system

Abstract

We provide the system. [Solution] As a means of collection, a means for acquiring status data and schedule data from a home appliance control device, As an analytical method, a means for generating an optimized household activity plan based on acquired data, As a control means, means for transmitting operation instructions to a home appliance control device based on an activity plan, As a monitoring means, it includes a means for monitoring the operating status of the home appliance control device and notifying when an abnormality occurs, As a proposed method, a means of generating and presenting educational activity programs, A system that includes this.

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】 Japanese Patent Application Laid-Open No. 2022-180282 【Summary of the Invention】 【Problems to be Solved by the Invention】 【0004】 In ordinary households, there is a problem that all family members are occupied with childcare, housework, and work, lacking time to pursue individual happiness and the happiness of the whole family. Moreover, these burdens lead to a decline in the marriage rate and birth rate, and as a result, there are problems of also having an adverse impact on the economy of the region and the country. With current technologies, household appliances and IoT devices operate separately, lacking means to integrate and streamline housework and childcare. This makes it difficult for people to have free time and reduces the quality of life. 【Means for Solving the Problems】 【0005】 The present invention solves the above problems by providing an autonomous AI agent system equipped with collection means, analysis means, control means, monitoring means, and proposal means. This system collects data from household appliance control devices and generates an optimized activity plan using a machine learning algorithm based on that data. Based on this, it sends appropriate control signals to the appliance control devices so that each device operates efficiently in an integrated manner. Furthermore, this system improves the overall well-being of the family by proposing educational programs related to childcare and providing the user with the necessary information. In addition, the system itself monitors the situation and notifies the user if there is an abnormality, allowing for peace of mind in entrusting household chores and childcare to it. This removes time constraints and is expected to improve engagement and birth rates. 【0006】 A "data collection means" is a system component that has the function of acquiring data from household appliance control devices. 【0007】 "Analysis tools" are system components that generate plans to optimize household activities based on acquired data. 【0008】 A "control means" is a system component that has the function of transmitting operation instructions to a home appliance control device based on the generated activity plan. 【0009】 A "monitoring device" is a system component that checks the operating status of a home appliance control device and notifies the user when an abnormality occurs. 【0010】 A "proposal means" is a system component that presents educational activity programs to users and has the function of promoting those activities. 【0011】 "Home appliance control devices" is a general term for devices and systems used to control and monitor the operation of home appliances. 【0012】 A "machine learning algorithm" is a computational method that learns patterns from data and predicts future behavior. [Brief explanation of the drawing] 【0013】 [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2, which combines an emotion engine. [Modes for carrying out the invention] 【0014】 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. 【0015】 First, the terms used in the following description will be explained. 【0016】 In the following embodiments, a labeled processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like. 【0017】 In the following embodiments, a labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor. 【0018】 In the following embodiments, a labeled storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like. 【0019】 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). 【0020】 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." 【0021】 [First Embodiment] 【0022】 Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment. 【0023】 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. 【0024】 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). 【0025】 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. 【0026】 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. 【0027】 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. 【0028】 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. 【0029】 Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14. 【0030】 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. 【0031】 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. 【0032】 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. 【0033】 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". 【0034】 The present invention is implemented as an autonomous AI agent system that utilizes IoT devices and home appliance control devices within the home. Sensing and control of this system are mainly performed by a server. One embodiment of the present invention is described below. 【0035】 The server communicates with various IoT devices in the home and collects device status data. This data includes the inventory status of the smart refrigerator, the operating status of the robot vacuum cleaner, and the usage history of the smart washing machine. The server also retrieves the user's digital calendar to keep track of everyone's schedule. 【0036】 The server uses machine learning algorithms to analyze the collected data and develop optimal household and childcare plans. For example, it analyzes the ingredients in the refrigerator to determine the family's meal menu. It also sets the optimal cleaning schedule for the robot vacuum cleaner and instructs it on specific cleaning times. 【0037】 Furthermore, the server generates educational activity programs tailored to the child's age and developmental stage, and proposes them to the user via the device. Educational apps for children are automatically launched at specific times, providing learning opportunities. 【0038】 The device notifies the user and prompts them to take appropriate action if an anomaly occurs. For example, if a washing machine malfunction is detected, it will report the details to the user and suggest the necessary service call. 【0039】 By introducing this system, users can increase the time they spend with their families and improve their quality of life by receiving automated household chores and childcare support. Thus, the embodiment of this invention aims to improve the overall well-being of families and solve the associated social issues. 【0040】 The following describes the processing flow. 【0041】 Step 1: 【0042】 The server collects data from all IoT devices and home appliance control devices. This includes information on the internal inventory of refrigerators, the current location and status of robotic vacuum cleaners, and the usage history of washing machines. 【0043】 Step 2: 【0044】 The server retrieves schedule information for all family members through access to the user's digital calendar. This information is used to understand the family's schedule and individual activity times. 【0045】 Step 3: 【0046】 The server uses machine learning algorithms to analyze the collected data and generate optimal household chore and childcare plans. For example, it can suggest menus based on ingredient information and create cleaning schedules. 【0047】 Step 4: 【0048】 The server sends specific operating instructions to each appliance control unit based on the generated plan. For example, it sets a time for the vacuum cleaner to start cleaning and sends an instruction to the refrigerator to list the necessary groceries. 【0049】 Step 5: 【0050】 The device notifies the user of the plan's contents, requests user approval, or provides information. For example, it might inform the user of the contents of a suggested menu. 【0051】 Step 6: 【0052】 The device runs educational apps and activity programs for the child and reports the progress to the server. During this process, the app is automatically launched to encourage the child to participate. 【0053】 Step 7: 【0054】 The server monitors the device's operation and notifies the user if any abnormalities occur. This includes detecting washing machine malfunctions or obstacles in robotic vacuum cleaners. 【0055】 Step 8: 【0056】 The server collects feedback on anomalies and areas for improvement, and makes adjustments to incorporate them into future activity plans. For example, it optimizes cleaning frequency based on user feedback. 【0057】 (Example 1) 【0058】 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." 【0059】 In modern households, managing household appliances and planning educational activities requires considerable time and effort. Therefore, to improve the quality of life at home, there is a need to build systems that efficiently automate household appliance management and childcare activities, enabling all family members to spend quality time. In particular, providing methods for effectively utilizing data generated by household information technology devices to automatically generate optimal plans is a key challenge. 【0060】 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. 【0061】 In this invention, the server includes means for acquiring status data and time information from information technology devices within the home, means for generating an optimized home activity plan based on the data acquired through machine learning processing, and means for transmitting operation instructions to the information technology devices based on the home activity plan. This enables the automation and efficient management of activities within the home. 【0062】 "In-home information technology devices" is a general term for various electronic devices and sensors used within the home, and they play a role in data collection and communication. 【0063】 "Status data" refers to information that specifically describes the current operating status and usage history of information technology equipment. 【0064】 "Time information" refers to data that indicates the time when a particular action or movement is scheduled to occur, or a historical record of that time. 【0065】 "Machine learning processing" is a computational process that uses algorithms to analyze collected data and perform pattern recognition and prediction. 【0066】 A "family activity plan" is a guideline that optimizes the schedule and procedures for household chores, childcare, and educational activities that should be carried out within the family. 【0067】 An "operation instruction" is a command or instruction sent to an information technology device to perform a specific action. 【0068】 A "developmental stage-appropriate educational activity program" is a plan to provide learning and educational content that is appropriate for the age and developmental stage of children and family members. 【0069】 This invention is implemented as an autonomous system for automating and optimizing various activities within the home. This system primarily operates with a server at its core and cooperates with information technology devices within the home. 【0070】 The server retrieves status and time information from information technology devices placed within the home. This includes inventory information from a smart refrigerator, the operating status of a robotic vacuum cleaner, and the usage history of a smart washing machine. These devices are commonly referred to as "information technology devices." 【0071】 The server uses machine learning algorithms based on the acquired data to generate an optimal household activity plan. The server is equipped with software that includes a generative AI model, which analyzes the data. For example, it can suggest next week's meal menu based on refrigerator inventory information, and instruct a robotic vacuum cleaner on the optimal cleaning schedule. 【0072】 Furthermore, the server automatically suggests educational activity programs tailored to the child's developmental stage. Users receive these programs through their devices, and educational apps are automatically launched at specific times. This system makes it possible to provide educational content that is appropriate for the child. 【0073】 Users receive notifications from their devices and can take appropriate action when an anomaly occurs. For example, if a washing machine malfunction is detected, the device will present the details to the user and suggest contacting a service center if necessary. 【0074】 As a concrete example, when a user enters the prompt "Suggest a meal and education plan for this week," the server quickly returns a suggestion based on data within the household. In this way, the present invention is implemented as a system that contributes to improving the quality of life in the home. 【0075】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0076】 Step 1: 【0077】 The server collects status and time information from information technology devices. Specifically, the server obtains inventory information from smart refrigerators, operating status from robotic vacuum cleaners, and usage history from smart washing machines. Input data is transmitted from each device, received by the server, and stored in a central database as output. 【0078】 Step 2: 【0079】 The server feeds the collected data into a machine learning algorithm for analysis. The input here consists of stored state data and time information, which the machine learning model processes. This process outputs an optimal household activity plan. For example, it analyzes refrigerator inventory information and suggests a weekly meal menu. 【0080】 Step 3: 【0081】 The server sends operational instructions to the information technology device to execute the household activity plan based on the analysis results. Here, the server communicates the optimal household schedule and childcare plan to the device. The input is the plan generated by the server, and the output is specific instructions for each device. For example, for a robotic vacuum cleaner, a schedule including the cleaning start time is set. 【0082】 Step 4: 【0083】 The terminal provides important notifications to the user and prompts them to take action as needed. The input is status monitoring data provided by the server, which is analyzed and output as alerts sent to the user. For example, if a washing machine malfunction is detected, the terminal will notify the user of the details and suggest repairs. 【0084】 Step 5: 【0085】 Based on notifications and suggestions from the device, the user takes manual action as needed. Specifically, they may enter prompt messages to request additional information from the server or arrange for suggested repair services. The input here consists of the user's selections and inputs, and the output is the execution of corresponding instructions and arrangements. 【0086】 (Application Example 1) 【0087】 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." 【0088】 In modern living spaces, there is a need to optimize energy use within individual households while efficiently and effectively managing the overall electricity consumption of the community. With the increase in IoT devices in homes, the challenge lies in effectively utilizing these devices to improve energy efficiency while more appropriately supporting household activities and education. The lack of such systems leads to wasted electricity consumption and inefficient household management, hindering improvements in residents' convenience and quality of life. 【0089】 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. 【0090】 In this invention, the server includes means for acquiring status information and timetable information from an information processing device as a collection means, means for generating an optimized activity plan within the living space based on the acquired information as an analysis means, and means for generating information for optimizing electricity use within the region as a regional energy management means and transmitting control commands based on that information. This makes it possible to optimize electricity consumption not only in individual households but also in the entire region, enabling efficient energy management and improved convenience for residents' lives. 【0091】 "Collection means" refers to devices and methods for acquiring status information and timetable information from an information processing device. 【0092】 "Analysis means" refers to devices or methods for generating an optimized activity plan within a living space based on acquired information. 【0093】 "Control means" refers to devices or methods for transmitting operation commands to an information processing device based on an activity plan. 【0094】 "Monitoring means" refers to devices or methods for monitoring the operating status of an information processing device and notifying the user when an abnormality occurs. 【0095】 "Proposed means" refers to devices or methods for generating and presenting programs for knowledge activities. 【0096】 "Regional energy management means" refers to devices and methods for generating information to optimize electricity use within a region and transmitting control commands based on that information. 【0097】 The system for implementing this invention integrates energy management within homes and communities, centered around a server. The server communicates with an information processing device and uses IoT technology to collect status information and timetable information for each home. Based on this information, the server analyzes the acquired data and generates an optimal activity plan within the living space using generative AI models and machine learning algorithms. Based on this plan, the server sends control commands to home devices to manage activities efficiently. 【0098】 Furthermore, the server generates an integrated power management plan by utilizing local energy management systems to optimize power usage across the entire region, and notifies each household's information processing device of this plan. In particular, it provides specific measures to reduce peak power consumption, ensuring convenience for residents. This makes it possible to improve energy efficiency and the quality of life for local residents. 