system

Abstract

Provide a system. 【Solution means】 Means for communicating with a plurality of electrical devices in the home and optimizing housework tasks based on this, Means for managing the user's schedule and automatically planning housework and childcare tasks based on the schedule, Means for analyzing the growth stage and interests of children and using generative artificial intelligence to generate appropriate early childhood education activities, Means for obtaining information on the external environment and making suggestions optimal for the user's life, Means for enabling operations from outside the home and performing remote monitoring, Means for sending notifications to the user terminal and receiving user interactions, Means for accumulating household data and learning for making improved suggestions, A system including the above.

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, and includes 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 as a 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 modern families, the burden of housework and child-rearing is increasing, which is a factor reducing the quality of life of individuals and families. This burden raises the hurdles for marriage and childbirth, leading to a decline in the birth rate and the happiness level within the family. In particular, in dual-income families, the constraints on time and labor are significant, and innovative solutions for efficiently managing housework and child-rearing are in demand.

Means for Solving the Problems

[0005] This invention provides an autonomous AI system for efficiently managing household chores and childcare within the home and improving family well-being. Specifically, it includes means for automating household tasks by communicating with multiple electrical devices, means for planning household and childcare tasks based on the user's schedule, and means for suggesting educational activities appropriate to the child's developmental stage using generative artificial intelligence. Furthermore, by sending notifications to the user terminal and accepting interaction, it is possible to make continuous improvements utilizing user feedback. The aim of such a system is to reduce the time and effort burden within the home and improve the quality of life and well-being of individuals and families as a whole.

[0006] "Within the home" refers to the internal environment of a house, which is the living space where family members reside, and where household chores and childcare take place.

[0007] "Electrical equipment" refers to devices that use electricity to perform specific functions, and in the home, this includes refrigerators, air conditioners, washing machines, and so on.

[0008] "Communication" refers to the process of sending and receiving information, and in this invention, it refers to the process of exchanging data with various electrical devices in the home.

[0009] "Household tasks" are the work and chores necessary to maintain daily life, and include things like cleaning, cooking, and laundry.

[0010] "Automation" refers to machines and systems operating autonomously without human intervention, with the aim of increasing efficiency.

[0011] A "schedule" is a chronological organization of appointments and plans for a specific period, and is a tool for managing a user's daily activities.

[0012] "Generative artificial intelligence" is a type of artificial intelligence that has the ability to create new information and content based on data, and is particularly responsible for generating activities for learning and play.

[0013] "Developmental stages" refer to the evolution of a child's physical and intellectual abilities according to their respective developmental stages.

[0014] "Educational activities" refer to activities that enable children to improve their knowledge and skills through learning and play, and in this invention, generated content is used.

[0015] A "user terminal" is a device that a user directly operates and uses to receive information, and this includes smartphones and tablets.

[0016] A "notification" is an alert or message that informs a user of specific information, and is delivered visually or audibly through the device.

[0017] "Interaction" refers to two-way communication between the user and the system, including user feedback and actions.

[0018] "Feedback" refers to the reactions and opinions received from users, and is information used to improve and optimize the system. [Brief explanation of the drawing]

[0019] [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]It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

Embodiments for Carrying Out the Invention

[0020] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0021] First, the terms used in the following description will be explained. <​In the following embodiments, the signed processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Furthermore, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include CPU (Central Processing Unit), GPU (Graphics Processing Unit), GPGPU (General-Purpose computing on Graphics Processing Units), and APU (Accelerated Processing Unit).

[0023] In the following embodiments, signed RAM (Random Access Memory) is a memory that temporarily stores information and is used as work memory by the processor.

[0024] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0025] 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).

[0026] 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."

[0027] [First Embodiment]

[0028] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0029] 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.

[0030] 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).

[0031] 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.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0036] 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.

[0037] 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.

[0038] 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.

[0039] 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".

[0040] The system based on this invention provides efficient management of household electrical appliances and features autonomous AI functions for childcare support. This system consists of a server, a user terminal, and electrical appliances that can communicate with each other.

[0041] The overall flow is as follows:

[0042] Optimizing home appliance management and household tasks

[0043] The server communicates with household electrical appliances via the network and retrieves real-time data from each device. For example, it can collect information such as the inventory status of the refrigerator and the operating status of the washing machine.

[0044] Based on this information, the server automatically optimizes household tasks. For example, the server analyzes the remaining ingredients in the refrigerator, suggests the best dinner recipe for the user, and creates a shopping list of necessary items.

[0045] The tasks created are added to the user's calendar and sent as notifications to their device. Based on these notifications, the user can check their daily household chore schedule.

[0046] Provision of childcare support

[0047] To support children's daily growth and activities based on their interests, the server analyzes user input and past data.

[0048] By utilizing generative AI, the server generates educational activities tailored to a child's developmental stage, as well as original stories designed to pique their interest.

[0049] These contents are periodically notified to users via their devices and used as suggestions to enrich the time spent with their children.

[0050] Interaction and Feedback

[0051] The device also has the functionality to accept input and feedback from the user when notifying the user of tasks and suggestions.

[0052] This allows the server to improve the accuracy of future suggestions by inputting the results of actions taken based on the suggestions provided by the user, as well as changes to their own schedule.

[0053] Users can easily interact with this system through an intuitive interface, allowing them to receive customized support tailored to their specific needs.

[0054] This system makes it possible to reduce the burden on households and improve the quality of life for users and their families. A concrete example is that on busy weekday mornings, necessary household chores can be completed automatically based on a pre-set schedule, allowing users to enjoy a more relaxed lifestyle. Thus, the aim of this invention is to increase time efficiency within the home while simultaneously increasing happy time spent with family.

[0055] The following describes the processing flow.

[0056] Step 1:

[0057] The server connects to various electrical appliances in the home and retrieves real-time data from them. For example, it can retrieve information on the refrigerator's inventory and the washing machine's operating status.

[0058] Step 2:

[0059] The server analyzes the acquired data and develops a plan to optimize household tasks. For example, it might select recipes needed for tonight's dinner based on the availability of ingredients.

[0060] Step 3:

[0061] The server sends instructions for optimized household tasks to home appliances. For example, it might instruct a robotic vacuum cleaner to clean the living room or set the air conditioner to maintain a constant temperature.

[0062] Step 4:

[0063] The server records the child's developmental status and analyzes user input. Based on this data, generative artificial intelligence is used to generate learning and play content suitable for the child.

[0064] Step 5:

[0065] The server notifies the terminal of the generated suggestions and tasks. The terminal provides the user with an interface to receive the information.

[0066] Step 6:

[0067] Users check notifications on their devices and obtain detailed task information. They can then review and carry out household chores and childcare activities as needed.

[0068] Step 7:

[0069] Users send feedback to the server via their devices. This allows the server to accumulate data to improve the accuracy of future suggestions and contribute to the overall improvement of the system.

[0070] (Example 1)

[0071] 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."

[0072] Daily household tasks and childcare activities are time-consuming and laborious, which can impair household efficiency and quality of life. Furthermore, effectively managing household electronic devices and providing appropriate educational activities tailored to a child's developmental stage are challenging for many families. There is a need for systems that efficiently address these challenges and improve users' lives.

[0073] 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.

[0074] In this invention, the server includes means for sending and receiving data with multiple electronic devices in the home and optimizing household tasks based on the acquired information; means for managing the user's activity schedule and automatically constructing household and childcare tasks based on the schedule; and means for analyzing the child's developmental stage and interests and using generative machine learning to generate appropriate educational activities. This makes it possible to improve the efficiency of household tasks and provide appropriate educational support for children.

[0075] "Electronic devices" are devices that can send and receive data and assist in performing various tasks within the home.

[0076] "Household work" refers to all activities related to housework and childcare in daily life.

[0077] "Data transmission and reception" refers to the act of exchanging information between a server and other devices or systems.

[0078] "Activity schedule" refers to the daily schedule or plan set by the user.

[0079] "Generative machine learning" is an artificial intelligence technology that analyzes data and generates new information and suggestions.

[0080] "Educational activities" refer to tasks and experiences designed to promote the development of children's knowledge and skills.

[0081] "Analysis" is the process of examining information in detail and understanding its structure and meaning.

[0082] This invention is a comprehensive system for improving work efficiency within the home and providing childcare support. The system consists of a server, user terminals, and a network including multiple electronic devices.

[0083] The server communicates with each electronic device in the home to obtain real-time data such as food inventory information and the operating status of household appliances. It uses APIs provided by each electronic device for data collection. Simultaneously, the server plans household and childcare tasks based on the user's activity schedule and utilizes generative machine learning to generate appropriate information. This process employs AI models that perform natural language processing.

[0084] Specifically, the server can analyze the contents of the refrigerator and suggest a dinner recipe based on the ingredients available at that time. In addition, the server generates a shopping list of necessary ingredients and notifies the user's terminal.

[0085] The device receives notifications from the server and relays them to the user. These notifications include details of scheduled household chores and childcare activities, which the user can review at any time. The user can also provide feedback to the server via the device, and this feedback is used to improve the accuracy of the system's suggestions.

[0086] This invention makes it possible to provide personalized suggestions to the user by prompting them with phrases such as, "Please suggest some fun educational activities for a 3-year-old," or "Please tell me a simple dinner recipe using ingredients I have in my refrigerator."

[0087] In this way, it is possible to reduce the workload within the home while improving the quality of life for the user and their family.

[0088] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0089] Step 1:

[0090] The server acquires data from electronic devices within the home. For example, it collects information such as refrigerator inventory and washing machine usage status via APIs. The input is digital data provided by each device, and the output is integrated, real-time household status data. This data is then used to prepare for analysis in the next step.

[0091] Step 2:

[0092] The server analyzes the acquired data. For example, it analyzes information about the ingredients in the refrigerator and performs data calculations to determine their freshness and remaining quantity. The input is the household situation data obtained in step 1, and the output generates a list of ingredients suitable for tonight's dinner or a list of ingredients that need to be repurchased. This forms the basis for suggestions tailored to the user's needs.

[0093] Step 3:

[0094] The server generates suggestions for the user using a generative AI model. Specifically, it suggests recipes or designs childcare activities based on the user's schedule and refrigerator information. The input is the ingredient list and childcare information obtained in step 2, and the output is "recommended recipes" or "suggestions for educational activities." Natural language processing technology is used in the generative AI model at this time.

[0095] Step 4:

[0096] The server notifies the user's device of the generated suggestions. The input is the output data from step 3, and the notification information, formatted based on this data, is sent to the device. The output is the specific suggestion content displayed on the notification screen of the user's smartphone or tablet. The user can review this and use it to improve their daily activities.

[0097] Step 5:

[0098] The terminal receives feedback from users. Users input their thoughts and results regarding the proposed content as feedback. This input is user feedback information, which the server receives and outputs. The server analyzes this data and uses it as foundational data to improve the accuracy of future proposals.

[0099] Step 6:

[0100] The server performs the system's learning process based on the collected feedback data. The feedback information obtained in step 5 is used as input, and the output is an improved proposed algorithm or an updated generative AI model. This improves the overall system performance and provides users with more customized support.

[0101] (Application Example 1)

[0102] 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."

[0103] Managing household affairs and the burden of childcare are significant challenges for many families. Furthermore, the influence of external factors and the difficulty of managing time outside the home are major sources of stress for busy modern people. Conventional technologies have only been able to manage individual household devices and provide childcare support; they have been unable to comprehensively manage information both inside and outside the home and optimize the user's overall life.

[0104] 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.

[0105] In this invention, the server includes means for communicating with multiple electrical devices in the home and optimizing household tasks based on this, means for acquiring information about the external environment and making suggestions best suited to the user's life, and means for enabling operation from outside the home and performing remote monitoring. This makes it possible to provide appropriate support tailored to the individual needs of the user, both inside and outside the home, and to reduce the burden of housework and childcare.

[0106] "Multiple electrical appliances in the home" refers to various electrical appliances installed in a home that can be connected via a network, such as refrigerators, washing machines, and air conditioners.

[0107] "Communicating" refers to the process of sending and receiving data, meaning the transmission of information between electrical equipment and a server.

[0108] "Optimizing household tasks" refers to organizing and adjusting the order and content of household chores in order to perform them efficiently.

[0109] "Managing user schedules" means recording each individual's schedule and coordinating activities based on that schedule.

[0110] "Child developmental stages and interests" refers to information about a child's age, mental development, and the things they are particularly interested in.

[0111] "Using generative artificial intelligence" means utilizing algorithms that automatically create new content and suggestions from data through machine learning.

[0112] "External environment information" refers to data collected from outside the home regarding factors that affect daily life, such as weather, traffic conditions, and local events.

[0113] "User terminal" refers to devices used directly by the user, such as smartphones, tablets, and smart glasses, that can communicate with the server.

[0114] "Remote monitoring" refers to a method of observing and checking the situation inside a home from an external location, and taking action as needed.

[0115] "Learning to accumulate data and make improved suggestions" refers to the machine learning process of collecting and analyzing past data to improve the accuracy of future suggestions.

[0116] To realize this invention, the server communicates with multiple electrical devices through the home network and acquires real-time status data for each device. This includes a refrigerator equipped with a temperature sensor and a washing machine whose usage is monitored. Based on this data, the server is designed to optimize household chores and suggest the most suitable tasks at the appropriate time. The server also collects and analyzes external environmental information such as weather and traffic conditions to provide dynamic suggestions for optimizing the user's overall life.

