system

Abstract

We provide the system. [Solution] An information input method for users to input growth information, A plan generation means that automatically generates an activity plan using a generative model based on growth information, A notification method for providing the generated activity plan to the user, A nutrition plan generation means that generates a meal plan including nutrients based on age and health information, An educational information generation means for generating educational information based on educational themes, A means of suggesting suitable information to users by researching local childcare support information, A system that uses a home appliance to implement the above-mentioned measures and includes a home appliance notification means that notifies parents in real time of activity plans and nutrition plans.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In families with child-rearing, there are a wide variety of problems, such as insufficient information on child growth, difficulty in schedule management, inability to efficiently handle many child-rearing related tasks, and lack of knowledge about how to use necessary child-rearing systems and services. In particular, in dual-income families and single-parent families, these problems have become a major burden in daily life. In such a situation, efficient and effective support is required so that parents can raise children with peace of mind.

Means for Solving the Problems

[0005] The present invention includes a data input means for inputting child growth information from the user, and an activity generation means for automatically generating daily and weekly activity lists using a generation model based on that information. It also includes a notification means for informing the user of the generated activity lists, thereby reducing the burden of schedule management. Furthermore, it includes a nutrition generation means for generating meal plans containing appropriate nutrients based on the child's age and health data, and an education generation means for generating educational content based on educational themes. In addition, it includes a system proposal means for researching local childcare support systems and suggesting systems suitable for the user, allowing parents to easily obtain information on available childcare systems. Thus, the present invention reduces the burden of parenting and provides an environment where parents can raise their children with greater peace of mind.

[0006] "Data input means" refers to an interface or device that allows users to input information about a child's growth.

[0007] A "generative model" is an algorithm or program that makes predictions or suggestions in response to specific inputs.

[0008] The "activity generation means" is a means for automatically generating daily and weekly activity lists suitable for a child based on the input growth information.

[0009] "Notification means" refers to a method or device for informing the user of the generated activity list or information.

[0010] A "nutrition generation method" is a means of automatically creating a meal plan containing appropriate nutrients based on a child's age and health condition.

[0011] An "educational generation tool" is a means of automatically generating appropriate educational content based on a child's developmental stage and educational themes.

[0012] "Methods for proposing systems" refer to methods for researching local childcare support systems and services and proposing systems that are suitable for users. [Brief explanation of the drawing]

[0013] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2, which combines an emotion engine. [Modes for carrying out the invention]

[0014] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0015] First, the terms used in the following description will be explained.

[0016] In the following embodiments, a labeled processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0017] In the following embodiments, a labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0018] In the following embodiments, a labeled storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like.

[0019] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0020] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0021] [First Embodiment]

[0022] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0023] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0024] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0025] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0026] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0027] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0028] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0029] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0030] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0031] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0032] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0033] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0034] This invention is an AI assistant system designed to make it easier for users to manage the growth of their children. This system functions through the exchange of information between a server, a terminal, and the user.

[0035] First, the user enters basic growth information about their child via their device. This information includes the child's age, gender, and any special notes regarding their growth (such as allergies or health conditions). The entered information is sent from the device to the server and stored in a database.

[0036] The server uses a generative model based on the received data to generate daily and weekly activity lists tailored to the child's developmental stage. These generated lists are used to streamline the user's childcare schedule and simplify management. Specific examples include appropriate play and educational activities, and health check-up dates.

[0037] Furthermore, the server analyzes the child's nutritional data and develops a meal plan that includes appropriate nutrients. This plan is notified to the user via their device and can be used to help with daily meal planning. It also provides advice on food selection for children with specific allergies.

[0038] To support education, the server sets specific educational themes and generates educational content using generative models. This content, delivered to users via their devices, helps parents provide their children with an appropriate learning environment.

[0039] In addition, the server searches a local childcare support system database and identifies and suggests suitable programs for the user. This is a particularly useful source of information for working parents and parents who are unfamiliar with childcare systems. The system also periodically prompts users to input health data, and the terminal manages the progress. By including the setting of medical reminders, it aims to ensure thorough health management.

[0040] In this way, this system provides multifaceted support for parents in childcare, realizing an efficient and effective child-rearing environment.

[0041] The following describes the processing flow.

[0042] Step 1:

[0043] Users input information about their child's development via their device. This information includes the child's age, gender, health status, and allergy information.

[0044] Step 2:

[0045] The terminal sends the entered information to the server. A secure protocol is used to ensure data security during this process.

[0046] Step 3:

[0047] The server saves the received data to the database. At the same time, it verifies the integrity and completeness of the information.

[0048] Step 4:

[0049] The server uses stored data to run a generative model that generates daily and weekly activity lists. These lists include activities and schedules that are optimal for the child.

[0050] Step 5:

[0051] The server sends the generated activity list to the terminal. The terminal notifies the user and displays it on the screen.

[0052] Step 6:

[0053] The server analyzes children's health data and generates meal plans that consider nutritional balance. It also incorporates allergy information to design safe menus.

[0054] Step 7:

[0055] The server generates a meal plan and sends it to the device, which then notifies the user. The user can then use this to plan their daily meals.

[0056] Step 8:

[0057] The server creates educational content based on educational themes using a generative model.

[0058] Step 9:

[0059] The server sends the created educational content to the terminal, and the terminal provides it to the user. The user then uses this content when their child is learning.

[0060] Step 10:

[0061] The server searches a database of local childcare support programs and collects information to identify the program best suited to the user.

[0062] Step 11:

[0063] The server sends system information to the terminal, and the terminal notifies the user. The user can then check the details of the system and how to use it.

[0064] Step 12:

[0065] The device prompts the user to periodically enter health data and manages their progress. This allows for the setting of necessary medical reminders and supports health management.

[0066] (Example 1)

[0067] 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."

[0068] Traditional childcare support systems often lack consistency and efficiency because information management, activities, nutrition, and educational content provision are all separate. Furthermore, customization to suit the specific characteristics of individual families and children is difficult, which can be a burden for caregivers. Therefore, there is a need for a system that reduces the user burden and provides a more efficient and effective childcare environment.

[0069] 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.

[0070] In this invention, the server includes data input means for receiving information related to the child's growth from the user, activity plan creation means for creating a time-series activity plan using a generative artificial intelligence model, and communication means for notifying the user of the created plan via communication means. This allows the user to easily receive individually optimized activity lists and nutrition plans, thereby improving the efficiency and effectiveness of childcare.

[0071] A "data input means" is a mechanism for collecting specific information from a user and handling it in a format usable within the system.

[0072] A "generative artificial intelligence model" is an algorithm that automatically generates complex patterns and predictions based on input data, and provides optimal results through a mechanical learning process.