【0099】 As a concrete example, the server plans for peak power consumption during a hot summer day and uses a prompt message to a generating AI model that says, "Please suggest the optimal air conditioner usage schedule that each household should consider in order to reduce peak power consumption this summer." Based on this instruction, the terminal can suggest things like shifting each household's air conditioner usage schedule to nighttime. Through such a system, sustainable energy management can be realized throughout the entire region as a smart city. 【0100】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0101】 Step 1: 【0102】 The server connects to an information processing unit and acquires status and timetable information from IoT devices within the home. Input is data from IoT devices, and output is raw data aggregated on the server. This data collection allows for an understanding of the activity of devices in each household. 【0103】 Step 2: 【0104】 The server analyzes the collected information using generative AI models and machine learning algorithms. The input is aggregated raw data, and the output is an optimized activity plan for the living space. This analysis determines the optimal operating schedule for home devices. 【0105】 Step 3: 【0106】 The server sends control commands to the information processing unit based on an optimized activity plan. The input is the optimized activity plan, and the output is the specific action command to be executed on the home device. This operation allows the device to run efficiently and reduces unnecessary energy consumption. 【0107】 Step 4: 【0108】 The server uses local energy management tools to develop an integrated management plan for electricity usage. Inputs include household activity plans and total local electricity consumption data, while output is an optimal electricity usage plan. This planning process optimizes electricity consumption across the entire region. 【0109】 Step 5: 【0110】 The terminal notifies each household's information processing device of the formulated electricity usage plan. The input is the optimal electricity usage plan, and the output is the action plan displayed in each household. This notification allows users to take specific actions based on the proposed plan. 【0111】 Step 6: 【0112】 The user adjusts the settings of their home devices according to notifications from the terminal. The input is the notification content from the terminal, and the output is the user's changes to the device settings. This adjustment results in optimized actual power consumption. 【0113】 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. 【0114】 This invention is implemented as an autonomous AI agent system incorporating an emotion engine, utilizing IoT devices and home appliance control devices within the home. This system provides a more personalized experience based on the user's emotional state. 【0115】 The server communicates with multiple IoT devices within the home and collects data. This data includes the status of home appliances and the user's schedule information. The server also uses voice input and camera data from the terminal to analyze the user's emotions using an emotion engine. 【0116】 The emotion engine uses voice analysis and image recognition technologies to identify emotions from the user's voice tone and facial expressions. For example, it can identify whether the user is anxious or relaxed. This emotional information is fed back to the server, and household activities are planned to be adjusted to suit the user's emotions. 【0117】 Next, the server generates an activity plan based on this information and sends specific control commands to devices within the home. For example, if the emotion engine determines that the user is feeling stressed, the server instructs the smart speaker to play relaxing background music. It also instructs smart lights to adjust the room lighting for relaxation. 【0118】 Educational activities are also optimized based on emotional information. The device suggests ways to encourage participation even if the child is not currently interested. For example, if the device analyzes that the child is experiencing stress, it will launch an educational app that includes game elements. 【0119】 Ultimately, the server monitors all devices in the home in real time and notifies the user if any abnormalities are detected. This system enables continuously optimized home management, supporting the user in enjoying their life with peace of mind. Providing a home environment that takes the user's feelings into consideration is an embodiment of the present invention. 【0120】 The following describes the processing flow. 【0121】 Step 1: 【0122】 The server collects status data from IoT devices and home appliance control devices within the home. This includes refrigerator inventory status, robot vacuum cleaner usage status, and smart lighting settings. 【0123】 Step 2: 【0124】 The server acquires the user's schedule data, and at the same time, collects the user's emotional data through an emotion engine using voice input and camera via the terminal. 【0125】 Step 3: 【0126】 The emotion engine analyzes collected voice and facial expression data to identify the user's current emotional state. For example, it can determine whether the user is calm or stressed. 【0127】 Step 4: 【0128】 The server optimizes the home activity plan based on the user's emotional state. For example, if the user is stressed, the plan will incorporate adjustments such as playing relaxing music. 【0129】 Step 5: 【0130】 The server sends operation instructions to the home appliance control unit based on the generated optimization plan. For example, it might change the color and brightness of the lighting or adjust the air conditioning settings. 【0131】 Step 6: 【0132】 The device optimizes suggestions related to children's educational activities based on emotional information. For example, it recommends apps that include game elements to pique a child's interest, even if the child initially shows no interest. 【0133】 Step 7: 【0134】 The server monitors the effectiveness of the appliance operations performed and collects feedback for any anomalies or for further optimization. For example, if the user is still experiencing stress, it will suggest an alternative approach. 【0135】 Step 8: 【0136】 The user evaluates the optimized home environment provided by the system and inputs individual settings and feedback into the system as needed. 【0137】 (Example 2) 【0138】 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." 【0139】 In modern homes, there is a growing demand for personalized optimization of the living environment using home information processing devices and other electronic devices. However, conventional systems struggle to provide appropriate control instructions according to the emotions and states of individual users, and there is a particular problem of insufficient real-time responses based on emotional states. Furthermore, in educational and learning activities, flexible suggestions tailored to children's interests and concerns are not adequately provided. 【0140】 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. 【0141】 In this invention, the server includes, as a collection means, means for acquiring environmental information and time management information from an information processing device; as an analysis means, means for generating an optimized living environment plan based on the acquired data; and as an emotion analysis means, means for collecting emotion information using voice analysis technology and image recognition technology. This makes it possible to provide an optimal living environment based on the user's emotion information and to efficiently support educational activities. 【0142】 "Collection means" refers to the function of acquiring environmental information and time management information from an information processing device. 【0143】 "Analysis tools" refer to the function of generating a plan to optimize the living environment based on the acquired data. 【0144】 A "control means" is a function that instructs the information processing device to perform specific operations based on the generated plan. 【0145】 A "monitoring means" is a function that constantly monitors the operation of the information processing device and immediately notifies the user if an abnormality is detected. 【0146】 "Proposal methods" refer to the function of setting up and presenting programs to efficiently advance learning and educational activities. 【0147】 "Emotion analysis means" refers to a function that recognizes and analyzes individual emotional information using voice analysis technology and image recognition technology. 【0148】 This invention is implemented through an in-home information processing system. It is primarily an autonomous system consisting of a server, terminals, and user interaction, aiming to optimize the living environment and support educational activities. 【0149】 First, the server connects with various sensor devices installed in the home to collect environmental information such as temperature, humidity, and illuminance, as well as user time management information, in real time. This information collection utilizes sensors built into devices such as smartphones and computers. The server uses this data to generate an activity plan to optimize the living environment. 【0150】 Next, the device collects user emotional information using a voice input device and camera. This emotional information is inferred from the user's voice tone and facial expressions using voice analysis and image recognition technologies. Specifically, it determines whether the user is relaxed or stressed. The result of this determination is sent to a server, which generates control commands that are reflected in the devices within the home. 【0151】 Based on this control command, the server sends specific operation instructions to smart devices. For example, if user fatigue is detected, it instructs the smart speaker to play healing music and the smart lights to adjust the lighting to relaxation mode. 【0152】 Furthermore, in educational activities, the device monitors the child's learning progress, and if the child shows no interest, it suggests a learning program incorporating game elements. This suggestion is an important way to capture the child's interest. 【0153】 If a user says "I'm tired today," the emotion analysis tool analyzes the tone, and the server decides to recommend relaxation mode. If the device determines that a child is losing focus during an educational activity, it recommends a quiz-style approach. 【0154】 An example of a prompt message is "Please suggest the optimal device operation based on the user's emotions," which is then input to the generating AI model. 【0155】 This system enables the provision of flexible functions that adapt to the user's emotional state, thereby improving comfort and learning efficiency within the home. 【0156】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0157】 Step 1: 【0158】 The server collects environmental and time management information as input from information processing devices within the home. This input data includes temperature, humidity, illuminance, and the user's schedule. The server analyzes this data and stores it as basic information for optimizing the living environment. Specifically, it aggregates data recorded in real time by smart sensors and prepares it for the next processing stage. 【0159】 Step 2: 【0160】 The device receives voice input from the user and facial expressions captured via the camera as input. Based on this input data, the emotion analysis system uses voice analysis and image recognition technologies to identify the user's emotions. This process analyzes changes in voice tone and facial expressions to identify various emotional states (e.g., relaxed, stressed, anxious). The analyzed emotion information is sent to a server and used in the next step. 【0161】 Step 3: 【0162】 The server receives collected environmental information and analyzed emotional information as input and uses analytical tools to generate a living environment plan. This process utilizes data mining techniques and machine learning algorithms to formulate optimal operational instructions adapted to the user's emotional state. The output is a specific device operation plan. For example, if the room temperature needs to be adjusted, it might include instructions to change the air conditioner settings. 【0163】 Step 4: 【0164】 Based on the generated plan, the server sends control commands as output to various devices in the home. This results in specific actions, such as a smart speaker playing healing music or smart lights adjusting to a warmer color. Each device receives commands from the server and operates according to those instructions. 【0165】 Step 5: 【0166】 The device has a suggestion mechanism specifically designed for educational activities, receiving the child's level of interest during learning as input. Based on the monitoring results, if interest is declining, it generates an output suggesting gamification of the activity. Specifically, this suggestion is made by adding quizzes or mini-games to the interface of the learning app. 【0167】 Step 6: 【0168】 When a user detects an anomaly in their living environment, the server uses monitoring tools to collect that information as input. Upon detecting an anomaly, it immediately sends a notification to the user as output, prompting them to take appropriate action. For example, if a door is left open for an extended period, a warning message is sent to the user's smartphone as a security measure. 【0169】 (Application Example 2) 【0170】 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". 【0171】 Conventional home appliances perform programmed actions without considering the user's emotional state, and therefore fail to adequately address the stress and anxiety users face. Furthermore, there was a need for home appliances that not only provide operation but also offer personalized experiences based on emotional information. Additionally, there was a lack of systems capable of generating activity plans optimized for the home environment and improving quality of life. 【0172】 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. 【0173】 In this invention, the server includes means for acquiring voice and image data and performing emotion analysis, means for generating an optimized home activity plan based on the acquired emotion data, and means for transmitting operation instructions to home devices based on the activity plan. This makes it possible for home devices to operate while taking the user's emotional state into consideration and to provide a personalized experience. 【0174】 "Voice data" refers to information used to record and analyze the user's voice in digital format. 【0175】 "Image data" refers to information used to record and analyze a user's facial expressions and surrounding visual information in digital format. 【0176】 "Emotional analysis" is a process that determines the user's emotional state based on acquired audio and image data. 【0177】 A "home activity plan" is a plan designed to optimize the operation and suggestions of devices at home, based on the user's emotional state and schedule. 【0178】 "Household appliances" refer to home appliances and IoT devices used within the home, and are the entities to which control commands are sent. 【0179】 This invention is a system that collects voice and image data and realizes optimized in-home activities through emotion analysis. The server uses smart devices and computing equipment in the home to acquire voice signals and facial expressions emitted by the user through a camera and microphone. This data is processed by image recognition software and voice analysis software, and the user's emotional state is determined by an emotion engine. 【0180】 Voice analysis identifies emotions by considering factors such as voice tone, speaking speed, and volume. Image recognition reads emotions from eye and mouth movements, and facial muscle tension. The acquired emotion data is sent to a server and used to generate an optimal operating plan for home devices. This operating plan sends commands to home devices to ensure optimal functionality according to the user's emotional state. 【0181】 For example, if the system determines that the user desires relaxation, it will instruct the system to play relaxation music through the speakers. It will also send a command to the smart lights to adjust their brightness to create a calmer environment. Furthermore, for children, when they are feeling stressed, the system will suggest using educational apps that include game elements to keep them engaged. 【0182】 A concrete example of a prompt is, "If the user appears to be having trouble, suggest a fun activity that suits them." Using such prompts makes it easier for the generative AI model to provide support tailored to the user's situation. 【0183】 In this way, the server can continuously adapt to the user's emotions, supporting a safe and comfortable life within the home. 【0184】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0185】 Step 1: 【0186】 The server acquires audio and image data through the home's microphone and camera. During this data collection phase, the user's voice and facial expressions are converted into digital data. The input consists of audio signals and image frames, which are provided to the server's analysis module. 【0187】 Step 2: 【0188】 Based on the voice data acquired by the server, voice analysis software is used to analyze voice tone, speed, and volume. The output is an estimated value of emotion, providing an initial determination of the user's emotional state. By identifying the user's emotional state through data analysis, a corresponding action plan is formulated. 【0189】 Step 3: 【0190】 The server uses image recognition software to analyze the user's facial expressions from image data. At this stage, eye and mouth movements, facial muscle tension, and other factors are evaluated. The input is an image frame, and the output is an emotion estimate. This is then integrated with the audio analysis results to obtain the final emotion data. 