system

Abstract

We provide the system. [Solution] An information processing device that learns each member's schedule data and can automatically assign the most suitable household chores or childcare tasks, A means for analyzing items in a storage environment using image processing technology, detecting shortages of items, and generating a replenishment list, A means of providing menu suggestions that take into account family preferences and nutrition, A means of monitoring the progress of each task and proposing task reassignment or new tasks based on progress, A means of notification or warning as necessary, 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 in 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 modern families, the burden of housework and child-rearing has increased, and many families are overwhelmed by the time and labor required to manage this. Especially in dual-income families and single-parent families, management may become insufficient, and an efficient and effective task allocation is required. Also, in daily shopping and meal preparation, unnecessary shopping and unhealthy diets often pose problems. 【0005】 The present invention aims to solve the problem of providing means for optimizing time and resources and improving the efficiency of in-home work in families with such problems. 【Means for Solving the Problems】 【0006】 This invention provides a system that includes information processing means for learning the schedule data of each household member and automatically assigning tasks optimized for each individual member. The system also uses image processing technology to analyze the storage environment, for example, items in a refrigerator, to detect missing items and generate a shopping list. Furthermore, the system has a function to suggest menus that take into account the family's preferences and nutritional needs. 【0007】 In addition, it includes notification mechanisms to monitor the progress of each task, reassign tasks or suggest new tasks as needed, and provide notifications and warnings as required. This enables the automation and optimization of household tasks, improving household efficiency. 【0008】 "Information processing means" refers to a combination of hardware and software for receiving, processing, and outputting all kinds of data according to their intended purpose. 【0009】 "Image processing technology" refers to techniques that analyze image and video data to extract or transform specific information. 【0010】 A "storage environment" refers to a space or equipment for storing food or other items, and in this invention, it often specifically refers to a refrigerator. 【0011】 A "shopping list" is a list of items that need to be purchased, generated based on current inventory and required items. 【0012】 "Menu planning" is the process of making suggestions for meal content, taking into account nutrients and preferences, and based on available ingredients. 【0013】 "Task reassignment" refers to reviewing already assigned tasks in response to changing circumstances and reassigning them in a newly optimized form. 【0014】 "Notification means" refers to functions or devices that notify users of information or warnings, and may include methods such as audio or screen display. 【Brief Description of the Drawings】 【0015】 [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It 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] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined. 【Modes for Carrying Out the Invention】 【0016】 Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings. 【0017】 First, the terms used in the following description will be explained. 【0018】 In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like. 【0019】 In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor. 【0020】 In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like. 【0021】 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). 【0022】 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." 【0023】 [First Embodiment] 【0024】 Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment. 【0025】 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. 【0026】 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). 【0027】 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. 【0028】 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. 【0029】 The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form 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. 【0030】 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. 【0031】 Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14. 【0032】 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. 【0033】 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. 【0034】 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. 【0035】 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". 【0036】 The present invention is a system for efficiently managing household chores and childcare tasks, and includes information processing means that can learn the schedules of each household member and assign optimal tasks. Specific embodiments thereof are described below. 【0037】 The server receives schedule data from household members and learns each member's activity patterns based on this data. Based on this learned data, the server automatically assigns household chores and childcare tasks to each member at the most appropriate time. The server can also adjust the types of tasks based on the user's strengths. 【0038】 Furthermore, the device sends image data of the refrigerator's contents to the server. The server, upon receiving this data, uses image analysis technology to determine the food inventory in the refrigerator and detect any missing items. Based on this information, the server automatically generates a shopping list, helping users reduce unnecessary purchases and providing efficient daily management. 【0039】 The server also suggests menus based on the ingredients in the refrigerator, taking into account the user's food preferences and nutritional requirements. These menus are presented to the user via a terminal, helping to make meal planning easier. 【0040】 Users can report task progress via their devices. These devices send this progress data to a server, which monitors the overall task status in real time. The server manages tasks to ensure smooth workflow, reassigning tasks or suggesting new ones as needed. 【0041】 As a concrete example, the server analyzes an image of the refrigerator received from the terminal in the morning and determines that "there is a shortage of milk." As a result, the server adds milk to the shopping list and assigns this shopping task to a user who has free time in the evening. This information is notified to the terminal, allowing the user to plan their schedule efficiently. 【0042】 This system can also send reminders and emergency notifications to users using notification methods. This helps to coordinate awareness within the household and establish a system for responding quickly to emergencies. Through these functions, household task management is automated, resulting in an improved quality of life. 【0043】 The following describes the processing flow. 【0044】 Step 1: 【0045】 The server receives schedule data entered by the user through their device. This data includes appointments for work, school, household chores, etc., and the server records it to learn the activity patterns of each member of the household. 【0046】 Step 2: 【0047】 The server optimally assigns household and childcare tasks based on learned schedule data. Assignments are made individually, taking into account each member's availability and areas of expertise. 【0048】 Step 3: 【0049】 The terminal allows the user to take photos of the inside of the refrigerator and send them to the server. The image data is received by the server and analyzed to understand the status of food inventory. 【0050】 Step 4: 【0051】 The server uses image analysis technology to analyze the contents of the refrigerator and identify missing food items. Based on these identified missing items, the server automatically generates a shopping list. 【0052】 Step 5: 【0053】 The server suggests menus that utilize the user's available ingredients, taking into account their preferences and nutritional requirements. The suggested menus are then notified to the user via their device. 【0054】 Step 6: 【0055】 Users use their devices to report the progress of their assigned tasks. The devices send this progress data to the server, which updates the task completion status in real time. 【0056】 Step 7: 【0057】 The server monitors aggregated progress data and, if necessary, reassigns tasks or proposes new tasks. If task delays or resource shortages are detected, corrective actions are taken immediately. 【0058】 Step 8: 【0059】 The server sends reminders and emergency notifications to household members as needed. The device receives these and displays them to the user, instantly conveying important information. 【0060】 (Example 1) 【0061】 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." 【0062】 In modern households, managing various household tasks is becoming increasingly complex. Especially in multi-member households, efficiently dividing household chores and childcare activities while considering each member's schedule is crucial. Furthermore, inadequate food inventory management can lead to wasteful shopping and unbalanced nutrition. To address these challenges, efficient and flexible task management, along with streamlined food inventory and nutrition planning, are essential. 【0063】 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. 【0064】 This invention includes a server that includes information processing means capable of learning each member's time management data and automatically assigning the most suitable household tasks or childcare activities; means for analyzing objects in the storage environment using image analysis technology, identifying shortages of objects, and generating replenishment tables; and means for suggesting meal plans that take into account the group's preferences and nutrition. This enables efficient task sharing within the household and streamlines food inventory and meal planning. 【0065】 "Time management data" refers to information about the schedules and tasks that each member uses in their daily activities, and includes data such as schedules and priorities. 【0066】 An "information processing device" is a device or system that has the function of performing calculations and analyses based on input data and deriving a specific result. 【0067】 "Image analysis technology" refers to techniques that analyze image data to recognize objects and detect features, often utilizing deep learning models. 【0068】 "Storage environment" refers to the place and conditions for storing and preserving food and goods, and includes refrigerators and pantries in the home. 【0069】 A "supply list" is a list of items that are currently missing, and is used for reference in future purchasing activities. 【0070】 "Meal plan suggestions" is a process that proposes ingredients and menus to be consumed, taking into account the user's preferences and nutritional balance. 【0071】 "Activity progress" refers to information indicating the extent to which each member has completed their assigned tasks. 【0072】 "Notification means" refers to a function for conveying important information, notifications, or warnings to the user, including alarms and message notifications. 【0073】 This invention provides a system for streamlining the management of household tasks, comprising a server for information processing and a terminal accessible to users. This system aggregates time management data from each member of the household and assigns optimal household tasks and childcare activities based on this data. The server analyzes the schedule information collected from each member using machine learning algorithms, specifically time-series analysis techniques such as long-term short-term memory (LSTM). This allows the system to learn each member's activity patterns and achieve efficient task assignment. 【0074】 Furthermore, image data of the inside of the refrigerator is acquired through a camera attached to the terminal. The server analyzes this image data using computer vision technology (for example, the YOLO model or a deep learning model built with TENSORFLOW®) to determine the food inventory. For items that are missing, the server automatically generates a shopping list for replenishment and notifies the user's terminal. 【0075】 Furthermore, the server considers the user's food preferences and nutritional requirements, and proposes a meal plan based on the ingredients in the refrigerator. This process utilizes a generative AI model to suggest the most suitable menu. Users can view these suggestions on their device, helping them plan healthier and more balanced meals. 【0076】 On the other hand, users can report task progress using their devices, allowing the server to monitor task completion in real time. If necessary, the server can reassign tasks or suggest new ones to help ensure smooth workflow within the home. 【0077】 As a concrete example, the server analyzes an image of the refrigerator sent via the terminal in the morning and determines that "there is a shortage of milk." Based on this result, it adds milk to the shopping list and assigns this shopping task to a user who has relatively more time in the evening. This information is notified to the terminal, allowing the user to shop efficiently on their way to work. 【0078】 Examples of prompts to be input to the generating AI model include: "Please tell me how to efficiently manage household chores and childcare. Specifically, please explain in detail the mechanisms for task assignment and food inventory management." In this way, it is expected that the system of the present invention will improve the efficiency of household tasks and enhance the quality of life. 【0079】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0080】 Step 1: 【0081】 The server receives schedule data sent from each member via their terminal. The input includes data about each member's schedule and tasks. Based on this data, the server uses machine learning algorithms to analyze and learn each member's activity patterns. Here, time series analysis techniques are used to create a predictive model, determining a work schedule suitable for each member. 【0082】 Step 2: 【0083】 The terminal periodically captures image data from inside the refrigerator and sends it to the server. The input is an image file of the inside of the refrigerator. The server receives this image data and uses image analysis technology to analyze the food inventory status. Specifically, it uses a computer vision model to recognize the type and quantity of food and identify items that are missing. An inventory list and a shortage list are generated as output. 【0084】 Step 3: 【0085】 The server uses accumulated inventory data to list missing items and create a shopping list. Inputs include the missing items list obtained in step 2 and the user's past purchasing patterns. Based on this information, the server automatically generates a shopping list and notifies the terminal. The output is a shopping list that the user can review. 【0086】 Step 4: 【0087】 The server suggests menus based on the user's food preferences and nutritional requirements, taking into account the contents of their refrigerator. The inputs are inventory data and user preference data. A generative AI model analyzes this data to generate optimal menu suggestions. The output is a menu suggestion displayed on the user's device. 【0088】 Step 5: 【0089】 Users input task progress via their terminals and report it to the server. Input includes data on the progress of each task. The server receives this data, monitors progress in real time, and reassigns tasks if necessary. Output includes updated task management information, which is sent to the terminal. 【0090】 (Application Example 1) 【0091】 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." 【0092】 Efficiently managing household chores and childcare tasks is a significant challenge for many families. It requires assigning tasks at the optimal time, taking into account the schedules of each family member. However, manually managing these tasks is difficult and inefficient. Furthermore, properly managing food inventory and suggesting menus that meet nutritional and taste requirements are also important needs within families, but currently, there is a lack of efficient means to achieve this. 【0093】 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. 【0094】 This invention includes a server that learns each member's time management data and automatically assigns the optimal household chore or childcare role; a server that uses image processing technology to analyze items in the storage environment, detect shortages of items, and generate a replenishment list; and a server that provides menu suggestions that take into account the preferences and nutritional needs of each member. This enables efficient management of tasks that are appropriate to each member's schedule and abilities, reducing the burden on the household and improving the quality of life. 【0095】 "Information processing means" refers to a device or software that learns the time management data of each member and automatically assigns the optimal household chore or childcare role. 【0096】 "Image processing technology" refers to image analysis techniques used to analyze items within a storage environment and detect shortages of items. 【0097】 A "replenishment list" is a list generated when a shortage of goods is detected, used to replenish the necessary items. 【0098】 "Member preferences and nutritional information" refers to information about each member's taste preferences and health-related nutritional needs, and serves as basic data for proposing menus based on this information. 【0099】 A "menu suggestion device" is a device or software that generates a plan for daily meals based on the preferences and nutritional needs of its members. 【0100】 A "generative AI model" is an information generation model that utilizes artificial intelligence and has the ability to propose optimal solutions based on the given data. 【0101】 A "prompt statement" is an instruction given to a generative AI model, used to control the AI's output based on specific conditions or data. 【0102】 To realize this invention, a system will be built in which a server and terminals work together to perform the necessary functions. The server will receive time management data from each member and assign the most suitable household chore or childcare role based on this data. The time management data will be managed based on each member's calendar information and activity data. 【0103】 The terminal operates a video acquisition device installed in the home to photograph items within the storage environment. This video data is processed using video processing technology and transmitted to a server. The server analyzes the video data, determines the shortage of items, and generates a replenishment list. 【0104】 Furthermore, the server uses a generative AI model to suggest optimal menus based on the preferences and nutritional information of its members. The generative AI model generates specific menu suggestions by inputting prompts. For example, one might send the prompt, "Please suggest a nutritionally balanced menu for my family's dinner." 