[0117] The user's device receives notifications sent from the server and functions as an interface for user interaction. Smartphones and tablets are primarily used as devices, through which users receive suggestions tailored to their environment both inside and outside the home. Furthermore, users can operate devices from outside the home using their devices, enabling remote control and monitoring of the home environment.

[0118] Generative artificial intelligence is implemented on the server as a module for generating educational activities and stories based on a child's developmental stage. The generative AI model utilizes user feedback to continuously improve the quality of the content it provides. It learns from data obtained through everyday interactions within the family to improve the accuracy of its suggestions.

[0119] For example, a server could analyze sensor data from a washing machine to detect available time slots and then suggest the optimal washing time based on the user's schedule. Furthermore, a generative AI model could, for instance, detect a child's interest in a particular animal and generate educational content related to that animal.

[0120] An example of a prompt message would be: "Please check the operating status of the household washing machine and suggest the optimal washing time. The user has time tomorrow morning." This invention makes it possible to comprehensively manage information both inside and outside the home and provide the user with optimized lifestyle support.

[0121] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0122] Step 1:

[0123] The server acquires real-time status data from each electrical appliance via the home network. This input data includes things like refrigerator temperature and washing machine operating status. Based on the acquired data, it can understand the current state of the home. The data is stored in a database and used in subsequent processing steps.

[0124] Step 2:

[0125] The server matches acquired device status data with the user's scheduled activities and executes an algorithm to plan the most suitable household tasks. For example, if the washing machine is free and the user has free time, it will create a laundry suggestion. The input data consists of device status data and the user's schedule, and based on this, an optimized task suggestion is output.

[0126] Step 3:

[0127] The server acquires external environmental information, including weather and traffic conditions, and retrieves data from external APIs via the internet. This input data provides elements to be considered in order to support the user's life, and appropriate suggestions are generated based on this. The acquired data is processed to model the impact of predicted conditions on the user.

[0128] Step 4:

[0129] The server uses a generative AI model to generate educational activities tailored to the child's interests and developmental stage. Based on user input and past data, the AI ​​generates relevant content, which is then output to the device as educational content. This process utilizes natural language processing technology, with generation based on prompt text.

[0130] Step 5:

[0131] The terminal notifies the user of suggestions from the server. The user receives these suggestions and provides feedback as needed. The input data is user feedback, which the server uses to update its machine learning model to improve the accuracy of future suggestions. Based on user interaction, the terminal provides an intuitive interface.

[0132] Step 6:

[0133] The server uses historical data accumulated in the system to perform analysis to further improve the suggestions. This includes past suggestion history and user behavior patterns. The input data is this historical data, and the output is a more accurate suggestion for the next time. Statistical analysis and machine learning techniques are used in this step.

[0134] 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.

[0135] This invention is a system that automates household life management and provides a personalized experience through user emotion recognition. By incorporating an emotion engine, this system enables user emotion-based interaction and improves the quality of household and childcare support.

[0136] Configuration and operation details

[0137] System configuration:

[0138] This system consists of a server, user terminals, household electrical appliances, and an emotion engine. The server manages communication between each component and aggregates and analyzes data. The emotion engine is responsible for recognizing the user's emotions through facial expression analysis cameras and voice recognition devices.

[0139] Server operation:

[0140] The server communicates with home appliances to optimize household tasks and automates the scheduling of household and childcare tasks using the user's calendar data. It also uses generative artificial intelligence to generate educational activities tailored to the child's development. This information is transmitted to the user's terminal in real time.

[0141] How the emotion engine works:

[0142] The emotion engine analyzes the user's emotions at that moment from their facial expressions and voice input. If the emotions are positive, it can suggest household chores and childcare tasks more proactively; if the emotions are negative, it will suggest things that prioritize relaxation and support.

[0143] Interaction process:

[0144] The user terminal notifies the user of tasks and suggestions through an intuitive user interface, based on information received from the server. User feedback is returned to the server via the terminal, contributing to improvements in the accuracy of future suggestions and actions.

[0145] Specific example

[0146] For example, when a user is tired, the emotion engine recognizes this and recommends relaxing activities. Based on this, the server instructs the smart speaker to play music, while simultaneously suggesting easy dinner recipes from the refrigerator. This makes it possible to maintain harmony and comfort within the home without requiring any effort from the user.

[0147] By implementing this system, the burden of housework and childcare within the home can be effectively reduced, improving the quality of life for individuals and families. The aim is to provide a more personalized and effective support environment through responses that take emotions into consideration.

[0148] The following describes the processing flow.

[0149] Step 1:

[0150] The server connects to each electrical appliance in the home via a network and retrieves data in real time. For example, it can retrieve inventory information from the refrigerator and check the usage status of the washing machine.

[0151] Step 2:

[0152] The server optimizes household tasks based on the acquired data. For example, it identifies recipes that can be suggested based on the contents of the refrigerator and adjusts the schedules of each appliance.

[0153] Step 3:

[0154] The emotion engine analyzes the user's facial expressions and voice in real time to recognize their emotional state. For example, it can detect a user's smile using the camera or sense fatigue from their voice.

[0155] Step 4:

[0156] The server adjusts the priority and content of household and childcare tasks based on the recognized emotional state. If the emotion is positive, it suggests active activities; if the emotion is negative, it creates a plan that prioritizes relaxation.

[0157] Step 5:

[0158] The server sends the created tasks and suggestions to the terminal. The terminal receives them and displays them to the user as notifications.

[0159] Step 6:

[0160] Users will see suggested tasks and activities through notifications on their devices and perform them as needed. They will also decide which activities to choose based on the information provided.

[0161] Step 7:

[0162] Users send feedback about their selected activities and the emotions they experienced to the server via their device.

[0163] Step 8:

[0164] The server integrates user feedback and stores it as learning data to improve the quality of future suggestions. This allows the system to provide more personalized support that is better suited to the user.

[0165] (Example 2)

[0166] 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 will be referred to as the "terminal."

[0167] In modern homes, multiple electronic devices and the management of daily schedules are scattered, requiring significant time and effort for each operation and management. Furthermore, there is a lack of adaptive support and suggestions based on the individual circumstances and emotions of users, compromising comfort and efficiency within the home. Addressing these challenges and fostering harmony within the home is essential.

[0168] 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.

[0169] In this invention, the server includes means for communicating with multiple electronic devices in the home and optimizing device operation tasks, means for analyzing the user's emotional state and using generative artificial intelligence to generate individual activities based on the analysis results, and means for accumulating user data and learning to make more effective suggestions. This makes it possible to comprehensively manage all devices and schedules in the home and provide services adapted to the user's state.

[0170] "Electronic devices" refer to all devices and equipment used in the home that require electricity and are capable of communication and operation.

[0171] A "device operation task" refers to a series of operations and setting procedures necessary to ensure that electronic devices in the home function properly.

[0172] "Users" refer to individual individuals within a household who use this system and are the entities that provide emotional data and schedules.

[0173] "Generative artificial intelligence" refers to a computer program that can generate new suggestions and activities based on input data.

[0174] A "user terminal" is a device used by users to interact with the system, and it is capable of providing information notifications and feedback.

[0175] "Learning methods" refer to methods for improving the performance of a system and the accuracy of its suggestions based on accumulated data.

[0176] "Emotional state" refers to the user's internal emotional condition, and is the result of analysis based on facial expression data and voice input.

[0177] "External services" refer to services and support provided outside the home, and can be coordinated as needed.

[0178] This invention is a system that provides users with a personalized experience by integrating in-home electronic devices and schedule management.

[0179] The server plays a central role in optimizing device operation tasks by managing communication with multiple electronic devices within the home. For example, the server controls smart home devices, optimizing the operation of lighting, music players, and air conditioning systems. Furthermore, the server accumulates user data and continuously improves its suggestions using learning algorithms.

[0180] By using emotion recognition technology, the system analyzes the user's instantaneous emotional state and generates appropriate activities using a generative artificial intelligence (AI) model. For example, it collects the user's emotional data through a facial recognition camera and a voice recognition device, and if it determines that relaxation is needed, it suggests calming music.

[0181] The user terminal is a device that communicates bidirectionally with the server and serves as an interface for notifications and interaction. This allows the user to review suggested tasks and activities and provide reactions to the options. For example, they can instantly provide feedback such as, "I like this music."

[0182] For example, if the emotion engine detects that the user is tired, the server will instruct the smart speaker to play relaxing music while simultaneously suggesting easy cooking recipes based on the ingredients in the refrigerator. Furthermore, if the user is in a motivated state, the system will suggest activating a cleaning robot to support more efficient household chores.

[0183] Examples of prompts generated using AI models include specific instructions such as, "Please select music suitable for when the user is currently feeling relaxed," or "Please create a schedule for efficiently performing household chores based on the user's availability." This improves the quality of life within the home and provides flexible, personalized support tailored to the user.

[0184] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0185] Step 1:

[0186] The user provides emotional data through a facial expression analysis camera and a voice recognition device. These devices collect emotion-related data from the user's facial expressions and voice. Inputs include facial image data and voice tone, and output is numerical data indicating the emotional state. This data is sent to a server and used in subsequent analysis steps.

[0187] Step 2:

[0188] The server analyzes the received emotional data using an emotion engine and determines the optimal interaction for the user using generative artificial intelligence. This analysis involves data processing to identify emotional states, such as determining that the user "needs to relax." It then generates prompt statements and determines appropriate suggestions. This process produces activity suggestions for the user as output.

[0189] Step 3:

[0190] The server communicates the generated activity suggestions to electronic devices in the home. Specific actions include instructing a smart speaker to play music or suggesting a suitable recipe from a list of ingredients in the refrigerator. At this stage, the input becomes the suggested content, and the output is distributed within the home as specific instructions or notifications.

[0191] Step 4:

[0192] The user terminal receives notifications from the server and notifies the user of suggestions and tasks through the interface. The user can review the interaction content and provide feedback. The input is suggestion information from the server, and the output is the user's selection or feedback. In this way, the system accumulates user responses in real time and uses them for future interactions.

[0193] Step 5:

[0194] The server collects and analyzes user feedback data. This activates the system's learning algorithms, improving the accuracy and personalization of suggestions. Using feedback data as input, an improved suggestion algorithm is obtained as output. This process is continuous, contributing to the optimization of the home life experience.

[0195] (Application Example 2)

[0196] 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".

[0197] In modern households, many tasks such as housework and childcare are not effectively managed, placing a burden on users. Furthermore, there is a lack of personalized support tailored to individual circumstances and emotions. Therefore, there is a need for a system that provides an optimal environment and support that responds to the emotional state of each user while maintaining harmony within the family.

[0198] 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.

[0199] This invention includes a server that communicates with multiple devices in the home and optimizes work tasks based on this communication; a server that manages the user's schedule and automatically plans work and childcare tasks based on the schedule; and a server that uses generative artificial intelligence to analyze the child's developmental stage and interests and generate appropriate educational activities. This makes it possible to analyze the user's emotions, adjust the home environment based on these emotions, and provide personalized support.

[0200] "Appliances" is a general term for communication-enabled electrical equipment and devices used within a household.

[0201] "Work tasks" refer to a series of activities related to housework and childcare performed within the home, and require efficient management.

[0202] "Schedules" refer to information that indicates a user's daily schedule or events, and are managed by the system.

[0203] "Developmental stages" refer to specific periods in a child's developmental process and serve as criteria for determining educational activities.

[0204] "Educational activities" is a general term for activities conducted to promote knowledge and abilities appropriate to a child's development.

[0205] "Generative artificial intelligence" refers to artificial intelligence technology that can generate new information and suggestions based on given data.

[0206] "Emotions" refer to the state of mind analyzed from the user's facial expression data and voice input, and are an important element for the system to provide the user with the optimal environment.

[0207] "Environment" refers to factors that affect user comfort, including lighting, sound, and temperature within the home.

[0208] "Support" refers to the assistance and services provided to help users in their daily lives, and the content of these services is personalized.

[0209] The system for implementing this invention mainly consists of a server, a user terminal, multiple household appliances, and an emotion analysis engine. The server communicates with household appliances and collects and manages information to optimize work tasks. For example, home appliances, including smart lighting and voice assistants, are adjusted based on instructions from the server. The server also has the function of generating educational activities tailored to a child's developmental stage and interests using generative artificial intelligence. This information is transmitted to the user terminal, which the user receives through an intuitive interface.

[0210] The emotion analysis engine calculates real-time emotions by analyzing the user's facial expressions and voice using cameras and voice recognition devices. For example, if a user wants to relax after returning home, the server uses the data obtained from the emotion analysis engine to instruct home appliances to dim the lights in the room and play music suitable for relaxation.

[0211] As a concrete example, when a user returns home feeling tired in the evening, the system detects this emotion and automatically switches to "relaxation mode." In this mode, soft lighting and quiet background music are set, and the user's preferred simple dinner menu is suggested on the user's device.

[0212] An example of a prompt using a generative AI model might be, "Please tell me what settings are possible if I want to create a relaxing environment for myself." This prompt is used to generate suggestions for optimal environment settings through the model.

[0213] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0214] Step 1:

[0215] The server communicates with household appliances and retrieves status data for each appliance. Inputs include the appliance's ID and current status, while outputs include the appliance's operating status and configuration information. This data is used to optimize tasks in the next step.