【0191】 Step 4: 【0192】 The emotion engine integrates voice and image analysis results to estimate an overall emotional state. This estimation is then used by a plan generation module on the server to develop a household activity plan. 【0193】 Step 5: 【0194】 The server generates an optimal household activity plan and appliance operation plan based on emotional data. The input is integrated emotional data, and the output is specific appliance control commands. Based on this plan, the server sends commands to household appliances to play relaxing music or adjust lighting. 【0195】 Step 6: 【0196】 The user experiences the changes in the home environment provided as a result of Step 5. This enables the implementation of home support that is adapted to the user's current emotional state. 【0197】 Integrated processing enables the automatic adjustment of home appliances based on emotions, thereby improving the user's quality of life. 【0198】 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. 【0199】 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. 【0200】 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. 【0201】 [Second Embodiment] 【0202】 Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment. 【0203】 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. 【0204】 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). 【0205】 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. 【0206】 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. 【0207】 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). 【0208】 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. 【0209】 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. 【0210】 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. 【0211】 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. 【0212】 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. 【0213】 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". 【0214】 The present invention is implemented as an autonomous AI agent system that utilizes IoT devices and home appliance control devices within the home. Sensing and control of this system are mainly performed by a server. One embodiment of the present invention is described below. 【0215】 The server communicates with various IoT devices in the home and collects device status data. This data includes the inventory status of the smart refrigerator, the operating status of the robot vacuum cleaner, and the usage history of the smart washing machine. The server also retrieves the user's digital calendar to keep track of everyone's schedule. 【0216】 The server uses machine learning algorithms to analyze the collected data and develop optimal household and childcare plans. For example, it analyzes the ingredients in the refrigerator to determine the family's meal menu. It also sets the optimal cleaning schedule for the robot vacuum cleaner and instructs it on specific cleaning times. 【0217】 Furthermore, the server generates educational activity programs tailored to the child's age and developmental stage, and proposes them to the user via the device. Educational apps for children are automatically launched at specific times, providing learning opportunities. 【0218】 The device notifies the user and prompts them to take appropriate action if an anomaly occurs. For example, if a washing machine malfunction is detected, it will report the details to the user and suggest the necessary service call. 【0219】 By introducing this system, users can increase the time they spend with their families and improve their quality of life by receiving automated household chores and childcare support. Thus, the embodiment of this invention aims to improve the overall well-being of families and solve the associated social issues. 【0220】 The following describes the processing flow. 【0221】 Step 1: 【0222】 The server collects data from all IoT devices and home appliance control devices. This includes information on the internal inventory of refrigerators, the current location and status of robotic vacuum cleaners, and the usage history of washing machines. 【0223】 Step 2: 【0224】 The server retrieves schedule information for all family members through access to the user's digital calendar. This information is used to understand the family's schedule and individual activity times. 【0225】 Step 3: 【0226】 The server uses machine learning algorithms to analyze the collected data and generate optimal household chore and childcare plans. For example, it can suggest menus based on ingredient information and create cleaning schedules. 【0227】 Step 4: 【0228】 The server sends specific operating instructions to each appliance control unit based on the generated plan. For example, it sets a time for the vacuum cleaner to start cleaning and sends an instruction to the refrigerator to list the necessary groceries. 【0229】 Step 5: 【0230】 The device notifies the user of the plan's contents, requests user approval, or provides information. For example, it might inform the user of the contents of a suggested menu. 【0231】 Step 6: 【0232】 The device runs educational apps and activity programs for the child and reports the progress to the server. During this process, the app is automatically launched to encourage the child to participate. 【0233】 Step 7: 【0234】 The server monitors the device's operation and notifies the user if any abnormalities occur. This includes detecting washing machine malfunctions or obstacles in robotic vacuum cleaners. 【0235】 Step 8: 【0236】 The server collects feedback on anomalies and areas for improvement, and makes adjustments to incorporate them into future activity plans. For example, it optimizes cleaning frequency based on user feedback. 【0237】 (Example 1) 【0238】 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." 【0239】 In modern households, managing household appliances and planning educational activities requires considerable time and effort. Therefore, to improve the quality of life at home, there is a need to build systems that efficiently automate household appliance management and childcare activities, enabling all family members to spend quality time. In particular, providing methods for effectively utilizing data generated by household information technology devices to automatically generate optimal plans is a key challenge. 【0240】 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. 【0241】 In this invention, the server includes means for acquiring status data and time information from information technology devices within the home, means for generating an optimized home activity plan based on the data acquired through machine learning processing, and means for transmitting operation instructions to the information technology devices based on the home activity plan. This enables the automation and efficient management of activities within the home. 【0242】 "In-home information technology devices" is a general term for various electronic devices and sensors used within the home, and they play a role in data collection and communication. 【0243】 "Status data" refers to information that specifically describes the current operating status and usage history of information technology equipment. 【0244】 "Time information" refers to data that indicates the time when a particular action or movement is scheduled to occur, or a historical record of that time. 【0245】 "Machine learning processing" is a computational process that uses algorithms to analyze collected data and perform pattern recognition and prediction. 【0246】 A "family activity plan" is a guideline that optimizes the schedule and procedures for household chores, childcare, and educational activities that should be carried out within the family. 【0247】 An "operation instruction" is a command or instruction sent to an information technology device to perform a specific action. 【0248】 A "developmental stage-appropriate educational activity program" is a plan to provide learning and educational content that is appropriate for the age and developmental stage of children and family members. 【0249】 This invention is implemented as an autonomous system for automating and optimizing various activities within the home. This system primarily operates with a server at its core and cooperates with information technology devices within the home. 【0250】 The server retrieves status and time information from information technology devices placed within the home. This includes inventory information from a smart refrigerator, the operating status of a robotic vacuum cleaner, and the usage history of a smart washing machine. These devices are commonly referred to as "information technology devices." 【0251】 The server uses machine learning algorithms based on the acquired data to generate an optimal household activity plan. The server is equipped with software that includes a generative AI model, which analyzes the data. For example, it can suggest next week's meal menu based on refrigerator inventory information, and instruct a robotic vacuum cleaner on the optimal cleaning schedule. 【0252】 Furthermore, the server automatically suggests educational activity programs tailored to the child's developmental stage. Users receive these programs through their devices, and educational apps are automatically launched at specific times. This system makes it possible to provide educational content that is appropriate for the child. 【0253】 Users receive notifications from their devices and can take appropriate action when an anomaly occurs. For example, if a washing machine malfunction is detected, the device will present the details to the user and suggest contacting a service center if necessary. 【0254】 As a concrete example, when a user enters the prompt "Suggest a meal and education plan for this week," the server quickly returns a suggestion based on data within the household. In this way, the present invention is implemented as a system that contributes to improving the quality of life in the home. 【0255】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0256】 Step 1: 【0257】 The server collects status and time information from information technology devices. Specifically, the server obtains inventory information from smart refrigerators, operating status from robotic vacuum cleaners, and usage history from smart washing machines. Input data is transmitted from each device, received by the server, and stored in a central database as output. 【0258】 Step 2: 【0259】 The server feeds the collected data into a machine learning algorithm for analysis. The input here consists of stored state data and time information, which the machine learning model processes. This process outputs an optimal household activity plan. For example, it analyzes refrigerator inventory information and suggests a weekly meal menu. 【0260】 Step 3: 【0261】 The server sends operational instructions to the information technology device to execute the household activity plan based on the analysis results. Here, the server communicates the optimal household schedule and childcare plan to the device. The input is the plan generated by the server, and the output is specific instructions for each device. For example, for a robotic vacuum cleaner, a schedule including the cleaning start time is set. 【0262】 Step 4: 【0263】 The terminal provides important notifications to the user and prompts them to take action as needed. The input is status monitoring data provided by the server, which is analyzed and output as alerts sent to the user. For example, if a washing machine malfunction is detected, the terminal will notify the user of the details and suggest repairs. 【0264】 Step 5: 【0265】 Based on notifications and suggestions from the device, the user takes manual action as needed. Specifically, they may enter prompt messages to request additional information from the server or arrange for suggested repair services. The input here consists of the user's selections and inputs, and the output is the execution of corresponding instructions and arrangements. 【0266】 (Application Example 1) 【0267】 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." 【0268】 In modern living spaces, there is a need to optimize energy use within individual households while efficiently and effectively managing the overall electricity consumption of the community. With the increase in IoT devices in homes, the challenge lies in effectively utilizing these devices to improve energy efficiency while more appropriately supporting household activities and education. The lack of such systems leads to wasted electricity consumption and inefficient household management, hindering improvements in residents' convenience and quality of life. 【0269】 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. 【0270】 In this invention, the server includes means for acquiring status information and timetable information from an information processing device as a collection means, means for generating an optimized activity plan within the living space based on the acquired information as an analysis means, and means for generating information for optimizing electricity use within the region as a regional energy management means and transmitting control commands based on that information. This makes it possible to optimize electricity consumption not only in individual households but also in the entire region, enabling efficient energy management and improved convenience for residents' lives. 【0271】 "Collection means" refers to devices and methods for acquiring status information and timetable information from an information processing device. 【0272】 "Analysis means" refers to devices or methods for generating an optimized activity plan within a living space based on acquired information. 【0273】 "Control means" refers to devices or methods for transmitting operation commands to an information processing device based on an activity plan. 【0274】 "Monitoring means" refers to devices or methods for monitoring the operating status of an information processing device and notifying the user when an abnormality occurs. 【0275】 "Proposed means" refers to devices or methods for generating and presenting programs for knowledge activities. 【0276】 "Regional energy management means" refers to devices and methods for generating information to optimize electricity use within a region and transmitting control commands based on that information. 【0277】 The system for implementing this invention integrates energy management within homes and communities, centered around a server. The server communicates with an information processing device and uses IoT technology to collect status information and timetable information for each home. Based on this information, the server analyzes the acquired data and generates an optimal activity plan within the living space using generative AI models and machine learning algorithms. Based on this plan, the server sends control commands to home devices to manage activities efficiently. 【0278】 Furthermore, the server generates an integrated power management plan by utilizing local energy management systems to optimize power usage across the entire region, and notifies each household's information processing device of this plan. In particular, it provides specific measures to reduce peak power consumption, ensuring convenience for residents. This makes it possible to improve energy efficiency and the quality of life for local residents. 【0279】 As a concrete example, the server plans for peak power consumption during a hot summer day and uses a prompt message to a generating AI model that says, "Please suggest the optimal air conditioner usage schedule that each household should consider in order to reduce peak power consumption this summer." Based on this instruction, the terminal can suggest things like shifting each household's air conditioner usage schedule to nighttime. Through such a system, sustainable energy management can be realized throughout the entire region as a smart city. 【0280】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0281】 Step 1: 【0282】 The server connects to an information processing unit and acquires status and timetable information from IoT devices within the home. Input is data from IoT devices, and output is raw data aggregated on the server. This data collection allows for an understanding of the activity of devices in each household. 【0283】 Step 2: 【0284】 Based on the collected information, the server analyzes the data using a generative AI model and machine learning algorithms. The input is the aggregated raw data, and the output is an optimized in-residence activity plan. Through this analysis, an optimal operation schedule for household devices is determined. 【0285】 Step 3: 【0286】 Based on the optimized activity plan, the server sends control instructions to the information processing device. The input is the optimized activity plan, and the output is specific operation instructions to be executed by household devices. Through this operation, the devices operate efficiently and wasteful energy consumption is suppressed. 【0287】 Step 4: 【0288】 Using regional energy management means, the server formulates an integrated management plan for power usage. The input is the in-residence activity plan and regional total power consumption data, and the output is an optimal power usage plan. Through this planning, the overall regional power consumption is made more efficient. 【0289】 Step 5: 【0290】 The terminal notifies each household's information processing device of the formulated power usage plan. The input is the optimal power usage plan, and the output is an action plan displayed to each household. Through this notification, users can take specific actions based on the proposed plan. 【0291】 Step 6: 【0292】 The user adjusts the settings of household devices according to the notification from the terminal. The input is the content of the notification from the terminal, and the output is the device setting changes made by the user. Through this adjustment, actual power consumption is realized in an optimized state. 【0293】 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. 【0294】 This invention is implemented as an autonomous AI agent system incorporating an emotion engine, utilizing IoT devices and home appliance control devices within the home. This system provides a more personalized experience based on the user's emotional state. 【0295】 The server communicates with multiple IoT devices within the home and collects data. This data includes the status of home appliances and the user's schedule information. The server also uses voice input and camera data from the terminal to analyze the user's emotions using an emotion engine. 