【0105】 As a concrete example, if the server analyzes video data in the morning and detects a shortage of milk, it adds milk to the replenishment list and suggests purchasing it to the most suitable member. Users receive the suggestion via their device and can confirm it through a smartphone app. 【0106】 This system improves the efficiency of daily household management, reduces the burden on family members, and maintains harmony within the household. The menu suggestions generated by the AI ​​model simplify daily meal planning and support a nutritious diet. 【0107】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0108】 Step 1: 【0109】 The server retrieves time management data for each member. The input consists of each member's calendar information and activity data. Based on this, the server analyzes each member's schedule to identify their free time and areas of expertise. The output is a list of optimized task candidates. 【0110】 Step 2: 【0111】 The terminal operates a video acquisition device installed in the home to photograph items within the storage environment. The input is video data. The terminal sends this data to a server, which analyzes the video data using video processing technology. As a result of the analysis, the output reveals the status of any missing items. 【0112】 Step 3: 【0113】 The server generates a replenishment list based on the analysis results. The input is the status data of the analyzed items. The server detects and lists the missing items. The output is a list of items that need to be replenished. 【0114】 Step 4: 【0115】 The server uses a generative AI model to generate menu suggestions based on the preferences and nutritional information of its members. The input consists of nutritional information, preference data, and a prompt. For example, the prompt might be "Please suggest a nutritionally balanced menu for my family's dinner." The AI ​​analyzes this data and outputs the optimal menu suggestion. 【0116】 Step 5: 【0117】 The user checks the replenishment list and menu suggestions sent from the server via their terminal. Input is the notification from the server. The user receives the notification and takes action as needed. Output is the user's action plan. 【0118】 Step 6: 【0119】 Users report task progress to their terminals and send it to the server. The input is the task completion status. The server receives the report, monitors the overall task progress, and makes role reassignments or new suggestions as needed. The output is the updated task assignment status. 【0120】 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. 【0121】 This invention is a system for streamlining task management within the home, and in particular, by combining it with an emotion engine, it achieves flexible task assignment and management that takes into account the user's emotional state. Specific embodiments are shown below. 【0122】 The server first receives schedule data from household members and learns their individual activity patterns based on this data. Then, it analyzes their emotional state using this data and an emotion engine to assign optimal tasks to each member. Emotional states are obtained through member input, voice, and facial recognition. For example, if it is determined that a member is experiencing stress, tasks are readjusted to reduce their burden. 【0123】 The device displays this information to the user and explains how emotion-based task assignments are performed. It also sends image data of the refrigerator to the server to track inventory levels. This information, along with the results of the emotion engine, is used to generate meal suggestions and shopping lists. 【0124】 The server further suggests menus that take into account the user's preferences and nutritional balance, and by combining this with emotional data, it creates a meal plan that reduces the user's psychological burden. The suggestions are notified to the user via their device, and the user confirms them. 【0125】 Users report task progress using their devices and provide feedback on the psychological burden they experience during the process. Based on this feedback, the server monitors task progress and reassigns tasks as needed. By using an emotion engine, it is possible to evaluate user satisfaction and stress levels and provide notifications and advice tailored to each user. 【0126】 As a concrete example, the server considers the busyness of the household and the feelings of individual members, and if it determines that the emotional burden is high, it sends encouraging messages or relaxation methods via the device. This allows the system to be more than just an efficiency tool, but also to implement initiatives that consider the mental health of the entire family. 【0127】 The following describes the processing flow. 【0128】 Step 1: 【0129】 The server receives schedule and emotion input data entered by the user through the terminal. This includes information about the user's daily schedule, mood, and energy level for the day. The server stores this data and learns each user's activity patterns and emotional tendencies. 【0130】 Step 2: 【0131】 The device takes a picture of the inside of the refrigerator and sends it to the server. The server performs image analysis to determine the current inventory status. This analysis identifies which food items are running low. 【0132】 Step 3: 【0133】 The server utilizes accumulated schedule and emotional data to assign household and childcare tasks to each family member. When assigning tasks, it takes into account the user's current energy level and stress level, adjusting them to avoid burdening them. If the emotional engine detects user fatigue, it reduces or reassigns tasks. 【0134】 Step 4: 【0135】 Based on the analysis results, the server lists the necessary food items and creates a shopping list. At the same time, it suggests a menu tailored to the user's preferences and emotional state. This suggestion is delivered to the user via their device. If the user's emotional state is negative, the server recommends a menu that includes many ingredients that improve mood. 【0136】 Step 5: 【0137】 Users check and complete assigned tasks on their devices. Information is sent to the server by reporting the task progress and their emotions during the process via the device. The server uses this data to evaluate the task progress and the user's emotional tendencies. 【0138】 Step 6: 【0139】 The server monitors progress information and emotional data, and adjusts tasks as needed. If the emotional engine determines that the user is experiencing significant physical or mental strain, it provides support by inserting rest periods or sending encouraging messages to the device. 【0140】 Step 7: 【0141】 The server monitors the overall system status, continuously learns emotional data to improve the efficiency of tasks performed within the home and member satisfaction, and provides improvement measures. The terminal delivers necessary information and advice to the user in a timely manner through notification functions. 【0142】 (Example 2) 【0143】 Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal". 【0144】 Conventional household task management systems struggle to flexibly assign tasks while considering the emotional state of individual users, and they lack sufficient consideration for reducing mental burden. Therefore, the challenge lies in suggesting optimal tasks according to the user's stress level and achieving efficient work distribution that meets the user's needs in complex household environments. 【0145】 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. 【0146】 In this invention, the server includes data processing means that learn each user's schedule information and automatically assign the most suitable tasks or caregiver duties, including sentiment analysis; means that analyze objects in the storage area using video analysis technology, detect shortages of objects, and generate a replenishment list; and means that suggest meal plans that take into account the family's preferences and nutritional needs. This makes it possible to manage tasks efficiently within the home while reducing the psychological burden on the user. 【0147】 A "user" refers to an individual person within the household who is the subject of task management and is the entity that provides the information that forms the basis for data processing and sentiment analysis. 【0148】 "Emotional analysis" is the process of evaluating a user's emotional state from voice, facial expressions, and other data, and using that information to inform tasks and suggestions. 【0149】 "Data processing means" refers to a set of functions for collecting and analyzing each user's schedule information and assigning optimal tasks through learning. 【0150】 "Video analysis technology" refers to the technology that processes image data acquired by cameras and sensors to recognize and classify objects. 【0151】 "Storage area" refers to the space within a home where items are stored and managed, and includes refrigerators, pantries, and other similar spaces. 【0152】 A "meal plan" is a meal plan created with consideration for the family's preferences and nutritional needs, and serves as a guide for cooking within the home. 【0153】 A "task" refers to a specific household chore or childcare activity that is divided among family members and is to be performed by the user. 【0154】 "Psychological burden" refers to the level of stress and anxiety a user experiences while performing a task, and is measured through emotion analysis. 【0155】 "Notification means" refers to a mechanism that provides users with necessary information and advice, and is executed through a device. 【0156】 This invention is a system for streamlining task management within the home, and it enables flexible task assignment incorporating sentiment analysis. This system mainly consists of a server, terminals, and users. 【0157】 The server collects each user's schedule data and analyzes it in combination with emotional data to assign the most suitable tasks. In this process, image analysis and voice analysis technologies are combined to obtain emotional states from the user's voice and facial expressions. Specifically, a commonly used image analysis API is used for facial recognition, and a standard voice recognition system is used for voice analysis. 【0158】 The terminal displays task information received from the server to the user and explains the task details. It also uses cameras installed in storage areas such as refrigerators to capture images of the contents and monitor the condition of the items. The captured images are periodically sent to the server to help monitor inventory levels. 【0159】 As a concrete example, the server considers the busyness of the household and the feelings of its members, and if it determines that the emotional burden is high, it sends encouraging messages and relaxation methods to the user via the terminal. In this way, the system can be more than just a task management tool; it can also play a role in improving the overall well-being of the household. 【0160】 An example of a prompt would be: "Evaluate the emotional state of the family based on data from yesterday and suggest the most appropriate tasks for each member. Also, if a member is experiencing stress, include specific suggestions to alleviate their burden." This prompt is used by a generative AI model to assign new tasks based on the user's situation. 【0161】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0162】 Step 1: 【0163】 The server receives schedule data from each user as input. This data includes each user's appointments and free time. The server analyzes this information and learns each user's activity patterns. Specifically, it uses data analysis algorithms to extract past schedule trends and use them to help plan future schedules. 【0164】 Step 2: 【0165】 The device acquires the user's voice input and facial expression data. Based on this input data, it analyzes the user's emotional state using voice recognition software and image recognition technology. The emotional analysis results are output and sent to the server. Specifically, the device collects voice using its built-in microphone, captures facial expressions with its camera, and processes this data in real time. 【0166】 Step 3: 【0167】 The server takes schedule data and sentiment analysis results as input and uses a generative AI model to calculate the optimal task assignment. This process outputs a task list that is individually customized based on each user's stress level and free time. Specifically, it rearranges and adjusts tasks based on prompt messages generated by the AI ​​model. 【0168】 Step 4: 【0169】 The device displays task assignment information sent from the server to the user. This information includes an explanation of why the task was assigned. Once the user has reviewed the task, they send their feedback back to the server. Specifically, the device uses its notification function to send an alert to the user and provides a user interface that allows for easy feedback input. 【0170】 Step 5: 【0171】 Users report task progress via their devices and provide feedback on the psychological burden they experience while performing the tasks. This feedback data serves as input for the server to adjust or suggest improvements to the tasks. Specifically, this involves users entering their progress and emotional evaluation using a form on their devices and sending the data to the server via a submit button. 【0172】 (Application Example 2) 【0173】 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". 【0174】 The problem that this invention aims to solve is to manage employee schedules and reduce stress in factory work, thereby enabling efficient and flexible work adjustments. It aims to lighten the burden and improve work efficiency while taking into account the emotional state of employees. Conventional systems have the problem of rigid work assignments that do not take into account individual emotions or areas of expertise, resulting in significant psychological burden. 【0175】 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. 【0176】 This invention includes a server that includes information processing means capable of learning each individual's activity plan data and automatically assigning the most suitable work or childcare tasks; means for analyzing items in the storage environment using image analysis technology, detecting shortages of items, and generating a replenishment list; and means for providing meal suggestions that take into account family preferences and nutrition. This enables efficient work support while performing sentiment analysis to evaluate the emotional state of employees and reduce their workload. 【0177】 "Activity plan data" refers to information about each individual's daily schedule and tasks, and this data is used as the basis for efficient task assignment. 【0178】 An "information processing means" is a component of a system that has the function of deriving the optimal result by analyzing and processing given data. 【0179】 "Image analysis technology" is a technique for analyzing digital image data and extracting useful information from it, and is used for recognizing and classifying objects. 【0180】 A "replenishment list" is a list generated when a shortage of an item is detected, indicating which items should be replenished. 【0181】 "Meal suggestions" refer to a method of proposing an optimal meal plan that takes into account individual preferences and nutritional needs. 【0182】 "Emotional analysis" is a technology that evaluates and analyzes an individual's emotional state based on information obtained from audio and video. 【0183】 "Work support" refers to functions that provide assistance and support to improve work efficiency, and plays a particularly important role in collaboration between humans and machines. 【0184】 The system for realizing this application consists of a cloud-based server, multiple sensors placed within the factory, and mobile devices used by employees. The server receives activity plan data sent from factory employees and image data acquired by the sensors, and based on this information, assigns the most suitable tasks to each employee. 【0185】 The server uses emotion recognition software such as Microsoft® Azure® Cognitive Services and Google® Cloud Vision API to perform emotion analysis. This allows it to analyze emotions in real time from employee facial and voice data and reflect the results in activity plan data. Based on this analysis, the server determines appropriate tasks and encouraging messages for each employee. 【0186】 Next, the server uses image analysis technology to retrieve item data from the storage environment within the factory, identifies missing items based on that data, and generates a replenishment list. This utilizes a deep learning model to precisely classify items and automatically identify the necessary replenishments. 【0187】 The generated work assignments and replenishment lists are notified to employees via mobile devices. Based on the notifications received via their devices, employees can efficiently proceed with their work. This reduces the workload on employees and improves the overall work efficiency of the factory. 【0188】 As a concrete example, the server uses emotion analysis to determine that employee B, who is feeling busy in the morning, is tired. Based on this information, a message such as, "Let's take a short break and refresh ourselves. How about taking a breather at the newly opened cafe?" is generated and sent to B via their mobile device. 【0189】 Examples of prompts to input into a generative AI model: 【0190】 "The role of the AI ​​system is to optimize work assignments and support messages based on employee emotional data." 【0191】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0192】 Step 1: 【0193】 The server receives activity plan data transmitted from employees within the factory and image data acquired by sensors. This input data relates to employee schedules and factory inventory status. The server stores this data and prepares it for use in subsequent processing. 【0194】 Step 2: 【0195】 The server analyzes the inventory items using image analysis techniques based on the received image data. In this step, a deep learning model is used to identify each item from the image and calculate their quantities. This identifies items that are low in stock and generates a replenishment list. The output includes the inventory status of each item and a list of items that are low in stock. 【0196】 Step 3: 【0197】 The server uses emotion recognition software to analyze employee facial images and voice data as input. This analysis evaluates each employee's current emotional state. The output provides information indicating each employee's emotional state. This information is used to determine work assignments and support messages. 【0198】 Step 4: 【0199】 The server integrates activity plan data, inventory status, and sentiment analysis results to determine the most suitable tasks and encouragement messages for each employee. Using a generative AI model, it creates and outputs a plan to optimize employee workload and efficiency, taking these factors into consideration. From this process, a list of work instructions and messages is generated. 