and notify users of the optimal time according to their own schedule."

[0518] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0519] Step 1:

[0520] The server collects information from each user within the home network, including schedules, preferences, and past task execution history. Input is data sent from users via their devices, and output is individual user profiles. To analyze this data, a database management system is used to organize the information and generate profiles.

[0521] Step 2:

[0522] The server uses an optimization algorithm to assign household chores based on collected user profile data. Inputs are user profiles and imported work tasks, while output is an individually optimized task schedule. Optimization techniques and scheduling algorithms are used for data processing.

[0523] Step 3:

[0524] The device receives schedules and notifies the user of household chore reminders. Inputs are assigned tasks from the server, and outputs are visual or audio reminders to the user. The device's notification functions and interface are used for notifications.

[0525] Step 4:

[0526] Users give voice commands and make change requests through their devices. Input is the user's voice commands, and output is converted speech-to-text data. Google Cloud Speech-to-Text API is used for speech recognition.

[0527] Step 5:

[0528] The server receives change requests from users and adjusts tasks accordingly. Input is text data converted from speech, and output is an updated task schedule. Natural language processing techniques and scheduling algorithms are used for data processing.

[0529] Step 6:

[0530] Users monitor task progress and report completion status via their terminal. Input is progress report data, and output is feedback information sent to the server. A dedicated user interface is used for reporting.

[0531] Step 7:

[0532] The server uses the received feedback information to update user profiles and utilize this information for future task assignments. The input is progress feedback data, and the output is updated profile information. Machine learning algorithms may be used for the updates.

[0533] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0534] This invention relates to a system that recognizes a user's emotional state and enables the scheduling of household tasks accordingly. This system consists of a server, a terminal, a user, and an emotion engine. The following describes its embodiments in detail.

[0535] First, the emotion engine is built into the device and analyzes the user's voice, facial expressions, and other biometric information in real time to recognize the user's emotional state. This emotional data indicates the user's stress, fatigue, and happiness levels, and is important information that can be used to assign tasks at home.

[0536] The server collects emotional data from the emotion engine, along with the user's schedule, past task history, preferences, and feedback. This data is integrated into a profile and used to assign household tasks optimized for the user. When assigning tasks, the user's emotional state is taken into consideration; for example, users who are highly stressed are assigned less burdensome tasks.

[0537] The server uses this information to generate an optimal household task schedule and sends it to the device. The device then sends reminders to the user based on this schedule, prompting them to complete tasks. This allows the user to perform tasks at the appropriate time according to their emotional state.

[0538] To give a specific example, if the emotion engine sends information to the server indicating that user A is tired one morning, the server will decide to postpone the demanding cleaning task scheduled for that afternoon until the next day and assign a lighter task instead. Based on this decision, the terminal will remind user A of the task change and notify them of the new schedule.

[0539] Once a task is completed, the user reports its progress. Later, the server dynamically updates the user's profile using emotional feedback provided by the emotion engine, improving scheduling accuracy for future tasks.

[0540] This system enables flexible and efficient task management tailored to the user's emotional state, which is expected to reduce the uneven distribution of household chores and improve the overall quality of life for the family.

[0541] The following describes the processing flow.

[0542] Step 1:

[0543] The device collects biometric information such as the user's voice, facial expressions, and heart rate. Based on this, an emotion engine analyzes the user's emotions and recognizes their current emotional state. This information is evaluated in categories such as stress, fatigue, and happiness.

[0544] Step 2:

[0545] The device sends emotional data, analyzed by the emotion engine, to the server. This allows the server to understand the user's emotional state in real time.

[0546] Step 3:

[0547] The server integrates emotional data along with the user's schedule, past task history, preferences, and feedback to update their profile. This profile contains detailed information about each user and forms the basis for optimal task assignment.

[0548] Step 4:

[0549] The server lists the household chores needed and optimizes task scheduling, taking into account the user's profile. This process includes adjustments based on the user's emotional state, such as prioritizing low-stress tasks based on emotional data.

[0550] Step 5:

[0551] Once the task schedule is determined, the server sends that information to the terminal. The terminal then prepares to notify the user of the task reminder according to this schedule.

[0552] Step 6:

[0553] The device displays a task reminder to the user at a specified time. For example, the notification might say, "You need to relax, so take a 20-minute walk."

[0554] Step 7:

[0555] Users can give voice commands to the device as needed. These commands can include requests to change or reschedule tasks.

[0556] Step 8:

[0557] The terminal interprets the voice commands from the user and sends the content to the server. Based on this, the server readjusts the task schedule.

[0558] Step 9:

[0559] The server sends the rescheduled schedule to the device, and the device updates the reminder based on the new information.

[0560] Step 10:

[0561] After completing a task, the user reports its progress on their device. This report includes the task's progress and their sense of accomplishment.

[0562] Step 11:

[0563] The device continuously monitors the user's emotional state and sends this information to the server. This allows the server to understand the user's long-term trends and incorporate them into future task assignments.

[0564] This series of processes is expected to enable household chore management that takes users' emotions into consideration, thereby improving harmony and efficiency within the home.

[0565] (Example 2)

[0566] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0567] In household task management, assigning tasks uniformly without considering the user's emotional state can increase user stress and workload. Furthermore, a lack of task assignments optimized for individual users leads to decreased overall efficiency and a decline in users' quality of life.