[0216] Step 2:

[0217] The server automatically plans work tasks based on the user's schedule. Inputs include calendar information and priority settings, and the output is an optimized work schedule. This enables efficient and streamlined scheduling.

[0218] Step 3:

[0219] The server uses generative artificial intelligence to generate educational activities tailored to a child's developmental stage and interests. Input includes information about the child's age and interests, and output provides suggestions for appropriate educational activities. This provides concrete activities that contribute to the child's development.

[0220] Step 4:

[0221] The emotion analysis engine analyzes the user's facial expressions and voice data to calculate their current emotion. It takes camera footage and audio as input and outputs the user's emotional state. This analysis result is used to provide support tailored to the user's needs.

[0222] Step 5:

[0223] The server adjusts the lighting and sound in the home based on the results of emotion analysis. The user's emotional state is the input, and specific appliance setting instructions are generated as the output. For example, if the user needs to relax, instructions are sent to dim the lights and play music.

[0224] Step 6:

[0225] The user terminal receives information from the server and notifies the user through an intuitive and easy-to-understand user interface. Inputs include instructions and suggestions from the server, while outputs include visual notifications and operational guidance. This allows the user to easily manage their home environment.

[0226] 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.

[0227] 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.

[0228] 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.

[0229] [Second Embodiment]

[0230] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0231] 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.

[0232] 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).

[0233] 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.

[0234] 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.

[0235] 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).

[0236] 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.

[0237] 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.

[0238] 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.

[0239] 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.

[0240] 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.

[0241] 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".

[0242] The system based on this invention provides efficient management of household electrical appliances and features autonomous AI functions for childcare support. This system consists of a server, a user terminal, and electrical appliances that can communicate with each other.

[0243] The overall flow is as follows:

[0244] Optimizing home appliance management and household tasks

[0245] The server communicates with household electrical appliances via the network and retrieves real-time data from each device. For example, it can collect information such as the inventory status of the refrigerator and the operating status of the washing machine.

[0246] Based on this information, the server automatically optimizes household tasks. For example, the server analyzes the remaining ingredients in the refrigerator, suggests the best dinner recipe for the user, and creates a shopping list of necessary items.

[0247] The tasks created are added to the user's calendar and sent as notifications to their device. Based on these notifications, the user can check their daily household chore schedule.

[0248] Provision of childcare support

[0249] To support children's daily growth and activities based on their interests, the server analyzes user input and past data.

[0250] By utilizing generative AI, the server generates educational activities tailored to a child's developmental stage, as well as original stories designed to pique their interest.

[0251] These contents are periodically notified to users via their devices and used as suggestions to enrich the time spent with their children.

[0252] Interaction and Feedback

[0253] The device also has the functionality to accept input and feedback from the user when notifying the user of tasks and suggestions.

[0254] This allows the server to improve the accuracy of future suggestions by inputting the results of actions taken based on the suggestions provided by the user, as well as changes to their own schedule.

[0255] Users can easily interact with this system through an intuitive interface, allowing them to receive customized support tailored to their specific needs.

[0256] This system makes it possible to reduce the burden on households and improve the quality of life for users and their families. A concrete example is that on busy weekday mornings, necessary household chores can be completed automatically based on a pre-set schedule, allowing users to enjoy a more relaxed lifestyle. Thus, the aim of this invention is to increase time efficiency within the home while simultaneously increasing happy time spent with family.

[0257] The following describes the processing flow.

[0258] Step 1:

[0259] The server connects to various electrical appliances in the home and retrieves real-time data from them. For example, it can retrieve information on the refrigerator's inventory and the washing machine's operating status.

[0260] Step 2:

[0261] The server analyzes the acquired data and develops a plan to optimize household tasks. For example, it might select recipes needed for tonight's dinner based on the availability of ingredients.

[0262] Step 3:

[0263] The server sends instructions for optimized household tasks to home appliances. For example, it might instruct a robotic vacuum cleaner to clean the living room or set the air conditioner to maintain a constant temperature.

[0264] Step 4:

[0265] The server records the child's developmental status and analyzes user input. Based on this data, generative artificial intelligence is used to generate learning and play content suitable for the child.

[0266] Step 5:

[0267] The server notifies the terminal of the generated suggestions and tasks. The terminal provides the user with an interface to receive the information.

[0268] Step 6:

[0269] Users check notifications on their devices and obtain detailed task information. They can then review and carry out household chores and childcare activities as needed.

[0270] Step 7:

[0271] Users send feedback to the server via their devices. This allows the server to accumulate data to improve the accuracy of future suggestions and contribute to the overall improvement of the system.

[0272] (Example 1)

[0273] 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."

[0274] Daily household tasks and childcare activities are time-consuming and laborious, which can impair household efficiency and quality of life. Furthermore, effectively managing household electronic devices and providing appropriate educational activities tailored to a child's developmental stage are challenging for many families. There is a need for systems that efficiently address these challenges and improve users' lives.

[0275] 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.

[0276] In this invention, the server includes means for transmitting and receiving data with a plurality of electronic devices in the home and optimizing in-home work based on the acquired information, means for managing the user's activity schedule and automatically constructing in-home work and childcare work based on the schedule, and means for analyzing the child's development stage and interests and using generative machine learning to generate appropriate educational activities. This enables the improvement of the efficiency of in-home work and the provision of appropriate educational support for children.

[0277] An "electronic device" is a device capable of transmitting and receiving data and supporting and executing various tasks in the home.

[0278] "In-home work" refers to all activities related to housework and childcare in daily life.

[0279] "Transmission and reception of data" is an act of exchanging information between the server and other devices or systems.

[0280] "Activity schedule" refers to the daily schedules or plans set by the user.

[0281] "Generative machine learning" is an artificial intelligence technology that performs analysis based on data and generates new information and proposals.

[0282] "Educational activity" refers to tasks and experiences designed to promote the development of children's knowledge and skills.

[0283] "Analysis" is the process of examining the target information in detail and understanding its structure and meaning.

[0284] This invention is an integrated system for improving work efficiency in the home and providing childcare support. This system is composed of a network including a server, the user's terminal, and a plurality of electronic devices.

[0285] The server communicates with each electronic device in the home and obtains real-time data such as the inventory information of food ingredients and the operating status of household appliances. At this time, the API provided by each electronic device is used for data collection. The server also plans housework and childcare tasks based on the user's activity schedule and utilizes generative machine learning to generate appropriate information. An AI model that performs natural language processing is used in this process.

[0286] As a specific operation, the server can analyze the contents of the refrigerator and propose a dinner recipe based on the ingredients available at that time. In addition to this, the server generates a shopping list of the necessary ingredients and notifies the user's terminal.

[0287] The terminal receives the notification from the server and conveys it to the user. The notification includes details of the scheduled housework and childcare activities, and the user can check the content at any time. The user can return feedback to the server via the terminal, and this feedback is used to improve the proposal accuracy of the system.

[0288] The present invention can make personalized proposals to the user by inputting prompt sentences such as "Please propose fun intellectual development activities for a 3-year-old child" or "Please teach me a dinner recipe that can be easily made with the ingredients in the refrigerator".

[0289] In this way, while reducing the workload within the home, the quality of life of the user and their family can be improved.

[0290] The flow of the specific process in Example 1 will be described using FIG. 11.

[0291] Step 1:

[0292] The server acquires data from electronic devices within the home. For example, it collects information such as refrigerator inventory and washing machine usage status via APIs. The input is digital data provided by each device, and the output is integrated, real-time household status data. This data is then used to prepare for analysis in the next step.

[0293] Step 2:

[0294] The server analyzes the acquired data. For example, it analyzes information about the ingredients in the refrigerator and performs data calculations to determine their freshness and remaining quantity. The input is the household situation data obtained in step 1, and the output generates a list of ingredients suitable for tonight's dinner or a list of ingredients that need to be repurchased. This forms the basis for suggestions tailored to the user's needs.

[0295] Step 3:

[0296] The server generates suggestions for the user using a generative AI model. Specifically, it suggests recipes or designs childcare activities based on the user's schedule and refrigerator information. The input is the ingredient list and childcare information obtained in step 2, and the output is "recommended recipes" or "suggestions for educational activities." Natural language processing technology is used in the generative AI model at this time.

[0297] Step 4:

[0298] The server notifies the user's device of the generated suggestions. The input is the output data from step 3, and the notification information, formatted based on this data, is sent to the device. The output is the specific suggestion content displayed on the notification screen of the user's smartphone or tablet. The user can review this and use it to improve their daily activities.

[0299] Step 5:

[0300] The terminal receives feedback from users. Users input their thoughts and results regarding the proposed content as feedback. This input is user feedback information, which the server receives and outputs. The server analyzes this data and uses it as foundational data to improve the accuracy of future proposals.

[0301] Step 6:

[0302] The server performs the system's learning process based on the collected feedback data. The feedback information obtained in step 5 is used as input, and the output is an improved proposed algorithm or an updated generative AI model. This improves the overall system performance and provides users with more customized support.

[0303] (Application Example 1)

[0304] 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."

[0305] Managing household affairs and the burden of childcare are significant challenges for many families. Furthermore, the influence of external factors and the difficulty of managing time outside the home are major sources of stress for busy modern people. Conventional technologies have only been able to manage individual household devices and provide childcare support; they have been unable to comprehensively manage information both inside and outside the home and optimize the user's overall life.

[0306] 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.

[0307] In this invention, the server includes means for communicating with a plurality of electrical appliances in the home and optimizing housework tasks based thereon, means for obtaining information on the external environment and making optimal proposals for the user's life, and means for enabling operations from outside the home and performing remote monitoring. This makes it possible to provide appropriate support according to the individual needs of the user, regardless of whether it is inside or outside the home, and to reduce the burden of housework and childcare.

[0308] The "plurality of electrical appliances in the home" refers to various electrical appliances installed in the home, such as refrigerators, washing machines, air conditioners, etc., that can be connected via a network.

[0309] "Performing communication" refers to the process of sending and receiving data, meaning transmitting information between the electrical appliances and the server.

[0310] "Optimization of housework tasks" means arranging and adjusting the order and content of their execution in order to efficiently perform the work within the home.

[0311] "Managing the user's schedule" means recording the individual schedules of each person and adjusting activities based thereon.

[0312] "The growth stage and interests of children" refers to information regarding the age and mental growth of children, and matters that they are particularly interested in.

[0313] "Using generative artificial intelligence" means utilizing an algorithm that automatically creates new content and proposals from data through machine learning.

[0314] "Information on the external environment" refers to data on factors that affect daily life, such as weather, traffic conditions, and local events, collected from outside the home.

[0315] The "user terminal" refers to devices directly used by the user, such as smartphones, tablets, smart glasses, etc., that can communicate with the server.

[0316] "Remote monitoring" refers to a method of observing and checking the situation inside a home from an external location, and taking action as needed.

[0317] "Learning to accumulate data and make improved suggestions" refers to the machine learning process of collecting and analyzing past data to improve the accuracy of future suggestions.

[0318] To realize this invention, the server communicates with multiple electrical devices through the home network and acquires real-time status data for each device. This includes a refrigerator equipped with a temperature sensor and a washing machine whose usage is monitored. Based on this data, the server is designed to optimize household chores and suggest the most suitable tasks at the appropriate time. The server also collects and analyzes external environmental information such as weather and traffic conditions to provide dynamic suggestions for optimizing the user's overall life.

[0319] The user's device receives notifications sent from the server and functions as an interface for user interaction. Smartphones and tablets are primarily used as devices, through which users receive suggestions tailored to their environment both inside and outside the home. Furthermore, users can operate devices from outside the home using their devices, enabling remote control and monitoring of the home environment.

[0320] Generative artificial intelligence is implemented on the server as a module for generating educational activities and stories based on a child's developmental stage. The generative AI model utilizes user feedback to continuously improve the quality of the content it provides. It learns from data obtained through everyday interactions within the family to improve the accuracy of its suggestions.

[0321] For example, a server could analyze sensor data from a washing machine to detect available time slots and then suggest the optimal washing time based on the user's schedule. Furthermore, a generative AI model could, for instance, detect a child's interest in a particular animal and generate educational content related to that animal.

[0322] An example of a prompt message would be: "Please check the operating status of the household washing machine and suggest the optimal washing time. The user has time tomorrow morning." This invention makes it possible to comprehensively manage information both inside and outside the home and provide the user with optimized lifestyle support.

[0323] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0324] Step 1:

[0325] The server acquires real-time status data from each electrical appliance via the home network. This input data includes things like refrigerator temperature and washing machine operating status. Based on the acquired data, it can understand the current state of the home. The data is stored in a database and used in subsequent processing steps.

[0326] Step 2:

[0327] The server matches acquired device status data with the user's scheduled activities and executes an algorithm to plan the most suitable household tasks. For example, if the washing machine is free and the user has free time, it will create a laundry suggestion. The input data consists of device status data and the user's schedule, and based on this, an optimized task suggestion is output.

[0328] Step 3:

[0329] The server acquires external environmental information, including weather and traffic conditions, and retrieves data from external APIs via the internet. This input data provides elements to be considered in order to support the user's life, and appropriate suggestions are generated based on this. The acquired data is processed to model the impact of predicted conditions on the user.