[0073] "Activity planning tools" refer to processes or tools for automatically creating daily or weekly activity lists tailored to a child's developmental stage.

[0074] "Communication means" refers to the infrastructure and technologies used by a system to transmit information and notifications to a user.

[0075] "Nutritional planning methods" refer to the process of creating meal menus that include appropriate nutrients based on a child's age and health information.

[0076] "Educational material generation means" refers to a method or tool for creating new educational content based on a specific theme related to education.

[0077] "Program proposal methods" refer to the process of researching local childcare support programs, identifying programs that are beneficial to users, and guiding them to those programs.

[0078] The present invention is a smart system that supports parents in efficiently managing the growth of their children. This system is built around the exchange and processing of information between a server, a terminal, and a user. Specifically, it is implemented using the following hardware and software.

[0079] First, the user enters basic growth information about their child using their device. This device includes smartphones and tablets. A dedicated application installed on the device verifies the data entered by the user and then sends the data to the server via the internet.

[0080] The server analyzes the received data and stores it in a database. A cloud-based server solution is suitable for this purpose. Next, the server uses a generative AI model based on the stored data to create appropriate activity and nutrition plans tailored to the child's age and health condition.

[0081] For example, the server takes the prompt "3-year-old girl with no allergies" as input, and the generating AI model outputs a list of recommended activities such as "playing in the sandbox, reading picture books." Furthermore, the server automatically creates a nutritional plan, taking health information into consideration. The plan includes a list of recipes that consider nutritional balance, which are then notified to the user via the application.

[0082] Furthermore, the server provides educational support by generating educational content aligned with specific educational themes and delivering it to users via their devices. For example, it can create educational games on the theme of "learning numbers" for preschool children, allowing them to learn through these games. It can also research local childcare support systems and provide users with useful information.

[0083] In this way, servers, terminals, and users cooperate to provide a consistent and efficient childcare environment.

[0084] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0085] Step 1:

[0086] Users input information about their child's growth, such as age, gender, allergies, and health status, using a dedicated application on the device. This information is verified according to a pre-specified format by the device, and the integrity of the input data is checked. Basic growth parameters are input, and the output is data that has been verified for integrity.

[0087] Step 2:

[0088] The terminal sends verified user input data to the server. This data transmission takes place over the internet, and the server registers the received data in its database. The input consists of growth information submitted by the user, and the output is the information stored in the database. The server also checks for duplicate and missing data during registration.

[0089] Step 3:

[0090] The server uses a generative AI model to create an activity list based on growth information stored in the database. In this process, the data is processed based on age and special notes to select the most suitable activities, and prompts are input into the generative AI model. Based on this, the model outputs a daily and weekly activity list tailored to the child.

[0091] Step 4:

[0092] The server further analyzes the child's health information and generates a nutrition plan. It pays attention to nutrient deficiencies and excesses, using an AI model to create appropriate meal menus. The input is health data, and the output is a nutrition plan tailored to the child. The server also considers combinations of ingredients.

[0093] Step 5:

[0094] The server inputs prompts into the AI ​​model to generate educational content tailored to the educational theme. This results in the output of educational content, including learning materials and games aligned with the specific theme. The input is the educational theme selected by the user, and the output is the educational content provided to the child.

[0095] Step 6:

[0096] The server investigates local childcare support programs and identifies support systems suitable for the user. This investigation uses database searches and takes into account information about the target area. Inputs are local information and user attributes, and output is available childcare support programs.

[0097] Step 7:

[0098] To notify the user, various lists, plans, and content generated by the server are sent to the terminal. The user reviews this content and uses it in actual childcare situations. Various generated items are inputs, and the output is displayed on the user's terminal.

[0099] (Application Example 1)

[0100] 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."

[0101] In recent years, the rise of nuclear families and dual-income households has increased the burden of childcare and the responsibility of managing children's development. Furthermore, the difficulty in obtaining specialized information and appropriate childcare support raises concerns about the impact on children's health and education. Therefore, there is a need for a system that allows parents to efficiently and effectively support their children's development with limited time.

[0102] 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.

[0103] In this invention, the server includes an information input means, a plan generation means, a notification means, a nutrition plan generation means, an educational information generation means, a suggestion means, and a home machine notification means. This makes it possible for parents to efficiently manage their children's growth, health, and education through a home machine, thereby reducing the burden of childcare.

[0104] "Information input means" refers to a device or software for users to input information about their child's growth and health.

[0105] A "plan generation means" is a system or function that automatically creates an activity plan using a generative model based on input growth information.

[0106] "Notification means" refers to technologies and methods for communicating generated activity plans and nutrition plans to users.

[0107] A "nutrition plan generation device" is a device or program that creates a meal plan including nutrients, taking into account the child's age and health information.

[0108] An "educational information generation means" is a system or process for generating educational information appropriate for a child's development based on an educational theme.

[0109] A "proposal tool" refers to a device or system that investigates local childcare support information and presents users with the most suitable support information and systems.

[0110] A "household mechanical notification means" is a function or mechanism that uses household mechanical devices to notify parents in real time about activity plans and nutrition plans.

[0111] This invention is a system designed to allow users to manage their children's development and receive efficient and effective support for childcare. The system utilizes home-use hardware, specifically household appliances, to perform various functions such as data entry, generation, and notification.

[0112] The server analyzes data using a generative AI model based on input information provided by the user. Specifically, it receives growth information and automatically generates daily and weekly activity plans using a plan generation system. The server provides information to the user through a notification system to notify them of the activity plan. The user receives the information via a home device and uses it in their daily childcare.

[0113] Furthermore, the server uses a nutrition plan generation system to create a nutrition plan based on the child's age and health information. This plan is notified to parents in real time via a home-use notification system to support appropriate dietary management. In addition, an educational information generation system generates and provides educational information based on specific educational themes to the user.

[0114] This system will utilize cloud services (e.g., AWS®, Google® Cloud) as servers, and will primarily use Python as the software, implementing AI models with Tensorflow®. The API server will be built using Flask.

[0115] As a concrete example, when providing play plans tailored to a child's development, the system is operated with a prompt message such as, "Based on current childcare information, please suggest today's activity schedule and meal plan." For instance, on a day when exercise is needed, the home device might notify parents in the morning, "It would be good to play in the park today," providing childcare suggestions.

[0116] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0117] Step 1:

[0118] Users use a device to input information about their child's development. This information includes age, health status, and any special notes. This information is sent from the device to a server and stored in a database.

[0119] Step 2:

[0120] The server retrieves growth information from the database and automatically generates daily and weekly activity plans using a generative AI model. The AI ​​model analyzes the input information and lists activities appropriate for each stage of growth. The generated plans are then saved on the server.