[0568] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0569] In this invention, the server includes analysis means for analyzing the user's emotional state, data means for collecting the user's plans, task progress, preferences, and evaluations, and assignment means for assigning tasks optimized for each individual user based on the collected data and emotional state. This enables flexible and efficient task management that takes the user's emotional state into account, and is expected to improve the quality of life.

[0570] "Analysis means" refers to a device or method that analyzes and quantifies a user's emotional state from voice, facial expressions, biometric information, etc.

[0571] "Data means" refers to a device or method for collecting, storing, and managing information such as a user's plans, task progress, preferences, and evaluations.

[0572] "Assignment means" refers to a device or method for determining and allocating tasks optimized for individual users based on collected data and emotional states.

[0573] "Notification means" refers to a device or method for sending information about an assigned task to the user's device and informing the user.

[0574] "Adjustment means" refers to a device or method for receiving voice instructions and changing or adjusting the content or schedule of assigned tasks.

[0575] An "update mechanism" is a device or method for updating a user's profile based on the completion status of tasks, thereby improving the accuracy of task scheduling for future tasks.

[0576] "Transmission means" refers to a device or method for transmitting user input received via a voice assistant to a data means.

[0577] This invention is a system that analyzes a user's emotional state and optimizes task management within the home. This system consists of multiple devices and programs, with the server, terminals, and users each playing their respective roles.

[0578] The device is equipped with an emotion recognition engine that acquires biometric information such as the user's voice, facial expressions, and heart rate from sensors. This data is analyzed in real time, and the user's emotional state, such as stress, fatigue, and happiness, is quantified. The emotion recognition engine utilizes commercially available facial recognition software and voice analysis software, for example.

[0579] The server receives emotional data provided by the terminal and stores it in a database. Furthermore, the server integrates this data with other information such as the user's schedule, past task history, preferences, and ratings. At this time, a generative AI model is used to assign optimal tasks based on the emotional state and preferences. The data processing performed by the server includes a database management system and predictive algorithms.

[0580] For example, if the device detects user B's stress level in the morning, the server will replace a heavy afternoon task, such as "heavy cleaning," with a lighter task like "organizing books," to alleviate the burden. This new schedule is sent to the device, and the device notifies the user.

[0581] After receiving a notification from their device, the user performs the task. Once the task is completed, they report the completion status via their device. The server receives these reports, updates the profile with new sentiment data, and improves the accuracy of future task scheduling.

[0582] This system enables flexible and efficient task management, reducing the workload within the home. It is expected to improve users' quality of life.

[0583] Example prompt: "Reschedule afternoon tasks based on the user's current emotional state."

[0584] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0585] Step 1:

[0586] The device acquires biometric information such as the user's voice, facial expressions, and heart rate from sensors. An emotion recognition engine analyzes this input data in real time, quantifying emotional data such as stress, fatigue, and happiness. This emotional data is then generated as output. Specifically, voice analysis software analyzes voice tone, and facial recognition software evaluates facial expressions.

[0587] Step 2:

[0588] The terminal sends the generated sentiment data to the server. The server receives the transmitted sentiment data and stores it in a database. The input sentiment data is integrated into the relevant user profile within the server. As output, the sentiment data is integrated with existing user data (schedule, history, ratings, etc.). This is where the database management system comes into play.

[0589] Step 3:

[0590] The server uses a generative AI model based on integrated data to generate optimal task schedules for individual users. Inputs include sentiment data and the entire user profile. Outputs include a task list optimized based on emotional state. This generative AI model uses a predictive algorithm to assign tasks.

[0591] Step 4:

[0592] The server sends the generated task schedule to the terminal. This becomes the input for the notification system, and the terminal notifies the user of the received schedule. The output is a task list displayed to the user. Specifically, the terminal uses alarms and pop-up notifications to inform the user.

[0593] Step 5:

[0594] The user receives notifications from their device, performs tasks, and reports their progress via the device upon completion. The input is the task progress information reported by the user. The output is the server receiving updated user data for the next time. Specific actions performed within this process include the user clicking a completion button.

[0595] Step 6:

[0596] The server receives a task completion report and dynamically updates the user profile based on the new sentiment data. Inputs include task completion status and sentiment feedback. Based on this, an updated profile is generated as output for use in future scheduling. Specifically, the data is then fed back into the generating AI model.

[0597] (Application Example 2)

[0598] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0599] In modern households, the management and adjustment of household tasks in accordance with users' emotions are often insufficient, creating a need for a system that can perform tasks efficiently and appropriately. Task management that does not consider users' emotional states can lead to stress and dissatisfaction, potentially lowering the quality of life within the home. The goal is to solve this problem by achieving flexible and appropriate task management that takes users' emotions into consideration, thereby improving the overall quality of life for the family.

[0600] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0601] In this invention, the server includes information processing means for collecting user plans, task progress, preferences, and evaluations; information processing means for assigning household tasks optimized for each individual user based on the collected data; and analysis means for recognizing the user's emotional state using an emotion analysis engine and dynamically adjusting task assignments using that information. This enables flexible task management that responds to the user's emotional state.

[0602] "User plans" refer to information that shows the activities and schedules that a user has planned for the future.

[0603] "Task progress" refers to status information that indicates the extent to which an assigned task has been completed.

[0604] "Preferences and ratings" refers to information that indicates a user's personal preferences and evaluations of past tasks.

[0605] "Information processing means" refers to a device or system that has the function of collecting and analyzing data and providing information necessary for task management.