[0330] Step 4:

[0331] The server uses a generative AI model to generate educational activities tailored to the child's interests and developmental stage. Based on user input and past data, the AI ​​generates relevant content, which is then output to the device as educational content. This process utilizes natural language processing technology, with generation based on prompt text.

[0332] Step 5:

[0333] The terminal notifies the user of suggestions from the server. The user receives these suggestions and provides feedback as needed. The input data is user feedback, which the server uses to update its machine learning model to improve the accuracy of future suggestions. Based on user interaction, the terminal provides an intuitive interface.

[0334] Step 6:

[0335] The server uses historical data accumulated in the system to perform analysis to further improve the suggestions. This includes past suggestion history and user behavior patterns. The input data is this historical data, and the output is a more accurate suggestion for the next time. Statistical analysis and machine learning techniques are used in this step.

[0336] 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.

[0337] This invention is a system that automates household life management and provides a personalized experience through user emotion recognition. By incorporating an emotion engine, this system enables user emotion-based interaction and improves the quality of household and childcare support.

[0338] Configuration and operation details

[0339] System configuration:

[0340] This system consists of a server, user terminals, household electrical appliances, and an emotion engine. The server manages communication between each component and aggregates and analyzes data. The emotion engine is responsible for recognizing the user's emotions through facial expression analysis cameras and voice recognition devices.

[0341] Server operation:

[0342] The server communicates with home appliances to optimize household tasks and automates the scheduling of household and childcare tasks using the user's calendar data. It also uses generative artificial intelligence to generate educational activities tailored to the child's development. This information is transmitted to the user's terminal in real time.

[0343] How the emotion engine works:

[0344] The emotion engine analyzes the user's emotions at that moment from their facial expressions and voice input. If the emotions are positive, it can suggest household chores and childcare tasks more proactively; if the emotions are negative, it will suggest things that prioritize relaxation and support.

[0345] Interaction process:

[0346] The user terminal notifies the user of tasks and suggestions through an intuitive user interface, based on information received from the server. User feedback is returned to the server via the terminal, contributing to improvements in the accuracy of future suggestions and actions.

[0347] Specific example

[0348] For example, when a user is tired, the emotion engine recognizes this and recommends relaxing activities. Based on this, the server instructs the smart speaker to play music, while simultaneously suggesting easy dinner recipes from the refrigerator. This makes it possible to maintain harmony and comfort within the home without requiring any effort from the user.

[0349] By implementing this system, the burden of housework and childcare within the home can be effectively reduced, improving the quality of life for individuals and families. The aim is to provide a more personalized and effective support environment through responses that take emotions into consideration.

[0350] The following describes the processing flow.

[0351] Step 1:

[0352] The server connects to each electrical appliance in the home via a network and retrieves data in real time. For example, it can retrieve inventory information from the refrigerator and check the usage status of the washing machine.

[0353] Step 2:

[0354] The server optimizes household tasks based on the acquired data. For example, it identifies recipes that can be suggested based on the contents of the refrigerator and adjusts the schedules of each appliance.

[0355] Step 3:

[0356] The emotion engine analyzes the user's facial expressions and voice in real time to recognize their emotional state. For example, it can detect a user's smile using the camera or sense fatigue from their voice.

[0357] Step 4:

[0358] The server adjusts the priority and content of household and childcare tasks based on the recognized emotional state. If the emotion is positive, it suggests active activities; if the emotion is negative, it creates a plan that prioritizes relaxation.

[0359] Step 5:

[0360] The server sends the created tasks and suggestions to the terminal. The terminal receives them and displays them to the user as notifications.

[0361] Step 6:

[0362] Users will see suggested tasks and activities through notifications on their devices and perform them as needed. They will also decide which activities to choose based on the information provided.

[0363] Step 7:

[0364] Users send feedback about their selected activities and the emotions they experienced to the server via their device.

[0365] Step 8:

[0366] The server integrates user feedback and stores it as learning data to improve the quality of future suggestions. This allows the system to provide more personalized support that is better suited to the user.

[0367] (Example 2)

[0368] 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".

[0369] In modern homes, multiple electronic devices and the management of daily schedules are scattered, requiring significant time and effort for each operation and management. Furthermore, there is a lack of adaptive support and suggestions based on the individual circumstances and emotions of users, compromising comfort and efficiency within the home. Addressing these challenges and fostering harmony within the home is essential.

[0370] 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.

[0371] In this invention, the server includes means for communicating with multiple electronic devices in the home and optimizing device operation tasks, means for analyzing the user's emotional state and using generative artificial intelligence to generate individual activities based on the analysis results, and means for accumulating user data and learning to make more effective suggestions. This makes it possible to comprehensively manage all devices and schedules in the home and provide services adapted to the user's state.

[0372] "Electronic devices" refer to all devices and equipment used in the home that require electricity and are capable of communication and operation.

[0373] A "device operation task" refers to a series of operations and setting procedures necessary to ensure that electronic devices in the home function properly.

[0374] "Users" refer to individual individuals within a household who use this system and are the entities that provide emotional data and schedules.

[0375] "Generative artificial intelligence" refers to a computer program that can generate new suggestions and activities based on input data.

[0376] A "user terminal" is a device used by users to interact with the system, and it is capable of providing information notifications and feedback.

[0377] "Learning methods" refer to methods for improving the performance of a system and the accuracy of its suggestions based on accumulated data.

[0378] "Emotional state" refers to the user's internal emotional condition, and is the result of analysis based on facial expression data and voice input.

[0379] "External services" refer to services and support provided outside the home, and can be coordinated as needed.

[0380] This invention is a system that provides users with a personalized experience by integrating in-home electronic devices and schedule management.

[0381] The server plays a central role in optimizing device operation tasks by managing communication with multiple electronic devices within the home. For example, the server controls smart home devices, optimizing the operation of lighting, music players, and air conditioning systems. Furthermore, the server accumulates user data and continuously improves its suggestions using learning algorithms.

[0382] By using emotion recognition technology, the system analyzes the user's instantaneous emotional state and generates appropriate activities using a generative artificial intelligence (AI) model. For example, it collects the user's emotional data through a facial recognition camera and a voice recognition device, and if it determines that relaxation is needed, it suggests calming music.

[0383] The user terminal is a device that communicates bidirectionally with the server and serves as an interface for notifications and interaction. This allows the user to review suggested tasks and activities and provide reactions to the options. For example, they can instantly provide feedback such as, "I like this music."

[0384] For example, if the emotion engine detects that the user is tired, the server will instruct the smart speaker to play relaxing music while simultaneously suggesting easy cooking recipes based on the ingredients in the refrigerator. Furthermore, if the user is in a motivated state, the system will suggest activating a cleaning robot to support more efficient household chores.

[0385] Examples of prompts generated using AI models include specific instructions such as, "Please select music suitable for when the user is currently feeling relaxed," or "Please create a schedule for efficiently performing household chores based on the user's availability." This improves the quality of life within the home and provides flexible, personalized support tailored to the user.

[0386] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0387] Step 1:

[0388] The user provides emotional data through a facial expression analysis camera and a voice recognition device. These devices collect emotion-related data from the user's facial expressions and voice. Inputs include facial image data and voice tone, and output is numerical data indicating the emotional state. This data is sent to a server and used in subsequent analysis steps.

[0389] Step 2:

[0390] The server analyzes the received emotional data using an emotion engine and determines the optimal interaction for the user using generative artificial intelligence. This analysis involves data processing to identify emotional states, such as determining that the user "needs to relax." It then generates prompt statements and determines appropriate suggestions. This process produces activity suggestions for the user as output.

[0391] Step 3:

[0392] The server communicates the generated activity suggestions to electronic devices in the home. Specific actions include instructing a smart speaker to play music or suggesting a suitable recipe from a list of ingredients in the refrigerator. At this stage, the input becomes the suggested content, and the output is distributed within the home as specific instructions or notifications.

[0393] Step 4:

[0394] The user terminal receives notifications from the server and notifies the user of suggestions and tasks through the interface. The user can review the interaction content and provide feedback. The input is suggestion information from the server, and the output is the user's selection or feedback. In this way, the system accumulates user responses in real time and uses them for future interactions.

[0395] Step 5:

[0396] The server collects and analyzes user feedback data. This activates the system's learning algorithms, improving the accuracy and personalization of suggestions. Using feedback data as input, an improved suggestion algorithm is obtained as output. This process is continuous, contributing to the optimization of the home life experience.

[0397] (Application Example 2)

[0398] 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."

[0399] In modern households, many tasks such as housework and childcare are not effectively managed, placing a burden on users. Furthermore, there is a lack of personalized support tailored to individual circumstances and emotions. Therefore, there is a need for a system that provides an optimal environment and support that responds to the emotional state of each user while maintaining harmony within the family.

[0400] 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.

[0401] This invention includes a server that communicates with multiple devices in the home and optimizes work tasks based on this communication; a server that manages the user's schedule and automatically plans work and childcare tasks based on the schedule; and a server that uses generative artificial intelligence to analyze the child's developmental stage and interests and generate appropriate educational activities. This makes it possible to analyze the user's emotions, adjust the home environment based on these emotions, and provide personalized support.

[0402] "Appliances" is a general term for communication-enabled electrical equipment and devices used within a household.

[0403] "Work tasks" refer to a series of activities related to housework and childcare performed within the home, and require efficient management.

[0404] "Schedules" refer to information that indicates a user's daily schedule or events, and are managed by the system.

[0405] "Developmental stages" refer to specific periods in a child's developmental process and serve as criteria for determining educational activities.

[0406] "Educational activities" is a general term for activities conducted to promote knowledge and abilities appropriate to a child's development.

[0407] "Generative artificial intelligence" refers to artificial intelligence technology that can generate new information and suggestions based on given data.

[0408] "Emotions" refer to the state of mind analyzed from the user's facial expression data and voice input, and are an important element for the system to provide the user with the optimal environment.

[0409] "Environment" refers to factors that affect user comfort, including lighting, sound, and temperature within the home.

[0410] "Support" refers to the assistance and services provided to help users in their daily lives, and the content of these services is personalized.

[0411] The system for implementing this invention mainly consists of a server, a user terminal, multiple household appliances, and an emotion analysis engine. The server communicates with household appliances and collects and manages information to optimize work tasks. For example, home appliances, including smart lighting and voice assistants, are adjusted based on instructions from the server. The server also has the function of generating educational activities tailored to a child's developmental stage and interests using generative artificial intelligence. This information is transmitted to the user terminal, which the user receives through an intuitive interface.

[0412] The emotion analysis engine calculates real-time emotions by analyzing the user's facial expressions and voice using cameras and voice recognition devices. For example, if a user wants to relax after returning home, the server uses the data obtained from the emotion analysis engine to instruct home appliances to dim the lights in the room and play music suitable for relaxation.

[0413] As a concrete example, when a user returns home feeling tired in the evening, the system detects this emotion and automatically switches to "relaxation mode." In this mode, soft lighting and quiet background music are set, and the user's preferred simple dinner menu is suggested on the user's device.

[0414] An example of a prompt using a generative AI model might be, "Please tell me what settings are possible if I want to create a relaxing environment for myself." This prompt is used to generate suggestions for optimal environment settings through the model.

[0415] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0416] Step 1:

[0417] The server communicates with household appliances and retrieves status data for each appliance. Inputs include the appliance's ID and current status, while outputs include the appliance's operating status and configuration information. This data is used to optimize tasks in the next step.

[0418] Step 2:

[0419] The server automatically plans work tasks based on the user's schedule. Inputs include calendar information and priority settings, and the output is an optimized work schedule. This enables efficient and streamlined scheduling.

[0420] Step 3:

[0421] The server uses generative artificial intelligence to generate educational activities tailored to a child's developmental stage and interests. Input includes information about the child's age and interests, and output provides suggestions for appropriate educational activities. This provides concrete activities that contribute to the child's development.

[0422] Step 4:

[0423] The emotion analysis engine analyzes the user's facial expressions and voice data to calculate their current emotion. It takes camera footage and audio as input and outputs the user's emotional state. This analysis result is used to provide support tailored to the user's needs.

[0424] Step 5:

[0425] The server adjusts the lighting and sound in the home based on the results of emotion analysis. The user's emotional state is the input, and specific appliance setting instructions are generated as the output. For example, if the user needs to relax, instructions are sent to dim the lights and play music.

[0426] Step 6:

[0427] The user terminal receives information from the server and notifies the user through an intuitive and easy-to-understand user interface. Inputs include instructions and suggestions from the server, while outputs include visual notifications and operational guidance. This allows the user to easily manage their home environment.

[0428] 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.

[0429] 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.

[0430] 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.

[0431] [Third Embodiment]

[0432] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0433] 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.

[0434] 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).

[0435] 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.

[0436] 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.

[0437] 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).

[0438] 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.

[0439] 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.

[0440] 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.

[0441] 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.

[0442] 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.

[0443] 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".

[0444] The system based on this invention provides efficient management of household electrical appliances and features autonomous AI functions for childcare support. This system consists of a server, a user terminal, and electrical appliances that can communicate with each other.

[0445] The overall flow is as follows:

[0446] Optimizing home appliance management and household tasks

[0447] The server communicates with household electrical appliances via the network and retrieves real-time data from each device. For example, it can collect information such as the inventory status of the refrigerator and the operating status of the washing machine.

[0448] Based on this information, the server automatically optimizes household tasks. For example, the server analyzes the remaining ingredients in the refrigerator, suggests the best dinner recipe for the user, and creates a shopping list of necessary items.