[0121] Step 3:

[0122] The server generates an activity plan using a plan generation mechanism and notifies the user through a home-use machine notification mechanism. The terminal receives the notification and displays the activity plan to the parent in real time. Based on the displayed information, the parent plans their daily childcare.

[0123] Step 4:

[0124] The server uses a nutrition plan generation system to generate a nutrition plan based on acquired growth information and health status. The AI ​​model calculates the required amount of nutrients and creates a meal plan based on this. The generated plan is stored on the server and provided to the user via a home-use notification system.

[0125] Step 5:

[0126] The server uses an educational information generation system to generate educational information based on a specific educational theme. The theme is input into an AI model using prompt messages, generating educational content suitable for children. The educational information is then displayed to the user via a terminal.

[0127] Step 6:

[0128] The server collects local childcare support information through suggestion mechanisms and selects the most suitable childcare support system based on the user's local information. The selected information is notified to the user using home electronic notification devices and used to support childcare.

[0129] 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.

[0130] This invention provides a system that incorporates an emotion engine into an AI assistant system for childcare support, thereby offering support that takes into account the user's emotional state. This system functions effectively through data interaction between the server, terminal, and user.

[0131] Users input basic developmental information about their children using their devices and register various information necessary for childcare. This information is sent from the device to the server and stored in a database. The server uses a generative model based on the stored data to create daily and weekly activity lists. These lists reflect the child's developmental stage and home environment, and are designed to support the child's development.

[0132] In addition to generating this activity list, the emotion engine monitors the user's facial expressions and voice, analyzing their emotions in real time. Once the user's emotions are identified, this information is sent to the server, and the activity list and educational content are adjusted accordingly. For example, if the user is feeling stressed, the system will suggest activities that are more likely to have a relaxing effect.

[0133] Furthermore, the server uses nutrition generation tools to create a meal plan suitable for the child. This plan is created based on the child's age and health data, and allergy information is also taken into consideration. The server also uses educational generation tools to provide educational content based on the child's educational themes. This content is adjusted as needed based on the user's emotional state.

[0134] The system proposal mechanism collects information on local childcare support systems and proposes support suitable for the user. By also incorporating a health monitoring mechanism, the server periodically receives health data from the user and analyzes and monitors their health status.

[0135] As a concrete example, the system has a function that suggests effective childcare activities in a short amount of time when it recognizes that the user is feeling busy. It also estimates the user's stress level from their facial expressions and informs them of relaxation methods and support systems as needed. This system, through emotion recognition, can provide more personalized childcare support to the user.

[0136] The following describes the processing flow.

[0137] Step 1:

[0138] Users input information about their child's development via their device. This information includes the child's age, gender, health status, and allergy information.

[0139] Step 2:

[0140] The terminal sends the entered information to the server. A secure protocol is used to ensure data security during this process.

[0141] Step 3:

[0142] The server saves the received data to the database. At the same time, it verifies the integrity and completeness of the information.

[0143] Step 4:

[0144] The emotion engine analyzes the user's facial expressions and voice to identify their emotional state. This allows the system to understand in real time whether the user is stressed or experiencing other emotions.

[0145] Step 5:

[0146] The server uses stored data and emotional information from the emotion engine to run a generative model and generate daily and weekly activity lists. These lists include content tailored to the user's emotional state.

[0147] Step 6:

[0148] The server sends the generated activity list to the terminal. The terminal notifies the user and displays it on the screen.

[0149] Step 7:

[0150] The server analyzes the child's health data and generates a meal plan that takes nutritional balance into consideration. The plan may be adjusted based on emotional information.

[0151] Step 8:

[0152] The server generates a meal plan and sends it to the device, which then notifies the user. The user can then use this to plan their daily meals.

[0153] Step 9:

[0154] The server creates educational content based on educational themes, using a generative model, and incorporates emotional information.

[0155] Step 10:

[0156] The server sends the created educational content to the terminal, and the terminal provides it to the user. The user then uses this content when their child is learning.

[0157] Step 11:

[0158] The server searches a database of local childcare support programs and collects information to identify the program best suited to the user.

[0159] Step 12:

[0160] The server sends system information to the terminal, and the terminal notifies the user. The user can then check the details of the system and how to use it.

[0161] Step 13:

[0162] The device prompts the user to periodically enter health data and manages their progress. Health alerts and medical reminders can be set as needed, with the server providing support.

[0163] Step 14:

[0164] The emotion engine continuously monitors the user's emotional state and makes adjustments that affect the overall system operation.

[0165] (Example 2)

[0166] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0167] In childcare, there is a need to efficiently manage diverse information regarding the development of young people and provide support tailored to individual needs. In particular, it is important to reduce the emotional burden felt by parents while appropriately managing activities and nutrition according to the child's health status and educational needs. However, with conventional methods, information collection and analysis are often done manually, making it difficult to grasp emotions and health status in real time.

[0168] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0169] In this invention, the server includes an information input means, an activity generation means, and an emotion analysis means. This enables the collection of information from the user, the automatic generation of an activity table, and the real-time analysis of the user's emotional state.

[0170] "Information input means" refers to a device or method for receiving information from a user regarding the growth of young people.

[0171] "Activity generation means" refers to a device or method that automatically generates hourly and weekly activity schedules based on growth information of young people using a generation AI model.

[0172] "Information notification means" refers to a device or method for informing users of the generated activity schedule.

[0173] "Nutritional plan generation means" refers to an apparatus or method for creating a meal plan containing appropriate nutrients based on the age and health information of young people.

[0174] "Educational production means" refers to a device or method for creating educational content based on educational themes for young people.

[0175] "System proposal tools" refer to devices or methods for investigating local childcare support systems and proposing systems suitable for users.

[0176] An "emotional analysis tool" is a device or method that analyzes a user's emotional state in real time and reflects it in activity charts or educational content.

[0177] A "health monitoring device" is a device or method that periodically receives health information from users and analyzes it to understand their health status.

[0178] "Information display means" refers to a device or method for showing users the generated activity schedule, meal plan, educational content, and system proposals.

[0179] This invention is an AI assistant system designed to support childcare. The system is based on data interaction between a server, a terminal, and a user. The embodiment of the invention comprises the following specific processes.

[0180] Users input growth and health information of young people using devices such as smartphones and tablets. This information includes age, weight, height, dietary preferences, allergy information, and learning progress. Users fill in this information via a dedicated app and, by answering specific questions, can also provide information based on advanced prompts.