【0296】 The emotion engine uses voice analysis and image recognition technologies to identify emotions from the user's voice tone and facial expressions. For example, it can identify whether the user is anxious or relaxed. This emotional information is fed back to the server, and household activities are planned to be adjusted to suit the user's emotions. 【0297】 Next, the server generates an activity plan based on this information and sends specific control commands to devices within the home. For example, if the emotion engine determines that the user is feeling stressed, the server instructs the smart speaker to play relaxing background music. It also instructs smart lights to adjust the room lighting for relaxation. 【0298】 Educational activities are also optimized based on emotional information. The device suggests ways to encourage participation even if the child is not currently interested. For example, if the device analyzes that the child is experiencing stress, it will launch an educational app that includes game elements. 【0299】 Finally, the server monitors all devices in the home in real time and notifies the user if there is an abnormality. Through this, the system realizes continuously optimized home operation and provides support for the user to enjoy life with peace of mind. Providing a home environment that takes into account the user's emotions in this way is an embodiment of the present invention. 【0300】 The following describes the processing flow. 【0301】 Step 1: 【0302】 The server collects status data from IoT devices and home appliance control devices in the home. This includes the inventory status of the refrigerator, the usage status of the robotic vacuum cleaner, and the settings of smart lighting. 【0303】 Step 2: 【0304】 The server obtains the user's schedule data and simultaneously collects the user's emotion data through voice input or the camera via the terminal by means of an emotion engine. 【0305】 Step 3: 【0306】 The emotion engine analyzes the collected voice and facial expression data to identify the user's current emotional state. For example, it determines whether the user is calm or feeling stressed. 【0307】 Step 4: 【0308】 The server optimizes the home activity plan based on the emotional state. For example, if the user is in a stressed state, adjustments such as playing relaxing music are incorporated into the plan. 【0309】 Step 5: 【0310】 The server sends operation instructions to the home appliance control device based on the generated optimization plan. For example, it changes the color or brightness of the lighting or adjusts the air conditioning management. 【0311】 Step 6: 【0312】 The device optimizes suggestions related to children's educational activities based on emotional information. For example, it recommends apps that include game elements to pique a child's interest, even if the child initially shows no interest. 【0313】 Step 7: 【0314】 The server monitors the effectiveness of the appliance operations performed and collects feedback for any anomalies or for further optimization. For example, if the user is still experiencing stress, it will suggest an alternative approach. 【0315】 Step 8: 【0316】 The user evaluates the optimized home environment provided by the system and inputs individual settings and feedback into the system as needed. 【0317】 (Example 2) 【0318】 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". 【0319】 In modern homes, there is a growing demand for personalized optimization of the living environment using home information processing devices and other electronic devices. However, conventional systems struggle to provide appropriate control instructions according to the emotions and states of individual users, and there is a particular problem of insufficient real-time responses based on emotional states. Furthermore, in educational and learning activities, flexible suggestions tailored to children's interests and concerns are not adequately provided. 【0320】 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. 【0321】 In this invention, the server includes, as a collection means, means for acquiring environmental information and time management information from an information processing device; as an analysis means, means for generating an optimized living environment plan based on the acquired data; and as an emotion analysis means, means for collecting emotion information using voice analysis technology and image recognition technology. This makes it possible to provide an optimal living environment based on the user's emotion information and to efficiently support educational activities. 【0322】 "Collection means" refers to the function of acquiring environmental information and time management information from an information processing device. 【0323】 "Analysis tools" refer to the function of generating a plan to optimize the living environment based on the acquired data. 【0324】 A "control means" is a function that instructs the information processing device to perform specific operations based on the generated plan. 【0325】 A "monitoring means" is a function that constantly monitors the operation of the information processing device and immediately notifies the user if an abnormality is detected. 【0326】 "Proposal methods" refer to the function of setting up and presenting programs to efficiently advance learning and educational activities. 【0327】 "Emotion analysis means" refers to a function that recognizes and analyzes individual emotional information using voice analysis technology and image recognition technology. 【0328】 This invention is implemented through an in-home information processing system. It is primarily an autonomous system consisting of a server, terminals, and user interaction, aiming to optimize the living environment and support educational activities. 【0329】 First, the server connects with various sensor devices installed in the home to collect environmental information such as temperature, humidity, and illuminance, as well as user time management information, in real time. This information collection utilizes sensors built into devices such as smartphones and computers. The server uses this data to generate an activity plan to optimize the living environment. 【0330】 Next, the device collects user emotional information using a voice input device and camera. This emotional information is inferred from the user's voice tone and facial expressions using voice analysis and image recognition technologies. Specifically, it determines whether the user is relaxed or stressed. The result of this determination is sent to a server, which generates control commands that are reflected in the devices within the home. 【0331】 Based on this control command, the server sends specific operation instructions to smart devices. For example, if user fatigue is detected, it instructs the smart speaker to play healing music and the smart lights to adjust the lighting to relaxation mode. 【0332】 Furthermore, in educational activities, the device monitors the child's learning progress, and if the child shows no interest, it suggests a learning program incorporating game elements. This suggestion is an important way to capture the child's interest. 【0333】 If a user says "I'm tired today," the emotion analysis tool analyzes the tone, and the server decides to recommend relaxation mode. If the device determines that a child is losing focus during an educational activity, it recommends a quiz-style approach. 【0334】 An example of a prompt message is "Please suggest the optimal device operation based on the user's emotions," which is then input to the generating AI model. 【0335】 This system enables the provision of flexible functions that adapt to the user's emotional state, thereby improving comfort and learning efficiency within the home. 【0336】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0337】 Step 1: 【0338】 The server collects environmental and time management information as input from information processing devices within the home. This input data includes temperature, humidity, illuminance, and the user's schedule. The server analyzes this data and stores it as basic information for optimizing the living environment. Specifically, it aggregates data recorded in real time by smart sensors and prepares it for the next processing stage. 【0339】 Step 2: 【0340】 The device receives voice input from the user and facial expressions captured via the camera as input. Based on this input data, the emotion analysis system uses voice analysis and image recognition technologies to identify the user's emotions. This process analyzes changes in voice tone and facial expressions to identify various emotional states (e.g., relaxed, stressed, anxious). The analyzed emotion information is sent to a server and used in the next step. 【0341】 Step 3: 【0342】 The server receives collected environmental information and analyzed emotional information as input and uses analytical tools to generate a living environment plan. This process utilizes data mining techniques and machine learning algorithms to formulate optimal operational instructions adapted to the user's emotional state. The output is a specific device operation plan. For example, if the room temperature needs to be adjusted, it might include instructions to change the air conditioner settings. 【0343】 Step 4: 【0344】 Based on the generated plan, the server sends control commands as output to various devices in the home. This results in specific actions, such as a smart speaker playing healing music or smart lights adjusting to a warmer color. Each device receives commands from the server and operates according to those instructions. 【0345】 Step 5: 【0346】 The device has a suggestion mechanism specifically designed for educational activities, receiving the child's level of interest during learning as input. Based on the monitoring results, if interest is declining, it generates an output suggesting gamification of the activity. Specifically, this suggestion is made by adding quizzes or mini-games to the interface of the learning app. 【0347】 Step 6: 【0348】 When a user detects an anomaly in their living environment, the server uses monitoring tools to collect that information as input. Upon detecting an anomaly, it immediately sends a notification to the user as output, prompting them to take appropriate action. For example, if a door is left open for an extended period, a warning message is sent to the user's smartphone as a security measure. 【0349】 (Application Example 2) 【0350】 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." 【0351】 Conventional home appliances perform programmed actions without considering the user's emotional state, and therefore fail to adequately address the stress and anxiety users face. Furthermore, there was a need for home appliances that not only provide operation but also offer personalized experiences based on emotional information. Additionally, there was a lack of systems capable of generating activity plans optimized for the home environment and improving quality of life. 【0352】 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. 【0353】 In this invention, the server includes means for acquiring voice and image data and performing emotion analysis, means for generating an optimized home activity plan based on the acquired emotion data, and means for transmitting operation instructions to home devices based on the activity plan. This makes it possible for home devices to operate while taking the user's emotional state into consideration and to provide a personalized experience. 【0354】 "Voice data" refers to information used to record and analyze the user's voice in digital format. 【0355】 "Image data" refers to information used to record and analyze a user's facial expressions and surrounding visual information in digital format. 【0356】 "Emotional analysis" is a process that determines the user's emotional state based on acquired audio and image data. 【0357】 A "home activity plan" is a plan designed to optimize the operation and suggestions of devices at home, based on the user's emotional state and schedule. 【0358】 "Household appliances" refer to home appliances and IoT devices used within the home, and are the entities to which control commands are sent. 【0359】 This invention is a system that collects voice and image data and realizes optimized in-home activities through emotion analysis. The server uses smart devices and computing equipment in the home to acquire voice signals and facial expressions emitted by the user through a camera and microphone. This data is processed by image recognition software and voice analysis software, and the user's emotional state is determined by an emotion engine. 【0360】 Voice analysis identifies emotions by considering factors such as voice tone, speaking speed, and volume. Image recognition reads emotions from eye and mouth movements, and facial muscle tension. The acquired emotion data is sent to a server and used to generate an optimal operating plan for home devices. This operating plan sends commands to home devices to ensure optimal functionality according to the user's emotional state. 【0361】 For example, if the system determines that the user desires relaxation, it will instruct the system to play relaxation music through the speakers. It will also send a command to the smart lights to adjust their brightness to create a calmer environment. Furthermore, for children, when they are feeling stressed, the system will suggest using educational apps that include game elements to keep them engaged. 【0362】 A concrete example of a prompt is, "If the user appears to be having trouble, suggest a fun activity that suits them." Using such prompts makes it easier for the generative AI model to provide support tailored to the user's situation. 【0363】 In this way, the server can continuously adapt to the user's emotions, supporting a safe and comfortable life within the home. 【0364】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0365】 Step 1: 【0366】 The server acquires audio and image data through the home's microphone and camera. During this data collection phase, the user's voice and facial expressions are converted into digital data. The input consists of audio signals and image frames, which are provided to the server's analysis module. 【0367】 Step 2: 【0368】 Based on the voice data acquired by the server, voice analysis software is used to analyze voice tone, speed, and volume. The output is an estimated value of emotion, providing an initial determination of the user's emotional state. By identifying the user's emotional state through data analysis, a corresponding action plan is formulated. 【0369】 Step 3: 【0370】 The server uses image recognition software to analyze the user's facial expressions from image data. At this stage, eye and mouth movements, facial muscle tension, and other factors are evaluated. The input is an image frame, and the output is an emotion estimate. This is then integrated with the audio analysis results to obtain the final emotion data. 【0371】 Step 4: 【0372】 The emotion engine integrates voice and image analysis results to estimate an overall emotional state. This estimation is then used by a plan generation module on the server to develop a household activity plan. 【0373】 Step 5: 【0374】 The server generates an optimal household activity plan and appliance operation plan based on emotional data. The input is integrated emotional data, and the output is specific appliance control commands. Based on this plan, the server sends commands to household appliances to play relaxing music or adjust lighting. 【0375】 Step 6: 【0376】 The user experiences the changes in the home environment provided as a result of Step 5. This enables the implementation of home support that is adapted to the user's current emotional state. 【0377】 Integrated processing enables the automatic adjustment of home appliances based on emotions, thereby improving the user's quality of life. 【0378】 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. 【0379】 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. 【0380】 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. 【0381】 [Third Embodiment] 【0382】 Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment. 【0383】 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. 【0384】 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). 【0385】 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. 【0386】 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. 【0387】 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). 【0388】 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. 【0389】 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. 【0390】 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. 【0391】 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. 【0392】 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. 【0393】 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". 【0394】 The present invention is implemented as an autonomous AI agent system that utilizes IoT devices and home appliance control devices within the home. Sensing and control of this system are mainly performed by a server. One embodiment of the present invention is described below. 【0395】 The server communicates with various IoT devices in the home and collects device status data. This data includes the inventory status of the smart refrigerator, the operating status of the robot vacuum cleaner, and the usage history of the smart washing machine. The server also retrieves the user's digital calendar to keep track of everyone's schedule. 【0396】 The server uses machine learning algorithms to analyze the collected data and develop optimal household and childcare plans. For example, it analyzes the ingredients in the refrigerator to determine the family's meal menu. It also sets the optimal cleaning schedule for the robot vacuum cleaner and instructs it on specific cleaning times. 【0397】 Furthermore, the server generates educational activity programs tailored to the child's age and developmental stage, and proposes them to the user via the device. Educational apps for children are automatically launched at specific times, providing learning opportunities. 