【0200】 Step 5: 【0201】 The server sends the determined work instructions and encouragement messages to the terminal. The terminal receives this information and notifies the employee. The user (employee) checks the tasks assigned to them and the messages received through the terminal and works efficiently. The instructions and encouragement messages for the employee are displayed as output. 【0202】 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. 【0203】 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. 【0204】 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. 【0205】 [Second Embodiment] 【0206】 Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment. 【0207】 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. 【0208】 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). 【0209】 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. 【0210】 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. 【0211】 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). 【0212】 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. 【0213】 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. 【0214】 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. 【0215】 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. 【0216】 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. 【0217】 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". 【0218】 The present invention is a system for efficiently managing household chores and childcare tasks, and includes information processing means that can learn the schedules of each household member and assign optimal tasks. Specific embodiments thereof are described below. 【0219】 The server receives schedule data from household members and learns each member's activity patterns based on this data. Based on this learned data, the server automatically assigns household chores and childcare tasks to each member at the most appropriate time. The server can also adjust the types of tasks based on the user's strengths. 【0220】 Furthermore, the device sends image data of the refrigerator's contents to the server. The server, upon receiving this data, uses image analysis technology to determine the food inventory in the refrigerator and detect any missing items. Based on this information, the server automatically generates a shopping list, helping users reduce unnecessary purchases and providing efficient daily management. 【0221】 The server also suggests menus based on the ingredients in the refrigerator, taking into account the user's food preferences and nutritional requirements. These menus are presented to the user via a terminal, helping to make meal planning easier. 【0222】 Users can report task progress via their devices. These devices send this progress data to a server, which monitors the overall task status in real time. The server manages tasks to ensure smooth workflow, reassigning tasks or suggesting new ones as needed. 【0223】 As a concrete example, the server analyzes an image of the refrigerator received from the terminal in the morning and determines that "there is a shortage of milk." As a result, the server adds milk to the shopping list and assigns this shopping task to a user who has free time in the evening. This information is notified to the terminal, allowing the user to plan their schedule efficiently. 【0224】 This system can also send reminders and emergency notifications to users using notification methods. This helps to coordinate awareness within the household and establish a system for responding quickly to emergencies. Through these functions, household task management is automated, resulting in an improved quality of life. 【0225】 The following describes the processing flow. 【0226】 Step 1: 【0227】 The server receives schedule data entered by the user through their device. This data includes appointments for work, school, household chores, etc., and the server records it to learn the activity patterns of each member of the household. 【0228】 Step 2: 【0229】 The server optimally assigns household and childcare tasks based on learned schedule data. Assignments are made individually, taking into account each member's availability and areas of expertise. 【0230】 Step 3: 【0231】 The terminal allows the user to take photos of the inside of the refrigerator and send them to the server. The image data is received by the server and analyzed to understand the status of food inventory. 【0232】 Step 4: 【0233】 The server uses image analysis technology to analyze the contents of the refrigerator and identify missing food items. Based on these identified missing items, the server automatically generates a shopping list. 【0234】 Step 5: 【0235】 The server suggests menus that utilize the user's available ingredients, taking into account their preferences and nutritional requirements. The suggested menus are then notified to the user via their device. 【0236】 Step 6: 【0237】 Users use their devices to report the progress of their assigned tasks. The devices send this progress data to the server, which updates the task completion status in real time. 【0238】 Step 7: 【0239】 The server monitors aggregated progress data and, if necessary, reassigns tasks or proposes new tasks. If task delays or resource shortages are detected, corrective actions are taken immediately. 【0240】 Step 8: 【0241】 The server sends reminders and emergency notifications to household members as needed. The device receives these and displays them to the user, instantly conveying important information. 【0242】 (Example 1) 【0243】 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." 【0244】 In modern households, managing various household tasks is becoming increasingly complex. Especially in multi-member households, efficiently dividing household chores and childcare activities while considering each member's schedule is crucial. Furthermore, inadequate food inventory management can lead to wasteful shopping and unbalanced nutrition. To address these challenges, efficient and flexible task management, along with streamlined food inventory and nutrition planning, are essential. 【0245】 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. 【0246】 This invention includes a server that includes information processing means capable of learning each member's time management data and automatically assigning the most suitable household tasks or childcare activities; means for analyzing objects in the storage environment using image analysis technology, identifying shortages of objects, and generating replenishment tables; and means for suggesting meal plans that take into account the group's preferences and nutrition. This enables efficient task sharing within the household and streamlines food inventory and meal planning. 【0247】 "Time management data" refers to information about the schedules and tasks that each member uses in their daily activities, and includes data such as schedules and priorities. 【0248】 An "information processing device" is a device or system that has the function of performing calculations and analyses based on input data and deriving a specific result. 【0249】 "Image analysis technology" refers to techniques that analyze image data to recognize objects and detect features, often utilizing deep learning models. 【0250】 "Storage environment" refers to the place and conditions for storing and preserving food and goods, and includes refrigerators and pantries in the home. 【0251】 A "supply list" is a list of items that are currently missing, and is used for reference in future purchasing activities. 【0252】 "Meal plan suggestions" is a process that proposes ingredients and menus to be consumed, taking into account the user's preferences and nutritional balance. 【0253】 "Activity progress" refers to information indicating the extent to which each member has completed their assigned tasks. 【0254】 "Notification means" refers to a function for conveying important information, notifications, or warnings to the user, including alarms and message notifications. 【0255】 This invention provides a system for streamlining the management of household tasks, comprising a server for information processing and a terminal accessible to users. This system aggregates time management data from each member of the household and assigns optimal household tasks and childcare activities based on this data. The server analyzes the schedule information collected from each member using machine learning algorithms, specifically time-series analysis techniques such as long-term short-term memory (LSTM). This allows the system to learn each member's activity patterns and achieve efficient task assignment. 【0256】 Additionally, image data of the inside of the refrigerator is acquired through a camera attached to the terminal. The server analyzes this image data using computer vision technology (for example, the YOLO model or a deep learning model built with TensorFlow) to determine the food inventory. For items that are missing, the server automatically generates a shopping list for replenishment and notifies the user's terminal. 【0257】 Furthermore, the server considers the user's food preferences and nutritional requirements, and proposes a meal plan based on the ingredients in the refrigerator. This process utilizes a generative AI model to suggest the most suitable menu. Users can view these suggestions on their device, helping them plan healthier and more balanced meals. 【0258】 On the other hand, users can report task progress using their devices, allowing the server to monitor task completion in real time. If necessary, the server can reassign tasks or suggest new ones to help ensure smooth workflow within the home. 【0259】 As a concrete example, the server analyzes an image of the refrigerator sent via the terminal in the morning and determines that "there is a shortage of milk." Based on this result, it adds milk to the shopping list and assigns this shopping task to a user who has relatively more time in the evening. This information is notified to the terminal, allowing the user to shop efficiently on their way to work. 【0260】 Examples of prompts to be input to the generating AI model include: "Please tell me how to efficiently manage household chores and childcare. Specifically, please explain in detail the mechanisms for task assignment and food inventory management." In this way, it is expected that the system of the present invention will improve the efficiency of household tasks and enhance the quality of life. 【0261】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0262】 Step 1: 【0263】 The server receives schedule data sent from each member via their terminal. The input includes data about each member's schedule and tasks. Based on this data, the server uses machine learning algorithms to analyze and learn each member's activity patterns. Here, time series analysis techniques are used to create a predictive model, determining a work schedule suitable for each member. 【0264】 Step 2: 【0265】 The terminal periodically captures image data from inside the refrigerator and sends it to the server. The input is an image file of the inside of the refrigerator. The server receives this image data and uses image analysis technology to analyze the food inventory status. Specifically, it uses a computer vision model to recognize the type and quantity of food and identify items that are missing. An inventory list and a shortage list are generated as output. 【0266】 Step 3: 【0267】 The server uses accumulated inventory data to list missing items and create a shopping list. Inputs include the missing items list obtained in step 2 and the user's past purchasing patterns. Based on this information, the server automatically generates a shopping list and notifies the terminal. The output is a shopping list that the user can review. 【0268】 Step 4: 【0269】 The server suggests menus based on the user's food preferences and nutritional requirements, taking into account the contents of their refrigerator. The inputs are inventory data and user preference data. A generative AI model analyzes this data to generate optimal menu suggestions. The output is a menu suggestion displayed on the user's device. 【0270】 Step 5: 【0271】 Users input task progress via their terminals and report it to the server. Input includes data on the progress of each task. The server receives this data, monitors progress in real time, and reassigns tasks if necessary. Output includes updated task management information, which is sent to the terminal. 【0272】 (Application Example 1) 【0273】 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." 【0274】 Efficiently managing household chores and childcare tasks is a significant challenge for many families. It requires assigning tasks at the optimal time, taking into account the schedules of each family member. However, manually managing these tasks is difficult and inefficient. Furthermore, properly managing food inventory and suggesting menus that meet nutritional and taste requirements are also important needs within families, but currently, there is a lack of efficient means to achieve this. 【0275】 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. 【0276】 This invention includes a server that learns each member's time management data and automatically assigns the optimal household chore or childcare role; a server that uses image processing technology to analyze items in the storage environment, detect shortages of items, and generate a replenishment list; and a server that provides menu suggestions that take into account the preferences and nutritional needs of each member. This enables efficient management of tasks that are appropriate to each member's schedule and abilities, reducing the burden on the household and improving the quality of life. 【0277】 "Information processing means" refers to a device or software that learns the time management data of each member and automatically assigns the optimal household chore or childcare role. 【0278】 The "image processing technology" is an image analysis method used to analyze the items in the storage environment and detect shortages of items. 【0279】 The "replenishment list" is a list for replenishing necessary items generated when shortages of items are detected. 【0280】 The "preferences and nutritional information of household members" refers to information on the taste preferences and health-related nutrition of each household member, and is the basic data for proposing recipes based on this. 【0281】 The "recipe proposal means" is a device or software that generates plans for daily meals based on the preferences and nutrition of household members. 【0282】 The "generation AI model" is an information generation model using artificial intelligence, and has the ability to propose optimal solutions based on the given data. 【0283】 The "prompt sentence" is an instruction sentence input to the generation AI model, and is used to control the output of the AI based on specific conditions and data. 【0284】 To implement this invention, a system for the server and the terminal to cooperate and execute necessary functions is constructed. The server receives the time management data of each household member, and based on this, assigns optimal housework or childcare roles. The time management data is managed based on the calendar information and activity data of individual household members. 【0285】 The terminal operates the video acquisition device installed in the home to photograph the items in the storage environment. This video data is introduced with image processing technology and transmitted to the server. The server analyzes the video data, determines the shortage status of the items, and generates a replenishment list. 【0286】 Furthermore, the server utilizes a generative AI model to propose an optimal menu based on the preferences and nutritional information of the household members. By inputting a prompt sentence into the generative AI model, a specific menu plan is created. For example, it is to send a prompt like "Please propose a menu considering nutritional balance for the family dinner" to the server. 【0287】 As a specific example, when the server analyzes video data in the morning and detects that milk is insufficient, it adds milk to the replenishment list and proposes the purchase to the most suitable household member. The user can receive the proposal through the terminal and confirm it through the smartphone app. 【0288】 With this system, the efficiency of daily household management is improved, the burden on household members is reduced, and harmony within the family is maintained. The menu proposal by the generative AI model simplifies the daily meal plan and plays a role in supporting a nutritious diet. 【0289】 The flow of the specific process in Application Example 1 will be described using FIG. 12. 【0290】 Step 1: 【0291】 The server acquires the time management data of each household member. The input is the calendar information and activity data of individual household members. Based on this, the server analyzes the schedule of each household member to identify free time and areas of expertise. The output is an optimized list of task candidates. 【0292】 Step 2: 【0293】 The terminal operates the video acquisition device installed in the house to photograph the items in the storage environment. The input is video data. The terminal sends this data to the server, and the server analyzes the video data using video processing technology. As a result of the analysis, the shortage situation of the items is found as the output. 【0294】 Step 3: 【0295】 The server generates a replenishment list based on the analysis results. The input is the status data of the analyzed items. The server detects and lists the missing items. The output is a list of items that need to be replenished. 【0296】 Step 4: 【0297】 The server uses a generative AI model to generate menu suggestions based on the preferences and nutritional information of its members. The input consists of nutritional information, preference data, and a prompt. For example, the prompt might be "Please suggest a nutritionally balanced menu for my family's dinner." The AI ​​analyzes this data and outputs the optimal menu suggestion. 【0298】 Step 5: 【0299】 The user checks the replenishment list and menu suggestions sent from the server via their terminal. Input is the notification from the server. The user receives the notification and takes action as needed. Output is the user's action plan. 【0300】 Step 6: 【0301】 Users report task progress to their terminals and send it to the server. The input is the task completion status. The server receives the report, monitors the overall task progress, and makes role reassignments or new suggestions as needed. The output is the updated task assignment status. 【0302】 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. 【0303】 This invention is a system for streamlining task management within the home, and in particular, by combining it with an emotion engine, it achieves flexible task assignment and management that takes into account the user's emotional state. Specific embodiments are shown below. 