[0181] The terminal then securely transmits the collected information to the server. This process uses encrypted communication technologies such as SSL / TLS. Upon receiving the information, the server stores it in a database and performs the necessary data processing to organize the information.

[0182] The server utilizes a generative AI model based on the received data. The generative AI model creates hourly and weekly activity schedules based on user progress information. These activity schedules include activities tailored to the interests and learning stages of young people, designed to support further growth.

[0183] Furthermore, the server executes emotion analysis tools to perform sentiment analysis. This allows for real-time analysis of the user's emotions and adjustments to activity schedules and educational content as needed. For example, if a user is feeling stressed, activities that are expected to have a relaxation effect will be recommended.

[0184] Furthermore, the server uses a nutritional plan generation system to provide meal plans based on the health information of young people. These plans include a balanced mix of various nutrients and take allergy information into full consideration.

[0185] The server further prepares educational content using educational generation tools, collects information on local childcare support systems, and proposes new systems.

[0186] As a concrete example, users input information such as, "Please tell us more about the young person's physical condition and mood today," or "Please tell us what you've been feeling about their recent dietary imbalances," as prompt messages. This information is used to enhance the system's personalization capabilities and provide more appropriate support.

[0187] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0188] Step 1:

[0189] The user enters information into the device.

[0190] Users input basic growth information, health status, dietary preferences, and learning progress of their children through a dedicated app. This input includes detailed data based on prompts. This input data forms the basis for analyzing growth patterns.

[0191] Step 2:

[0192] The device sends information to the server.

[0193] The terminal encrypts the information collected from the user and sends it to the server using a secure communication protocol (SSL / TLS). The input data includes matters related to emotions, which are used for analysis on the server side.

[0194] Step 3:

[0195] The server saves the data to the database.

[0196] The server classifies the data it receives and stores it in a database. Data processing includes adding metadata and imputing missing values, which allows for smoother subsequent data processing.

[0197] Step 4:

[0198] The server generates an activity table using an AI model.

[0199] The server uses a generative AI model to generate activity schedules tailored to the developmental stages of young people, based on stored growth data. The model organizes activities on a daily and weekly basis, and creates personalized activities as needed. The output provides a detailed schedule including specific activities.

[0200] Step 5:

[0201] The server performs sentiment analysis.

[0202] The server analyzes the user's facial expressions and voice data, and reflects the processed emotional information in the activity log. It identifies the user's emotional state from the input data and visualizes emotions such as stress and anxiety. This analysis is performed by an AI-powered emotion recognition algorithm, and the generated activity log and educational content are adjusted according to the user's emotions.

[0203] Step 6:

[0204] The server generates a meal plan using its nutritional generation function.

[0205] Based on health information and dietary preferences, a nutritionally balanced meal plan is generated. Allergy information is also considered, and an appropriate ingredient list is created. The output provides daily meal recipes and ingredient lists.

[0206] Step 7:

[0207] The server prepares educational content using educational generation tools.

[0208] The server generates appropriate educational content based on the educational themes for young people. This content includes visual aids and audio guides, and is optimized to reflect the results of sentiment analysis. Content is output to support learning objectives.

[0209] Step 8:

[0210] The server submits the policy proposal.

[0211] This system investigates local childcare support programs and proposes programs that meet the user's needs. The collected program information is analyzed in a user-friendly format, and its benefits and usage procedures are summarized. A list of available programs is provided as output.

[0212] Step 9:

[0213] The server analyzes health data using health monitoring tools.

[0214] The server periodically analyzes received health data to detect anomalies and risk factors. Based on the analysis results, alerts and advice for health improvement are generated and notified to the user. The output provides an overview of the health status and recommended actions.

[0215] (Application Example 2)

[0216] 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".

[0217] In child-rearing, a parent's emotional state is a crucial factor influencing the quality of care. When parents are stressed, their interactions with their children and the educational content they provide may not be optimal. To improve this situation, a system is needed that accurately understands parents' emotional states and provides child-rearing support based on that understanding. While suggesting appropriate meals and educational content based on a child's age and health data is also important, the lack of individualized and emotionally responsive adjustments remains a challenge.

[0218] 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.

[0219] In this invention, the server includes emotion recognition means for analyzing the user's emotional state in real time, activity generation means for automatically generating an activity list using a generative model based on growth information and emotional state, and adjustment means for adjusting the activity list, educational materials, and meal plan according to the emotional state. This enables individualized and flexible childcare support that responds to the parent's emotional state.

[0220] An "emotion recognition method" is a means of monitoring a user's facial expressions and voice in real time and analyzing their emotional state.

[0221] A "data input method" is a means for users to input various information related to their child's growth.

[0222] The "activity generation method" is a method that uses a generative model based on input growth information and emotional states to automatically generate daily and weekly activity lists.

[0223] A "notification method" is a means of informing the user of the generated activity list.

[0224] A "nutrition generation method" is a method for generating a meal plan that includes appropriate nutrients, taking into account the child's age and health data.

[0225] "Educational production methods" refer to methods for generating educational materials based on children's educational themes.

[0226] "Methods for proposing systems" refer to methods for researching local childcare support systems and proposing systems that are suitable for users.

[0227] "Adjustment methods" refer to means for appropriately adjusting the activity list, educational materials, and meal plans according to the user's emotional state.

[0228] This invention is a system aimed at supporting child-rearing within the home. It uses an emotion engine to analyze the emotional state of parents in real time and, based on that analysis, proposes activity lists, educational materials, meal plans, and the like.

[0229] The server monitors the user's facial expressions and voice using emotion recognition tools to determine their emotional state. This emotional information is transmitted to the server and stored in a database. Based on the emotional state and the child's growth information entered by the user, the server uses a generative AI model to generate daily and weekly activity lists. The server also uses nutrition generation tools to create meal plans tailored to the child's age and health data. Furthermore, it provides educational materials suitable for the child's educational themes through educational generation tools.

[0230] The system adjusts based on the user's emotional state, appropriately tailoring activity lists, learning materials, and meal plans. This means that when the user is stressed, relaxing activities are recommended, and when they are in a positive emotional state, educational activities are suggested.

[0231] For example, when parents are busy and stressed, the server might suggest relaxation activities such as, "It would be good to set aside time to take a nap with your child." Also, if a smile is detected using emotion recognition technology, it can suggest activities that parents and children can enjoy together.

[0232] Examples of prompts for the generative AI model include, "Please suggest an effective relaxation activity for when the user is feeling stressed," and "Please suggest some fun, short activities that children can do at home."

[0233] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0234] Step 1:

[0235] The user enters their child's growth information into the terminal. This growth information includes age, height, weight, and medical history, and this information is transmitted to the server via the data entry system. This data is stored in a database and becomes the basic information used for subsequent data processing.