【0398】 The device notifies the user and prompts them to take appropriate action if an anomaly occurs. For example, if a washing machine malfunction is detected, it will report the details to the user and suggest the necessary service call. 【0399】 By introducing this system, users can increase the time they spend with their families and improve their quality of life by receiving automated household chores and childcare support. Thus, the embodiment of this invention aims to improve the overall well-being of families and solve the associated social issues. 【0400】 The following describes the processing flow. 【0401】 Step 1: 【0402】 The server collects data from all IoT devices and home appliance control devices. This includes information on the internal inventory of refrigerators, the current location and status of robotic vacuum cleaners, and the usage history of washing machines. 【0403】 Step 2: 【0404】 The server retrieves schedule information for all family members through access to the user's digital calendar. This information is used to understand the family's schedule and individual activity times. 【0405】 Step 3: 【0406】 The server uses machine learning algorithms to analyze the collected data and generate optimal household chore and childcare plans. For example, it can suggest menus based on ingredient information and create cleaning schedules. 【0407】 Step 4: 【0408】 The server sends specific operating instructions to each appliance control unit based on the generated plan. For example, it sets a time for the vacuum cleaner to start cleaning and sends an instruction to the refrigerator to list the necessary groceries. 【0409】 Step 5: 【0410】 The device notifies the user of the plan's contents, requests user approval, or provides information. For example, it might inform the user of the contents of a suggested menu. 【0411】 Step 6: 【0412】 The device runs educational apps and activity programs for the child and reports the progress to the server. During this process, the app is automatically launched to encourage the child to participate. 【0413】 Step 7: 【0414】 The server monitors the device's operation and notifies the user if any abnormalities occur. This includes detecting washing machine malfunctions or obstacles in robotic vacuum cleaners. 【0415】 Step 8: 【0416】 The server collects feedback on anomalies and areas for improvement, and makes adjustments to incorporate them into future activity plans. For example, it optimizes cleaning frequency based on user feedback. 【0417】 (Example 1) 【0418】 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." 【0419】 In modern households, managing household appliances and planning educational activities requires considerable time and effort. Therefore, to improve the quality of life at home, there is a need to build systems that efficiently automate household appliance management and childcare activities, enabling all family members to spend quality time. In particular, providing methods for effectively utilizing data generated by household information technology devices to automatically generate optimal plans is a key challenge. 【0420】 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. 【0421】 In this invention, the server includes means for acquiring status data and time information from information technology devices within the home, means for generating an optimized home activity plan based on the data acquired through machine learning processing, and means for transmitting operation instructions to the information technology devices based on the home activity plan. This enables the automation and efficient management of activities within the home. 【0422】 "In-home information technology devices" is a general term for various electronic devices and sensors used within the home, and they play a role in data collection and communication. 【0423】 "Status data" refers to information that specifically describes the current operating status and usage history of information technology equipment. 【0424】 "Time information" refers to data that indicates the time when a particular action or movement is scheduled to occur, or a historical record of that time. 【0425】 "Machine learning processing" is a computational process that uses algorithms to analyze collected data and perform pattern recognition and prediction. 【0426】 A "family activity plan" is a guideline that optimizes the schedule and procedures for household chores, childcare, and educational activities that should be carried out within the family. 【0427】 An "operation instruction" is a command or instruction sent to an information technology device to perform a specific action. 【0428】 A "developmental stage-appropriate educational activity program" is a plan to provide learning and educational content that is appropriate for the age and developmental stage of children and family members. 【0429】 This invention is implemented as an autonomous system for automating and optimizing various activities within the home. This system primarily operates with a server at its core and cooperates with information technology devices within the home. 【0430】 The server retrieves status and time information from information technology devices placed within the home. This includes inventory information from a smart refrigerator, the operating status of a robotic vacuum cleaner, and the usage history of a smart washing machine. These devices are commonly referred to as "information technology devices." 【0431】 The server uses machine learning algorithms based on the acquired data to generate an optimal household activity plan. The server is equipped with software that includes a generative AI model, which analyzes the data. For example, it can suggest next week's meal menu based on refrigerator inventory information, and instruct a robotic vacuum cleaner on the optimal cleaning schedule. 【0432】 Furthermore, the server automatically suggests educational activity programs tailored to the child's developmental stage. Users receive these programs through their devices, and educational apps are automatically launched at specific times. This system makes it possible to provide educational content that is appropriate for the child. 【0433】 Users receive notifications from their devices and can take appropriate action when an anomaly occurs. For example, if a washing machine malfunction is detected, the device will present the details to the user and suggest contacting a service center if necessary. 【0434】 As a concrete example, when a user enters the prompt "Suggest a meal and education plan for this week," the server quickly returns a suggestion based on data within the household. In this way, the present invention is implemented as a system that contributes to improving the quality of life in the home. 【0435】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0436】 Step 1: 【0437】 The server collects status and time information from information technology devices. Specifically, the server obtains inventory information from smart refrigerators, operating status from robotic vacuum cleaners, and usage history from smart washing machines. Input data is transmitted from each device, received by the server, and stored in a central database as output. 【0438】 Step 2: 【0439】 The server feeds the collected data into a machine learning algorithm for analysis. The input here consists of stored state data and time information, which the machine learning model processes. This process outputs an optimal household activity plan. For example, it analyzes refrigerator inventory information and suggests a weekly meal menu. 【0440】 Step 3: 【0441】 The server sends operational instructions to the information technology device to execute the household activity plan based on the analysis results. Here, the server communicates the optimal household schedule and childcare plan to the device. The input is the plan generated by the server, and the output is specific instructions for each device. For example, for a robotic vacuum cleaner, a schedule including the cleaning start time is set. 【0442】 Step 4: 【0443】 The terminal provides important notifications to the user and prompts them to take action as needed. The input is status monitoring data provided by the server, which is analyzed and output as alerts sent to the user. For example, if a washing machine malfunction is detected, the terminal will notify the user of the details and suggest repairs. 【0444】 Step 5: 【0445】 Based on notifications and suggestions from the device, the user takes manual action as needed. Specifically, they may enter prompt messages to request additional information from the server or arrange for suggested repair services. The input here consists of the user's selections and inputs, and the output is the execution of corresponding instructions and arrangements. 【0446】 (Application Example 1) 【0447】 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." 【0448】 In modern living spaces, there is a need to optimize energy use within individual households while efficiently and effectively managing the overall electricity consumption of the community. With the increase in IoT devices in homes, the challenge lies in effectively utilizing these devices to improve energy efficiency while more appropriately supporting household activities and education. The lack of such systems leads to wasted electricity consumption and inefficient household management, hindering improvements in residents' convenience and quality of life. 【0449】 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. 【0450】 In this invention, the server includes means for acquiring status information and timetable information from an information processing device as a collection means, means for generating an optimized activity plan within the living space based on the acquired information as an analysis means, and means for generating information for optimizing electricity use within the region as a regional energy management means and transmitting control commands based on that information. This makes it possible to optimize electricity consumption not only in individual households but also in the entire region, enabling efficient energy management and improved convenience for residents' lives. 【0451】 "Collection means" refers to devices and methods for acquiring status information and timetable information from an information processing device. 【0452】 "Analysis means" refers to devices or methods for generating an optimized activity plan within a living space based on acquired information. 【0453】 "Control means" refers to devices or methods for transmitting operation commands to an information processing device based on an activity plan. 【0454】 "Monitoring means" refers to devices or methods for monitoring the operating status of an information processing device and notifying the user when an abnormality occurs. 【0455】 "Proposed means" refers to devices or methods for generating and presenting programs for knowledge activities. 【0456】 "Regional energy management means" refers to devices and methods for generating information to optimize electricity use within a region and transmitting control commands based on that information. 【0457】 The system for implementing this invention integrates energy management within homes and communities, centered around a server. The server communicates with an information processing device and uses IoT technology to collect status information and timetable information for each home. Based on this information, the server analyzes the acquired data and generates an optimal activity plan within the living space using generative AI models and machine learning algorithms. Based on this plan, the server sends control commands to home devices to manage activities efficiently. 【0458】 Furthermore, the server generates an integrated power management plan by utilizing local energy management systems to optimize power usage across the entire region, and notifies each household's information processing device of this plan. In particular, it provides specific measures to reduce peak power consumption, ensuring convenience for residents. This makes it possible to improve energy efficiency and the quality of life for local residents. 【0459】 As a concrete example, the server plans for peak power consumption during a hot summer day and uses a prompt message to a generating AI model that says, "Please suggest the optimal air conditioner usage schedule that each household should consider in order to reduce peak power consumption this summer." Based on this instruction, the terminal can suggest things like shifting each household's air conditioner usage schedule to nighttime. Through such a system, sustainable energy management can be realized throughout the entire region as a smart city. 【0460】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0461】 Step 1: 【0462】 The server connects to an information processing unit and acquires status and timetable information from IoT devices within the home. Input is data from IoT devices, and output is raw data aggregated on the server. This data collection allows for an understanding of the activity of devices in each household. 【0463】 Step 2: 【0464】 The server analyzes the collected information using generative AI models and machine learning algorithms. The input is aggregated raw data, and the output is an optimized activity plan for the living space. This analysis determines the optimal operating schedule for home devices. 【0465】 Step 3: 【0466】 The server sends control commands to the information processing unit based on an optimized activity plan. The input is the optimized activity plan, and the output is the specific action command to be executed on the home device. This operation allows the device to run efficiently and reduces unnecessary energy consumption. 【0467】 Step 4: 【0468】 The server uses local energy management tools to develop an integrated management plan for electricity usage. Inputs include household activity plans and total local electricity consumption data, while output is an optimal electricity usage plan. This planning process optimizes electricity consumption across the entire region. 【0469】 Step 5: 【0470】 The terminal notifies each household's information processing device of the formulated electricity usage plan. The input is the optimal electricity usage plan, and the output is the action plan displayed in each household. This notification allows users to take specific actions based on the proposed plan. 【0471】 Step 6: 【0472】 The user adjusts the settings of their home devices according to notifications from the terminal. The input is the notification content from the terminal, and the output is the user's changes to the device settings. This adjustment results in optimized actual power consumption. 【0473】 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. 【0474】 This invention is implemented as an autonomous AI agent system incorporating an emotion engine, utilizing IoT devices and home appliance control devices within the home. This system provides a more personalized experience based on the user's emotional state. 【0475】 The server communicates with multiple IoT devices within the home and collects data. This data includes the status of home appliances and the user's schedule information. The server also uses voice input and camera data from the terminal to analyze the user's emotions using an emotion engine. 【0476】 The emotion engine uses voice analysis and image recognition technologies to identify emotions from the user's voice tone and facial expressions. For example, it can identify whether the user is anxious or relaxed. This emotional information is fed back to the server, and household activities are planned to be adjusted to suit the user's emotions. 【0477】 Next, the server generates an activity plan based on this information and sends specific control commands to devices within the home. For example, if the emotion engine determines that the user is feeling stressed, the server instructs the smart speaker to play relaxing background music. It also instructs smart lights to adjust the room lighting for relaxation. 【0478】 Educational activities are also optimized based on emotional information. The device suggests ways to encourage participation even if the child is not currently interested. For example, if the device analyzes that the child is experiencing stress, it will launch an educational app that includes game elements. 【0479】 Ultimately, the server monitors all devices in the home in real time and notifies the user if any abnormalities are detected. This system enables continuously optimized home management, supporting the user in enjoying their life with peace of mind. Providing a home environment that takes the user's feelings into consideration is an embodiment of the present invention. 【0480】 The following describes the processing flow. 【0481】 Step 1: 【0482】 The server collects status data from IoT devices and home appliance control devices within the home. This includes refrigerator inventory status, robot vacuum cleaner usage status, and smart lighting settings. 【0483】 Step 2: 【0484】 The server acquires the user's schedule data, and at the same time, collects the user's emotional data through an emotion engine using voice input and camera via the terminal. 【0485】 Step 3: 【0486】 The emotion engine analyzes collected voice and facial expression data to identify the user's current emotional state. For example, it can determine whether the user is calm or stressed. 【0487】 Step 4: 【0488】 The server optimizes the home activity plan based on the user's emotional state. For example, if the user is stressed, the plan will incorporate adjustments such as playing relaxing music. 【0489】 Step 5: 【0490】 The server sends operation instructions to the home appliance control unit based on the generated optimization plan. For example, it might change the color and brightness of the lighting or adjust the air conditioning settings. 【0491】 Step 6: 【0492】 The device optimizes suggestions related to children's educational activities based on emotional information. For example, it recommends apps that include game elements to pique a child's interest, even if the child initially shows no interest. 【0493】 Step 7: 【0494】 The server monitors the effectiveness of the appliance operations performed and collects feedback for any anomalies or for further optimization. For example, if the user is still experiencing stress, it will suggest an alternative approach. 