【0304】 The server first receives the schedule data of household members and learns individual activity patterns based on this. Then, it analyzes the emotional state with this data and the emotion engine, and performs an optimal task assignment for each member. The emotional state is obtained through the input, voice, and facial expression recognition of the members. For example, if a member is judged to be feeling stressed, the task is readjusted to reduce the burden. 【0305】 The terminal displays this information to the user and explains how the task assignment based on emotions is performed. Also, it transmits the image data inside the refrigerator to the server to grasp the inventory of items. This information is used for menu proposals and the generation of shopping lists in consideration of the results of the emotion engine. 【0306】 The server further proposes a menu considering the user's preferences and nutritional balance, and creates a meal plan that reduces the user's psychological burden by combining this with the emotional data. The proposal is notified to the user through the terminal, and the user confirms it. 【0307】 The user reports the progress of the task using the terminal and also provides the psychological burden at that time as feedback. Based on this feedback, the server monitors the progress of the task and reassigns the task if necessary. By using the emotion engine, it becomes possible to evaluate the user's satisfaction and stress level and provide notifications and advice suitable for each user. 【0308】 As a specific example, when the server considers the busyness within the household and the mood of individual members and determines that the emotional burden is large, it transmits a cheering message and a notification of relaxation methods from the terminal. As a result, the system can go beyond being just an efficiency tool and can implement measures that also take into account the mental health of the entire family. 【0309】 The processing flow will be described below. 【0310】 Step 1: 【0311】 The server receives schedule and emotion input data entered by the user through the terminal. This includes information about the user's daily schedule, mood, and energy level for the day. The server stores this data and learns each user's activity patterns and emotional tendencies. 【0312】 Step 2: 【0313】 The device takes a picture of the inside of the refrigerator and sends it to the server. The server performs image analysis to determine the current inventory status. This analysis identifies which food items are running low. 【0314】 Step 3: 【0315】 The server utilizes accumulated schedule and emotional data to assign household and childcare tasks to each family member. When assigning tasks, it takes into account the user's current energy level and stress level, adjusting them to avoid burdening them. If the emotional engine detects user fatigue, it reduces or reassigns tasks. 【0316】 Step 4: 【0317】 Based on the analysis results, the server lists the necessary food items and creates a shopping list. At the same time, it suggests a menu tailored to the user's preferences and emotional state. This suggestion is delivered to the user via their device. If the user's emotional state is negative, the server recommends a menu that includes many ingredients that improve mood. 【0318】 Step 5: 【0319】 Users check and complete assigned tasks on their devices. Information is sent to the server by reporting the task progress and their emotions during the process via the device. The server uses this data to evaluate the task progress and the user's emotional tendencies. 【0320】 Step 6: 【0321】 The server monitors progress information and emotional data, and adjusts tasks as needed. If the emotional engine determines that the user is experiencing significant physical or mental strain, it provides support by inserting rest periods or sending encouraging messages to the device. 【0322】 Step 7: 【0323】 The server monitors the overall system status, continuously learns emotional data to improve the efficiency of tasks performed within the home and member satisfaction, and provides improvement measures. The terminal delivers necessary information and advice to the user in a timely manner through notification functions. 【0324】 (Example 2) 【0325】 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". 【0326】 Conventional household task management systems struggle to flexibly assign tasks while considering the emotional state of individual users, and they lack sufficient consideration for reducing mental burden. Therefore, the challenge lies in suggesting optimal tasks according to the user's stress level and achieving efficient work distribution that meets the user's needs in complex household environments. 【0327】 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. 【0328】 In this invention, the server includes data processing means that learn each user's schedule information and automatically assign the most suitable tasks or caregiver duties, including sentiment analysis; means that analyze objects in the storage area using video analysis technology, detect shortages of objects, and generate a replenishment list; and means that suggest meal plans that take into account the family's preferences and nutritional needs. This makes it possible to manage tasks efficiently within the home while reducing the psychological burden on the user. 【0329】 A "user" refers to an individual person within the household who is the subject of task management and is the entity that provides the information that forms the basis for data processing and sentiment analysis. 【0330】 "Emotional analysis" is the process of evaluating a user's emotional state from voice, facial expressions, and other data, and using that information to inform tasks and suggestions. 【0331】 "Data processing means" refers to a set of functions for collecting and analyzing each user's schedule information and assigning optimal tasks through learning. 【0332】 "Video analysis technology" refers to the technology that processes image data acquired by cameras and sensors to recognize and classify objects. 【0333】 "Storage area" refers to the space within a home where items are stored and managed, and includes refrigerators, pantries, and other similar spaces. 【0334】 A "meal plan" is a meal plan created with consideration for the family's preferences and nutritional needs, and serves as a guide for cooking within the home. 【0335】 A "task" refers to a specific household chore or childcare activity that is divided among family members and is to be performed by the user. 【0336】 "Psychological burden" refers to the level of stress and anxiety a user experiences while performing a task, and is measured through emotion analysis. 【0337】 "Notification means" refers to a mechanism that provides users with necessary information and advice, and is executed through a device. 【0338】 This invention is a system for streamlining task management within the home, and it enables flexible task assignment incorporating sentiment analysis. This system mainly consists of a server, terminals, and users. 【0339】 The server collects each user's schedule data and analyzes it in combination with emotional data to assign the most suitable tasks. In this process, image analysis and voice analysis technologies are combined to obtain emotional states from the user's voice and facial expressions. Specifically, a commonly used image analysis API is used for facial recognition, and a standard voice recognition system is used for voice analysis. 【0340】 The terminal displays task information received from the server to the user and explains the task details. It also uses cameras installed in storage areas such as refrigerators to capture images of the contents and monitor the condition of the items. The captured images are periodically sent to the server to help monitor inventory levels. 【0341】 As a concrete example, the server considers the busyness of the household and the feelings of its members, and if it determines that the emotional burden is high, it sends encouraging messages and relaxation methods to the user via the terminal. In this way, the system can be more than just a task management tool; it can also play a role in improving the overall well-being of the household. 【0342】 An example of a prompt would be: "Evaluate the emotional state of the family based on data from yesterday and suggest the most appropriate tasks for each member. Also, if a member is experiencing stress, include specific suggestions to alleviate their burden." This prompt is used by a generative AI model to assign new tasks based on the user's situation. 【0343】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0344】 Step 1: 【0345】 The server receives schedule data from each user as input. This data includes each user's appointments and free time. The server analyzes this information and learns each user's activity patterns. Specifically, it uses data analysis algorithms to extract past schedule trends and use them to help plan future schedules. 【0346】 Step 2: 【0347】 The device acquires the user's voice input and facial expression data. Based on this input data, it analyzes the user's emotional state using voice recognition software and image recognition technology. The emotional analysis results are output and sent to the server. Specifically, the device collects voice using its built-in microphone, captures facial expressions with its camera, and processes this data in real time. 【0348】 Step 3: 【0349】 The server takes schedule data and sentiment analysis results as input and uses a generative AI model to calculate the optimal task assignment. This process outputs a task list that is individually customized based on each user's stress level and free time. Specifically, it rearranges and adjusts tasks based on prompt messages generated by the AI ​​model. 【0350】 Step 4: 【0351】 The device displays task assignment information sent from the server to the user. This information includes an explanation of why the task was assigned. Once the user has reviewed the task, they send their feedback back to the server. Specifically, the device uses its notification function to send an alert to the user and provides a user interface that allows for easy feedback input. 【0352】 Step 5: 【0353】 Users report task progress via their devices and provide feedback on the psychological burden they experience while performing the tasks. This feedback data serves as input for the server to adjust or suggest improvements to the tasks. Specifically, this involves users entering their progress and emotional evaluation using a form on their devices and sending the data to the server via a submit button. 【0354】 (Application Example 2) 【0355】 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." 【0356】 The problem that this invention aims to solve is to manage employee schedules and reduce stress in factory work, thereby enabling efficient and flexible work adjustments. It aims to lighten the burden and improve work efficiency while taking into account the emotional state of employees. Conventional systems have the problem of rigid work assignments that do not take into account individual emotions or areas of expertise, resulting in significant psychological burden. 【0357】 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. 【0358】 This invention includes a server that includes information processing means capable of learning each individual's activity plan data and automatically assigning the most suitable work or childcare tasks; means for analyzing items in the storage environment using image analysis technology, detecting shortages of items, and generating a replenishment list; and means for providing meal suggestions that take into account family preferences and nutrition. This enables efficient work support while performing sentiment analysis to evaluate the emotional state of employees and reduce their workload. 【0359】 "Activity plan data" refers to information about each individual's daily schedule and tasks, and this data is used as the basis for efficient task assignment. 【0360】 An "information processing means" is a component of a system that has the function of deriving the optimal result by analyzing and processing given data. 【0361】 "Image analysis technology" is a technique for analyzing digital image data and extracting useful information from it, and is used for recognizing and classifying objects. 【0362】 A "replenishment list" is a list generated when a shortage of an item is detected, indicating which items should be replenished. 【0363】 "Meal suggestions" refer to a method of proposing an optimal meal plan that takes into account individual preferences and nutritional needs. 【0364】 "Emotional analysis" is a technology that evaluates and analyzes an individual's emotional state based on information obtained from audio and video. 【0365】 "Work support" refers to functions that provide assistance and support to improve work efficiency, and plays a particularly important role in collaboration between humans and machines. 【0366】 The system for realizing this application consists of a cloud-based server, multiple sensors placed within the factory, and mobile devices used by employees. The server receives activity plan data sent from factory employees and image data acquired by the sensors, and based on this information, assigns the most suitable tasks to each employee. 【0367】 The server uses emotion recognition software such as Microsoft Azure Cognitive Services and Google Cloud Vision API to perform emotion analysis. This allows it to analyze employees' emotions in real time from their facial and voice data and reflect the results in activity plan data. Based on this analysis, the server determines appropriate tasks and encouraging messages for each employee. 【0368】 Next, the server uses image analysis technology to retrieve item data from the storage environment within the factory, identifies missing items based on that data, and generates a replenishment list. This utilizes a deep learning model to precisely classify items and automatically identify the necessary replenishments. 【0369】 The generated work assignments and replenishment lists are notified to employees via mobile devices. Based on the notifications received via their devices, employees can efficiently proceed with their work. This reduces the workload on employees and improves the overall work efficiency of the factory. 【0370】 As a concrete example, the server uses emotion analysis to determine that employee B, who is feeling busy in the morning, is tired. Based on this information, a message such as, "Let's take a short break and refresh ourselves. How about taking a breather at the newly opened cafe?" is generated and sent to B via their mobile device. 【0371】 Examples of prompts to input into a generative AI model: 【0372】 "The role of the AI ​​system is to optimize work assignments and support messages based on employee emotional data." 【0373】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0374】 Step 1: 【0375】 The server receives activity plan data transmitted from employees within the factory and image data acquired by sensors. This input data relates to employee schedules and factory inventory status. The server stores this data and prepares it for use in subsequent processing. 【0376】 Step 2: 【0377】 The server analyzes the inventory items using image analysis techniques based on the received image data. In this step, a deep learning model is used to identify each item from the image and calculate their quantities. This identifies items that are low in stock and generates a replenishment list. The output includes the inventory status of each item and a list of items that are low in stock. 【0378】 Step 3: 【0379】 The server uses emotion recognition software to analyze employee facial images and voice data as input. This analysis evaluates each employee's current emotional state. The output provides information indicating each employee's emotional state. This information is used to determine work assignments and support messages. 【0380】 Step 4: 【0381】 The server integrates activity plan data, inventory status, and sentiment analysis results to determine the most suitable tasks and encouragement messages for each employee. Using a generative AI model, it creates and outputs a plan to optimize employee workload and efficiency, taking these factors into consideration. From this process, a list of work instructions and messages is generated. 【0382】 Step 5: 【0383】 The server sends the determined work instructions and encouragement messages to the terminal. The terminal receives this information and notifies the employee. The user (employee) checks the tasks assigned to them and the messages received through the terminal and works efficiently. The instructions and encouragement messages for the employee are displayed as output. 【0384】 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. 【0385】 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. 【0386】 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. 【0387】 [Third Embodiment] 【0388】 Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment. 【0389】 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. 【0390】 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). 【0391】 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. 【0392】 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. 【0393】 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). 【0394】 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. 【0395】 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. 【0396】 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. 【0397】 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. 【0398】 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. 【0399】 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". 【0400】 The present invention is a system for efficiently managing household chores and childcare tasks, and includes information processing means that can learn the schedules of each household member and assign optimal tasks. Specific embodiments thereof are described below. 【0401】 The server receives schedule data from household members and learns each member's activity patterns based on this data. Based on this learned data, the server automatically assigns household chores and childcare tasks to each member at the most appropriate time. The server can also adjust the types of tasks based on the user's strengths. 【0402】 Furthermore, the device sends image data of the refrigerator's contents to the server. The server, upon receiving this data, uses image analysis technology to determine the food inventory in the refrigerator and detect any missing items. Based on this information, the server automatically generates a shopping list, helping users reduce unnecessary purchases and providing efficient daily management. 【0403】 The server also suggests menus based on the ingredients in the refrigerator, taking into account the user's food preferences and nutritional requirements. These menus are presented to the user via a terminal, helping to make meal planning easier. 【0404】 Users can report task progress via their devices. These devices send this progress data to a server, which monitors the overall task status in real time. The server manages tasks to ensure smooth workflow, reassigning tasks or suggesting new ones as needed. 