[0606] "Display means" refers to devices or systems used to present information to users visually or audibly.

[0607] "Communication means" refers to technologies or systems for sending and receiving data between other devices or systems.

[0608] "Analysis means" refers to a device or system that has the function of analyzing data and extracting useful information.

[0609] A "mobile device" is a terminal or device that can provide information to users while being carried around.

[0610] An "emotion analysis engine" is a technology or system that analyzes a user's voice, facial expressions, and other biometric information to recognize their emotional state.

[0611] The system for realizing this invention flexibly manages household tasks based on the user's emotions and consists of several main components.

[0612] The server collects information on the user's plans, task progress, preferences, and ratings, and assigns household tasks optimized for each individual user. It can recognize the user's emotional state from their voice and facial expressions, and analyze this information using an emotion analysis engine. For example, if the server determines that the user is tired, it will prioritize assigning less demanding tasks.

[0613] The device serves to notify the user's mobile device of assigned tasks. Through voice assistants and display methods, it can inform the user of task schedules and allow for adjustments as needed. Specifically, it provides voice reminders at user-specified times, such as, "You have laundry scheduled for today, would you like to do it at a different time?"

[0614] Users report the progress of their tasks through the system interface. This allows the system to receive the necessary feedback to improve the accuracy of future task scheduling.

[0615] As an example of a prompt, the question "What household chores would you recommend when the user is not under heavy load?" is input to the generating AI model. This allows the system to obtain information to make appropriate task suggestions. This information is used for dynamic task assignment, helping to streamline household task management.

[0616] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0617] Step 1:

[0618] The server collects user plans, task progress, preferences, and evaluations. It uses the user's past scheduling data and feedback as input to build foundational data for optimal task allocation. This data is referenced in the subsequent task assignment process.

[0619] Step 2:

[0620] The device analyzes the user's voice and facial expressions through an emotion analysis engine to recognize their emotional state. The input is real-time collected audio and video data, which is then analyzed to generate an output representing the user's emotional state (e.g., fatigue, stress, happiness). This analysis result is then sent to a server.

[0621] Step 3:

[0622] The server assigns optimized household tasks based on collected emotional data. It uses emotional data and user profiles collected in the previous step as input. This dynamically generates task schedules, resulting in output task lists with varying execution orders and content.

[0623] Step 4:

[0624] The device notifies the user of the generated task schedule. The input is a task list sent from the server, which is then communicated to the user using a voice assistant or notification function. Specifically, notifications such as, "You seem tired today, so let's do the cleaning tomorrow?" are sent.

[0625] Step 5:

[0626] Users report the completion status of tasks via their terminal. The input consists of completion reports for tasks displayed on the terminal, and the results are sent to the server. The output is updated data including the task completion status.

[0627] Step 6:

[0628] The server updates the profile to improve scheduling accuracy for the next task based on user feedback and completion status. Inputs include completion reports and sentiment feedback, and the server outputs an improved profile to provide the optimal task schedule.

[0629] Through this series of steps, the system supports a comfortable living environment for the user.

[0630] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0631] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0632] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0633] [Fourth Embodiment]

[0634] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0635] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0636] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0637] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0638] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0639] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0640] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0641] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0642] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0643] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0644] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0645] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0646] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0647] This invention is a system for efficiently managing the division of household chores in dual-income households, aiming to optimally schedule tasks by exchanging information among a server, terminal, and user. The embodiments of this system are described below.

[0648] First, the server collects various information from the household members. This includes each member's schedule, history of past household tasks, preferences, and feedback. Based on this data, the server creates user profiles and plans for the efficient distribution of household tasks.

[0649] The server then uses an optimization algorithm to assign household tasks to each member. This algorithm takes into account task priorities and each user's available time to generate a manageable schedule. Finally, it notifies each user via their device of the assigned tasks, thereby promoting that household chores are completed according to plan.

[0650] Users receive notifications when tasks are assigned during their daily lives and begin taking action to complete them. Furthermore, if users wish to adjust tasks, they can give voice commands via their device. These voice commands are interpreted by the device and transmitted to the server. The server receives the voice commands, readjusts the schedule, and sends the new schedule to the device.

[0651] Once a task is completed, the user reports its progress on their device. The information reported from the device is sent to the server and used for scheduling future tasks. The server uses the feedback information to update the user profile and optimize the system for more accurate task assignment.

[0652] As a concrete example, suppose a household schedules are set up so that user A is responsible for preparing dinner on weekends, and user B is responsible for cleaning during the week. User A receives a reminder on their device to "prepare dinner on Saturday afternoon," and if that day is inconvenient, they can give a voice command to "change it to Sunday." Based on this command, the server updates the schedule and notifies user A of the new appointment.

[0653] In this way, the system aims to improve overall family harmony and quality of life by efficiently distributing household tasks and ensuring fairness in the burden of housework.

[0654] The following describes the processing flow.

[0655] Step 1:

[0656] The server collects and analyzes the user's schedule, past task history, preferences, and feedback. This creates a user profile that includes the tasks the user excels at, tasks they want to avoid, and their time constraints.

[0657] Step 2:

[0658] The server lists all necessary household tasks, including common chores like cooking, cleaning, laundry, and shopping. Each task is assigned a priority and a deadline.

[0659] Step 3:

[0660] The server uses an optimization algorithm to optimally distribute household tasks based on each user's profile. This takes into account each user's free time, the urgency of the tasks, and their individual strengths in task allocation.