[0236] Step 2:

[0237] The server uses a generative model based on growth information obtained from the terminal to generate daily and weekly activity lists. It analyzes the input information and uses an algorithm to select the most suitable activities. The output is a customized activity list tailored to the child's developmental stage.

[0238] Step 3:

[0239] The emotion recognition system monitors the user's facial expressions and voice data transmitted from the terminal and analyzes their emotional state. Inputs include real-time video and audio information acquired by the camera and microphone. Based on this, the system interprets the user's emotional state (e.g., stress, joy, fatigue) and outputs an identification result of that emotional state.

[0240] Step 4:

[0241] The server uses an AI model to generate and refine activity lists, educational materials, and meal plans based on emotional state and growth information. Inputs include the activity list and emotional state identification results from step 2, which are combined to create more personalized suggestions. The output is an activity list, educational materials, and meal plan optimized for the emotional state.

[0242] Step 5:

[0243] The server notifies the terminal of the coordinated activity list, educational materials, and meal plans. Here, the suggestions are communicated directly to the user through the notification system, allowing the user to plan activities and meals with their child based on them. The output is a final suggestion message sent to the user.

[0244] Step 6:

[0245] Users review the notified activity list and meal plan and proceed to the next step. User feedback is sent to the system and used as data to improve the accuracy of future suggestions.

[0246] 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.

[0247] 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.

[0248] 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.

[0249] [Second Embodiment]

[0250] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0251] 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.

[0252] 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).

[0253] 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.

[0254] 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.

[0255] 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).

[0256] 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.

[0257] 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.

[0258] 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.

[0259] 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.

[0260] 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.

[0261] 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".

[0262] This invention is an AI assistant system designed to make it easier for users to manage the growth of their children. This system functions through the exchange of information between a server, a terminal, and the user.

[0263] First, the user enters basic growth information about their child via their device. This information includes the child's age, gender, and any special notes regarding their growth (such as allergies or health conditions). The entered information is sent from the device to the server and stored in a database.

[0264] The server uses a generative model based on the received data to generate daily and weekly activity lists tailored to the child's developmental stage. These generated lists are used to streamline the user's childcare schedule and simplify management. Specific examples include appropriate play and educational activities, and health check-up dates.

[0265] Furthermore, the server analyzes the child's nutritional data and develops a meal plan that includes appropriate nutrients. This plan is notified to the user via their device and can be used to help with daily meal planning. It also provides advice on food selection for children with specific allergies.

[0266] To support education, the server sets specific educational themes and generates educational content using generative models. This content, delivered to users via their devices, helps parents provide their children with an appropriate learning environment.

[0267] In addition, the server searches a local childcare support system database and identifies and suggests suitable programs for the user. This is a particularly useful source of information for working parents and parents who are unfamiliar with childcare systems. The system also periodically prompts users to input health data, and the terminal manages the progress. By including the setting of medical reminders, it aims to ensure thorough health management.

[0268] In this way, this system provides multifaceted support for parents in childcare, realizing an efficient and effective child-rearing environment.

[0269] The following describes the processing flow.

[0270] Step 1:

[0271] Users input information about their child's development via their device. This information includes the child's age, gender, health status, and allergy information.

[0272] Step 2:

[0273] The terminal sends the input information to the server. At this time, a secure protocol is used to ensure the security of the data.

[0274] Step 3:

[0275] The server saves the received data in the database. At the same time, the integrity and completeness of the information are checked and verified.

[0276] Step 4:

[0277] Based on the data saved by the server, the generation model is operated to generate a daily and weekly activity list. This list includes activities and schedules optimal for children.

[0278] Step 5:

[0279] The server sends the generated activity list to the terminal. The terminal notifies the user of it and displays it on the screen.

[0280] Step 6:

[0281] The server analyzes the health data of the child and generates a meal plan considering the balance of nutrients. Allergy information is also reflected to design a safe menu. <00​​​​​​​​​​​​​​​​​​​​​​The server sends the created educational content to the terminal, and the terminal provides it to the user. The user then uses this content when their child is learning.

[0288] Step 10:

[0289] The server searches a database of local childcare support programs and collects information to identify the program best suited to the user.

[0290] Step 11:

[0291] The server sends system information to the terminal, and the terminal notifies the user. The user can then check the details of the system and how to use it.

[0292] Step 12:

[0293] The device prompts the user to periodically enter health data and manages their progress. This allows for the setting of necessary medical reminders and supports health management.

[0294] (Example 1)

[0295] 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."

[0296] Traditional childcare support systems often lack consistency and efficiency because information management, activities, nutrition, and educational content provision are all separate. Furthermore, customization to suit the specific characteristics of individual families and children is difficult, which can be a burden for caregivers. Therefore, there is a need for a system that reduces the user burden and provides a more efficient and effective childcare environment.

[0297] 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.

[0298] In this invention, the server includes data input means for receiving information related to the child's growth from the user, activity plan creation means for creating a time-series activity plan using a generative artificial intelligence model, and communication means for notifying the user of the created plan via communication means. This allows the user to easily receive individually optimized activity lists and nutrition plans, thereby improving the efficiency and effectiveness of childcare.

[0299] A "data input means" is a mechanism for collecting specific information from a user and handling it in a format usable within the system.

[0300] A "generative artificial intelligence model" is an algorithm that automatically generates complex patterns and predictions based on input data, and provides optimal results through a mechanical learning process.

[0301] "Activity planning tools" refer to processes or tools for automatically creating daily or weekly activity lists tailored to a child's developmental stage.

[0302] "Communication means" refers to the infrastructure and technologies used by a system to transmit information and notifications to a user.

[0303] "Nutritional planning methods" refer to the process of creating meal menus that include appropriate nutrients based on a child's age and health information.

[0304] "Educational material generation means" refers to a method or tool for creating new educational content based on a specific theme related to education.

[0305] "Program proposal methods" refer to the process of researching local childcare support programs, identifying programs that are beneficial to users, and guiding them to those programs.

[0306] The system of the present invention is a smart system that supports parents in efficiently managing the growth of their children. This system is constructed around the exchange and processing of information among a server, a terminal, and a user. Specifically, it is realized by using the following hardware and software.

[0307] First, the user uses the terminal at hand to input the basic growth information of the child. This terminal includes smartphones and tablets. The dedicated application installed on the terminal verifies the data input by the user and then transmits the data to the server via the Internet.

[0308] The server analyzes the received data and saves it in the database. A cloud-based server solution is suitable for the server used here. Next, based on the saved data, the server uses the generated AI model to create an appropriate activity plan and nutrition plan according to the child's age and health condition.