【0495】 Step 8: 【0496】 The user evaluates the optimized home environment provided by the system and inputs individual settings and feedback into the system as needed. 【0497】 (Example 2) 【0498】 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." 【0499】 In modern homes, there is a growing demand for personalized optimization of the living environment using home information processing devices and other electronic devices. However, conventional systems struggle to provide appropriate control instructions according to the emotions and states of individual users, and there is a particular problem of insufficient real-time responses based on emotional states. Furthermore, in educational and learning activities, flexible suggestions tailored to children's interests and concerns are not adequately provided. 【0500】 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. 【0501】 In this invention, the server includes, as a collection means, means for acquiring environmental information and time management information from an information processing device; as an analysis means, means for generating an optimized living environment plan based on the acquired data; and as an emotion analysis means, means for collecting emotion information using voice analysis technology and image recognition technology. This makes it possible to provide an optimal living environment based on the user's emotion information and to efficiently support educational activities. 【0502】 "Collection means" refers to the function of acquiring environmental information and time management information from an information processing device. 【0503】 "Analysis tools" refer to the function of generating a plan to optimize the living environment based on the acquired data. 【0504】 A "control means" is a function that instructs the information processing device to perform specific operations based on the generated plan. 【0505】 A "monitoring means" is a function that constantly monitors the operation of the information processing device and immediately notifies the user if an abnormality is detected. 【0506】 "Proposal methods" refer to the function of setting up and presenting programs to efficiently advance learning and educational activities. 【0507】 "Emotion analysis means" refers to a function that recognizes and analyzes individual emotional information using voice analysis technology and image recognition technology. 【0508】 This invention is implemented through an in-home information processing system. It is primarily an autonomous system consisting of a server, terminals, and user interaction, aiming to optimize the living environment and support educational activities. 【0509】 First, the server connects with various sensor devices installed in the home to collect environmental information such as temperature, humidity, and illuminance, as well as user time management information, in real time. This information collection utilizes sensors built into devices such as smartphones and computers. The server uses this data to generate an activity plan to optimize the living environment. 【0510】 Next, the device collects user emotional information using a voice input device and camera. This emotional information is inferred from the user's voice tone and facial expressions using voice analysis and image recognition technologies. Specifically, it determines whether the user is relaxed or stressed. The result of this determination is sent to a server, which generates control commands that are reflected in the devices within the home. 【0511】 Based on this control command, the server sends specific operation instructions to smart devices. For example, if user fatigue is detected, it instructs the smart speaker to play healing music and the smart lights to adjust the lighting to relaxation mode. 【0512】 Furthermore, in educational activities, the device monitors the child's learning progress, and if the child shows no interest, it suggests a learning program incorporating game elements. This suggestion is an important way to capture the child's interest. 【0513】 If a user says "I'm tired today," the emotion analysis tool analyzes the tone, and the server decides to recommend relaxation mode. If the device determines that a child is losing focus during an educational activity, it recommends a quiz-style approach. 【0514】 An example of a prompt message is "Please suggest the optimal device operation based on the user's emotions," which is then input to the generating AI model. 【0515】 This system enables the provision of flexible functions that adapt to the user's emotional state, thereby improving comfort and learning efficiency within the home. 【0516】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0517】 Step 1: 【0518】 The server collects environmental and time management information as input from information processing devices within the home. This input data includes temperature, humidity, illuminance, and the user's schedule. The server analyzes this data and stores it as basic information for optimizing the living environment. Specifically, it aggregates data recorded in real time by smart sensors and prepares it for the next processing stage. 【0519】 Step 2: 【0520】 The device receives voice input from the user and facial expressions captured via the camera as input. Based on this input data, the emotion analysis system uses voice analysis and image recognition technologies to identify the user's emotions. This process analyzes changes in voice tone and facial expressions to identify various emotional states (e.g., relaxed, stressed, anxious). The analyzed emotion information is sent to a server and used in the next step. 【0521】 Step 3: 【0522】 The server receives collected environmental information and analyzed emotional information as input and uses analytical tools to generate a living environment plan. This process utilizes data mining techniques and machine learning algorithms to formulate optimal operational instructions adapted to the user's emotional state. The output is a specific device operation plan. For example, if the room temperature needs to be adjusted, it might include instructions to change the air conditioner settings. 【0523】 Step 4: 【0524】 Based on the generated plan, the server sends control commands as output to various devices in the home. This results in specific actions, such as a smart speaker playing healing music or smart lights adjusting to a warmer color. Each device receives commands from the server and operates according to those instructions. 【0525】 Step 5: 【0526】 The device has a suggestion mechanism specifically designed for educational activities, receiving the child's level of interest during learning as input. Based on the monitoring results, if interest is declining, it generates an output suggesting gamification of the activity. Specifically, this suggestion is made by adding quizzes or mini-games to the interface of the learning app. 【0527】 Step 6: 【0528】 When a user detects an anomaly in their living environment, the server uses monitoring tools to collect that information as input. Upon detecting an anomaly, it immediately sends a notification to the user as output, prompting them to take appropriate action. For example, if a door is left open for an extended period, a warning message is sent to the user's smartphone as a security measure. 【0529】 (Application Example 2) 【0530】 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." 【0531】 Conventional home appliances perform programmed actions without considering the user's emotional state, and therefore fail to adequately address the stress and anxiety users face. Furthermore, there was a need for home appliances that not only provide operation but also offer personalized experiences based on emotional information. Additionally, there was a lack of systems capable of generating activity plans optimized for the home environment and improving quality of life. 【0532】 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. 【0533】 In this invention, the server includes means for acquiring voice and image data and performing emotion analysis, means for generating an optimized home activity plan based on the acquired emotion data, and means for transmitting operation instructions to home devices based on the activity plan. This makes it possible for home devices to operate while taking the user's emotional state into consideration and to provide a personalized experience. 【0534】 "Voice data" refers to information used to record and analyze the user's voice in digital format. 【0535】 "Image data" refers to information used to record and analyze a user's facial expressions and surrounding visual information in digital format. 【0536】 "Emotional analysis" is a process that determines the user's emotional state based on acquired audio and image data. 【0537】 A "home activity plan" is a plan designed to optimize the operation and suggestions of devices at home, based on the user's emotional state and schedule. 【0538】 "Household appliances" refer to home appliances and IoT devices used within the home, and are the entities to which control commands are sent. 【0539】 This invention is a system that collects voice and image data and realizes optimized in-home activities through emotion analysis. The server uses smart devices and computing equipment in the home to acquire voice signals and facial expressions emitted by the user through a camera and microphone. This data is processed by image recognition software and voice analysis software, and the user's emotional state is determined by an emotion engine. 【0540】 Voice analysis identifies emotions by considering factors such as voice tone, speaking speed, and volume. Image recognition reads emotions from eye and mouth movements, and facial muscle tension. The acquired emotion data is sent to a server and used to generate an optimal operating plan for home devices. This operating plan sends commands to home devices to ensure optimal functionality according to the user's emotional state. 【0541】 For example, if the system determines that the user desires relaxation, it will instruct the system to play relaxation music through the speakers. It will also send a command to the smart lights to adjust their brightness to create a calmer environment. Furthermore, for children, when they are feeling stressed, the system will suggest using educational apps that include game elements to keep them engaged. 【0542】 A concrete example of a prompt is, "If the user appears to be having trouble, suggest a fun activity that suits them." Using such prompts makes it easier for the generative AI model to provide support tailored to the user's situation. 【0543】 In this way, the server can continuously adapt to the user's emotions, supporting a safe and comfortable life within the home. 【0544】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0545】 Step 1: 【0546】 The server acquires audio and image data through the home's microphone and camera. During this data collection phase, the user's voice and facial expressions are converted into digital data. The input consists of audio signals and image frames, which are provided to the server's analysis module. 【0547】 Step 2: 【0548】 Based on the voice data acquired by the server, voice analysis software is used to analyze voice tone, speed, and volume. The output is an estimated value of emotion, providing an initial determination of the user's emotional state. By identifying the user's emotional state through data analysis, a corresponding action plan is formulated. 【0549】 Step 3: 【0550】 The server uses image recognition software to analyze the user's facial expressions from image data. At this stage, eye and mouth movements, facial muscle tension, and other factors are evaluated. The input is an image frame, and the output is an emotion estimate. This is then integrated with the audio analysis results to obtain the final emotion data. 【0551】 Step 4: 【0552】 The emotion engine integrates voice and image analysis results to estimate an overall emotional state. This estimation is then used by a plan generation module on the server to develop a household activity plan. 【0553】 Step 5: 【0554】 The server generates an optimal household activity plan and appliance operation plan based on emotional data. The input is integrated emotional data, and the output is specific appliance control commands. Based on this plan, the server sends commands to household appliances to play relaxing music or adjust lighting. 【0555】 Step 6: 【0556】 The user experiences the changes in the home environment provided as a result of Step 5. This enables the implementation of home support that is adapted to the user's current emotional state. 【0557】 Integrated processing enables the automatic adjustment of home appliances based on emotions, thereby improving the user's quality of life. 【0558】 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. 【0559】 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. 【0560】 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. 【0561】 [Fourth Embodiment] 【0562】 Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment. 【0563】 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. 【0564】 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). 【0565】 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. 【0566】 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. 【0567】 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). 【0568】 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. 【0569】 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. 【0570】 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. 【0571】 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. 【0572】 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. 【0573】 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. 【0574】 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". 【0575】 The present invention is implemented as an autonomous AI agent system that utilizes IoT devices and home appliance control devices within the home. Sensing and control of this system are mainly performed by a server. One embodiment of the present invention is described below. 【0576】 The server communicates with various IoT devices in the home and collects device status data. This data includes the inventory status of the smart refrigerator, the operating status of the robot vacuum cleaner, and the usage history of the smart washing machine. The server also retrieves the user's digital calendar to keep track of everyone's schedule. 【0577】 The server uses machine learning algorithms to analyze the collected data and develop optimal household and childcare plans. For example, it analyzes the ingredients in the refrigerator to determine the family's meal menu. It also sets the optimal cleaning schedule for the robot vacuum cleaner and instructs it on specific cleaning times. 【0578】 Furthermore, the server generates educational activity programs tailored to the child's age and developmental stage, and proposes them to the user via the device. Educational apps for children are automatically launched at specific times, providing learning opportunities. 【0579】 The device notifies the user and prompts them to take appropriate action if an anomaly occurs. For example, if a washing machine malfunction is detected, it will report the details to the user and suggest the necessary service call. 【0580】 By introducing this system, users can increase the time they spend with their families and improve their quality of life by receiving automated household chores and childcare support. Thus, the embodiment of this invention aims to improve the overall well-being of families and solve the associated social issues. 【0581】 The following describes the processing flow. 【0582】 Step 1: 【0583】 The server collects data from all IoT devices and home appliance control devices. This includes information on the internal inventory of refrigerators, the current location and status of robotic vacuum cleaners, and the usage history of washing machines. 【0584】 Step 2: 【0585】 The server retrieves schedule information for all family members through access to the user's digital calendar. This information is used to understand the family's schedule and individual activity times. 【0586】 Step 3: 【0587】 The server uses machine learning algorithms to analyze the collected data and generate optimal household chore and childcare plans. For example, it can suggest menus based on ingredient information and create cleaning schedules. 【0588】 Step 4: 【0589】 The server sends specific operating instructions to each appliance control unit based on the generated plan. For example, it sets a time for the vacuum cleaner to start cleaning and sends an instruction to the refrigerator to list the necessary groceries. 【0590】 Step 5: 【0591】 The device notifies the user of the plan's contents, requests user approval, or provides information. For example, it might inform the user of the contents of a suggested menu. 【0592】 Step 6: 【0593】 The device runs educational apps and activity programs for the child and reports the progress to the server. During this process, the app is automatically launched to encourage the child to participate. 【0594】 Step 7: 【0595】 The server monitors the device's operation and notifies the user if any abnormalities occur. This includes detecting washing machine malfunctions or obstacles in robotic vacuum cleaners. 【0596】 Step 8: 【0597】 The server collects feedback on anomalies and areas for improvement, and makes adjustments to incorporate them into future activity plans. For example, it optimizes cleaning frequency based on user feedback. 【0598】 (Example 1) 【0599】 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". 【0600】 In modern households, managing household appliances and planning educational activities requires considerable time and effort. Therefore, to improve the quality of life at home, there is a need to build systems that efficiently automate household appliance management and childcare activities, enabling all family members to spend quality time. In particular, providing methods for effectively utilizing data generated by household information technology devices to automatically generate optimal plans is a key challenge. 【0601】 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. 