[0661] Step 4:

[0662] The server sends the allocation results to the terminal. This prepares the terminal to notify the user of the household tasks assigned to it and their schedules.

[0663] Step 5:

[0664] The device displays a task reminder to the user at a specified time. For example, it might send a message saying, "Please prepare dinner at 6 PM today."

[0665] Step 6:

[0666] Users can give voice commands to their devices. For example, if they want to change the time of a task, they can say, "Change the time for preparing dinner to 7 PM."

[0667] Step 7:

[0668] The terminal interprets the voice command and sends the content to the server. The server then readjusts the schedule based on this information.

[0669] Step 8:

[0670] The server sends the updated schedule back to the terminal and sets up new reminders as needed.

[0671] Step 9:

[0672] Users report their progress using their device after completing a task. This might involve simple reports such as, "I've finished preparing dinner."

[0673] Step 10:

[0674] The terminal sends a report to the server, which then updates the user profile based on this information. This improves scheduling accuracy by providing useful information for future task assignments.

[0675] (Example 1)

[0676] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0677] In dual-income households, the division of household chores tends to be uneven, resulting in an excessive burden on certain members. Furthermore, a lack of flexibility to respond to daily schedules and unexpected changes can make time management difficult. The purpose of this invention is to solve these problems and realize efficient and fair management of household chores.

[0678] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0679] In this invention, the server includes an information processing device that collects users' schedules, work progress, preferences, and evaluations; an information processing device that assigns home-based tasks optimized for each individual user based on the collected information; and an information device that transmits notifications regarding the assigned tasks to the user's information device. This enables efficient and fair assignment of home-based tasks to each member, as well as flexible responses to schedule changes and feedback.

[0680] "Users" refers to individual household members who utilize a system designed to efficiently manage household tasks.

[0681] An "information processing device" refers to a computer system that has the function of assigning tasks based on data collected from users and updating records based on feedback.

[0682] "Information equipment" refers to devices that have the function of sending work notifications to users and receiving voice instructions, and includes smartphones and tablets.

[0683] "Work" refers to household chores and other tasks performed within the home, and signifies a unit of action assigned by the system.

[0684] "Notification" refers to information that information devices transmit to users to inform them of the start time of work or other important matters.

[0685] "Voice support function" refers to technology that allows users to give voice instructions to the system, and includes a function that analyzes voice input and converts the instructions into text.

[0686] This invention is a system for achieving efficient division and management of household tasks in dual-income households. This system consists of an information processing device (hereinafter referred to as a server), information devices (hereinafter referred to as terminals), and household members (hereinafter referred to as users).

[0687] The server collects various information from each member of the household. This information includes the user's schedule, past work history, work preferences, and feedback. The collected data is used to create optimized profiles for each user. A database management system (e.g., SQL database) is used for data processing to efficiently manage the information.

[0688] Next, the server uses a linear programming algorithm to plan the optimal distribution of household tasks based on the collected data. This plan takes into account task priorities and user availability to generate a reasonable schedule. This ensures that tasks are distributed to each member in a manageable manner.

[0689] The generated schedule is notified to each user via a device. The device is a common computing device such as a smartphone or tablet, which sends reminders to users using push notifications or voice assistants. The device also receives voice commands (e.g., using "voice assistance") and transmits instructions to the server.

[0690] Users initiate actions based on notifications they receive from their devices during their daily lives. If they wish to change their schedule, they can request adjustments via voice input. This allows for flexible responses tailored to the user's needs.

[0691] As a concrete example, a schedule is created in a household to efficiently divide the tasks of "preparing dinner" and "cleaning the house." If the user gives a voice command saying, "I want to change the time for preparing dinner from Saturday to Sunday," the server receives this command and readjusts the schedule. The new, adjusted schedule is then notified to the user again via the terminal.

[0692] An example of a prompt message is: "I would like to design a system to optimally manage the division of household chores in dual-income households. Please specify how the server, terminal, and user will cooperate, and what algorithms and technologies (e.g., optimization algorithms, speech recognition technology) will be used to efficiently distribute the work."

[0693] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0694] Step 1:

[0695] The server collects information such as the user's schedule, past work history, preferences, and ratings. This information is obtained from home calendar applications and task management tools. Input data includes the user's schedule and feedback, and the server uses this to create a user profile. Specific data processing involves converting the acquired schedule into a standardized format and saving it to a database. The output is a detailed profile for each user.

[0696] Step 2:

[0697] The server assigns home-based tasks based on collected user profiles. At this stage, a linear programming algorithm is used to generate an optimal schedule, considering task priorities and user availability. The inputs are user profiles and task lists, and the schedule is created through calculations based on these. The generated schedule is output, determining the tasks assigned to each user.

[0698] Step 3:

[0699] The terminal notifies the user of schedule information received from the server. Notifications are primarily sent via smartphone push notifications or reminder apps. The input is schedule data from the server, and based on this, the terminal sets reminders to inform the user of information such as the start time and duration of the task. The output is the schedule notification that has been confirmed by the user.

[0700] Step 4:

[0701] The user begins work based on the received notification. If a change to the schedule is needed, they send a voice command via the terminal. The input is the user's voice instruction, which the terminal converts to text using speech recognition technology. The converted text instruction is sent to the server. The output is a schedule change request.

[0702] Step 5:

[0703] The server receives a schedule change request from the user and re-optimizes the schedule. It recalculates based on the new conditions and outputs an adjusted result with minimal impact. The input data is the user's change request and the current schedule. The output is the adjusted new schedule.