【0405】 As a concrete example, the server analyzes an image of the refrigerator received from the terminal in the morning and determines that "there is a shortage of milk." As a result, the server adds milk to the shopping list and assigns this shopping task to a user who has free time in the evening. This information is notified to the terminal, allowing the user to plan their schedule efficiently. 【0406】 This system can also send reminders and emergency notifications to users using notification methods. This helps to coordinate awareness within the household and establish a system for responding quickly to emergencies. Through these functions, household task management is automated, resulting in an improved quality of life. 【0407】 The following describes the processing flow. 【0408】 Step 1: 【0409】 The server receives schedule data entered by the user through their device. This data includes appointments for work, school, household chores, etc., and the server records it to learn the activity patterns of each member of the household. 【0410】 Step 2: 【0411】 The server optimally assigns household and childcare tasks based on learned schedule data. Assignments are made individually, taking into account each member's availability and areas of expertise. 【0412】 Step 3: 【0413】 The terminal allows the user to take photos of the inside of the refrigerator and send them to the server. The image data is received by the server and analyzed to understand the status of food inventory. 【0414】 Step 4: 【0415】 The server uses image analysis technology to analyze the contents of the refrigerator and identify missing food items. Based on these identified missing items, the server automatically generates a shopping list. 【0416】 Step 5: 【0417】 The server suggests menus that utilize the user's available ingredients, taking into account their preferences and nutritional requirements. The suggested menus are then notified to the user via their device. 【0418】 Step 6: 【0419】 Users use their devices to report the progress of their assigned tasks. The devices send this progress data to the server, which updates the task completion status in real time. 【0420】 Step 7: 【0421】 The server monitors aggregated progress data and, if necessary, reassigns tasks or proposes new tasks. If task delays or resource shortages are detected, corrective actions are taken immediately. 【0422】 Step 8: 【0423】 The server sends reminders and emergency notifications to household members as needed. The device receives these and displays them to the user, instantly conveying important information. 【0424】 (Example 1) 【0425】 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." 【0426】 In modern households, managing various household tasks is becoming increasingly complex. Especially in multi-member households, efficiently dividing household chores and childcare activities while considering each member's schedule is crucial. Furthermore, inadequate food inventory management can lead to wasteful shopping and unbalanced nutrition. To address these challenges, efficient and flexible task management, along with streamlined food inventory and nutrition planning, are essential. 【0427】 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. 【0428】 This invention includes a server that includes information processing means capable of learning each member's time management data and automatically assigning the most suitable household tasks or childcare activities; means for analyzing objects in the storage environment using image analysis technology, identifying shortages of objects, and generating replenishment tables; and means for suggesting meal plans that take into account the group's preferences and nutrition. This enables efficient task sharing within the household and streamlines food inventory and meal planning. 【0429】 "Time management data" refers to information about the schedules and tasks that each member uses in their daily activities, and includes data such as schedules and priorities. 【0430】 An "information processing device" is a device or system that has the function of performing calculations and analyses based on input data and deriving a specific result. 【0431】 "Image analysis technology" refers to techniques that analyze image data to recognize objects and detect features, often utilizing deep learning models. 【0432】 "Storage environment" refers to the place and conditions for storing and preserving food and goods, and includes refrigerators and pantries in the home. 【0433】 A "supply list" is a list of items that are currently missing, and is used for reference in future purchasing activities. 【0434】 "Meal plan suggestions" is a process that proposes ingredients and menus to be consumed, taking into account the user's preferences and nutritional balance. 【0435】 "Activity progress" refers to information indicating the extent to which each member has completed their assigned tasks. 【0436】 "Notification means" refers to a function for conveying important information, notifications, or warnings to the user, including alarms and message notifications. 【0437】 This invention provides a system for streamlining the management of household tasks, comprising a server for information processing and a terminal accessible to users. This system aggregates time management data from each member of the household and assigns optimal household tasks and childcare activities based on this data. The server analyzes the schedule information collected from each member using machine learning algorithms, specifically time-series analysis techniques such as long-term short-term memory (LSTM). This allows the system to learn each member's activity patterns and achieve efficient task assignment. 【0438】 Additionally, image data of the inside of the refrigerator is acquired through a camera attached to the terminal. The server analyzes this image data using computer vision technology (for example, the YOLO model or a deep learning model built with TensorFlow) to determine the food inventory. For items that are missing, the server automatically generates a shopping list for replenishment and notifies the user's terminal. 【0439】 Furthermore, the server considers the user's food preferences and nutritional requirements, and proposes a meal plan based on the ingredients in the refrigerator. This process utilizes a generative AI model to suggest the most suitable menu. Users can view these suggestions on their device, helping them plan healthier and more balanced meals. 【0440】 On the other hand, users can report task progress using their devices, allowing the server to monitor task completion in real time. If necessary, the server can reassign tasks or suggest new ones to help ensure smooth workflow within the home. 【0441】 As a concrete example, the server analyzes an image of the refrigerator sent via the terminal in the morning and determines that "there is a shortage of milk." Based on this result, it adds milk to the shopping list and assigns this shopping task to a user who has relatively more time in the evening. This information is notified to the terminal, allowing the user to shop efficiently on their way to work. 【0442】 Examples of prompts to be input to the generating AI model include: "Please tell me how to efficiently manage household chores and childcare. Specifically, please explain in detail the mechanisms for task assignment and food inventory management." In this way, it is expected that the system of the present invention will improve the efficiency of household tasks and enhance the quality of life. 【0443】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0444】 Step 1: 【0445】 The server receives schedule data sent from each member via their terminal. The input includes data about each member's schedule and tasks. Based on this data, the server uses machine learning algorithms to analyze and learn each member's activity patterns. Here, time series analysis techniques are used to create a predictive model, determining a work schedule suitable for each member. 【0446】 Step 2: 【0447】 The terminal periodically captures image data from inside the refrigerator and sends it to the server. The input is an image file of the inside of the refrigerator. The server receives this image data and uses image analysis technology to analyze the food inventory status. Specifically, it uses a computer vision model to recognize the type and quantity of food and identify items that are missing. An inventory list and a shortage list are generated as output. 【0448】 Step 3: 【0449】 The server uses accumulated inventory data to list missing items and create a shopping list. Inputs include the missing items list obtained in step 2 and the user's past purchasing patterns. Based on this information, the server automatically generates a shopping list and notifies the terminal. The output is a shopping list that the user can review. 【0450】 Step 4: 【0451】 The server suggests menus based on the user's food preferences and nutritional requirements, taking into account the contents of their refrigerator. The inputs are inventory data and user preference data. A generative AI model analyzes this data to generate optimal menu suggestions. The output is a menu suggestion displayed on the user's device. 【0452】 Step 5: 【0453】 Users input task progress via their terminals and report it to the server. Input includes data on the progress of each task. The server receives this data, monitors progress in real time, and reassigns tasks if necessary. Output includes updated task management information, which is sent to the terminal. 【0454】 (Application Example 1) 【0455】 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." 【0456】 Efficiently managing household chores and childcare tasks is a significant challenge for many families. It requires assigning tasks at the optimal time, taking into account the schedules of each family member. However, manually managing these tasks is difficult and inefficient. Furthermore, properly managing food inventory and suggesting menus that meet nutritional and taste requirements are also important needs within families, but currently, there is a lack of efficient means to achieve this. 【0457】 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. 【0458】 This invention includes a server that learns each member's time management data and automatically assigns the optimal household chore or childcare role; a server that uses image processing technology to analyze items in the storage environment, detect shortages of items, and generate a replenishment list; and a server that provides menu suggestions that take into account the preferences and nutritional needs of each member. This enables efficient management of tasks that are appropriate to each member's schedule and abilities, reducing the burden on the household and improving the quality of life. 【0459】 "Information processing means" refers to a device or software that learns the time management data of each member and automatically assigns the optimal household chore or childcare role. 【0460】 "Image processing technology" refers to image analysis techniques used to analyze items within a storage environment and detect shortages of items. 【0461】 A "replenishment list" is a list generated when a shortage of goods is detected, used to replenish the necessary items. 【0462】 "Member preferences and nutritional information" refers to information about each member's taste preferences and health-related nutritional needs, and serves as basic data for proposing menus based on this information. 【0463】 A "menu suggestion device" is a device or software that generates a plan for daily meals based on the preferences and nutritional needs of its members. 【0464】 A "generative AI model" is an information generation model that utilizes artificial intelligence and has the ability to propose optimal solutions based on the given data. 【0465】 A "prompt statement" is an instruction given to a generative AI model, used to control the AI's output based on specific conditions or data. 【0466】 To realize this invention, a system will be built in which a server and terminals work together to perform the necessary functions. The server will receive time management data from each member and assign the most suitable household chore or childcare role based on this data. The time management data will be managed based on each member's calendar information and activity data. 【0467】 The terminal operates a video acquisition device installed in the home to photograph items within the storage environment. This video data is processed using video processing technology and transmitted to a server. The server analyzes the video data, determines the shortage of items, and generates a replenishment list. 【0468】 Furthermore, the server uses a generative AI model to suggest optimal menus based on the preferences and nutritional information of its members. The generative AI model generates specific menu suggestions by inputting prompts. For example, one might send the prompt, "Please suggest a nutritionally balanced menu for my family's dinner." 【0469】 As a concrete example, if the server analyzes video data in the morning and detects a shortage of milk, it adds milk to the replenishment list and suggests purchasing it to the most suitable member. Users receive the suggestion via their device and can confirm it through a smartphone app. 【0470】 This system improves the efficiency of daily household management, reduces the burden on family members, and maintains harmony within the household. The menu suggestions generated by the AI ​​model simplify daily meal planning and support a nutritious diet. 【0471】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0472】 Step 1: 【0473】 The server retrieves time management data for each member. The input consists of each member's calendar information and activity data. Based on this, the server analyzes each member's schedule to identify their free time and areas of expertise. The output is a list of optimized task candidates. 【0474】 Step 2: 【0475】 The terminal operates a video acquisition device installed in the home to photograph items within the storage environment. The input is video data. The terminal sends this data to a server, which analyzes the video data using video processing technology. As a result of the analysis, the output reveals the status of any missing items. 【0476】 Step 3: 【0477】 The server generates a replenishment list based on the analysis results. The input is the status data of the analyzed items. The server detects and lists the missing items. The output is a list of items that need to be replenished. 【0478】 Step 4: 【0479】 The server uses a generative AI model to generate menu suggestions based on the preferences and nutritional information of its members. The input consists of nutritional information, preference data, and a prompt. For example, the prompt might be "Please suggest a nutritionally balanced menu for my family's dinner." The AI ​​analyzes this data and outputs the optimal menu suggestion. 【0480】 Step 5: 【0481】 The user checks the replenishment list and menu suggestions sent from the server via their terminal. Input is the notification from the server. The user receives the notification and takes action as needed. Output is the user's action plan. 【0482】 Step 6: 【0483】 Users report task progress to their terminals and send it to the server. The input is the task completion status. The server receives the report, monitors the overall task progress, and makes role reassignments or new suggestions as needed. The output is the updated task assignment status. 【0484】 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. 【0485】 This invention is a system for streamlining task management within the home, and in particular, by combining it with an emotion engine, it achieves flexible task assignment and management that takes into account the user's emotional state. Specific embodiments are shown below. 【0486】 The server first receives schedule data from household members and learns their individual activity patterns based on this data. Then, it analyzes their emotional state using this data and an emotion engine to assign optimal tasks to each member. Emotional states are obtained through member input, voice, and facial recognition. For example, if it is determined that a member is experiencing stress, tasks are readjusted to reduce their burden. 【0487】 The device displays this information to the user and explains how emotion-based task assignments are performed. It also sends image data of the refrigerator to the server to track inventory levels. This information, along with the results of the emotion engine, is used to generate meal suggestions and shopping lists. 【0488】 The server further suggests menus that take into account the user's preferences and nutritional balance, and by combining this with emotional data, it creates a meal plan that reduces the user's psychological burden. The suggestions are notified to the user via their device, and the user confirms them. 【0489】 Users report task progress using their devices and provide feedback on the psychological burden they experience during the process. Based on this feedback, the server monitors task progress and reassigns tasks as needed. By using an emotion engine, it is possible to evaluate user satisfaction and stress levels and provide notifications and advice tailored to each user. 【0490】 As a concrete example, the server considers the busyness of the household and the feelings of individual members, and if it determines that the emotional burden is high, it sends encouraging messages or relaxation methods via the device. This allows the system to be more than just an efficiency tool, but also to implement initiatives that consider the mental health of the entire family. 【0491】 The following describes the processing flow. 【0492】 Step 1: 【0493】 The server receives schedule and emotion input data entered by the user through the terminal. This includes information about the user's daily schedule, mood, and energy level for the day. The server stores this data and learns each user's activity patterns and emotional tendencies. 【0494】 Step 2: 【0495】 The device takes a picture of the inside of the refrigerator and sends it to the server. The server performs image analysis to determine the current inventory status. This analysis identifies which food items are running low. 【0496】 Step 3: 【0497】 The server utilizes accumulated schedule and emotional data to assign household and childcare tasks to each family member. When assigning tasks, it takes into account the user's current energy level and stress level, adjusting them to avoid burdening them. If the emotional engine detects user fatigue, it reduces or reassigns tasks. 【0498】 Step 4: 【0499】 Based on the analysis results, the server lists the necessary food items and creates a shopping list. At the same time, it suggests a menu tailored to the user's preferences and emotional state. This suggestion is delivered to the user via their device. If the user's emotional state is negative, the server recommends a menu that includes many ingredients that improve mood. 【0500】 Step 5: 【0501】 Users check and complete assigned tasks on their devices. Information is sent to the server by reporting the task progress and their emotions during the process via the device. The server uses this data to evaluate the task progress and the user's emotional tendencies. 