[0449] The tasks created are added to the user's calendar and sent as notifications to their device. Based on these notifications, the user can check their daily household chore schedule.

[0450] Provision of childcare support

[0451] To support children's daily growth and activities based on their interests, the server analyzes user input and past data.

[0452] By utilizing generative AI, the server generates educational activities tailored to a child's developmental stage, as well as original stories designed to pique their interest.

[0453] These contents are periodically notified to users via their devices and used as suggestions to enrich the time spent with their children.

[0454] Interaction and Feedback

[0455] The device also has the functionality to accept input and feedback from the user when notifying the user of tasks and suggestions.

[0456] This allows the server to improve the accuracy of future suggestions by inputting the results of actions taken based on the suggestions provided by the user, as well as changes to their own schedule.

[0457] Users can easily interact with this system through an intuitive interface, allowing them to receive customized support tailored to their specific needs.

[0458] This system makes it possible to reduce the burden on households and improve the quality of life for users and their families. A concrete example is that on busy weekday mornings, necessary household chores can be completed automatically based on a pre-set schedule, allowing users to enjoy a more relaxed lifestyle. Thus, the aim of this invention is to increase time efficiency within the home while simultaneously increasing happy time spent with family.

[0459] The following describes the processing flow.

[0460] Step 1:

[0461] The server connects to various electrical appliances in the home and retrieves real-time data from them. For example, it can retrieve information on the refrigerator's inventory and the washing machine's operating status.

[0462] Step 2:

[0463] The server analyzes the acquired data and develops a plan to optimize household tasks. For example, it might select recipes needed for tonight's dinner based on the availability of ingredients.

[0464] Step 3:

[0465] The server sends instructions for optimized household tasks to home appliances. For example, it might instruct a robotic vacuum cleaner to clean the living room or set the air conditioner to maintain a constant temperature.

[0466] Step 4:

[0467] The server records the child's developmental status and analyzes user input. Based on this data, generative artificial intelligence is used to generate learning and play content suitable for the child.

[0468] Step 5:

[0469] The server notifies the terminal of the generated suggestions and tasks. The terminal provides the user with an interface to receive the information.

[0470] Step 6:

[0471] Users check notifications on their devices and obtain detailed task information. They can then review and carry out household chores and childcare activities as needed.

[0472] Step 7:

[0473] Users send feedback to the server via their devices. This allows the server to accumulate data to improve the accuracy of future suggestions and contribute to the overall improvement of the system.

[0474] (Example 1)

[0475] 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."

[0476] Daily household tasks and childcare activities are time-consuming and laborious, which can impair household efficiency and quality of life. Furthermore, effectively managing household electronic devices and providing appropriate educational activities tailored to a child's developmental stage are challenging for many families. There is a need for systems that efficiently address these challenges and improve users' lives.

[0477] 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.

[0478] In this invention, the server includes means for sending and receiving data with multiple electronic devices in the home and optimizing household tasks based on the acquired information; means for managing the user's activity schedule and automatically constructing household and childcare tasks based on the schedule; and means for analyzing the child's developmental stage and interests and using generative machine learning to generate appropriate educational activities. This makes it possible to improve the efficiency of household tasks and provide appropriate educational support for children.

[0479] "Electronic devices" are devices that can send and receive data and assist in performing various tasks within the home.

[0480] "Household work" refers to all activities related to housework and childcare in daily life.

[0481] "Data transmission and reception" refers to the act of exchanging information between a server and other devices or systems.

[0482] "Activity schedule" refers to the daily schedule or plan set by the user.

[0483] "Generative machine learning" is an artificial intelligence technology that analyzes data and generates new information and suggestions.

[0484] "Educational activities" refer to tasks and experiences designed to promote the development of children's knowledge and skills.

[0485] "Analysis" is the process of examining information in detail and understanding its structure and meaning.

[0486] This invention is a comprehensive system for improving work efficiency within the home and providing childcare support. The system consists of a server, user terminals, and a network including multiple electronic devices.

[0487] The server communicates with each electronic device in the home to obtain real-time data such as food inventory information and the operating status of household appliances. It uses APIs provided by each electronic device for data collection. Simultaneously, the server plans household and childcare tasks based on the user's activity schedule and utilizes generative machine learning to generate appropriate information. This process employs AI models that perform natural language processing.

[0488] Specifically, the server can analyze the contents of the refrigerator and suggest a dinner recipe based on the ingredients available at that time. In addition, the server generates a shopping list of necessary ingredients and notifies the user's terminal.

[0489] The device receives notifications from the server and relays them to the user. These notifications include details of scheduled household chores and childcare activities, which the user can review at any time. The user can also provide feedback to the server via the device, and this feedback is used to improve the accuracy of the system's suggestions.

[0490] This invention makes it possible to provide personalized suggestions to the user by prompting them with phrases such as, "Please suggest some fun educational activities for a 3-year-old," or "Please tell me a simple dinner recipe using ingredients I have in my refrigerator."

[0491] In this way, it is possible to reduce the workload within the home while improving the quality of life for the user and their family.

[0492] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0493] Step 1:

[0494] The server acquires data from electronic devices within the home. For example, it collects information such as refrigerator inventory and washing machine usage status via APIs. The input is digital data provided by each device, and the output is integrated, real-time household status data. This data is then used to prepare for analysis in the next step.

[0495] Step 2:

[0496] The server analyzes the acquired data. For example, it analyzes information about the ingredients in the refrigerator and performs data calculations to determine their freshness and remaining quantity. The input is the household situation data obtained in step 1, and the output generates a list of ingredients suitable for tonight's dinner or a list of ingredients that need to be repurchased. This forms the basis for suggestions tailored to the user's needs.

[0497] Step 3:

[0498] The server generates suggestions for the user using a generative AI model. Specifically, it suggests recipes or designs childcare activities based on the user's schedule and refrigerator information. The input is the ingredient list and childcare information obtained in step 2, and the output is "recommended recipes" or "suggestions for educational activities." Natural language processing technology is used in the generative AI model at this time.

[0499] Step 4:

[0500] The server notifies the user's device of the generated suggestions. The input is the output data from step 3, and the notification information, formatted based on this data, is sent to the device. The output is the specific suggestion content displayed on the notification screen of the user's smartphone or tablet. The user can review this and use it to improve their daily activities.

[0501] Step 5:

[0502] The terminal receives feedback from users. Users input their thoughts and results regarding the proposed content as feedback. This input is user feedback information, which the server receives and outputs. The server analyzes this data and uses it as foundational data to improve the accuracy of future proposals.

[0503] Step 6:

[0504] The server performs the system's learning process based on the collected feedback data. The feedback information obtained in step 5 is used as input, and the output is an improved proposed algorithm or an updated generative AI model. This improves the overall system performance and provides users with more customized support.

[0505] (Application Example 1)

[0506] 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."

[0507] Managing household affairs and the burden of childcare are significant challenges for many families. Furthermore, the influence of external factors and the difficulty of managing time outside the home are major sources of stress for busy modern people. Conventional technologies have only been able to manage individual household devices and provide childcare support; they have been unable to comprehensively manage information both inside and outside the home and optimize the user's overall life.

[0508] 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.

[0509] In this invention, the server includes means for communicating with multiple electrical devices in the home and optimizing household tasks based on this, means for acquiring information about the external environment and making suggestions best suited to the user's life, and means for enabling operation from outside the home and performing remote monitoring. This makes it possible to provide appropriate support tailored to the individual needs of the user, both inside and outside the home, and to reduce the burden of housework and childcare.

[0510] "Multiple electrical appliances in the home" refers to various electrical appliances installed in a home that can be connected via a network, such as refrigerators, washing machines, and air conditioners.

[0511] "Communicating" refers to the process of sending and receiving data, meaning the transmission of information between electrical equipment and a server.

[0512] "Optimizing household tasks" refers to organizing and adjusting the order and content of household chores in order to perform them efficiently.

[0513] "Managing user schedules" means recording each individual's schedule and coordinating activities based on that schedule.

[0514] "Child developmental stages and interests" refers to information about a child's age, mental development, and the things they are particularly interested in.

[0515] "Using generative artificial intelligence" means utilizing algorithms that automatically create new content and suggestions from data through machine learning.

[0516] "External environment information" refers to data collected from outside the home regarding factors that affect daily life, such as weather, traffic conditions, and local events.

[0517] "User terminal" refers to devices used directly by the user, such as smartphones, tablets, and smart glasses, that can communicate with the server.

[0518] "Remote monitoring" refers to a method of observing and checking the situation inside a home from an external location, and taking action as needed.

[0519] "Learning to accumulate data and make improved suggestions" refers to the machine learning process of collecting and analyzing past data to improve the accuracy of future suggestions.

[0520] To realize this invention, the server communicates with multiple electrical devices through the home network and acquires real-time status data for each device. This includes a refrigerator equipped with a temperature sensor and a washing machine whose usage is monitored. Based on this data, the server is designed to optimize household chores and suggest the most suitable tasks at the appropriate time. The server also collects and analyzes external environmental information such as weather and traffic conditions to provide dynamic suggestions for optimizing the user's overall life.

[0521] The user's device receives notifications sent from the server and functions as an interface for user interaction. Smartphones and tablets are primarily used as devices, through which users receive suggestions tailored to their environment both inside and outside the home. Furthermore, users can operate devices from outside the home using their devices, enabling remote control and monitoring of the home environment.

[0522] Generative artificial intelligence is implemented on the server as a module for generating educational activities and stories based on a child's developmental stage. The generative AI model utilizes user feedback to continuously improve the quality of the content it provides. It learns from data obtained through everyday interactions within the family to improve the accuracy of its suggestions.

[0523] For example, a server could analyze sensor data from a washing machine to detect available time slots and then suggest the optimal washing time based on the user's schedule. Furthermore, a generative AI model could, for instance, detect a child's interest in a particular animal and generate educational content related to that animal.

[0524] An example of a prompt message would be: "Please check the operating status of the household washing machine and suggest the optimal washing time. The user has time tomorrow morning." This invention makes it possible to comprehensively manage information both inside and outside the home and provide the user with optimized lifestyle support.

[0525] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0526] Step 1:

[0527] The server acquires real-time status data from each electrical appliance via the home network. This input data includes things like refrigerator temperature and washing machine operating status. Based on the acquired data, it can understand the current state of the home. The data is stored in a database and used in subsequent processing steps.

[0528] Step 2:

[0529] The server matches acquired device status data with the user's scheduled activities and executes an algorithm to plan the most suitable household tasks. For example, if the washing machine is free and the user has free time, it will create a laundry suggestion. The input data consists of device status data and the user's schedule, and based on this, an optimized task suggestion is output.

[0530] Step 3:

[0531] The server acquires external environmental information, including weather and traffic conditions, and retrieves data from external APIs via the internet. This input data provides elements to be considered in order to support the user's life, and appropriate suggestions are generated based on this. The acquired data is processed to model the impact of predicted conditions on the user.

[0532] Step 4:

[0533] The server uses a generative AI model to generate educational activities tailored to the child's interests and developmental stage. Based on user input and past data, the AI ​​generates relevant content, which is then output to the device as educational content. This process utilizes natural language processing technology, with generation based on prompt text.

[0534] Step 5:

[0535] The terminal notifies the user of suggestions from the server. The user receives these suggestions and provides feedback as needed. The input data is user feedback, which the server uses to update its machine learning model to improve the accuracy of future suggestions. Based on user interaction, the terminal provides an intuitive interface.

[0536] Step 6:

[0537] The server uses historical data accumulated in the system to perform analysis to further improve the suggestions. This includes past suggestion history and user behavior patterns. The input data is this historical data, and the output is a more accurate suggestion for the next time. Statistical analysis and machine learning techniques are used in this step.

[0538] 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.

[0539] This invention is a system that automates household life management and provides a personalized experience through user emotion recognition. By incorporating an emotion engine, this system enables user emotion-based interaction and improves the quality of household and childcare support.

[0540] Configuration and operation details

[0541] System configuration:

[0542] This system consists of a server, user terminals, household electrical appliances, and an emotion engine. The server manages communication between each component and aggregates and analyzes data. The emotion engine is responsible for recognizing the user's emotions through facial expression analysis cameras and voice recognition devices.

[0543] Server operation:

[0544] The server communicates with home appliances to optimize household tasks and automates the scheduling of household and childcare tasks using the user's calendar data. It also uses generative artificial intelligence to generate educational activities tailored to the child's development. This information is transmitted to the user's terminal in real time.

[0545] How the emotion engine works:

[0546] The emotion engine analyzes the user's emotions at that moment from their facial expressions and voice input. If the emotions are positive, it can suggest household chores and childcare tasks more proactively; if the emotions are negative, it will suggest things that prioritize relaxation and support.

[0547] Interaction process:

[0548] The user terminal notifies the user of tasks and suggestions through an intuitive user interface, based on information received from the server. User feedback is returned to the server via the terminal, contributing to improvements in the accuracy of future suggestions and actions.

[0549] Specific example

[0550] For example, when a user is tired, the emotion engine recognizes this and recommends relaxing activities. Based on this, the server instructs the smart speaker to play music, while simultaneously suggesting easy dinner recipes from the refrigerator. This makes it possible to maintain harmony and comfort within the home without requiring any effort from the user.