[0704] Step 6:

[0705] Users report the completion of a task via their terminal. The terminal sends the completion data to the server, providing feedback information that will be used for future task assignments. The input is the task completion status, and based on this, the server reflects the feedback in the user profile, generating an updated profile as output.

[0706] (Application Example 1)

[0707] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0708] In dual-income families, efficiently managing and fairly dividing household chores can be challenging, often leading to an uneven distribution of time and effort. Furthermore, tracking the progress of chores and adjusting tasks as needed is a time-consuming process. Maintaining harmony within the household through intuitive voice-activated operation and feedback is also a challenge.

[0709] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0710] In this invention, the server includes an information processing device that collects user information and creates individual profiles; an information processing device that optimally assigns household chores based on the collected information and adjusts the assignment information; a communication device that transmits notifications of assigned household chores to an output device; an input processing device that processes voice input and makes changes to the tasks; an information processing device that collects the status of the work performed and reflects it in the next task assignment; and a mechanical device that supports physical work. This enables the efficient and fair distribution of household chores.

[0711] "User" refers to the individual person who manages and performs household chore tasks within the home.

[0712] An "information processing device" is a device that acquires and analyzes data and performs calculations to optimize the schedule of household chores.

[0713] A "communication device" is a device used to transmit task information output from an information processing device to the user's terminal.

[0714] An "input processing device" is a device that receives voice commands from a user, analyzes them, and performs further processing.

[0715] A "mechanical device" is a device that physically performs assigned household tasks and assists or automates household work.

[0716] This invention is a system for efficiently managing and performing household chores within the home, and consists of a server, terminals, and users. The main hardware necessary for carrying out the invention includes an information processing device, a communication device, an input processing device, and a mechanical device.

[0717] The server collects information from users to generate individual profiles. This involves using devices such as smartphones and tablets to obtain schedules and preferences from users through a database. The information processing unit then analyzes this data and assigns household chores optimized for each individual user. An optimization algorithm is used for this assignment.

[0718] The device is responsible for notifying the user of assigned household chores. Notifications are provided as voice and visual reminders to encourage actions within the home. The device also utilizes speech recognition software (e.g., Google Cloud Speech-to-Text API) to receive voice commands. The received voice commands are analyzed by an input processing unit, and the necessary processing is performed.

[0719] Users utilize a home assistant robot to manage the progress of assigned tasks and adjust them via voice as needed. The server updates the work plan based on this information and improves future task assignments based on the feedback.

[0720] A concrete example is a scenario where a user gives a voice command such as "Do this week's cleaning on Saturday," and the robot incorporates this into its regular cleaning schedule, automating the task. The following are examples of prompts used for the generated AI model:

[0721] "Design a feature that allows a home robot to create a cleaning schedule based on voice commands and notify users of the optimal time according to their own schedule."

[0722] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0723] Step 1:

[0724] The server collects information from each user within the home network, including schedules, preferences, and past task execution history. Input is data sent from users via their devices, and output is individual user profiles. To analyze this data, a database management system is used to organize the information and generate profiles.

[0725] Step 2:

[0726] The server uses an optimization algorithm to assign household chores based on collected user profile data. Inputs are user profiles and imported work tasks, while output is an individually optimized task schedule. Optimization techniques and scheduling algorithms are used for data processing.

[0727] Step 3:

[0728] The device receives schedules and notifies the user of household chore reminders. Inputs are assigned tasks from the server, and outputs are visual or audio reminders to the user. The device's notification functions and interface are used for notifications.

[0729] Step 4:

[0730] Users give voice commands and make change requests through their devices. Input is the user's voice commands, and output is converted speech-to-text data. Google Cloud Speech-to-Text API is used for speech recognition.

[0731] Step 5:

[0732] The server receives change requests from users and adjusts tasks accordingly. Input is text data converted from speech, and output is an updated task schedule. Natural language processing techniques and scheduling algorithms are used for data processing.

[0733] Step 6:

[0734] Users monitor task progress and report completion status via their terminal. Input is progress report data, and output is feedback information sent to the server. A dedicated user interface is used for reporting.

[0735] Step 7:

[0736] The server uses the received feedback information to update user profiles and utilize this information for future task assignments. The input is progress feedback data, and the output is updated profile information. Machine learning algorithms may be used for the updates.

[0737] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0738] This invention relates to a system that recognizes a user's emotional state and enables the scheduling of household tasks accordingly. This system consists of a server, a terminal, a user, and an emotion engine. The following describes its embodiments in detail.

[0739] First, the emotion engine is built into the device and analyzes the user's voice, facial expressions, and other biometric information in real time to recognize the user's emotional state. This emotional data indicates the user's stress, fatigue, and happiness levels, and is important information that can be used to assign tasks at home.

[0740] The server collects emotional data from the emotion engine, along with the user's schedule, past task history, preferences, and feedback. This data is integrated into a profile and used to assign household tasks optimized for the user. When assigning tasks, the user's emotional state is taken into consideration; for example, users who are highly stressed are assigned less burdensome tasks.

[0741] The server uses this information to generate an optimal household task schedule and sends it to the device. The device then sends reminders to the user based on this schedule, prompting them to complete tasks. This allows the user to perform tasks at the appropriate time according to their emotional state.