【0502】 Step 6: 【0503】 The server monitors progress information and emotional data, and adjusts tasks as needed. If the emotional engine determines that the user is experiencing significant physical or mental strain, it provides support by inserting rest periods or sending encouraging messages to the device. 【0504】 Step 7: 【0505】 The server monitors the overall system status, continuously learns emotional data to improve the efficiency of tasks performed within the home and member satisfaction, and provides improvement measures. The terminal delivers necessary information and advice to the user in a timely manner through notification functions. 【0506】 (Example 2) 【0507】 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." 【0508】 Conventional household task management systems struggle to flexibly assign tasks while considering the emotional state of individual users, and they lack sufficient consideration for reducing mental burden. Therefore, the challenge lies in suggesting optimal tasks according to the user's stress level and achieving efficient work distribution that meets the user's needs in complex household environments. 【0509】 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. 【0510】 In this invention, the server includes data processing means that learn each user's schedule information and automatically assign the most suitable tasks or caregiver duties, including sentiment analysis; means that analyze objects in the storage area using video analysis technology, detect shortages of objects, and generate a replenishment list; and means that suggest meal plans that take into account the family's preferences and nutritional needs. This makes it possible to manage tasks efficiently within the home while reducing the psychological burden on the user. 【0511】 A "user" refers to an individual person within the household who is the subject of task management and is the entity that provides the information that forms the basis for data processing and sentiment analysis. 【0512】 "Emotional analysis" is the process of evaluating a user's emotional state from voice, facial expressions, and other data, and using that information to inform tasks and suggestions. 【0513】 "Data processing means" refers to a set of functions for collecting and analyzing each user's schedule information and assigning optimal tasks through learning. 【0514】 "Video analysis technology" refers to the technology that processes image data acquired by cameras and sensors to recognize and classify objects. 【0515】 "Storage area" refers to the space within a home where items are stored and managed, and includes refrigerators, pantries, and other similar spaces. 【0516】 A "meal plan" is a meal plan created with consideration for the family's preferences and nutritional needs, and serves as a guide for cooking within the home. 【0517】 A "task" refers to a specific household chore or childcare activity that is divided among family members and is to be performed by the user. 【0518】 "Psychological burden" refers to the level of stress and anxiety a user experiences while performing a task, and is measured through emotion analysis. 【0519】 "Notification means" refers to a mechanism that provides users with necessary information and advice, and is executed through a device. 【0520】 This invention is a system for streamlining task management within the home, and it enables flexible task assignment incorporating sentiment analysis. This system mainly consists of a server, terminals, and users. 【0521】 The server collects each user's schedule data and analyzes it in combination with emotional data to assign the most suitable tasks. In this process, image analysis and voice analysis technologies are combined to obtain emotional states from the user's voice and facial expressions. Specifically, a commonly used image analysis API is used for facial recognition, and a standard voice recognition system is used for voice analysis. 【0522】 The terminal displays task information received from the server to the user and explains the task details. It also uses cameras installed in storage areas such as refrigerators to capture images of the contents and monitor the condition of the items. The captured images are periodically sent to the server to help monitor inventory levels. 【0523】 As a concrete example, the server considers the busyness of the household and the feelings of its members, and if it determines that the emotional burden is high, it sends encouraging messages and relaxation methods to the user via the terminal. In this way, the system can be more than just a task management tool; it can also play a role in improving the overall well-being of the household. 【0524】 An example of a prompt would be: "Evaluate the emotional state of the family based on data from yesterday and suggest the most appropriate tasks for each member. Also, if a member is experiencing stress, include specific suggestions to alleviate their burden." This prompt is used by a generative AI model to assign new tasks based on the user's situation. 【0525】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0526】 Step 1: 【0527】 The server receives schedule data from each user as input. This data includes each user's appointments and free time. The server analyzes this information and learns each user's activity patterns. Specifically, it uses data analysis algorithms to extract past schedule trends and use them to help plan future schedules. 【0528】 Step 2: 【0529】 The device acquires the user's voice input and facial expression data. Based on this input data, it analyzes the user's emotional state using voice recognition software and image recognition technology. The emotional analysis results are output and sent to the server. Specifically, the device collects voice using its built-in microphone, captures facial expressions with its camera, and processes this data in real time. 【0530】 Step 3: 【0531】 The server takes schedule data and sentiment analysis results as input and uses a generative AI model to calculate the optimal task assignment. This process outputs a task list that is individually customized based on each user's stress level and free time. Specifically, it rearranges and adjusts tasks based on prompt messages generated by the AI ​​model. 【0532】 Step 4: 【0533】 The device displays task assignment information sent from the server to the user. This information includes an explanation of why the task was assigned. Once the user has reviewed the task, they send their feedback back to the server. Specifically, the device uses its notification function to send an alert to the user and provides a user interface that allows for easy feedback input. 【0534】 Step 5: 【0535】 Users report task progress via their devices and provide feedback on the psychological burden they experience while performing the tasks. This feedback data serves as input for the server to adjust or suggest improvements to the tasks. Specifically, this involves users entering their progress and emotional evaluation using a form on their devices and sending the data to the server via a submit button. 【0536】 (Application Example 2) 【0537】 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." 【0538】 The problem that this invention aims to solve is to manage employee schedules and reduce stress in factory work, thereby enabling efficient and flexible work adjustments. It aims to lighten the burden and improve work efficiency while taking into account the emotional state of employees. Conventional systems have the problem of rigid work assignments that do not take into account individual emotions or areas of expertise, resulting in significant psychological burden. 【0539】 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. 【0540】 This invention includes a server that includes information processing means capable of learning each individual's activity plan data and automatically assigning the most suitable work or childcare tasks; means for analyzing items in the storage environment using image analysis technology, detecting shortages of items, and generating a replenishment list; and means for providing meal suggestions that take into account family preferences and nutrition. This enables efficient work support while performing sentiment analysis to evaluate the emotional state of employees and reduce their workload. 【0541】 "Activity plan data" refers to information about each individual's daily schedule and tasks, and this data is used as the basis for efficient task assignment. 【0542】 An "information processing means" is a component of a system that has the function of deriving the optimal result by analyzing and processing given data. 【0543】 "Image analysis technology" is a technique for analyzing digital image data and extracting useful information from it, and is used for recognizing and classifying objects. 【0544】 A "replenishment list" is a list generated when a shortage of an item is detected, indicating which items should be replenished. 【0545】 "Meal suggestions" refer to a method of proposing an optimal meal plan that takes into account individual preferences and nutritional needs. 【0546】 "Emotional analysis" is a technology that evaluates and analyzes an individual's emotional state based on information obtained from audio and video. 【0547】 "Work support" refers to functions that provide assistance and support to improve work efficiency, and plays a particularly important role in collaboration between humans and machines. 【0548】 The system for realizing this application consists of a cloud-based server, multiple sensors placed within the factory, and mobile devices used by employees. The server receives activity plan data sent from factory employees and image data acquired by the sensors, and based on this information, assigns the most suitable tasks to each employee. 【0549】 The server uses emotion recognition software such as Microsoft Azure Cognitive Services and Google Cloud Vision API to perform emotion analysis. This allows it to analyze employees' emotions in real time from their facial and voice data and reflect the results in activity plan data. Based on this analysis, the server determines appropriate tasks and encouraging messages for each employee. 【0550】 Next, the server uses image analysis technology to retrieve item data from the storage environment within the factory, identifies missing items based on that data, and generates a replenishment list. This utilizes a deep learning model to precisely classify items and automatically identify the necessary replenishments. 【0551】 The generated work assignments and replenishment lists are notified to employees via mobile devices. Based on the notifications received via their devices, employees can efficiently proceed with their work. This reduces the workload on employees and improves the overall work efficiency of the factory. 【0552】 As a concrete example, the server uses emotion analysis to determine that employee B, who is feeling busy in the morning, is tired. Based on this information, a message such as, "Let's take a short break and refresh ourselves. How about taking a breather at the newly opened cafe?" is generated and sent to B via their mobile device. 【0553】 Examples of prompts to input into a generative AI model: 【0554】 "The role of the AI ​​system is to optimize work assignments and support messages based on employee emotional data." 【0555】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0556】 Step 1: 【0557】 The server receives activity plan data transmitted from employees within the factory and image data acquired by sensors. This input data relates to employee schedules and factory inventory status. The server stores this data and prepares it for use in subsequent processing. 【0558】 Step 2: 【0559】 The server analyzes the inventory items using image analysis techniques based on the received image data. In this step, a deep learning model is used to identify each item from the image and calculate their quantities. This identifies items that are low in stock and generates a replenishment list. The output includes the inventory status of each item and a list of items that are low in stock. 【0560】 Step 3: 【0561】 The server uses emotion recognition software to analyze employee facial images and voice data as input. This analysis evaluates each employee's current emotional state. The output provides information indicating each employee's emotional state. This information is used to determine work assignments and support messages. 【0562】 Step 4: 【0563】 The server integrates activity plan data, inventory status, and sentiment analysis results to determine the most suitable tasks and encouragement messages for each employee. Using a generative AI model, it creates and outputs a plan to optimize employee workload and efficiency, taking these factors into consideration. From this process, a list of work instructions and messages is generated. 【0564】 Step 5: 【0565】 The server sends the determined work instructions and encouragement messages to the terminal. The terminal receives this information and notifies the employee. The user (employee) checks the tasks assigned to them and the messages received through the terminal and works efficiently. The instructions and encouragement messages for the employee are displayed as output. 【0566】 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. 【0567】 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. 【0568】 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. 【0569】 [Fourth Embodiment] 【0570】 Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment. 【0571】 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. 【0572】 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). 【0573】 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. 【0574】 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. 【0575】 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). 【0576】 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. 【0577】 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. 【0578】 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. 【0579】 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. 【0580】 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. 【0581】 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. 【0582】 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". 【0583】 The present invention is a system for efficiently managing household chores and childcare tasks, and includes information processing means that can learn the schedules of each household member and assign optimal tasks. Specific embodiments thereof are described below. 【0584】 The server receives schedule data from household members and learns each member's activity patterns based on this data. Based on this learned data, the server automatically assigns household chores and childcare tasks to each member at the most appropriate time. The server can also adjust the types of tasks based on the user's strengths. 【0585】 Furthermore, the device sends image data of the refrigerator's contents to the server. The server, upon receiving this data, uses image analysis technology to determine the food inventory in the refrigerator and detect any missing items. Based on this information, the server automatically generates a shopping list, helping users reduce unnecessary purchases and providing efficient daily management. 【0586】 The server also suggests menus based on the ingredients in the refrigerator, taking into account the user's food preferences and nutritional requirements. These menus are presented to the user via a terminal, helping to make meal planning easier. 【0587】 Users can report task progress via their devices. These devices send this progress data to a server, which monitors the overall task status in real time. The server manages tasks to ensure smooth workflow, reassigning tasks or suggesting new ones as needed. 【0588】 As a concrete example, the server analyzes an image of the refrigerator received from the terminal in the morning and determines that "there is a shortage of milk." As a result, the server adds milk to the shopping list and assigns this shopping task to a user who has free time in the evening. This information is notified to the terminal, allowing the user to plan their schedule efficiently. 【0589】 This system can also send reminders and emergency notifications to users using notification methods. This helps to coordinate awareness within the household and establish a system for responding quickly to emergencies. Through these functions, household task management is automated, resulting in an improved quality of life. 【0590】 The following describes the processing flow. 【0591】 Step 1: 【0592】 The server receives schedule data entered by the user through their device. This data includes appointments for work, school, household chores, etc., and the server records it to learn the activity patterns of each member of the household. 【0593】 Step 2: 【0594】 The server optimally assigns household and childcare tasks based on learned schedule data. Assignments are made individually, taking into account each member's availability and areas of expertise. 【0595】 Step 3: 【0596】 The terminal allows the user to take photos of the inside of the refrigerator and send them to the server. The image data is received by the server and analyzed to understand the status of food inventory. 【0597】 Step 4: 【0598】 The server uses image analysis technology to analyze the contents of the refrigerator and identify missing food items. Based on these identified missing items, the server automatically generates a shopping list. 【0599】 Step 5: 【0600】 The server suggests menus that utilize the user's available ingredients, taking into account their preferences and nutritional requirements. The suggested menus are then notified to the user via their device. 【0601】 Step 6: 【0602】 Users use their devices to report the progress of their assigned tasks. The devices send this progress data to the server, which updates the task completion status in real time. 【0603】 Step 7: 【0604】 The server monitors aggregated progress data and, if necessary, reassigns tasks or proposes new tasks. If task delays or resource shortages are detected, corrective actions are taken immediately. 【0605】 Step 8: 【0606】 The server sends reminders and emergency notifications to household members as needed. The device receives these and displays them to the user, instantly conveying important information. 【0607】 (Example 1) 【0608】 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". 【0609】 In modern households, managing various household tasks is becoming increasingly complex. Especially in multi-member households, efficiently dividing household chores and childcare activities while considering each member's schedule is crucial. Furthermore, inadequate food inventory management can lead to wasteful shopping and unbalanced nutrition. To address these challenges, efficient and flexible task management, along with streamlined food inventory and nutrition planning, are essential. 【0610】 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. 