[0309] Taking a specific example, the server inputs a prompt sentence of "a 3-year-old girl without allergies", and the generated AI model outputs activities such as "playing in the sandbox and reading picture books" as a recommended list. Also, considering the health information, the server automatically creates a nutrition plan. As materials, it lists recipes considering nutritional balance and notifies the user via the application.

[0310] Furthermore, as educational support, the server generates educational content along a specific educational theme and also provides it to the user through the terminal. For example, it creates an educational game themed on "learning numbers" for preschool children, and the child can learn through this game. It is also possible to investigate the local childcare support system and provide useful information to the user.

[0311] In this way, by the cooperation of the server, the terminal, and the user, a consistent and efficient childcare environment is provided.

[0312] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0313] Step 1:

[0314] Users input information about their child's growth, such as age, gender, allergies, and health status, using a dedicated application on the device. This information is verified according to a pre-specified format by the device, and the integrity of the input data is checked. Basic growth parameters are input, and the output is data that has been verified for integrity.

[0315] Step 2:

[0316] The terminal sends verified user input data to the server. This data transmission takes place over the internet, and the server registers the received data in its database. The input consists of growth information submitted by the user, and the output is the information stored in the database. The server also checks for duplicate and missing data during registration.

[0317] Step 3:

[0318] The server uses a generative AI model to create an activity list based on growth information stored in the database. In this process, the data is processed based on age and special notes to select the most suitable activities, and prompts are input into the generative AI model. Based on this, the model outputs a daily and weekly activity list tailored to the child.

[0319] Step 4:

[0320] The server further analyzes the child's health information and generates a nutrition plan. It pays attention to nutrient deficiencies and excesses, using an AI model to create appropriate meal menus. The input is health data, and the output is a nutrition plan tailored to the child. The server also considers combinations of ingredients.

[0321] Step 5:

[0322] The server inputs prompts into the AI ​​model to generate educational content tailored to the educational theme. This results in the output of educational content, including learning materials and games aligned with the specific theme. The input is the educational theme selected by the user, and the output is the educational content provided to the child.

[0323] Step 6:

[0324] The server investigates local childcare support programs and identifies support systems suitable for the user. This investigation uses database searches and takes into account information about the target area. Inputs are local information and user attributes, and output is available childcare support programs.

[0325] Step 7:

[0326] To notify the user, various lists, plans, and content generated by the server are sent to the terminal. The user reviews this content and uses it in actual childcare situations. Various generated items are inputs, and the output is displayed on the user's terminal.

[0327] (Application Example 1)

[0328] 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."

[0329] In recent years, the rise of nuclear families and dual-income households has increased the burden of childcare and the responsibility of managing children's development. Furthermore, the difficulty in obtaining specialized information and appropriate childcare support raises concerns about the impact on children's health and education. Therefore, there is a need for a system that allows parents to efficiently and effectively support their children's development with limited time.

[0330] 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.

[0331] In this invention, the server includes an information input means, a plan generation means, a notification means, a nutrition plan generation means, an educational information generation means, a suggestion means, and a home machine notification means. This makes it possible for parents to efficiently manage their children's growth, health, and education through a home machine, thereby reducing the burden of childcare.

[0332] "Information input means" refers to a device or software for users to input information about their child's growth and health.

[0333] A "plan generation means" is a system or function that automatically creates an activity plan using a generative model based on input growth information.

[0334] "Notification means" refers to technologies and methods for communicating generated activity plans and nutrition plans to users.

[0335] A "nutrition plan generation device" is a device or program that creates a meal plan including nutrients, taking into account the child's age and health information.

[0336] An "educational information generation means" is a system or process for generating educational information appropriate for a child's development based on an educational theme.

[0337] A "proposal tool" refers to a device or system that investigates local childcare support information and presents users with the most suitable support information and systems.

[0338] A "household mechanical notification means" is a function or mechanism that uses household mechanical devices to notify parents in real time about activity plans and nutrition plans.

[0339] This invention is a system designed to allow users to manage their children's development and receive efficient and effective support for childcare. The system utilizes home-use hardware, specifically household appliances, to perform various functions such as data entry, generation, and notification.

[0340] The server analyzes data using a generative AI model based on input information provided by the user. Specifically, it receives growth information and automatically generates daily and weekly activity plans using a plan generation system. The server provides information to the user through a notification system to notify them of the activity plan. The user receives the information via a home device and uses it in their daily childcare.

[0341] Furthermore, the server uses a nutrition plan generation system to create a nutrition plan based on the child's age and health information. This plan is notified to parents in real time via a home-use notification system to support appropriate dietary management. In addition, an educational information generation system generates and provides educational information based on specific educational themes to the user.

[0342] This system will utilize cloud services (e.g., AWS, Google Cloud) as servers, and the software will primarily use Python, with AI models implemented using TensorFlow. The API server will be built using Flask.

[0343] As a concrete example, when providing play plans tailored to a child's development, the system is operated with a prompt message such as, "Based on current childcare information, please suggest today's activity schedule and meal plan." For instance, on a day when exercise is needed, the home device might notify parents in the morning, "It would be good to play in the park today," providing childcare suggestions.

[0344] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0345] Step 1:

[0346] Users use a device to input information about their child's development. This information includes age, health status, and any special notes. This information is sent from the device to a server and stored in a database.

[0347] Step 2:

[0348] The server retrieves growth information from the database and automatically generates daily and weekly activity plans using a generative AI model. The AI ​​model analyzes the input information and lists activities appropriate for each stage of growth. The generated plans are then saved on the server.

[0349] Step 3:

[0350] The server generates an activity plan using a plan generation mechanism and notifies the user through a home-use machine notification mechanism. The terminal receives the notification and displays the activity plan to the parent in real time. Based on the displayed information, the parent plans their daily childcare.

[0351] Step 4:

[0352] The server uses a nutrition plan generation system to generate a nutrition plan based on acquired growth information and health status. The AI ​​model calculates the required amount of nutrients and creates a meal plan based on this. The generated plan is stored on the server and provided to the user via a home-use notification system.

[0353] Step 5:

[0354] The server uses an educational information generation system to generate educational information based on a specific educational theme. The theme is input into an AI model using prompt messages, generating educational content suitable for children. The educational information is then displayed to the user via a terminal.

[0355] Step 6:

[0356] The server collects local childcare support information through suggestion mechanisms and selects the most suitable childcare support system based on the user's local information. The selected information is notified to the user using home electronic notification devices and used to support childcare.

[0357] 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.

[0358] This invention provides a system that incorporates an emotion engine into an AI assistant system for childcare support, thereby offering support that takes into account the user's emotional state. This system functions effectively through data interaction between the server, terminal, and user.