[0742] To give a specific example, if the emotion engine sends information to the server indicating that user A is tired one morning, the server will decide to postpone the demanding cleaning task scheduled for that afternoon until the next day and assign a lighter task instead. Based on this decision, the terminal will remind user A of the task change and notify them of the new schedule.

[0743] Once a task is completed, the user reports its progress. Later, the server dynamically updates the user's profile using emotional feedback provided by the emotion engine, improving scheduling accuracy for future tasks.

[0744] This system enables flexible and efficient task management tailored to the user's emotional state, which is expected to reduce the uneven distribution of household chores and improve the overall quality of life for the family.

[0745] The following describes the processing flow.

[0746] Step 1:

[0747] The device collects biometric information such as the user's voice, facial expressions, and heart rate. Based on this, an emotion engine analyzes the user's emotions and recognizes their current emotional state. This information is evaluated in categories such as stress, fatigue, and happiness.

[0748] Step 2:

[0749] The device sends emotional data, analyzed by the emotion engine, to the server. This allows the server to understand the user's emotional state in real time.

[0750] Step 3:

[0751] The server integrates emotional data along with the user's schedule, past task history, preferences, and feedback to update their profile. This profile contains detailed information about each user and forms the basis for optimal task assignment.

[0752] Step 4:

[0753] The server lists the household chores needed and optimizes task scheduling, taking into account the user's profile. This process includes adjustments based on the user's emotional state, such as prioritizing low-stress tasks based on emotional data.

[0754] Step 5:

[0755] Once the task schedule is determined, the server sends that information to the terminal. The terminal then prepares to notify the user of the task reminder according to this schedule.

[0756] Step 6:

[0757] The device displays a task reminder to the user at a specified time. For example, the notification might say, "You need to relax, so take a 20-minute walk."

[0758] Step 7:

[0759] Users can give voice commands to the device as needed. These commands can include requests to change or reschedule tasks.

[0760] Step 8:

[0761] The terminal interprets the voice commands from the user and sends the content to the server. Based on this, the server readjusts the task schedule.

[0762] Step 9:

[0763] The server sends the rescheduled schedule to the device, and the device updates the reminder based on the new information.

[0764] Step 10:

[0765] After completing a task, the user reports its progress on their device. This report includes the task's progress and their sense of accomplishment.

[0766] Step 11:

[0767] The device continuously monitors the user's emotional state and sends this information to the server. This allows the server to understand the user's long-term trends and incorporate them into future task assignments.

[0768] This series of processes is expected to enable household chore management that takes users' emotions into consideration, thereby improving harmony and efficiency within the home.

[0769] (Example 2)

[0770] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0771] In household task management, assigning tasks uniformly without considering the user's emotional state can increase user stress and workload. Furthermore, a lack of task assignments optimized for individual users leads to decreased overall efficiency and a decline in users' quality of life.

[0772] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0773] In this invention, the server includes analysis means for analyzing the user's emotional state, data means for collecting the user's plans, task progress, preferences, and evaluations, and assignment means for assigning tasks optimized for each individual user based on the collected data and emotional state. This enables flexible and efficient task management that takes the user's emotional state into account, and is expected to improve the quality of life.

[0774] "Analysis means" refers to a device or method that analyzes and quantifies a user's emotional state from voice, facial expressions, biometric information, etc.

[0775] "Data means" refers to a device or method for collecting, storing, and managing information such as a user's plans, task progress, preferences, and evaluations.

[0776] "Assignment means" refers to a device or method for determining and allocating tasks optimized for individual users based on collected data and emotional states.

[0777] "Notification means" refers to a device or method for sending information about an assigned task to the user's device and informing the user.

[0778] "Adjustment means" refers to a device or method for receiving voice instructions and changing or adjusting the content or schedule of assigned tasks.

[0779] An "update mechanism" is a device or method for updating a user's profile based on the completion status of tasks, thereby improving the accuracy of task scheduling for future tasks.

[0780] "Transmission means" refers to a device or method for transmitting user input received via a voice assistant to a data means.

[0781] This invention is a system that analyzes a user's emotional state and optimizes task management within the home. This system consists of multiple devices and programs, with the server, terminals, and users each playing their respective roles.

[0782] The device is equipped with an emotion recognition engine that acquires biometric information such as the user's voice, facial expressions, and heart rate from sensors. This data is analyzed in real time, and the user's emotional state, such as stress, fatigue, and happiness, is quantified. The emotion recognition engine utilizes commercially available facial recognition software and voice analysis software, for example.

[0783] The server receives emotional data provided by the terminal and stores it in a database. Furthermore, the server integrates this data with other information such as the user's schedule, past task history, preferences, and ratings. At this time, a generative AI model is used to assign optimal tasks based on the emotional state and preferences. The data processing performed by the server includes a database management system and predictive algorithms.

[0784] For example, if the device detects user B's stress level in the morning, the server will replace a heavy afternoon task, such as "heavy cleaning," with a lighter task like "organizing books," to alleviate the burden. This new schedule is sent to the device, and the device notifies the user.

[0785] After receiving a notification from their device, the user performs the task. Once the task is completed, they report the completion status via their device. The server receives these reports, updates the profile with new sentiment data, and improves the accuracy of future task scheduling.

[0786] This system enables flexible and efficient task management, reducing the workload within the home. It is expected to improve users' quality of life.

[0787] Example prompt: "Reschedule afternoon tasks based on the user's current emotional state."