【0611】 This invention includes a server that includes information processing means capable of learning each member's time management data and automatically assigning the most suitable household tasks or childcare activities; means for analyzing objects in the storage environment using image analysis technology, identifying shortages of objects, and generating replenishment tables; and means for suggesting meal plans that take into account the group's preferences and nutrition. This enables efficient task sharing within the household and streamlines food inventory and meal planning. 【0612】 "Time management data" refers to information about the schedules and tasks that each member uses in their daily activities, and includes data such as schedules and priorities. 【0613】 An "information processing device" is a device or system that has the function of performing calculations and analyses based on input data and deriving a specific result. 【0614】 "Image analysis technology" refers to techniques that analyze image data to recognize objects and detect features, often utilizing deep learning models. 【0615】 "Storage environment" refers to the place and conditions for storing and preserving food and goods, and includes refrigerators and pantries in the home. 【0616】 A "supply list" is a list of items that are currently missing, and is used for reference in future purchasing activities. 【0617】 "Meal plan suggestions" is a process that proposes ingredients and menus to be consumed, taking into account the user's preferences and nutritional balance. 【0618】 "Activity progress" refers to information indicating the extent to which each member has completed their assigned tasks. 【0619】 "Notification means" refers to a function for conveying important information, notifications, or warnings to the user, including alarms and message notifications. 【0620】 This invention provides a system for streamlining the management of household tasks, comprising a server for information processing and a terminal accessible to users. This system aggregates time management data from each member of the household and assigns optimal household tasks and childcare activities based on this data. The server analyzes the schedule information collected from each member using machine learning algorithms, specifically time-series analysis techniques such as long-term short-term memory (LSTM). This allows the system to learn each member's activity patterns and achieve efficient task assignment. 【0621】 Additionally, image data of the inside of the refrigerator is acquired through a camera attached to the terminal. The server analyzes this image data using computer vision technology (for example, the YOLO model or a deep learning model built with TensorFlow) to determine the food inventory. For items that are missing, the server automatically generates a shopping list for replenishment and notifies the user's terminal. 【0622】 Furthermore, the server considers the user's food preferences and nutritional requirements, and proposes a meal plan based on the ingredients in the refrigerator. This process utilizes a generative AI model to suggest the most suitable menu. Users can view these suggestions on their device, helping them plan healthier and more balanced meals. 【0623】 On the other hand, users can report task progress using their devices, allowing the server to monitor task completion in real time. If necessary, the server can reassign tasks or suggest new ones to help ensure smooth workflow within the home. 【0624】 As a concrete example, the server analyzes an image of the refrigerator sent via the terminal in the morning and determines that "there is a shortage of milk." Based on this result, it adds milk to the shopping list and assigns this shopping task to a user who has relatively more time in the evening. This information is notified to the terminal, allowing the user to shop efficiently on their way to work. 【0625】 Examples of prompts to be input to the generating AI model include: "Please tell me how to efficiently manage household chores and childcare. Specifically, please explain in detail the mechanisms for task assignment and food inventory management." In this way, it is expected that the system of the present invention will improve the efficiency of household tasks and enhance the quality of life. 【0626】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0627】 Step 1: 【0628】 The server receives schedule data sent from each member via their terminal. The input includes data about each member's schedule and tasks. Based on this data, the server uses machine learning algorithms to analyze and learn each member's activity patterns. Here, time series analysis techniques are used to create a predictive model, determining a work schedule suitable for each member. 【0629】 Step 2: 【0630】 The terminal periodically captures image data from inside the refrigerator and sends it to the server. The input is an image file of the inside of the refrigerator. The server receives this image data and uses image analysis technology to analyze the food inventory status. Specifically, it uses a computer vision model to recognize the type and quantity of food and identify items that are missing. An inventory list and a shortage list are generated as output. 【0631】 Step 3: 【0632】 The server uses accumulated inventory data to list missing items and create a shopping list. Inputs include the missing items list obtained in step 2 and the user's past purchasing patterns. Based on this information, the server automatically generates a shopping list and notifies the terminal. The output is a shopping list that the user can review. 【0633】 Step 4: 【0634】 The server suggests menus based on the user's food preferences and nutritional requirements, taking into account the contents of their refrigerator. The inputs are inventory data and user preference data. A generative AI model analyzes this data to generate optimal menu suggestions. The output is a menu suggestion displayed on the user's device. 【0635】 Step 5: 【0636】 Users input task progress via their terminals and report it to the server. Input includes data on the progress of each task. The server receives this data, monitors progress in real time, and reassigns tasks if necessary. Output includes updated task management information, which is sent to the terminal. 【0637】 (Application Example 1) 【0638】 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". 【0639】 Efficiently managing household chores and childcare tasks is a significant challenge for many families. It requires assigning tasks at the optimal time, taking into account the schedules of each family member. However, manually managing these tasks is difficult and inefficient. Furthermore, properly managing food inventory and suggesting menus that meet nutritional and taste requirements are also important needs within families, but currently, there is a lack of efficient means to achieve this. 【0640】 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. 【0641】 This invention includes a server that learns each member's time management data and automatically assigns the optimal household chore or childcare role; a server that uses image processing technology to analyze items in the storage environment, detect shortages of items, and generate a replenishment list; and a server that provides menu suggestions that take into account the preferences and nutritional needs of each member. This enables efficient management of tasks that are appropriate to each member's schedule and abilities, reducing the burden on the household and improving the quality of life. 【0642】 "Information processing means" refers to a device or software that learns the time management data of each member and automatically assigns the optimal household chore or childcare role. 【0643】 "Image processing technology" refers to image analysis techniques used to analyze items within a storage environment and detect shortages of items. 【0644】 A "replenishment list" is a list generated when a shortage of goods is detected, used to replenish the necessary items. 【0645】 "Member preferences and nutritional information" refers to information about each member's taste preferences and health-related nutritional needs, and serves as basic data for proposing menus based on this information. 【0646】 A "menu suggestion device" is a device or software that generates a plan for daily meals based on the preferences and nutritional needs of its members. 【0647】 A "generative AI model" is an information generation model that utilizes artificial intelligence and has the ability to propose optimal solutions based on the given data. 【0648】 A "prompt statement" is an instruction given to a generative AI model, used to control the AI's output based on specific conditions or data. 【0649】 To realize this invention, a system will be built in which a server and terminals work together to perform the necessary functions. The server will receive time management data from each member and assign the most suitable household chore or childcare role based on this data. The time management data will be managed based on each member's calendar information and activity data. 【0650】 The terminal operates a video acquisition device installed in the home to photograph items within the storage environment. This video data is processed using video processing technology and transmitted to a server. The server analyzes the video data, determines the shortage of items, and generates a replenishment list. 【0651】 Furthermore, the server uses a generative AI model to suggest optimal menus based on the preferences and nutritional information of its members. The generative AI model generates specific menu suggestions by inputting prompts. For example, one might send the prompt, "Please suggest a nutritionally balanced menu for my family's dinner." 【0652】 As a concrete example, if the server analyzes video data in the morning and detects a shortage of milk, it adds milk to the replenishment list and suggests purchasing it to the most suitable member. Users receive the suggestion via their device and can confirm it through a smartphone app. 【0653】 This system improves the efficiency of daily household management, reduces the burden on family members, and maintains harmony within the household. The menu suggestions generated by the AI ​​model simplify daily meal planning and support a nutritious diet. 【0654】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0655】 Step 1: 【0656】 The server retrieves time management data for each member. The input consists of each member's calendar information and activity data. Based on this, the server analyzes each member's schedule to identify their free time and areas of expertise. The output is a list of optimized task candidates. 【0657】 Step 2: 【0658】 The terminal operates a video acquisition device installed in the home to photograph items within the storage environment. The input is video data. The terminal sends this data to a server, which analyzes the video data using video processing technology. As a result of the analysis, the output reveals the status of any missing items. 【0659】 Step 3: 【0660】 The server generates a replenishment list based on the analysis results. The input is the status data of the analyzed items. The server detects and lists the missing items. The output is a list of items that need to be replenished. 【0661】 Step 4: 【0662】 The server uses a generative AI model to generate menu suggestions based on the preferences and nutritional information of its members. The input consists of nutritional information, preference data, and a prompt. For example, the prompt might be "Please suggest a nutritionally balanced menu for my family's dinner." The AI ​​analyzes this data and outputs the optimal menu suggestion. 【0663】 Step 5: 【0664】 The user checks the replenishment list and menu suggestions sent from the server via their terminal. Input is the notification from the server. The user receives the notification and takes action as needed. Output is the user's action plan. 【0665】 Step 6: 【0666】 Users report task progress to their terminals and send it to the server. The input is the task completion status. The server receives the report, monitors the overall task progress, and makes role reassignments or new suggestions as needed. The output is the updated task assignment status. 【0667】 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. 【0668】 This invention is a system for streamlining task management within the home, and in particular, by combining it with an emotion engine, it achieves flexible task assignment and management that takes into account the user's emotional state. Specific embodiments are shown below. 【0669】 The server first receives schedule data from household members and learns their individual activity patterns based on this data. Then, it analyzes their emotional state using this data and an emotion engine to assign optimal tasks to each member. Emotional states are obtained through member input, voice, and facial recognition. For example, if it is determined that a member is experiencing stress, tasks are readjusted to reduce their burden. 【0670】 The device displays this information to the user and explains how emotion-based task assignments are performed. It also sends image data of the refrigerator to the server to track inventory levels. This information, along with the results of the emotion engine, is used to generate meal suggestions and shopping lists. 【0671】 The server further suggests menus that take into account the user's preferences and nutritional balance, and by combining this with emotional data, it creates a meal plan that reduces the user's psychological burden. The suggestions are notified to the user via their device, and the user confirms them. 【0672】 Users report task progress using their devices and provide feedback on the psychological burden they experience during the process. Based on this feedback, the server monitors task progress and reassigns tasks as needed. By using an emotion engine, it is possible to evaluate user satisfaction and stress levels and provide notifications and advice tailored to each user. 【0673】 As a concrete example, the server considers the busyness of the household and the feelings of individual members, and if it determines that the emotional burden is high, it sends encouraging messages or relaxation methods via the device. This allows the system to be more than just an efficiency tool, but also to implement initiatives that consider the mental health of the entire family. 【0674】 The following describes the processing flow. 【0675】 Step 1: 【0676】 The server receives schedule and emotion input data entered by the user through the terminal. This includes information about the user's daily schedule, mood, and energy level for the day. The server stores this data and learns each user's activity patterns and emotional tendencies. 【0677】 Step 2: 【0678】 The device takes a picture of the inside of the refrigerator and sends it to the server. The server performs image analysis to determine the current inventory status. This analysis identifies which food items are running low. 【0679】 Step 3: 【0680】 The server utilizes accumulated schedule and emotional data to assign household and childcare tasks to each family member. When assigning tasks, it takes into account the user's current energy level and stress level, adjusting them to avoid burdening them. If the emotional engine detects user fatigue, it reduces or reassigns tasks. 【0681】 Step 4: 【0682】 Based on the analysis results, the server lists the necessary food items and creates a shopping list. At the same time, it suggests a menu tailored to the user's preferences and emotional state. This suggestion is delivered to the user via their device. If the user's emotional state is negative, the server recommends a menu that includes many ingredients that improve mood. 【0683】 Step 5: 【0684】 Users check and complete assigned tasks on their devices. Information is sent to the server by reporting the task progress and their emotions during the process via the device. The server uses this data to evaluate the task progress and the user's emotional tendencies. 【0685】 Step 6: 【0686】 The server monitors progress information and emotional data, and adjusts tasks as needed. If the emotional engine determines that the user is experiencing significant physical or mental strain, it provides support by inserting rest periods or sending encouraging messages to the device. 【0687】 Step 7: 【0688】 The server monitors the overall system status, continuously learns emotional data to improve the efficiency of tasks performed within the home and member satisfaction, and provides improvement measures. The terminal delivers necessary information and advice to the user in a timely manner through notification functions. 【0689】 (Example 2) 【0690】 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". 【0691】 Conventional household task management systems struggle to flexibly assign tasks while considering the emotional state of individual users, and they lack sufficient consideration for reducing mental burden. Therefore, the challenge lies in suggesting optimal tasks according to the user's stress level and achieving efficient work distribution that meets the user's needs in complex household environments. 【0692】 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. 【0693】 In this invention, the server includes data processing means that learn each user's schedule information and automatically assign the most suitable tasks or caregiver duties, including sentiment analysis; means that analyze objects in the storage area using video analysis technology, detect shortages of objects, and generate a replenishment list; and means that suggest meal plans that take into account the family's preferences and nutritional needs. This makes it possible to manage tasks efficiently within the home while reducing the psychological burden on the user. 【0694】 A "user" refers to an individual person within the household who is the subject of task management and is the entity that provides the information that forms the basis for data processing and sentiment analysis. 【0695】 "Emotional analysis" is the process of evaluating a user's emotional state from voice, facial expressions, and other data, and using that information to inform tasks and suggestions. 【0696】 "Data processing means" refers to a set of functions for collecting and analyzing each user's schedule information and assigning optimal tasks through learning. 【0697】 "Video analysis technology" refers to the technology that processes image data acquired by cameras and sensors to recognize and classify objects. 【0698】 "Storage area" refers to the space within a home where items are stored and managed, and includes refrigerators, pantries, and other similar spaces. 【0699】 A "meal plan" is a meal plan created with consideration for the family's preferences and nutritional needs, and serves as a guide for cooking within the home. 【0700】 A "task" refers to a specific household chore or childcare activity that is divided among family members and is to be performed by the user. 【0701】 "Psychological burden" refers to the level of stress and anxiety a user experiences while performing a task, and is measured through emotion analysis. 