【0602】 In this invention, the server includes means for acquiring status data and time information from information technology devices within the home, means for generating an optimized home activity plan based on the data acquired through machine learning processing, and means for transmitting operation instructions to the information technology devices based on the home activity plan. This enables the automation and efficient management of activities within the home. 【0603】 "In-home information technology devices" is a general term for various electronic devices and sensors used within the home, and they play a role in data collection and communication. 【0604】 "Status data" refers to information that specifically describes the current operating status and usage history of information technology equipment. 【0605】 "Time information" refers to data that indicates the time when a particular action or movement is scheduled to occur, or a historical record of that time. 【0606】 "Machine learning processing" is a computational process that uses algorithms to analyze collected data and perform pattern recognition and prediction. 【0607】 A "family activity plan" is a guideline that optimizes the schedule and procedures for household chores, childcare, and educational activities that should be carried out within the family. 【0608】 An "operation instruction" is a command or instruction sent to an information technology device to perform a specific action. 【0609】 A "developmental stage-appropriate educational activity program" is a plan to provide learning and educational content that is appropriate for the age and developmental stage of children and family members. 【0610】 This invention is implemented as an autonomous system for automating and optimizing various activities within the home. This system primarily operates with a server at its core and cooperates with information technology devices within the home. 【0611】 The server retrieves status and time information from information technology devices placed within the home. This includes inventory information from a smart refrigerator, the operating status of a robotic vacuum cleaner, and the usage history of a smart washing machine. These devices are commonly referred to as "information technology devices." 【0612】 The server uses machine learning algorithms based on the acquired data to generate an optimal household activity plan. The server is equipped with software that includes a generative AI model, which analyzes the data. For example, it can suggest next week's meal menu based on refrigerator inventory information, and instruct a robotic vacuum cleaner on the optimal cleaning schedule. 【0613】 Furthermore, the server automatically suggests educational activity programs tailored to the child's developmental stage. Users receive these programs through their devices, and educational apps are automatically launched at specific times. This system makes it possible to provide educational content that is appropriate for the child. 【0614】 Users receive notifications from their devices and can take appropriate action when an anomaly occurs. For example, if a washing machine malfunction is detected, the device will present the details to the user and suggest contacting a service center if necessary. 【0615】 As a concrete example, when a user enters the prompt "Suggest a meal and education plan for this week," the server quickly returns a suggestion based on data within the household. In this way, the present invention is implemented as a system that contributes to improving the quality of life in the home. 【0616】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0617】 Step 1: 【0618】 The server collects status and time information from information technology devices. Specifically, the server obtains inventory information from smart refrigerators, operating status from robotic vacuum cleaners, and usage history from smart washing machines. Input data is transmitted from each device, received by the server, and stored in a central database as output. 【0619】 Step 2: 【0620】 The server feeds the collected data into a machine learning algorithm for analysis. The input here consists of stored state data and time information, which the machine learning model processes. This process outputs an optimal household activity plan. For example, it analyzes refrigerator inventory information and suggests a weekly meal menu. 【0621】 Step 3: 【0622】 The server sends operational instructions to the information technology device to execute the household activity plan based on the analysis results. Here, the server communicates the optimal household schedule and childcare plan to the device. The input is the plan generated by the server, and the output is specific instructions for each device. For example, for a robotic vacuum cleaner, a schedule including the cleaning start time is set. 【0623】 Step 4: 【0624】 The terminal provides important notifications to the user and prompts them to take action as needed. The input is status monitoring data provided by the server, which is analyzed and output as alerts sent to the user. For example, if a washing machine malfunction is detected, the terminal will notify the user of the details and suggest repairs. 【0625】 Step 5: 【0626】 Based on notifications and suggestions from the device, the user takes manual action as needed. Specifically, they may enter prompt messages to request additional information from the server or arrange for suggested repair services. The input here consists of the user's selections and inputs, and the output is the execution of corresponding instructions and arrangements. 【0627】 (Application Example 1) 【0628】 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". 【0629】 In modern living spaces, there is a need to optimize energy use within individual households while efficiently and effectively managing the overall electricity consumption of the community. With the increase in IoT devices in homes, the challenge lies in effectively utilizing these devices to improve energy efficiency while more appropriately supporting household activities and education. The lack of such systems leads to wasted electricity consumption and inefficient household management, hindering improvements in residents' convenience and quality of life. 【0630】 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. 【0631】 In this invention, the server includes means for acquiring status information and timetable information from an information processing device as a collection means, means for generating an optimized activity plan within the living space based on the acquired information as an analysis means, and means for generating information for optimizing electricity use within the region as a regional energy management means and transmitting control commands based on that information. This makes it possible to optimize electricity consumption not only in individual households but also in the entire region, enabling efficient energy management and improved convenience for residents' lives. 【0632】 "Collection means" refers to devices and methods for acquiring status information and timetable information from an information processing device. 【0633】 "Analysis means" refers to devices or methods for generating an optimized activity plan within a living space based on acquired information. 【0634】 "Control means" refers to devices or methods for transmitting operation commands to an information processing device based on an activity plan. 【0635】 "Monitoring means" refers to devices or methods for monitoring the operating status of an information processing device and notifying the user when an abnormality occurs. 【0636】 "Proposed means" refers to devices or methods for generating and presenting programs for knowledge activities. 【0637】 "Regional energy management means" refers to devices and methods for generating information to optimize electricity use within a region and transmitting control commands based on that information. 【0638】 The system for implementing this invention integrates energy management within homes and communities, centered around a server. The server communicates with an information processing device and uses IoT technology to collect status information and timetable information for each home. Based on this information, the server analyzes the acquired data and generates an optimal activity plan within the living space using generative AI models and machine learning algorithms. Based on this plan, the server sends control commands to home devices to manage activities efficiently. 【0639】 Furthermore, the server generates an integrated power management plan by utilizing local energy management systems to optimize power usage across the entire region, and notifies each household's information processing device of this plan. In particular, it provides specific measures to reduce peak power consumption, ensuring convenience for residents. This makes it possible to improve energy efficiency and the quality of life for local residents. 【0640】 As a concrete example, the server plans for peak power consumption during a hot summer day and uses a prompt message to a generating AI model that says, "Please suggest the optimal air conditioner usage schedule that each household should consider in order to reduce peak power consumption this summer." Based on this instruction, the terminal can suggest things like shifting each household's air conditioner usage schedule to nighttime. Through such a system, sustainable energy management can be realized throughout the entire region as a smart city. 【0641】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0642】 Step 1: 【0643】 The server connects to an information processing unit and acquires status and timetable information from IoT devices within the home. Input is data from IoT devices, and output is raw data aggregated on the server. This data collection allows for an understanding of the activity of devices in each household. 【0644】 Step 2: 【0645】 The server analyzes the collected information using generative AI models and machine learning algorithms. The input is aggregated raw data, and the output is an optimized activity plan for the living space. This analysis determines the optimal operating schedule for home devices. 【0646】 Step 3: 【0647】 The server sends control commands to the information processing unit based on an optimized activity plan. The input is the optimized activity plan, and the output is the specific action command to be executed on the home device. This operation allows the device to run efficiently and reduces unnecessary energy consumption. 【0648】 Step 4: 【0649】 The server uses local energy management tools to develop an integrated management plan for electricity usage. Inputs include household activity plans and total local electricity consumption data, while output is an optimal electricity usage plan. This planning process optimizes electricity consumption across the entire region. 【0650】 Step 5: 【0651】 The terminal notifies each household's information processing device of the formulated electricity usage plan. The input is the optimal electricity usage plan, and the output is the action plan displayed in each household. This notification allows users to take specific actions based on the proposed plan. 【0652】 Step 6: 【0653】 The user adjusts the settings of their home devices according to notifications from the terminal. The input is the notification content from the terminal, and the output is the user's changes to the device settings. This adjustment results in optimized actual power consumption. 【0654】 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. 【0655】 This invention is implemented as an autonomous AI agent system incorporating an emotion engine, utilizing IoT devices and home appliance control devices within the home. This system provides a more personalized experience based on the user's emotional state. 【0656】 The server communicates with multiple IoT devices within the home and collects data. This data includes the status of home appliances and the user's schedule information. The server also uses voice input and camera data from the terminal to analyze the user's emotions using an emotion engine. 【0657】 The emotion engine uses voice analysis and image recognition technologies to identify emotions from the user's voice tone and facial expressions. For example, it can identify whether the user is anxious or relaxed. This emotional information is fed back to the server, and household activities are planned to be adjusted to suit the user's emotions. 【0658】 Next, the server generates an activity plan based on this information and sends specific control commands to devices within the home. For example, if the emotion engine determines that the user is feeling stressed, the server instructs the smart speaker to play relaxing background music. It also instructs smart lights to adjust the room lighting for relaxation. 【0659】 Educational activities are also optimized based on emotional information. The device suggests ways to encourage participation even if the child is not currently interested. For example, if the device analyzes that the child is experiencing stress, it will launch an educational app that includes game elements. 【0660】 Ultimately, the server monitors all devices in the home in real time and notifies the user if any abnormalities are detected. This system enables continuously optimized home management, supporting the user in enjoying their life with peace of mind. Providing a home environment that takes the user's feelings into consideration is an embodiment of the present invention. 【0661】 The following describes the processing flow. 【0662】 Step 1: 【0663】 The server collects status data from IoT devices and home appliance control devices within the home. This includes refrigerator inventory status, robot vacuum cleaner usage status, and smart lighting settings. 【0664】 Step 2: 【0665】 The server acquires the user's schedule data, and at the same time, collects the user's emotional data through an emotion engine using voice input and camera via the terminal. 【0666】 Step 3: 【0667】 The emotion engine analyzes collected voice and facial expression data to identify the user's current emotional state. For example, it can determine whether the user is calm or stressed. 【0668】 Step 4: 【0669】 The server optimizes the home activity plan based on the user's emotional state. For example, if the user is stressed, the plan will incorporate adjustments such as playing relaxing music. 【0670】 Step 5: 【0671】 The server sends operation instructions to the home appliance control unit based on the generated optimization plan. For example, it might change the color and brightness of the lighting or adjust the air conditioning settings. 【0672】 Step 6: 【0673】 The device optimizes suggestions related to children's educational activities based on emotional information. For example, it recommends apps that include game elements to pique a child's interest, even if the child initially shows no interest. 【0674】 Step 7: 【0675】 The server monitors the effectiveness of the appliance operations performed and collects feedback for any anomalies or for further optimization. For example, if the user is still experiencing stress, it will suggest an alternative approach. 【0676】 Step 8: 【0677】 The user evaluates the optimized home environment provided by the system and inputs individual settings and feedback into the system as needed. 【0678】 (Example 2) 【0679】 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". 【0680】 In modern homes, there is a growing demand for personalized optimization of the living environment using home information processing devices and other electronic devices. However, conventional systems struggle to provide appropriate control instructions according to the emotions and states of individual users, and there is a particular problem of insufficient real-time responses based on emotional states. Furthermore, in educational and learning activities, flexible suggestions tailored to children's interests and concerns are not adequately provided. 【0681】 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. 【0682】 In this invention, the server includes, as a collection means, means for acquiring environmental information and time management information from an information processing device; as an analysis means, means for generating an optimized living environment plan based on the acquired data; and as an emotion analysis means, means for collecting emotion information using voice analysis technology and image recognition technology. This makes it possible to provide an optimal living environment based on the user's emotion information and to efficiently support educational activities. 【0683】 "Collection means" refers to the function of acquiring environmental information and time management information from an information processing device. 【0684】 "Analysis tools" refer to the function of generating a plan to optimize the living environment based on the acquired data. 【0685】 A "control means" is a function that instructs the information processing device to perform specific operations based on the generated plan. 【0686】 A "monitoring means" is a function that constantly monitors the operation of the information processing device and immediately notifies the user if an abnormality is detected. 【0687】 "Proposal methods" refer to the function of setting up and presenting programs to efficiently advance learning and educational activities. 【0688】 "Emotion analysis means" refers to a function that recognizes and analyzes individual emotional information using voice analysis technology and image recognition technology. 【0689】 This invention is implemented through an in-home information processing system. It is primarily an autonomous system consisting of a server, terminals, and user interaction, aiming to optimize the living environment and support educational activities. 【0690】 First, the server connects with various sensor devices installed in the home to collect environmental information such as temperature, humidity, and illuminance, as well as user time management information, in real time. This information collection utilizes sensors built into devices such as smartphones and computers. The server uses this data to generate an activity plan to optimize the living environment. 