[0788] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0789] Step 1:

[0790] The device acquires biometric information such as the user's voice, facial expressions, and heart rate from sensors. An emotion recognition engine analyzes this input data in real time, quantifying emotional data such as stress, fatigue, and happiness. This emotional data is then generated as output. Specifically, voice analysis software analyzes voice tone, and facial recognition software evaluates facial expressions.

[0791] Step 2:

[0792] The terminal sends the generated sentiment data to the server. The server receives the transmitted sentiment data and stores it in a database. The input sentiment data is integrated into the relevant user profile within the server. As output, the sentiment data is integrated with existing user data (schedule, history, ratings, etc.). This is where the database management system comes into play.

[0793] Step 3:

[0794] The server uses a generative AI model based on integrated data to generate optimal task schedules for individual users. Inputs include sentiment data and the entire user profile. Outputs include a task list optimized based on emotional state. This generative AI model uses a predictive algorithm to assign tasks.

[0795] Step 4:

[0796] The server sends the generated task schedule to the terminal. This becomes the input for the notification system, and the terminal notifies the user of the received schedule. The output is a task list displayed to the user. Specifically, the terminal uses alarms and pop-up notifications to inform the user.

[0797] Step 5:

[0798] The user receives notifications from their device, performs tasks, and reports their progress via the device upon completion. The input is the task progress information reported by the user. The output is the server receiving updated user data for the next time. Specific actions performed within this process include the user clicking a completion button.

[0799] Step 6:

[0800] The server receives a task completion report and dynamically updates the user profile based on the new sentiment data. Inputs include task completion status and sentiment feedback. Based on this, an updated profile is generated as output for use in future scheduling. Specifically, the data is then fed back into the generating AI model.

[0801] (Application Example 2)

[0802] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0803] In modern households, the management and adjustment of household tasks in accordance with users' emotions are often insufficient, creating a need for a system that can perform tasks efficiently and appropriately. Task management that does not consider users' emotional states can lead to stress and dissatisfaction, potentially lowering the quality of life within the home. The goal is to solve this problem by achieving flexible and appropriate task management that takes users' emotions into consideration, thereby improving the overall quality of life for the family.

[0804] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0805] In this invention, the server includes information processing means for collecting user plans, task progress, preferences, and evaluations; information processing means for assigning household tasks optimized for each individual user based on the collected data; and analysis means for recognizing the user's emotional state using an emotion analysis engine and dynamically adjusting task assignments using that information. This enables flexible task management that responds to the user's emotional state.

[0806] "User plans" refer to information that shows the activities and schedules that a user has planned for the future.

[0807] "Task progress" refers to status information that indicates the extent to which an assigned task has been completed.

[0808] "Preferences and ratings" refers to information that indicates a user's personal preferences and evaluations of past tasks.

[0809] "Information processing means" refers to a device or system that has the function of collecting and analyzing data and providing information necessary for task management.

[0810] "Display means" refers to devices or systems used to present information to users visually or audibly.

[0811] "Communication means" refers to technologies or systems for sending and receiving data between other devices or systems.

[0812] "Analysis means" refers to a device or system that has the function of analyzing data and extracting useful information.

[0813] A "mobile device" is a terminal or device that can provide information to users while being carried around.

[0814] An "emotion analysis engine" is a technology or system that analyzes a user's voice, facial expressions, and other biometric information to recognize their emotional state.

[0815] The system for realizing this invention flexibly manages household tasks based on the user's emotions and consists of several main components.

[0816] The server collects information on the user's plans, task progress, preferences, and ratings, and assigns household tasks optimized for each individual user. It can recognize the user's emotional state from their voice and facial expressions, and analyze this information using an emotion analysis engine. For example, if the server determines that the user is tired, it will prioritize assigning less demanding tasks.

[0817] The device serves to notify the user's mobile device of assigned tasks. Through voice assistants and display methods, it can inform the user of task schedules and allow for adjustments as needed. Specifically, it provides voice reminders at user-specified times, such as, "You have laundry scheduled for today, would you like to do it at a different time?"

[0818] Users report the progress of their tasks through the system interface. This allows the system to receive the necessary feedback to improve the accuracy of future task scheduling.

[0819] As an example of a prompt, the question "What household chores would you recommend when the user is not under heavy load?" is input to the generating AI model. This allows the system to obtain information to make appropriate task suggestions. This information is used for dynamic task assignment, helping to streamline household task management.

[0820] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0821] Step 1:

[0822] The server collects user plans, task progress, preferences, and evaluations. It uses the user's past scheduling data and feedback as input to build foundational data for optimal task allocation. This data is referenced in the subsequent task assignment process.

[0823] Step 2:

[0824] The device analyzes the user's voice and facial expressions through an emotion analysis engine to recognize their emotional state. The input is real-time collected audio and video data, which is then analyzed to generate an output representing the user's emotional state (e.g., fatigue, stress, happiness). This analysis result is then sent to a server.

[0825] Step 3:

[0826] The server assigns optimized household tasks based on collected emotional data. It uses emotional data and user profiles collected in the previous step as input. This dynamically generates task schedules, resulting in output task lists with varying execution orders and content.

[0827] Step 4:

[0828] The device notifies the user of the generated task schedule. The input is a task list sent from the server, which is then communicated to the user using a voice assistant or notification function. Specifically, notifications such as, "You seem tired today, so let's do the cleaning tomorrow?" are sent.