[0551] By implementing this system, the burden of housework and childcare within the home can be effectively reduced, improving the quality of life for individuals and families. The aim is to provide a more personalized and effective support environment through responses that take emotions into consideration.

[0552] The following describes the processing flow.

[0553] Step 1:

[0554] The server connects to each electrical appliance in the home via a network and retrieves data in real time. For example, it can retrieve inventory information from the refrigerator and check the usage status of the washing machine.

[0555] Step 2:

[0556] The server optimizes household tasks based on the acquired data. For example, it identifies recipes that can be suggested based on the contents of the refrigerator and adjusts the schedules of each appliance.

[0557] Step 3:

[0558] The emotion engine analyzes the user's facial expressions and voice in real time to recognize their emotional state. For example, it can detect a user's smile using the camera or sense fatigue from their voice.

[0559] Step 4:

[0560] The server adjusts the priority and content of household and childcare tasks based on the recognized emotional state. If the emotion is positive, it suggests active activities; if the emotion is negative, it creates a plan that prioritizes relaxation.

[0561] Step 5:

[0562] The server sends the created tasks and suggestions to the terminal. The terminal receives them and displays them to the user as notifications.

[0563] Step 6:

[0564] Users will see suggested tasks and activities through notifications on their devices and perform them as needed. They will also decide which activities to choose based on the information provided.

[0565] Step 7:

[0566] Users send feedback about their selected activities and the emotions they experienced to the server via their device.

[0567] Step 8:

[0568] The server integrates user feedback and stores it as learning data to improve the quality of future suggestions. This allows the system to provide more personalized support that is better suited to the user.

[0569] (Example 2)

[0570] 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."

[0571] In modern homes, multiple electronic devices and the management of daily schedules are scattered, requiring significant time and effort for each operation and management. Furthermore, there is a lack of adaptive support and suggestions based on the individual circumstances and emotions of users, compromising comfort and efficiency within the home. Addressing these challenges and fostering harmony within the home is essential.

[0572] 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.

[0573] In this invention, the server includes means for communicating with multiple electronic devices in the home and optimizing device operation tasks, means for analyzing the user's emotional state and using generative artificial intelligence to generate individual activities based on the analysis results, and means for accumulating user data and learning to make more effective suggestions. This makes it possible to comprehensively manage all devices and schedules in the home and provide services adapted to the user's state.

[0574] "Electronic devices" refer to all devices and equipment used in the home that require electricity and are capable of communication and operation.

[0575] A "device operation task" refers to a series of operations and setting procedures necessary to ensure that electronic devices in the home function properly.

[0576] "Users" refer to individual individuals within a household who use this system and are the entities that provide emotional data and schedules.

[0577] "Generative artificial intelligence" refers to a computer program that can generate new suggestions and activities based on input data.

[0578] A "user terminal" is a device used by users to interact with the system, and it is capable of providing information notifications and feedback.

[0579] "Learning methods" refer to methods for improving the performance of a system and the accuracy of its suggestions based on accumulated data.

[0580] "Emotional state" refers to the user's internal emotional condition, and is the result of analysis based on facial expression data and voice input.

[0581] "External services" refer to services and support provided outside the home, and can be coordinated as needed.

[0582] This invention is a system that provides users with a personalized experience by integrating in-home electronic devices and schedule management.

[0583] The server plays a central role in optimizing device operation tasks by managing communication with multiple electronic devices within the home. For example, the server controls smart home devices, optimizing the operation of lighting, music players, and air conditioning systems. Furthermore, the server accumulates user data and continuously improves its suggestions using learning algorithms.

[0584] By using emotion recognition technology, the system analyzes the user's instantaneous emotional state and generates appropriate activities using a generative artificial intelligence (AI) model. For example, it collects the user's emotional data through a facial recognition camera and a voice recognition device, and if it determines that relaxation is needed, it suggests calming music.

[0585] The user terminal is a device that communicates bidirectionally with the server and serves as an interface for notifications and interaction. This allows the user to review suggested tasks and activities and provide reactions to the options. For example, they can instantly provide feedback such as, "I like this music."

[0586] For example, if the emotion engine detects that the user is tired, the server will instruct the smart speaker to play relaxing music while simultaneously suggesting easy cooking recipes based on the ingredients in the refrigerator. Furthermore, if the user is in a motivated state, the system will suggest activating a cleaning robot to support more efficient household chores.

[0587] Examples of prompts generated using AI models include specific instructions such as, "Please select music suitable for when the user is currently feeling relaxed," or "Please create a schedule for efficiently performing household chores based on the user's availability." This improves the quality of life within the home and provides flexible, personalized support tailored to the user.

[0588] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0589] Step 1:

[0590] The user provides emotional data through a facial expression analysis camera and a voice recognition device. These devices collect emotion-related data from the user's facial expressions and voice. Inputs include facial image data and voice tone, and output is numerical data indicating the emotional state. This data is sent to a server and used in subsequent analysis steps.

[0591] Step 2:

[0592] The server analyzes the received emotional data using an emotion engine and determines the optimal interaction for the user using generative artificial intelligence. This analysis involves data processing to identify emotional states, such as determining that the user "needs to relax." It then generates prompt statements and determines appropriate suggestions. This process produces activity suggestions for the user as output.

[0593] Step 3:

[0594] The server communicates the generated activity suggestions to electronic devices in the home. Specific actions include instructing a smart speaker to play music or suggesting a suitable recipe from a list of ingredients in the refrigerator. At this stage, the input becomes the suggested content, and the output is distributed within the home as specific instructions or notifications.

[0595] Step 4:

[0596] The user terminal receives notifications from the server and notifies the user of suggestions and tasks through the interface. The user can review the interaction content and provide feedback. The input is suggestion information from the server, and the output is the user's selection or feedback. In this way, the system accumulates user responses in real time and uses them for future interactions.

[0597] Step 5:

[0598] The server collects and analyzes user feedback data. This activates the system's learning algorithms, improving the accuracy and personalization of suggestions. Using feedback data as input, an improved suggestion algorithm is obtained as output. This process is continuous, contributing to the optimization of the home life experience.

[0599] (Application Example 2)

[0600] 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."

[0601] In modern households, many tasks such as housework and childcare are not effectively managed, placing a burden on users. Furthermore, there is a lack of personalized support tailored to individual circumstances and emotions. Therefore, there is a need for a system that provides an optimal environment and support that responds to the emotional state of each user while maintaining harmony within the family.

[0602] 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.

[0603] This invention includes a server that communicates with multiple devices in the home and optimizes work tasks based on this communication; a server that manages the user's schedule and automatically plans work and childcare tasks based on the schedule; and a server that uses generative artificial intelligence to analyze the child's developmental stage and interests and generate appropriate educational activities. This makes it possible to analyze the user's emotions, adjust the home environment based on these emotions, and provide personalized support.

[0604] "Appliances" is a general term for communication-enabled electrical equipment and devices used within a household.

[0605] "Work tasks" refer to a series of activities related to housework and childcare performed within the home, and require efficient management.

[0606] "Schedules" refer to information that indicates a user's daily schedule or events, and are managed by the system.

[0607] "Developmental stages" refer to specific periods in a child's developmental process and serve as criteria for determining educational activities.

[0608] "Educational activities" is a general term for activities conducted to promote knowledge and abilities appropriate to a child's development.

[0609] "Generative artificial intelligence" refers to artificial intelligence technology that can generate new information and suggestions based on given data.

[0610] "Emotions" refer to the state of mind analyzed from the user's facial expression data and voice input, and are an important element for the system to provide the user with the optimal environment.

[0611] "Environment" refers to factors that affect user comfort, including lighting, sound, and temperature within the home.

[0612] "Support" refers to the assistance and services provided to help users in their daily lives, and the content of these services is personalized.

[0613] The system for implementing this invention mainly consists of a server, a user terminal, multiple household appliances, and an emotion analysis engine. The server communicates with household appliances and collects and manages information to optimize work tasks. For example, home appliances, including smart lighting and voice assistants, are adjusted based on instructions from the server. The server also has the function of generating educational activities tailored to a child's developmental stage and interests using generative artificial intelligence. This information is transmitted to the user terminal, which the user receives through an intuitive interface.

[0614] The emotion analysis engine calculates real-time emotions by analyzing the user's facial expressions and voice using cameras and voice recognition devices. For example, if a user wants to relax after returning home, the server uses the data obtained from the emotion analysis engine to instruct home appliances to dim the lights in the room and play music suitable for relaxation.

[0615] As a concrete example, when a user returns home feeling tired in the evening, the system detects this emotion and automatically switches to "relaxation mode." In this mode, soft lighting and quiet background music are set, and the user's preferred simple dinner menu is suggested on the user's device.

[0616] An example of a prompt using a generative AI model might be, "Please tell me what settings are possible if I want to create a relaxing environment for myself." This prompt is used to generate suggestions for optimal environment settings through the model.

[0617] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0618] Step 1:

[0619] The server communicates with household appliances and retrieves status data for each appliance. Inputs include the appliance's ID and current status, while outputs include the appliance's operating status and configuration information. This data is used to optimize tasks in the next step.

[0620] Step 2:

[0621] The server automatically plans work tasks based on the user's schedule. Inputs include calendar information and priority settings, and the output is an optimized work schedule. This enables efficient and streamlined scheduling.

[0622] Step 3:

[0623] The server uses generative artificial intelligence to generate educational activities tailored to a child's developmental stage and interests. Input includes information about the child's age and interests, and output provides suggestions for appropriate educational activities. This provides concrete activities that contribute to the child's development.

[0624] Step 4:

[0625] The emotion analysis engine analyzes the user's facial expressions and voice data to calculate their current emotion. It takes camera footage and audio as input and outputs the user's emotional state. This analysis result is used to provide support tailored to the user's needs.

[0626] Step 5:

[0627] The server adjusts the lighting and sound in the home based on the results of emotion analysis. The user's emotional state is the input, and specific appliance setting instructions are generated as the output. For example, if the user needs to relax, instructions are sent to dim the lights and play music.

[0628] Step 6:

[0629] The user terminal receives information from the server and notifies the user through an intuitive and easy-to-understand user interface. Inputs include instructions and suggestions from the server, while outputs include visual notifications and operational guidance. This allows the user to easily manage their home environment.

[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] The system based on this invention provides efficient management of household electrical appliances and features autonomous AI functions for childcare support. This system consists of a server, a user terminal, and electrical appliances that can communicate with each other.

[0648] The overall flow is as follows:

[0649] Optimizing home appliance management and household tasks

[0650] The server communicates with household electrical appliances via the network and retrieves real-time data from each device. For example, it can collect information such as the inventory status of the refrigerator and the operating status of the washing machine.

[0651] Based on this information, the server automatically optimizes household tasks. For example, the server analyzes the remaining ingredients in the refrigerator, suggests the best dinner recipe for the user, and creates a shopping list of necessary items.

[0652] The tasks created are added to the user's calendar and sent as notifications to their device. Based on these notifications, the user can check their daily household chore schedule.

[0653] Provision of childcare support

[0654] To support children's daily growth and activities based on their interests, the server analyzes user input and past data.

[0655] By utilizing generative AI, the server generates educational activities tailored to a child's developmental stage, as well as original stories designed to pique their interest.

[0656] These contents are periodically notified to users via their devices and used as suggestions to enrich the time spent with their children.

[0657] Interaction and Feedback

[0658] The device also has the functionality to accept input and feedback from the user when notifying the user of tasks and suggestions.

[0659] This allows the server to improve the accuracy of future suggestions by inputting the results of actions taken based on the suggestions provided by the user, as well as changes to their own schedule.

[0660] Users can easily interact with this system through an intuitive interface, allowing them to receive customized support tailored to their specific needs.

[0661] This system makes it possible to reduce the burden on households and improve the quality of life for users and their families. A concrete example is that on busy weekday mornings, necessary household chores can be completed automatically based on a pre-set schedule, allowing users to enjoy a more relaxed lifestyle. Thus, the aim of this invention is to increase time efficiency within the home while simultaneously increasing happy time spent with family.

[0662] The following describes the processing flow.

[0663] Step 1:

[0664] The server connects to various electrical appliances in the home and retrieves real-time data from them. For example, it can retrieve information on the refrigerator's inventory and the washing machine's operating status.

[0665] Step 2:

[0666] The server analyzes the acquired data and develops a plan to optimize household tasks. For example, it might select recipes needed for tonight's dinner based on the availability of ingredients.

[0667] Step 3:

[0668] The server sends instructions for optimized household tasks to home appliances. For example, it might instruct a robotic vacuum cleaner to clean the living room or set the air conditioner to maintain a constant temperature.

[0669] Step 4:

[0670] The server records the child's developmental status and analyzes user input. Based on this data, generative artificial intelligence is used to generate learning and play content suitable for the child.

[0671] Step 5:

[0672] The server notifies the terminal of the generated suggestions and tasks. The terminal provides the user with an interface to receive the information.

[0673] Step 6:

[0674] Users check notifications on their devices and obtain detailed task information. They can then review and carry out household chores and childcare activities as needed.

[0675] Step 7:

[0676] Users send feedback to the server via their devices. This allows the server to accumulate data to improve the accuracy of future suggestions and contribute to the overall improvement of the system.

[0677] (Example 1)

[0678] 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".