[0359] Users input basic developmental information about their children using their devices and register various information necessary for childcare. This information is sent from the device to the server and stored in a database. The server uses a generative model based on the stored data to create daily and weekly activity lists. These lists reflect the child's developmental stage and home environment, and are designed to support the child's development.

[0360] In addition to generating this activity list, the emotion engine monitors the user's facial expressions and voice, analyzing their emotions in real time. Once the user's emotions are identified, this information is sent to the server, and the activity list and educational content are adjusted accordingly. For example, if the user is feeling stressed, the system will suggest activities that are more likely to have a relaxing effect.

[0361] Furthermore, the server uses nutrition generation tools to create a meal plan suitable for the child. This plan is created based on the child's age and health data, and allergy information is also taken into consideration. The server also uses educational generation tools to provide educational content based on the child's educational themes. This content is adjusted as needed based on the user's emotional state.

[0362] The system proposal mechanism collects information on local childcare support systems and proposes support suitable for the user. By also incorporating a health monitoring mechanism, the server periodically receives health data from the user and analyzes and monitors their health status.

[0363] As a concrete example, the system has a function that suggests effective childcare activities in a short amount of time when it recognizes that the user is feeling busy. It also estimates the user's stress level from their facial expressions and informs them of relaxation methods and support systems as needed. This system, through emotion recognition, can provide more personalized childcare support to the user.

[0364] The following describes the processing flow.

[0365] Step 1:

[0366] Users input information about their child's development via their device. This information includes the child's age, gender, health status, and allergy information.

[0367] Step 2:

[0368] The terminal sends the entered information to the server. A secure protocol is used to ensure data security during this process.

[0369] Step 3:

[0370] The server saves the received data to the database. At the same time, it verifies the integrity and completeness of the information.

[0371] Step 4:

[0372] The emotion engine analyzes the user's facial expressions and voice to identify their emotional state. This allows the system to understand in real time whether the user is stressed or experiencing other emotions.

[0373] Step 5:

[0374] The server uses stored data and emotional information from the emotion engine to run a generative model and generate daily and weekly activity lists. These lists include content tailored to the user's emotional state.

[0375] Step 6:

[0376] The server sends the generated activity list to the terminal. The terminal notifies the user and displays it on the screen.

[0377] Step 7:

[0378] The server analyzes the child's health data and generates a meal plan that takes nutritional balance into consideration. The plan may be adjusted based on emotional information.

[0379] Step 8:

[0380] The server generates a meal plan and sends it to the device, which then notifies the user. The user can then use this to plan their daily meals.

[0381] Step 9:

[0382] The server creates educational content based on educational themes, using a generative model, and incorporates emotional information.

[0383] Step 10:

[0384] The server sends the created educational content to the terminal, and the terminal provides it to the user. The user then uses this content when their child is learning.

[0385] Step 11:

[0386] The server searches a database of local childcare support programs and collects information to identify the program best suited to the user.

[0387] Step 12:

[0388] The server sends system information to the terminal, and the terminal notifies the user. The user can then check the details of the system and how to use it.

[0389] Step 13:

[0390] The device prompts the user to periodically enter health data and manages their progress. Health alerts and medical reminders can be set as needed, with the server providing support.

[0391] Step 14:

[0392] The emotion engine continuously monitors the user's emotional state and makes adjustments that affect the overall system operation.

[0393] (Example 2)

[0394] 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".

[0395] In childcare, there is a need to efficiently manage diverse information regarding the development of young people and provide support tailored to individual needs. In particular, it is important to reduce the emotional burden felt by parents while appropriately managing activities and nutrition according to the child's health status and educational needs. However, with conventional methods, information collection and analysis are often done manually, making it difficult to grasp emotions and health status in real time.

[0396] 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.

[0397] In this invention, the server includes an information input means, an activity generation means, and an emotion analysis means. This enables the collection of information from the user, the automatic generation of an activity table, and the real-time analysis of the user's emotional state.

[0398] "Information input means" refers to a device or method for receiving information from a user regarding the growth of young people.

[0399] "Activity generation means" refers to a device or method that automatically generates hourly and weekly activity schedules based on growth information of young people using a generation AI model.

[0400] "Information notification means" refers to a device or method for informing users of the generated activity schedule.

[0401] "Nutritional plan generation means" refers to an apparatus or method for creating a meal plan containing appropriate nutrients based on the age and health information of young people.

[0402] "Educational production means" refers to a device or method for creating educational content based on educational themes for young people.

[0403] "System proposal tools" refer to devices or methods for investigating local childcare support systems and proposing systems suitable for users.

[0404] An "emotional analysis tool" is a device or method that analyzes a user's emotional state in real time and reflects it in activity charts or educational content.

[0405] A "health monitoring device" is a device or method that periodically receives health information from users and analyzes it to understand their health status.

[0406] "Information display means" refers to a device or method for showing users the generated activity schedule, meal plan, educational content, and system proposals.

[0407] This invention is an AI assistant system designed to support childcare. The system is based on data interaction between a server, a terminal, and a user. The embodiment of the invention comprises the following specific processes.

[0408] Users input growth and health information of young people using devices such as smartphones and tablets. This information includes age, weight, height, dietary preferences, allergy information, and learning progress. Users fill in this information via a dedicated app and, by answering specific questions, can also provide information based on advanced prompts.

[0409] The terminal then securely transmits the collected information to the server. This process uses encrypted communication technologies such as SSL / TLS. Upon receiving the information, the server stores it in a database and performs the necessary data processing to organize the information.

[0410] The server utilizes a generative AI model based on the received data. The generative AI model creates hourly and weekly activity schedules based on user progress information. These activity schedules include activities tailored to the interests and learning stages of young people, designed to support further growth.

[0411] Furthermore, the server executes emotion analysis tools to perform sentiment analysis. This allows for real-time analysis of the user's emotions and adjustments to activity schedules and educational content as needed. For example, if a user is feeling stressed, activities that are expected to have a relaxation effect will be recommended.

[0412] Furthermore, the server uses a nutritional plan generation system to provide meal plans based on the health information of young people. These plans include a balanced mix of various nutrients and take allergy information into full consideration.

[0413] The server further prepares educational content using educational generation tools, collects information on local childcare support systems, and proposes new systems.

[0414] As a concrete example, users input information such as, "Please tell us more about the young person's physical condition and mood today," or "Please tell us what you've been feeling about their recent dietary imbalances," as prompt messages. This information is used to enhance the system's personalization capabilities and provide more appropriate support.

[0415] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0416] Step 1:

[0417] The user enters information into the device.