【0702】 "Notification means" refers to a mechanism that provides users with necessary information and advice, and is executed through a device. 【0703】 This invention is a system for streamlining task management within the home, and it enables flexible task assignment incorporating sentiment analysis. This system mainly consists of a server, terminals, and users. 【0704】 The server collects each user's schedule data and analyzes it in combination with emotional data to assign the most suitable tasks. In this process, image analysis and voice analysis technologies are combined to obtain emotional states from the user's voice and facial expressions. Specifically, a commonly used image analysis API is used for facial recognition, and a standard voice recognition system is used for voice analysis. 【0705】 The terminal displays task information received from the server to the user and explains the task details. It also uses cameras installed in storage areas such as refrigerators to capture images of the contents and monitor the condition of the items. The captured images are periodically sent to the server to help monitor inventory levels. 【0706】 As a concrete example, the server considers the busyness of the household and the feelings of its members, and if it determines that the emotional burden is high, it sends encouraging messages and relaxation methods to the user via the terminal. In this way, the system can be more than just a task management tool; it can also play a role in improving the overall well-being of the household. 【0707】 An example of a prompt would be: "Evaluate the emotional state of the family based on data from yesterday and suggest the most appropriate tasks for each member. Also, if a member is experiencing stress, include specific suggestions to alleviate their burden." This prompt is used by a generative AI model to assign new tasks based on the user's situation. 【0708】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0709】 Step 1: 【0710】 The server receives schedule data from each user as input. This data includes each user's appointments and free time. The server analyzes this information and learns each user's activity patterns. Specifically, it uses data analysis algorithms to extract past schedule trends and use them to help plan future schedules. 【0711】 Step 2: 【0712】 The device acquires the user's voice input and facial expression data. Based on this input data, it analyzes the user's emotional state using voice recognition software and image recognition technology. The emotional analysis results are output and sent to the server. Specifically, the device collects voice using its built-in microphone, captures facial expressions with its camera, and processes this data in real time. 【0713】 Step 3: 【0714】 The server takes schedule data and sentiment analysis results as input and uses a generative AI model to calculate the optimal task assignment. This process outputs a task list that is individually customized based on each user's stress level and free time. Specifically, it rearranges and adjusts tasks based on prompt messages generated by the AI ​​model. 【0715】 Step 4: 【0716】 The device displays task assignment information sent from the server to the user. This information includes an explanation of why the task was assigned. Once the user has reviewed the task, they send their feedback back to the server. Specifically, the device uses its notification function to send an alert to the user and provides a user interface that allows for easy feedback input. 【0717】 Step 5: 【0718】 Users report task progress via their devices and provide feedback on the psychological burden they experience while performing the tasks. This feedback data serves as input for the server to adjust or suggest improvements to the tasks. Specifically, this involves users entering their progress and emotional evaluation using a form on their devices and sending the data to the server via a submit button. 【0719】 (Application Example 2) 【0720】 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". 【0721】 The problem that this invention aims to solve is to manage employee schedules and reduce stress in factory work, thereby enabling efficient and flexible work adjustments. It aims to lighten the burden and improve work efficiency while taking into account the emotional state of employees. Conventional systems have the problem of rigid work assignments that do not take into account individual emotions or areas of expertise, resulting in significant psychological burden. 【0722】 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. 【0723】 This invention includes a server that includes information processing means capable of learning each individual's activity plan data and automatically assigning the most suitable work or childcare tasks; means for analyzing items in the storage environment using image analysis technology, detecting shortages of items, and generating a replenishment list; and means for providing meal suggestions that take into account family preferences and nutrition. This enables efficient work support while performing sentiment analysis to evaluate the emotional state of employees and reduce their workload. 【0724】 "Activity plan data" refers to information about each individual's daily schedule and tasks, and this data is used as the basis for efficient task assignment. 【0725】 An "information processing means" is a component of a system that has the function of deriving the optimal result by analyzing and processing given data. 【0726】 "Image analysis technology" is a technique for analyzing digital image data and extracting useful information from it, and is used for recognizing and classifying objects. 【0727】 A "replenishment list" is a list generated when a shortage of an item is detected, indicating which items should be replenished. 【0728】 "Meal suggestions" refer to a method of proposing an optimal meal plan that takes into account individual preferences and nutritional needs. 【0729】 "Emotional analysis" is a technology that evaluates and analyzes an individual's emotional state based on information obtained from audio and video. 【0730】 "Work support" refers to functions that provide assistance and support to improve work efficiency, and plays a particularly important role in collaboration between humans and machines. 【0731】 The system for realizing this application consists of a cloud-based server, multiple sensors placed within the factory, and mobile devices used by employees. The server receives activity plan data sent from factory employees and image data acquired by the sensors, and based on this information, assigns the most suitable tasks to each employee. 【0732】 The server uses emotion recognition software such as Microsoft Azure Cognitive Services and Google Cloud Vision API to perform emotion analysis. This allows it to analyze employees' emotions in real time from their facial and voice data and reflect the results in activity plan data. Based on this analysis, the server determines appropriate tasks and encouraging messages for each employee. 【0733】 Next, the server uses image analysis technology to retrieve item data from the storage environment within the factory, identifies missing items based on that data, and generates a replenishment list. This utilizes a deep learning model to precisely classify items and automatically identify the necessary replenishments. 【0734】 The generated work assignments and replenishment lists are notified to employees via mobile devices. Based on the notifications received via their devices, employees can efficiently proceed with their work. This reduces the workload on employees and improves the overall work efficiency of the factory. 【0735】 As a concrete example, the server uses emotion analysis to determine that employee B, who is feeling busy in the morning, is tired. Based on this information, a message such as, "Let's take a short break and refresh ourselves. How about taking a breather at the newly opened cafe?" is generated and sent to B via their mobile device. 【0736】 Examples of prompts to input into a generative AI model: 【0737】 "The role of the AI ​​system is to optimize work assignments and support messages based on employee emotional data." 【0738】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0739】 Step 1: 【0740】 The server receives activity plan data transmitted from employees within the factory and image data acquired by sensors. This input data relates to employee schedules and factory inventory status. The server stores this data and prepares it for use in subsequent processing. 【0741】 Step 2: 【0742】 The server analyzes the inventory items using image analysis techniques based on the received image data. In this step, a deep learning model is used to identify each item from the image and calculate their quantities. This identifies items that are low in stock and generates a replenishment list. The output includes the inventory status of each item and a list of items that are low in stock. 【0743】 Step 3: 【0744】 The server uses emotion recognition software to analyze employee facial images and voice data as input. This analysis evaluates each employee's current emotional state. The output provides information indicating each employee's emotional state. This information is used to determine work assignments and support messages. 【0745】 Step 4: 【0746】 The server integrates activity plan data, inventory status, and sentiment analysis results to determine the most suitable tasks and encouragement messages for each employee. Using a generative AI model, it creates and outputs a plan to optimize employee workload and efficiency, taking these factors into consideration. From this process, a list of work instructions and messages is generated. 【0747】 Step 5: 【0748】 The server sends the determined work instructions and encouragement messages to the terminal. The terminal receives this information and notifies the employee. The user (employee) checks the tasks assigned to them and the messages received through the terminal and works efficiently. The instructions and encouragement messages for the employee are displayed as output. 【0749】 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. 【0750】 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. 【0751】 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. 【0752】 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. 【0753】 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. 【0754】 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. 【0755】 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. 【0756】 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. 【0757】 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." 【0758】 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. 【0759】 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. 【0760】 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. 【0761】 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. 【0762】 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. 【0763】 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. 【0764】 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. 【0765】 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. 【0766】 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. 【0767】 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. 【0768】 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. 【0769】 All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference. 【0770】 The following is further disclosed regarding the embodiments described above. 【0771】 (Claim 1) 【0772】 An information processing device that learns each member's schedule data and can automatically assign the most suitable household chores or childcare tasks, 【0773】 A means for analyzing items in a storage environment using image processing technology, detecting shortages of items, and generating a replenishment list, 【0774】 A means of providing menu suggestions that take into account family preferences and nutrition, 【0775】 A means of monitoring the progress of each task and proposing task reassignment or new tasks based on progress, 【0776】 A means of notification or warning as necessary, 【0777】 A system that includes this. 【0778】 (Claim 2) 【0779】 The system according to claim 1, characterized in that it takes into account the free time and areas of expertise of individual members when optimally assigning tasks. 【0780】 (Claim 3) 【0781】 The system according to claim 1, characterized in that, in the analysis of items in a storage environment, a deep learning model is used to classify the stored items and identify the necessary replacement items. 【0782】 "Example 1" 【0783】 (Claim 1) 【0784】 An information processing means that can learn the time management data of each member and automatically assign the most suitable household chores or childcare activities, 【0785】 A means for analyzing objects in a storage environment using image analysis technology, identifying missing objects, and generating a replenishment list, 【0786】 A means of proposing a meal plan that takes into account the preferences and nutritional needs of a group, 【0787】 A means of monitoring the progress of each activity and proposing the reallocation of activities or new activities according to the progress, 【0788】 A means of notification or warning as necessary, 【0789】 A system that includes this. 【0790】 (Claim 2) 【0791】 The system according to claim 1, characterized in that it takes into account the available time and areas of expertise of each member when optimally allocating activities. 【0792】 (Claim 3) 【0793】 The system according to claim 1, characterized in that, in object analysis within a storage environment, a deep learning model is used to classify the stored objects and identify the necessary replacement objects. 【0794】 "Application Example 1" 【0795】 (Claim 1) 【0796】 An information processing device that learns the time management data of each member and can automatically assign the optimal household chore or childcare role, 【0797】 A means for analyzing items in a storage environment using image processing technology, detecting shortages of items, and generating a replenishment list, 【0798】 A means of proposing menus that take into account the preferences and nutritional needs of the members, 【0799】 A means of monitoring the performance of each role and proposing role reassignment or new roles based on progress, 【0800】 A means of notification or warning as necessary, 【0801】 A module for automatically suggesting replenishment based on the results of item analysis within the storage environment, and a means for generating menu suggestions based on preferences and nutritional information using a generation AI model, 【0802】 A system that includes this. 【0803】 (Claim 2) 【0804】 The system according to claim 1, characterized in that it includes taking into account the free time and areas of expertise of individual members in the optimal assignment of roles, and means for transmitting information about items in the storage environment to the cloud and automatically suggesting necessary replenishment items. 【0805】 (Claim 3) 【0806】 The system according to claim 1, characterized in that, in analyzing items within a storage environment, it uses deep learning technology to classify the stored items and identify the necessary replenishment items, and generates prompt sentences based on input data to a generated AI model, thereby generating menus linked to user preferences and nutritional information. 【0807】 "Example 2 of combining an emotion engine" 【0808】 (Claim 1) 【0809】 A data processing method that learns each user's schedule information and automatically assigns the most suitable tasks or caregiver duties, including sentiment analysis. 【0810】 A means for analyzing objects in a storage area using video analysis technology, detecting missing objects, and generating a replenishment list, 【0811】 A means of suggesting meal plans that take into account the family's preferences and nutritional needs, 【0812】 A means of monitoring the progress of each task and proposing task reallocation or new tasks according to the progress, 【0813】 A notification method for providing advice or encouragement to reduce psychological burden using emotional data, 【0814】 A system that includes this. 【0815】 (Claim 2) 【0816】 The system according to claim 1, characterized in that, in optimizing the allocation of tasks, it takes into account the free time and areas of expertise of individual users, as well as their emotional state. 【0817】 (Claim 3) 【0818】 The system according to claim 1, characterized in that, in object analysis within a storage area, a machine learning model is used to classify the stored objects and identify the necessary replenishment items. 【0819】 "Application example 2 when combining with an emotional engine" 【0820】 (Claim 1) 【0821】 An information processing device that learns each individual's activity plan data and can automatically assign the most suitable tasks or childcare duties, 【0822】 A means for analyzing items in a storage environment using image analysis technology, detecting shortages of items, and generating a replenishment list, 【0823】 A means of providing meal suggestions that take into account family preferences and nutrition, 【0824】 A means of monitoring the progress of each task and proposing task reassignment or new tasks according to the progress, 【0825】 Notification means for providing notification or warning as needed, 【0826】 An emotion analysis tool that evaluates the emotional state during collaborative work between humans and machines and provides optimal work support, 【0827】 A system that includes this. 【0828】 (Claim 2) 【0829】 The system according to claim 1, characterized in that, in optimizing task assignment, it takes into account the free time and areas of expertise of each individual, and further reduces the workload by using their emotional state. 【0830】 (Claim 3) 【0831】 The system according to claim 1, characterized in that, in item analysis within the storage environment, it uses a deep learning model to classify stored items, identifies necessary replenishment items, and further provides work support to reduce the burden on employees based on the classification results. [Explanation of symbols] 【0832】 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] An information processing device that learns each member's schedule data and can automatically assign the most suitable household chores or childcare tasks, A means for analyzing items in a storage environment using image processing technology, detecting shortages of items, and generating a replenishment list, A means of providing menu suggestions that take into account family preferences and nutrition, A means of monitoring the progress of each task and proposing task reassignment or new tasks based on progress, A means of notification or warning as necessary, A system that includes this. [Claim 2] The system according to claim 1, characterized in that it takes into account the free time and areas of expertise of individual members when optimally assigning tasks. [Claim 3] The system according to claim 1, characterized in that, in the analysis of items in a storage environment, a deep learning model is used to classify the stored items and identify the necessary replacement items.

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