[0679] Daily household tasks and childcare activities are time-consuming and laborious, which can impair household efficiency and quality of life. Furthermore, effectively managing household electronic devices and providing appropriate educational activities tailored to a child's developmental stage are challenging for many families. There is a need for systems that efficiently address these challenges and improve users' lives.

[0680] 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.

[0681] In this invention, the server includes means for sending and receiving data with multiple electronic devices in the home and optimizing household tasks based on the acquired information; means for managing the user's activity schedule and automatically constructing household and childcare tasks based on the schedule; and means for analyzing the child's developmental stage and interests and using generative machine learning to generate appropriate educational activities. This makes it possible to improve the efficiency of household tasks and provide appropriate educational support for children.

[0682] "Electronic devices" are devices that can send and receive data and assist in performing various tasks within the home.

[0683] "Household work" refers to all activities related to housework and childcare in daily life.

[0684] "Data transmission and reception" refers to the act of exchanging information between a server and other devices or systems.

[0685] "Activity schedule" refers to the daily schedule or plan set by the user.

[0686] "Generative machine learning" is an artificial intelligence technology that analyzes data and generates new information and suggestions.

[0687] "Educational activities" refer to tasks and experiences designed to promote the development of children's knowledge and skills.

[0688] "Analysis" is the process of examining information in detail and understanding its structure and meaning.

[0689] This invention is a comprehensive system for improving work efficiency within the home and providing childcare support. The system consists of a server, user terminals, and a network including multiple electronic devices.

[0690] The server communicates with each electronic device in the home to obtain real-time data such as food inventory information and the operating status of household appliances. It uses APIs provided by each electronic device for data collection. Simultaneously, the server plans household and childcare tasks based on the user's activity schedule and utilizes generative machine learning to generate appropriate information. This process employs AI models that perform natural language processing.

[0691] Specifically, the server can analyze the contents of the refrigerator and suggest a dinner recipe based on the ingredients available at that time. In addition, the server generates a shopping list of necessary ingredients and notifies the user's terminal.

[0692] The device receives notifications from the server and relays them to the user. These notifications include details of scheduled household chores and childcare activities, which the user can review at any time. The user can also provide feedback to the server via the device, and this feedback is used to improve the accuracy of the system's suggestions.

[0693] This invention makes it possible to provide personalized suggestions to the user by prompting them with phrases such as, "Please suggest some fun educational activities for a 3-year-old," or "Please tell me a simple dinner recipe using ingredients I have in my refrigerator."

[0694] In this way, it is possible to reduce the workload within the home while improving the quality of life for the user and their family.

[0695] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0696] Step 1:

[0697] The server acquires data from electronic devices within the home. For example, it collects information such as refrigerator inventory and washing machine usage status via APIs. The input is digital data provided by each device, and the output is integrated, real-time household status data. This data is then used to prepare for analysis in the next step.

[0698] Step 2:

[0699] The server analyzes the acquired data. For example, it analyzes information about the ingredients in the refrigerator and performs data calculations to determine their freshness and remaining quantity. The input is the household situation data obtained in step 1, and the output generates a list of ingredients suitable for tonight's dinner or a list of ingredients that need to be repurchased. This forms the basis for suggestions tailored to the user's needs.

[0700] Step 3:

[0701] The server generates suggestions for the user using a generative AI model. Specifically, it suggests recipes or designs childcare activities based on the user's schedule and refrigerator information. The input is the ingredient list and childcare information obtained in step 2, and the output is "recommended recipes" or "suggestions for educational activities." Natural language processing technology is used in the generative AI model at this time.

[0702] Step 4:

[0703] The server notifies the user's device of the generated suggestions. The input is the output data from step 3, and the notification information, formatted based on this data, is sent to the device. The output is the specific suggestion content displayed on the notification screen of the user's smartphone or tablet. The user can review this and use it to improve their daily activities.

[0704] Step 5:

[0705] The terminal receives feedback from users. Users input their thoughts and results regarding the proposed content as feedback. This input is user feedback information, which the server receives and outputs. The server analyzes this data and uses it as foundational data to improve the accuracy of future proposals.

[0706] Step 6:

[0707] The server performs the system's learning process based on the collected feedback data. The feedback information obtained in step 5 is used as input, and the output is an improved proposed algorithm or an updated generative AI model. This improves the overall system performance and provides users with more customized support.

[0708] (Application Example 1)

[0709] 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".

[0710] Managing household affairs and the burden of childcare are significant challenges for many families. Furthermore, the influence of external factors and the difficulty of managing time outside the home are major sources of stress for busy modern people. Conventional technologies have only been able to manage individual household devices and provide childcare support; they have been unable to comprehensively manage information both inside and outside the home and optimize the user's overall life.

[0711] 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.

[0712] In this invention, the server includes means for communicating with multiple electrical devices in the home and optimizing household tasks based on this, means for acquiring information about the external environment and making suggestions best suited to the user's life, and means for enabling operation from outside the home and performing remote monitoring. This makes it possible to provide appropriate support tailored to the individual needs of the user, both inside and outside the home, and to reduce the burden of housework and childcare.

[0713] "Multiple electrical appliances in the home" refers to various electrical appliances installed in a home that can be connected via a network, such as refrigerators, washing machines, and air conditioners.

[0714] "Communicating" refers to the process of sending and receiving data, meaning the transmission of information between electrical equipment and a server.

[0715] "Optimizing household tasks" refers to organizing and adjusting the order and content of household chores in order to perform them efficiently.

[0716] "Managing user schedules" means recording each individual's schedule and coordinating activities based on that schedule.

[0717] "Child developmental stages and interests" refers to information about a child's age, mental development, and the things they are particularly interested in.

[0718] "Using generative artificial intelligence" means utilizing algorithms that automatically create new content and suggestions from data through machine learning.

[0719] "External environment information" refers to data collected from outside the home regarding factors that affect daily life, such as weather, traffic conditions, and local events.

[0720] "User terminal" refers to devices used directly by the user, such as smartphones, tablets, and smart glasses, that can communicate with the server.

[0721] "Remote monitoring" refers to a method of observing and checking the situation inside a home from an external location, and taking action as needed.

[0722] "Learning to accumulate data and make improved suggestions" refers to the machine learning process of collecting and analyzing past data to improve the accuracy of future suggestions.

[0723] To realize this invention, the server communicates with multiple electrical devices through the home network and acquires real-time status data for each device. This includes a refrigerator equipped with a temperature sensor and a washing machine whose usage is monitored. Based on this data, the server is designed to optimize household chores and suggest the most suitable tasks at the appropriate time. The server also collects and analyzes external environmental information such as weather and traffic conditions to provide dynamic suggestions for optimizing the user's overall life.

[0724] The user's device receives notifications sent from the server and functions as an interface for user interaction. Smartphones and tablets are primarily used as devices, through which users receive suggestions tailored to their environment both inside and outside the home. Furthermore, users can operate devices from outside the home using their devices, enabling remote control and monitoring of the home environment.

[0725] Generative artificial intelligence is implemented on the server as a module for generating educational activities and stories based on a child's developmental stage. The generative AI model utilizes user feedback to continuously improve the quality of the content it provides. It learns from data obtained through everyday interactions within the family to improve the accuracy of its suggestions.

[0726] For example, a server could analyze sensor data from a washing machine to detect available time slots and then suggest the optimal washing time based on the user's schedule. Furthermore, a generative AI model could, for instance, detect a child's interest in a particular animal and generate educational content related to that animal.

[0727] An example of a prompt message would be: "Please check the operating status of the household washing machine and suggest the optimal washing time. The user has time tomorrow morning." This invention makes it possible to comprehensively manage information both inside and outside the home and provide the user with optimized lifestyle support.

[0728] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0729] Step 1:

[0730] The server acquires real-time status data from each electrical appliance via the home network. This input data includes things like refrigerator temperature and washing machine operating status. Based on the acquired data, it can understand the current state of the home. The data is stored in a database and used in subsequent processing steps.

[0731] Step 2:

[0732] The server matches acquired device status data with the user's scheduled activities and executes an algorithm to plan the most suitable household tasks. For example, if the washing machine is free and the user has free time, it will create a laundry suggestion. The input data consists of device status data and the user's schedule, and based on this, an optimized task suggestion is output.

[0733] Step 3:

[0734] The server acquires external environmental information, including weather and traffic conditions, and retrieves data from external APIs via the internet. This input data provides elements to be considered in order to support the user's life, and appropriate suggestions are generated based on this. The acquired data is processed to model the impact of predicted conditions on the user.

[0735] Step 4:

[0736] The server uses a generative AI model to generate educational activities tailored to the child's interests and developmental stage. Based on user input and past data, the AI ​​generates relevant content, which is then output to the device as educational content. This process utilizes natural language processing technology, with generation based on prompt text.

[0737] Step 5:

[0738] The terminal notifies the user of suggestions from the server. The user receives these suggestions and provides feedback as needed. The input data is user feedback, which the server uses to update its machine learning model to improve the accuracy of future suggestions. Based on user interaction, the terminal provides an intuitive interface.

[0739] Step 6:

[0740] The server uses historical data accumulated in the system to perform analysis to further improve the suggestions. This includes past suggestion history and user behavior patterns. The input data is this historical data, and the output is a more accurate suggestion for the next time. Statistical analysis and machine learning techniques are used in this step.

[0741] 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.

[0742] This invention is a system that automates household life management and provides a personalized experience through user emotion recognition. By incorporating an emotion engine, this system enables user emotion-based interaction and improves the quality of household and childcare support.

[0743] Configuration and operation details

[0744] System configuration:

[0745] This system consists of a server, user terminals, household electrical appliances, and an emotion engine. The server manages communication between each component and aggregates and analyzes data. The emotion engine is responsible for recognizing the user's emotions through facial expression analysis cameras and voice recognition devices.

[0746] Server operation:

[0747] The server communicates with home appliances to optimize household tasks and automates the scheduling of household and childcare tasks using the user's calendar data. It also uses generative artificial intelligence to generate educational activities tailored to the child's development. This information is transmitted to the user's terminal in real time.

[0748] How the emotion engine works:

[0749] The emotion engine analyzes the user's emotions at that moment from their facial expressions and voice input. If the emotions are positive, it can suggest household chores and childcare tasks more proactively; if the emotions are negative, it will suggest things that prioritize relaxation and support.

[0750] Interaction process:

[0751] The user terminal notifies the user of tasks and suggestions through an intuitive user interface, based on information received from the server. User feedback is returned to the server via the terminal, contributing to improvements in the accuracy of future suggestions and actions.

[0752] Specific example

[0753] For example, when a user is tired, the emotion engine recognizes this and recommends relaxing activities. Based on this, the server instructs the smart speaker to play music, while simultaneously suggesting easy dinner recipes from the refrigerator. This makes it possible to maintain harmony and comfort within the home without requiring any effort from the user.

[0754] By implementing this system, the burden of housework and childcare within the home can be effectively reduced, improving the quality of life for individuals and families. The aim is to provide a more personalized and effective support environment through responses that take emotions into consideration.

[0755] The following describes the processing flow.

[0756] Step 1:

[0757] The server connects to each electrical appliance in the home via a network and retrieves data in real time. For example, it can retrieve inventory information from the refrigerator and check the usage status of the washing machine.

[0758] Step 2:

[0759] The server optimizes household tasks based on the acquired data. For example, it identifies recipes that can be suggested based on the contents of the refrigerator and adjusts the schedules of each appliance.

[0760] Step 3:

[0761] The emotion engine analyzes the user's facial expressions and voice in real time to recognize their emotional state. For example, it can detect a user's smile using the camera or sense fatigue from their voice.

[0762] Step 4:

[0763] The server adjusts the priority and content of household and childcare tasks based on the recognized emotional state. If the emotion is positive, it suggests active activities; if the emotion is negative, it creates a plan that prioritizes relaxation.

[0764] Step 5:

[0765] The server sends the created tasks and suggestions to the terminal. The terminal receives them and displays them to the user as notifications.

[0766] Step 6:

[0767] Users will see suggested tasks and activities through notifications on their devices and perform them as needed. They will also decide which activities to choose based on the information provided.

[0768] Step 7:

[0769] Users send feedback about their selected activities and the emotions they experienced to the server via their device.

[0770] Step 8:

[0771] The server integrates user feedback and stores it as learning data to improve the quality of future suggestions. This allows the system to provide more personalized support that is better suited to the user.

[0772] (Example 2)

[0773] 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".

[0774] In modern homes, multiple electronic devices and the management of daily schedules are scattered, requiring significant time and effort for each operation and management. Furthermore, there is a lack of adaptive support and suggestions based on the individual circumstances and emotions of users, compromising comfort and efficiency within the home. Addressing these challenges and fostering harmony within the home is essential.

[0775] 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.

[0776] In this invention, the server includes means for communicating with multiple electronic devices in the home and optimizing device operation tasks, means for analyzing the user's emotional state and using generative artificial intelligence to generate individual activities based on the analysis results, and means for accumulating user data and learning to make more effective suggestions. This makes it possible to comprehensively manage all devices and schedules in the home and provide services adapted to the user's state.

[0777] "Electronic devices" refer to all devices and equipment used in the home that require electricity and are capable of communication and operation.

[0778] A "device operation task" refers to a series of operations and setting procedures necessary to ensure that electronic devices in the home function properly.

[0779] "Users" refer to individual individuals within a household who use this system and are the entities that provide emotional data and schedules.