[0829] Step 5:

[0830] Users report the completion status of tasks via their terminal. The input consists of completion reports for tasks displayed on the terminal, and the results are sent to the server. The output is updated data including the task completion status.

[0831] Step 6:

[0832] The server updates the profile to improve scheduling accuracy for the next task based on user feedback and completion status. Inputs include completion reports and sentiment feedback, and the server outputs an improved profile to provide the optimal task schedule.

[0833] Through this series of steps, the system supports a comfortable living environment for the user.

[0834] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0835] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0836] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0837] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0838] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0839] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0840] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0841] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0842] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0843] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0844] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0845] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0846] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0847] 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.

[0848] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0849] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0850] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0851] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0852] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0853] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0854] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0855] The following is further disclosed regarding the embodiments described above.

[0856] (Claim 1)

[0857] A server mechanism for collecting user plans, task progress, preferences, and ratings,

[0858] A server means that assigns household chore tasks optimized for individual users based on collected data,

[0859] A terminal means that notifies the user's terminal of a reminder for an assigned task,

[0860] A terminal device that receives voice instructions and adjusts tasks,

[0861] A server mechanism to collect task completion status and reflect it in the next scheduling,

[0862] A system that includes this.

[0863] (Claim 2)

[0864] The system according to claim 1, wherein the server means dynamically updates the profile based on user feedback to improve the accuracy of the schedule.

[0865] (Claim 3)

[0866] The system according to claim 1, wherein the terminal means receives user input via a voice assistant and transmits it to the server means.

[0867] "Example 1"

[0868] (Claim 1)

[0869] An information processing device that collects users' schedules, work progress, preferences, and evaluations,

[0870] An information processing device that assigns home tasks optimized for each individual user based on the collected information,

[0871] Information equipment that sends notifications to the user's information equipment regarding assigned tasks,

[0872] Information equipment that receives voice instructions and adjusts work accordingly,

[0873] An information processing device that collects the completion status of tasks and reflects it in the next plan,

[0874] A system that includes this.

[0875] (Claim 2)

[0876] The system according to claim 1, wherein the information processing device dynamically updates records based on user feedback to improve the accuracy of the plan.

[0877] (Claim 3)

[0878] The system according to claim 1, wherein the information device receives user input via a voice support function and transmits it to an information processing device.

[0879] "Application Example 1"

[0880] (Claim 1)

[0881] An information processing device that collects user information and creates individual profiles,

[0882] An information processing device that optimally assigns household chores based on collected information and adjusts the assignment information,

[0883] A communication device that transmits notifications of assigned household chores to an output device,

[0884] An input processing device that processes voice input and makes changes to business processes,

[0885] An information processing device that collects information on the status of work completion and reflects it in the next work assignment,

[0886] A system including mechanical devices that assist in physical work.

[0887] (Claim 2)

[0888] The system according to claim 1, wherein the information processing device dynamically updates the profile based on user evaluations to improve the accuracy of the work plan.

[0889] (Claim 3)

[0890] The system according to claim 1, wherein the input processing device receives user instructions via a voice assistant and transmits them to an information processing device.

[0891] "Example 2 of combining an emotion engine"

[0892] (Claim 1)

[0893] An analytical method for analyzing the emotional state of users,

[0894] Data collection methods for users' plans, task progress, preferences, and evaluations,

[0895] An assignment means that assigns tasks optimized for individual users based on collected data and emotional states,

[0896] A notification method that notifies the user's device of a reminder for assigned tasks,

[0897] A means of receiving voice instructions and adjusting tasks,

[0898] A means of collecting task completion status and reflecting it in the next scheduling,

[0899] A system that includes this.

[0900] (Claim 2)

[0901] The system according to claim 1, comprising an update means for dynamically updating profiles and improving the accuracy of schedules.

[0902] (Claim 3)

[0903] The system according to claim 1, comprising a transmission means for receiving user input via a voice assistant and transmitting it to a data means.

[0904] "Application example 2 when combining with an emotional engine"

[0905] (Claim 1)

[0906] Information processing means for collecting user plans, task progress, preferences and evaluations,

[0907] An information processing means that assigns household chore tasks optimized for individual users based on collected data,

[0908] A display means for notifying the user's mobile device of a reminder regarding an assigned task,

[0909] A communication means for receiving voice instructions and adjusting tasks,

[0910] An information processing system that collects task completion status and reflects it in the next scheduling,

[0911] An analysis method that uses an emotion analysis engine to recognize the user's emotional state and dynamically adjusts task assignments using that information,

[0912] A system that includes this.

[0913] (Claim 2)

[0914] The system according to claim 1, wherein the information processing means dynamically updates the profile based on sentiment data obtained by user feedback and analysis means, thereby improving the accuracy of the schedule.

[0915] (Claim 3)

[0916] The system according to claim 1, wherein the display means receives user input via a voice assistant and transmits it to the information processing means. [Explanation of symbols]

[0917] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. An information processing device that collects user information and creates individual profiles, An information processing device that optimally assigns household chores based on collected information and adjusts the assignment information, A communication device that transmits notifications of assigned household chores to an output device, An input processing device that processes voice input and makes changes to business processes, An information processing device that collects information on the status of work completion and reflects it in the next work assignment, A system including mechanical devices that assist in physical work.

2. The system according to claim 1, wherein the information processing device dynamically updates the profile based on user evaluations to improve the accuracy of the work plan.

3. The system according to claim 1, wherein the input processing device receives user instructions via a voice assistant and transmits them to an information processing device.

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