【0691】 Next, the device collects user emotional information using a voice input device and camera. This emotional information is inferred from the user's voice tone and facial expressions using voice analysis and image recognition technologies. Specifically, it determines whether the user is relaxed or stressed. The result of this determination is sent to a server, which generates control commands that are reflected in the devices within the home. 【0692】 Based on this control command, the server sends specific operation instructions to smart devices. For example, if user fatigue is detected, it instructs the smart speaker to play healing music and the smart lights to adjust the lighting to relaxation mode. 【0693】 Furthermore, in educational activities, the device monitors the child's learning progress, and if the child shows no interest, it suggests a learning program incorporating game elements. This suggestion is an important way to capture the child's interest. 【0694】 If a user says "I'm tired today," the emotion analysis tool analyzes the tone, and the server decides to recommend relaxation mode. If the device determines that a child is losing focus during an educational activity, it recommends a quiz-style approach. 【0695】 An example of a prompt message is "Please suggest the optimal device operation based on the user's emotions," which is then input to the generating AI model. 【0696】 This system enables the provision of flexible functions that adapt to the user's emotional state, thereby improving comfort and learning efficiency within the home. 【0697】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0698】 Step 1: 【0699】 The server collects environmental and time management information as input from information processing devices within the home. This input data includes temperature, humidity, illuminance, and the user's schedule. The server analyzes this data and stores it as basic information for optimizing the living environment. Specifically, it aggregates data recorded in real time by smart sensors and prepares it for the next processing stage. 【0700】 Step 2: 【0701】 The device receives voice input from the user and facial expressions captured via the camera as input. Based on this input data, the emotion analysis system uses voice analysis and image recognition technologies to identify the user's emotions. This process analyzes changes in voice tone and facial expressions to identify various emotional states (e.g., relaxed, stressed, anxious). The analyzed emotion information is sent to a server and used in the next step. 【0702】 Step 3: 【0703】 The server receives collected environmental information and analyzed emotional information as input and uses analytical tools to generate a living environment plan. This process utilizes data mining techniques and machine learning algorithms to formulate optimal operational instructions adapted to the user's emotional state. The output is a specific device operation plan. For example, if the room temperature needs to be adjusted, it might include instructions to change the air conditioner settings. 【0704】 Step 4: 【0705】 Based on the generated plan, the server sends control commands as output to various devices in the home. This results in specific actions, such as a smart speaker playing healing music or smart lights adjusting to a warmer color. Each device receives commands from the server and operates according to those instructions. 【0706】 Step 5: 【0707】 The device has a suggestion mechanism specifically designed for educational activities, receiving the child's level of interest during learning as input. Based on the monitoring results, if interest is declining, it generates an output suggesting gamification of the activity. Specifically, this suggestion is made by adding quizzes or mini-games to the interface of the learning app. 【0708】 Step 6: 【0709】 When a user detects an anomaly in their living environment, the server uses monitoring tools to collect that information as input. Upon detecting an anomaly, it immediately sends a notification to the user as output, prompting them to take appropriate action. For example, if a door is left open for an extended period, a warning message is sent to the user's smartphone as a security measure. 【0710】 (Application Example 2) 【0711】 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". 【0712】 Conventional home appliances perform programmed actions without considering the user's emotional state, and therefore fail to adequately address the stress and anxiety users face. Furthermore, there was a need for home appliances that not only provide operation but also offer personalized experiences based on emotional information. Additionally, there was a lack of systems capable of generating activity plans optimized for the home environment and improving quality of life. 【0713】 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. 【0714】 In this invention, the server includes means for acquiring voice and image data and performing emotion analysis, means for generating an optimized home activity plan based on the acquired emotion data, and means for transmitting operation instructions to home devices based on the activity plan. This makes it possible for home devices to operate while taking the user's emotional state into consideration and to provide a personalized experience. 【0715】 "Voice data" refers to information used to record and analyze the user's voice in digital format. 【0716】 "Image data" refers to information used to record and analyze a user's facial expressions and surrounding visual information in digital format. 【0717】 "Emotional analysis" is a process that determines the user's emotional state based on acquired audio and image data. 【0718】 A "home activity plan" is a plan designed to optimize the operation and suggestions of devices at home, based on the user's emotional state and schedule. 【0719】 "Household appliances" refer to home appliances and IoT devices used within the home, and are the entities to which control commands are sent. 【0720】 This invention is a system that collects voice and image data and realizes optimized in-home activities through emotion analysis. The server uses smart devices and computing equipment in the home to acquire voice signals and facial expressions emitted by the user through a camera and microphone. This data is processed by image recognition software and voice analysis software, and the user's emotional state is determined by an emotion engine. 【0721】 Voice analysis identifies emotions by considering factors such as voice tone, speaking speed, and volume. Image recognition reads emotions from eye and mouth movements, and facial muscle tension. The acquired emotion data is sent to a server and used to generate an optimal operating plan for home devices. This operating plan sends commands to home devices to ensure optimal functionality according to the user's emotional state. 【0722】 For example, if the system determines that the user desires relaxation, it will instruct the system to play relaxation music through the speakers. It will also send a command to the smart lights to adjust their brightness to create a calmer environment. Furthermore, for children, when they are feeling stressed, the system will suggest using educational apps that include game elements to keep them engaged. 【0723】 A concrete example of a prompt is, "If the user appears to be having trouble, suggest a fun activity that suits them." Using such prompts makes it easier for the generative AI model to provide support tailored to the user's situation. 【0724】 In this way, the server can continuously adapt to the user's emotions, supporting a safe and comfortable life within the home. 【0725】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0726】 Step 1: 【0727】 The server acquires audio and image data through the home's microphone and camera. During this data collection phase, the user's voice and facial expressions are converted into digital data. The input consists of audio signals and image frames, which are provided to the server's analysis module. 【0728】 Step 2: 【0729】 Based on the voice data acquired by the server, voice analysis software is used to analyze voice tone, speed, and volume. The output is an estimated value of emotion, providing an initial determination of the user's emotional state. By identifying the user's emotional state through data analysis, a corresponding action plan is formulated. 【0730】 Step 3: 【0731】 The server uses image recognition software to analyze the user's facial expressions from image data. At this stage, eye and mouth movements, facial muscle tension, and other factors are evaluated. The input is an image frame, and the output is an emotion estimate. This is then integrated with the audio analysis results to obtain the final emotion data. 【0732】 Step 4: 【0733】 The emotion engine integrates voice and image analysis results to estimate an overall emotional state. This estimation is then used by a plan generation module on the server to develop a household activity plan. 【0734】 Step 5: 【0735】 The server generates an optimal household activity plan and appliance operation plan based on emotional data. The input is integrated emotional data, and the output is specific appliance control commands. Based on this plan, the server sends commands to household appliances to play relaxing music or adjust lighting. 【0736】 Step 6: 【0737】 The user experiences the changes in the home environment provided as a result of Step 5. This enables the implementation of home support that is adapted to the user's current emotional state. 【0738】 Integrated processing enables the automatic adjustment of home appliances based on emotions, thereby improving the user's quality of life. 【0739】 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. 【0740】 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. 【0741】 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. 【0742】 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. 【0743】 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. 【0744】 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. 【0745】 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. 【0746】 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. 【0747】 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." 【0748】 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. 【0749】 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. 【0750】 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. 【0751】 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. 【0752】 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. 【0753】 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. 【0754】 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. 【0755】 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. 【0756】 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. 【0757】 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. 【0758】 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. 【0759】 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 as being incorporated by reference. 【0760】 The following is further disclosed regarding the embodiments described above. 【0761】 (Claim 1) 【0762】 As a means of collection, a means for acquiring status data and schedule data from a home appliance control device, 【0763】 As an analytical method, a means for generating an optimized household activity plan based on acquired data, 【0764】 As a control means, means for transmitting operation instructions to a home appliance control device based on an activity plan, 【0765】 As a monitoring means, it includes a means for monitoring the operating status of the home appliance control device and notifying when an abnormality occurs, 【0766】 As a proposed method, a means of generating and presenting educational activity programs, 【0767】 A system that includes this. 【0768】 (Claim 2) 【0769】 The system according to claim 1, comprising means for acquiring family structure information and personal activity schedule information as collection means. 【0770】 (Claim 3) 【0771】 The system according to claim 1, further comprising, as an analysis means, a means for generating an optimized operation plan from the usage history of a home appliance control device using a machine learning algorithm. 【0772】 "Example 1" 【0773】 (Claim 1) 【0774】 A means for acquiring status data and time information from information technology devices within the home, 【0775】 A means for generating an optimized family activity plan based on data acquired through machine learning processing, 【0776】 A means for transmitting operation instructions to an information technology device based on a family activity plan, 【0777】 A means for monitoring the operating status of information technology devices and notifying when an abnormality occurs, 【0778】 A means of generating and presenting educational activity programs tailored to different stages of development, 【0779】 A system that includes this. 【0780】 (Claim 2) 【0781】 The system according to claim 1, comprising means for obtaining family composition information and personal schedule information. 【0782】 (Claim 3) 【0783】 The system according to claim 1, comprising means for generating an optimized operation plan from the usage history of an information technology device using machine learning processing. 【0784】 "Application Example 1" 【0785】 (Claim 1) 【0786】 As a means of collection, means for acquiring status information and timetable information from an information processing device, 【0787】 As an analytical means, a means for generating an optimized activity plan within the living space based on the acquired information, 【0788】 As a control means, means for transmitting operation commands to an information processing device based on an activity plan, 【0789】 As a monitoring means, it includes a means for monitoring the operating status of the information processing device and notifying when an abnormality occurs, 【0790】 As a proposed means, a means for generating and presenting a program for knowledge activities, 【0791】 As a means of regional energy management, it includes means for generating information to optimize electricity use within the region and transmitting control commands based on that information, 【0792】 A system that includes this. 【0793】 (Claim 2) 【0794】 The system according to claim 1, comprising means for formulating a plan to optimize the overall electricity consumption of a city and notifying electronic devices in each household, as a means for managing energy within a region. 【0795】 (Claim 3) 【0796】 The system according to claim 1, comprising, as an analytical means, a machine learning algorithm, and means for generating an optimized operation plan and a regional power management plan from the usage history of an information processing device. 【0797】 "Example 2 of combining an emotion engine" 【0798】 (Claim 1) 【0799】 As a means of collection, a means for acquiring environmental information and time management information from an information processing device, 【0800】 As an analytical method, a means for generating an optimized living environment plan based on acquired data, 【0801】 As a control means, means for transmitting operation instructions to an information processing device based on a plan, 【0802】 As a monitoring means, the means of monitoring the operating status of the information processing device and notifying when an abnormality occurs, 【0803】 As a proposed method, a means for generating and presenting a learning activity program, 【0804】 As a means of emotion analysis, a means of collecting emotion information using voice analysis technology and image recognition technology, 【0805】 A system that includes this. 【0806】 (Claim 2) 【0807】 The system according to claim 1, comprising means for analyzing emotional information within the household and optimizing device operation based thereon. 【0808】 (Claim 3) 【0809】 The system according to claim 1, comprising means for proposing to gamify educational activities based on emotional information. 【0810】 "Application example 2 when combining with an emotional engine" 【0811】 (Claim 1) 【0812】 The collection means include acquiring audio data and image data, and means for performing sentiment analysis. 【0813】 As an analytical method, a means of generating an optimized household activity plan based on acquired emotional data, 【0814】 As a control means, means for transmitting operation instructions to household appliances based on an activity plan, 【0815】 As a monitoring method, it includes a means to monitor the user's psychological state based on emotion analysis and to notify the user when an abnormality occurs. 【0816】 As a proposed method, a means of generating and presenting activities and games that correspond to the user's emotional state, 【0817】 A system that includes this. 【0818】 (Claim 2) 【0819】 The system according to claim 1, wherein a home appliance is equipped with means for acquiring voice and image information and for analyzing the user's emotional state in cooperation with an emotion engine. 【0820】 (Claim 3) 【0821】 The system according to claim 1, comprising, as an analysis means, machine learning technology and means for generating an optimized household activity plan based on the sentiment analysis results. [Explanation of symbols] 【0822】 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

[Claim 1] As a means of collection, a means for acquiring status data and schedule data from a home appliance control device, As an analytical method, a means for generating an optimized household activity plan based on acquired data, As a control means, means for transmitting operation instructions to a home appliance control device based on an activity plan, As a monitoring means, it includes a means for monitoring the operating status of the home appliance control device and notifying when an abnormality occurs, As a proposed method, a means of generating and presenting educational activity programs, A system that includes this. [Claim 2] The system according to claim 1, comprising means for acquiring family structure information and personal activity schedule information as collection means. [Claim 3] The system according to claim 1, further comprising, as an analysis means, a means for generating an optimized operation plan from the usage history of a home appliance control device using a machine learning algorithm.

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