[0780] "Generative artificial intelligence" refers to a computer program that can generate new suggestions and activities based on input data.

[0781] A "user terminal" is a device used by users to interact with the system, and it is capable of providing information notifications and feedback.

[0782] "Learning methods" refer to methods for improving the performance of a system and the accuracy of its suggestions based on accumulated data.

[0783] "Emotional state" refers to the user's internal emotional condition, and is the result of analysis based on facial expression data and voice input.

[0784] "External services" refer to services and support provided outside the home, and can be coordinated as needed.

[0785] This invention is a system that provides users with a personalized experience by integrating in-home electronic devices and schedule management.

[0786] The server plays a central role in optimizing device operation tasks by managing communication with multiple electronic devices within the home. For example, the server controls smart home devices, optimizing the operation of lighting, music players, and air conditioning systems. Furthermore, the server accumulates user data and continuously improves its suggestions using learning algorithms.

[0787] By using emotion recognition technology, the system analyzes the user's instantaneous emotional state and generates appropriate activities using a generative artificial intelligence (AI) model. For example, it collects the user's emotional data through a facial recognition camera and a voice recognition device, and if it determines that relaxation is needed, it suggests calming music.

[0788] The user terminal is a device that communicates bidirectionally with the server and serves as an interface for notifications and interaction. This allows the user to review suggested tasks and activities and provide reactions to the options. For example, they can instantly provide feedback such as, "I like this music."

[0789] For example, if the emotion engine detects that the user is tired, the server will instruct the smart speaker to play relaxing music while simultaneously suggesting easy cooking recipes based on the ingredients in the refrigerator. Furthermore, if the user is in a motivated state, the system will suggest activating a cleaning robot to support more efficient household chores.

[0790] Examples of prompts generated using AI models include specific instructions such as, "Please select music suitable for when the user is currently feeling relaxed," or "Please create a schedule for efficiently performing household chores based on the user's availability." This improves the quality of life within the home and provides flexible, personalized support tailored to the user.

[0791] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0792] Step 1:

[0793] The user provides emotional data through a facial expression analysis camera and a voice recognition device. These devices collect emotion-related data from the user's facial expressions and voice. Inputs include facial image data and voice tone, and output is numerical data indicating the emotional state. This data is sent to a server and used in subsequent analysis steps.

[0794] Step 2:

[0795] The server analyzes the received emotional data using an emotion engine and determines the optimal interaction for the user using generative artificial intelligence. This analysis involves data processing to identify emotional states, such as determining that the user "needs to relax." It then generates prompt statements and determines appropriate suggestions. This process produces activity suggestions for the user as output.

[0796] Step 3:

[0797] The server communicates the generated activity suggestions to electronic devices in the home. Specific actions include instructing a smart speaker to play music or suggesting a suitable recipe from a list of ingredients in the refrigerator. At this stage, the input becomes the suggested content, and the output is distributed within the home as specific instructions or notifications.

[0798] Step 4:

[0799] The user terminal receives notifications from the server and notifies the user of suggestions and tasks through the interface. The user can review the interaction content and provide feedback. The input is suggestion information from the server, and the output is the user's selection or feedback. In this way, the system accumulates user responses in real time and uses them for future interactions.

[0800] Step 5:

[0801] The server collects and analyzes user feedback data. This activates the system's learning algorithms, improving the accuracy and personalization of suggestions. Using feedback data as input, an improved suggestion algorithm is obtained as output. This process is continuous, contributing to the optimization of the home life experience.

[0802] (Application Example 2)

[0803] 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".

[0804] In modern households, many tasks such as housework and childcare are not effectively managed, placing a burden on users. Furthermore, there is a lack of personalized support tailored to individual circumstances and emotions. Therefore, there is a need for a system that provides an optimal environment and support that responds to the emotional state of each user while maintaining harmony within the family.

[0805] 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.

[0806] This invention includes a server that communicates with multiple devices in the home and optimizes work tasks based on this communication; a server that manages the user's schedule and automatically plans work and childcare tasks based on the schedule; and a server that uses generative artificial intelligence to analyze the child's developmental stage and interests and generate appropriate educational activities. This makes it possible to analyze the user's emotions, adjust the home environment based on these emotions, and provide personalized support.

[0807] "Appliances" is a general term for communication-enabled electrical equipment and devices used within a household.

[0808] "Work tasks" refer to a series of activities related to housework and childcare performed within the home, and require efficient management.

[0809] "Schedules" refer to information that indicates a user's daily schedule or events, and are managed by the system.

[0810] "Developmental stages" refer to specific periods in a child's developmental process and serve as criteria for determining educational activities.

[0811] "Educational activities" is a general term for activities conducted to promote knowledge and abilities appropriate to a child's development.

[0812] "Generative artificial intelligence" refers to artificial intelligence technology that can generate new information and suggestions based on given data.

[0813] "Emotions" refer to the state of mind analyzed from the user's facial expression data and voice input, and are an important element for the system to provide the user with the optimal environment.

[0814] "Environment" refers to factors that affect user comfort, including lighting, sound, and temperature within the home.

[0815] "Support" refers to the assistance and services provided to help users in their daily lives, and the content of these services is personalized.

[0816] The system for implementing this invention mainly consists of a server, a user terminal, multiple household appliances, and an emotion analysis engine. The server communicates with household appliances and collects and manages information to optimize work tasks. For example, home appliances, including smart lighting and voice assistants, are adjusted based on instructions from the server. The server also has the function of generating educational activities tailored to a child's developmental stage and interests using generative artificial intelligence. This information is transmitted to the user terminal, which the user receives through an intuitive interface.

[0817] The emotion analysis engine calculates real-time emotions by analyzing the user's facial expressions and voice using cameras and voice recognition devices. For example, if a user wants to relax after returning home, the server uses the data obtained from the emotion analysis engine to instruct home appliances to dim the lights in the room and play music suitable for relaxation.

[0818] As a concrete example, when a user returns home feeling tired in the evening, the system detects this emotion and automatically switches to "relaxation mode." In this mode, soft lighting and quiet background music are set, and the user's preferred simple dinner menu is suggested on the user's device.

[0819] An example of a prompt using a generative AI model might be, "Please tell me what settings are possible if I want to create a relaxing environment for myself." This prompt is used to generate suggestions for optimal environment settings through the model.

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

[0821] Step 1:

[0822] The server communicates with household appliances and retrieves status data for each appliance. Inputs include the appliance's ID and current status, while outputs include the appliance's operating status and configuration information. This data is used to optimize tasks in the next step.

[0823] Step 2:

[0824] The server automatically plans work tasks based on the user's schedule. Inputs include calendar information and priority settings, and the output is an optimized work schedule. This enables efficient and streamlined scheduling.

[0825] Step 3:

[0826] The server uses generative artificial intelligence to generate educational activities tailored to a child's developmental stage and interests. Input includes information about the child's age and interests, and output provides suggestions for appropriate educational activities. This provides concrete activities that contribute to the child's development.

[0827] Step 4:

[0828] The emotion analysis engine analyzes the user's facial expressions and voice data to calculate their current emotion. It takes camera footage and audio as input and outputs the user's emotional state. This analysis result is used to provide support tailored to the user's needs.

[0829] Step 5:

[0830] The server adjusts the lighting and sound in the home based on the results of emotion analysis. The user's emotional state is the input, and specific appliance setting instructions are generated as the output. For example, if the user needs to relax, instructions are sent to dim the lights and play music.

[0831] Step 6:

[0832] The user terminal receives information from the server and notifies the user through an intuitive and easy-to-understand user interface. Inputs include instructions and suggestions from the server, while outputs include visual notifications and operational guidance. This allows the user to easily manage their home environment.

[0833] 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.

[0834] 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.

[0835] 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.

[0836] 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.

[0837] 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.

[0838] 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.

[0839] 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.

[0840] 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.

[0841] 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."

[0842] 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.

[0843] 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.

[0844] 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.

[0845] 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.

[0846] 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.

[0847] 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.

[0848] 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.

[0849] 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.

[0850] 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.

[0851] 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.

[0852] 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.

[0853] 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.

[0854] The following is further disclosed regarding the embodiments described above.

[0855] (Claim 1)

[0856] A means of communicating with multiple electrical devices in the home and optimizing household tasks based on this communication,

[0857] A means of managing the user's schedule and automatically planning household and childcare tasks based on that schedule,

[0858] A method using generative artificial intelligence to analyze a child's developmental stage and interests and generate appropriate educational activities,

[0859] A means of sending notifications to the user's terminal and accepting user interaction,

[0860] A learning tool for accumulating household data and making improved suggestions,

[0861] A system that includes this.

[0862] (Claim 2)

[0863] The system according to claim 1, comprising an algorithm for providing personalized household and childcare support based on information entered by the user.

[0864] (Claim 3)

[0865] The system according to claim 1, comprising means for controlling multiple electrical appliances in a household and, when necessary, connecting to an external service to procure goods.

[0866] "Example 1"

[0867] (Claim 1)

[0868] A means of sending and receiving data between multiple electronic devices in the home and optimizing home tasks based on the acquired information,

[0869] A means for managing the user's activity schedule and automatically constructing household and childcare tasks based on that schedule,

[0870] A method using generative machine learning to analyze children's developmental stages and interests and generate appropriate educational activities,

[0871] A means of transmitting information to the user's mobile device and receiving communication with the user,

[0872] A means for collecting household information and performing a learning process to make improved suggestions,

[0873] A system that includes this.

[0874] (Claim 2)

[0875] The system according to claim 1, comprising a processing flow for providing personalized household tasks and childcare support based on information entered by the user.

[0876] (Claim 3)

[0877] The system according to claim 1, comprising means for operating multiple electronic devices within a household and, when necessary, connecting to external support to procure goods.

[0878] "Application Example 1"

[0879] (Claim 1)

[0880] A means of communicating with multiple electrical devices in the home and optimizing household tasks based on this communication,

[0881] A means of managing the user's schedule and automatically planning household and childcare tasks based on that schedule,

[0882] A method using generative artificial intelligence to analyze a child's developmental stage and interests and generate appropriate educational activities,

[0883] A means of acquiring information about the external environment and making suggestions that are best suited to the user's life,

[0884] A means to enable operation from outside the home and perform remote monitoring,

[0885] A means of sending notifications to the user's terminal and accepting user interaction,

[0886] A learning tool for accumulating household data and making improved suggestions,

[0887] A system that includes this.

[0888] (Claim 2)

[0889] The system according to claim 1, comprising an algorithm for providing personalized household and childcare support based on information entered by the user, and making suggestions based on external environmental information.

[0890] (Claim 3)

[0891] The system according to claim 1, comprising means for controlling multiple electrical appliances in a household, connecting to external services when necessary to procure goods, and further performing these under optimal conditions by reflecting external environmental information.

[0892] "Example 2 of combining an emotion engine"

[0893] (Claim 1)

[0894] A means for communicating with multiple electronic devices within the home and optimizing device operation tasks,

[0895] A means for managing the user's schedule and automatically planning equipment operation and support tasks based on the schedule,

[0896] A means of using generative artificial intelligence to analyze the emotional state of users and generate individual activities based on the analysis results,

[0897] A means of sending notifications to the user's terminal and receiving the user's response,

[0898] A learning tool to accumulate user data and make more effective suggestions,

[0899] A system that includes this.

[0900] (Claim 2)

[0901] The system according to claim 1, comprising a method for performing personalized device operation and support based on data provided by the user.

[0902] (Claim 3)

[0903] The system according to claim 1, comprising means for controlling multiple electronic devices within a household and procuring supplies in cooperation with external services as needed.

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

[0905] (Claim 1)

[0906] A means of communicating with multiple devices within the home and optimizing work tasks based on this communication,

[0907] A means of managing the user's schedule and automatically planning work and childcare tasks based on that schedule,

[0908] A means of using generative artificial intelligence to analyze a child's developmental stage and interests and generate appropriate educational activities,

[0909] A means of sending information to the user terminal and accepting user interaction,

[0910] A learning tool for accumulating household data and making improved suggestions,

[0911] A means for analyzing emotions from user facial expression data and voice input, and adjusting the lighting and sound environment based on that analysis,

[0912] A system that includes this.

[0913] (Claim 2)

[0914] The system according to claim 1, comprising an algorithm for providing personalized tasks and childcare support based on information entered by the user.

[0915] (Claim 3)

[0916] The system according to claim 1, comprising means for controlling multiple appliances within a household and, when necessary, connecting to external services to procure goods. [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. A means of communicating with multiple electrical devices in the home and optimizing household tasks based on this communication, A means of managing the user's schedule and automatically planning household and childcare tasks based on that schedule, A method using generative artificial intelligence to analyze a child's developmental stage and interests and generate appropriate educational activities, A means of acquiring information about the external environment and making suggestions that are best suited to the user's life, A means to enable operation from outside the home and perform remote monitoring, A means of sending notifications to the user's terminal and accepting user interaction, A learning tool for accumulating household data and making improved suggestions, A system that includes this.

2. The system according to claim 1, comprising an algorithm for providing personalized household and childcare support based on information entered by the user, and making suggestions based on external environmental information.

3. The system according to claim 1, which controls multiple electrical appliances in a household, has means for connecting to external services to procure goods when necessary, and further performs these operations under optimal conditions by reflecting external environmental information.

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