[0418] Users input basic growth information, health status, dietary preferences, and learning progress of their children through a dedicated app. This input includes detailed data based on prompts. This input data forms the basis for analyzing growth patterns.

[0419] Step 2:

[0420] The device sends information to the server.

[0421] The terminal encrypts the information collected from the user and sends it to the server using a secure communication protocol (SSL / TLS). The input data includes matters related to emotions, which are used for analysis on the server side.

[0422] Step 3:

[0423] The server saves the data to the database.

[0424] The server classifies the data it receives and stores it in a database. Data processing includes adding metadata and imputing missing values, which allows for smoother subsequent data processing.

[0425] Step 4:

[0426] The server generates an activity table using an AI model.

[0427] The server uses a generative AI model to generate activity schedules tailored to the developmental stages of young people, based on stored growth data. The model organizes activities on a daily and weekly basis, and creates personalized activities as needed. The output provides a detailed schedule including specific activities.

[0428] Step 5:

[0429] The server performs sentiment analysis.

[0430] The server analyzes the user's facial expressions and voice data, and reflects the processed emotional information in the activity log. It identifies the user's emotional state from the input data and visualizes emotions such as stress and anxiety. This analysis is performed by an AI-powered emotion recognition algorithm, and the generated activity log and educational content are adjusted according to the user's emotions.

[0431] Step 6:

[0432] The server generates a meal plan using its nutritional generation function.

[0433] Based on health information and dietary preferences, a nutritionally balanced meal plan is generated. Allergy information is also considered, and an appropriate ingredient list is created. The output provides daily meal recipes and ingredient lists.

[0434] Step 7:

[0435] The server prepares educational content using educational generation tools.

[0436] The server generates appropriate educational content based on the educational themes for young people. This content includes visual aids and audio guides, and is optimized to reflect the results of sentiment analysis. Content is output to support learning objectives.

[0437] Step 8:

[0438] The server submits the policy proposal.

[0439] This system investigates local childcare support programs and proposes programs that meet the user's needs. The collected program information is analyzed in a user-friendly format, and its benefits and usage procedures are summarized. A list of available programs is provided as output.

[0440] Step 9:

[0441] The server analyzes health data using health monitoring tools.

[0442] The server periodically analyzes received health data to detect anomalies and risk factors. Based on the analysis results, alerts and advice for health improvement are generated and notified to the user. The output provides an overview of the health status and recommended actions.

[0443] (Application Example 2)

[0444] 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."

[0445] In child-rearing, a parent's emotional state is a crucial factor influencing the quality of care. When parents are stressed, their interactions with their children and the educational content they provide may not be optimal. To improve this situation, a system is needed that accurately understands parents' emotional states and provides child-rearing support based on that understanding. While suggesting appropriate meals and educational content based on a child's age and health data is also important, the lack of individualized and emotionally responsive adjustments remains a challenge.

[0446] 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.

[0447] In this invention, the server includes emotion recognition means for analyzing the user's emotional state in real time, activity generation means for automatically generating an activity list using a generative model based on growth information and emotional state, and adjustment means for adjusting the activity list, educational materials, and meal plan according to the emotional state. This enables individualized and flexible childcare support that responds to the parent's emotional state.

[0448] An "emotion recognition method" is a means of monitoring a user's facial expressions and voice in real time and analyzing their emotional state.

[0449] A "data input method" is a means for users to input various information related to their child's growth.

[0450] The "activity generation method" is a method that uses a generative model based on input growth information and emotional states to automatically generate daily and weekly activity lists.

[0451] A "notification method" is a means of informing the user of the generated activity list.

[0452] A "nutrition generation method" is a method for generating a meal plan that includes appropriate nutrients, taking into account the child's age and health data.

[0453] "Educational production methods" refer to methods for generating educational materials based on children's educational themes.

[0454] "Methods for proposing systems" refer to methods for researching local childcare support systems and proposing systems that are suitable for users.

[0455] "Adjustment methods" refer to means for appropriately adjusting the activity list, educational materials, and meal plans according to the user's emotional state.

[0456] This invention is a system aimed at supporting child-rearing within the home. It uses an emotion engine to analyze the emotional state of parents in real time and, based on that analysis, proposes activity lists, educational materials, meal plans, and the like.

[0457] The server monitors the user's facial expressions and voice using emotion recognition tools to determine their emotional state. This emotional information is transmitted to the server and stored in a database. Based on the emotional state and the child's growth information entered by the user, the server uses a generative AI model to generate daily and weekly activity lists. The server also uses nutrition generation tools to create meal plans tailored to the child's age and health data. Furthermore, it provides educational materials suitable for the child's educational themes through educational generation tools.

[0458] The system adjusts based on the user's emotional state, appropriately tailoring activity lists, learning materials, and meal plans. This means that when the user is stressed, relaxing activities are recommended, and when they are in a positive emotional state, educational activities are suggested.

[0459] For example, when parents are busy and stressed, the server might suggest relaxation activities such as, "It would be good to set aside time to take a nap with your child." Also, if a smile is detected using emotion recognition technology, it can suggest activities that parents and children can enjoy together.

[0460] Examples of prompts for the generative AI model include, "Please suggest an effective relaxation activity for when the user is feeling stressed," and "Please suggest some fun, short activities that children can do at home."

[0461] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0462] Step 1:

[0463] The user enters their child's growth information into the terminal. This growth information includes age, height, weight, and medical history, and this information is transmitted to the server via the data entry system. This data is stored in a database and becomes the basic information used for subsequent data processing.

[0464] Step 2:

[0465] The server uses a generative model based on growth information obtained from the terminal to generate daily and weekly activity lists. It analyzes the input information and uses an algorithm to select the most suitable activities. The output is a customized activity list tailored to the child's developmental stage.

[0466] Step 3:

[0467] The emotion recognition system monitors the user's facial expressions and voice data transmitted from the terminal and analyzes their emotional state. Inputs include real-time video and audio information acquired by the camera and microphone. Based on this, the system interprets the user's emotional state (e.g., stress, joy, fatigue) and outputs an identification result of that emotional state.

[0468] Step 4:

[0469] The server uses an AI model to generate and refine activity lists, educational materials, and meal plans based on emotional state and growth information. Inputs include the activity list and emotional state identification results from step 2, which are combined to create more personalized suggestions. The output is an activity list, educational materials, and meal plan optimized for the emotional state.

[0470] Step 5:

[0471] The server notifies the terminal of the coordinated activity list, educational materials, and meal plans. Here, the suggestions are communicated directly to the user through the notification system, allowing the user to plan activities and meals with their child based on them. The output is a final suggestion message sent to the user.

[0472] Step 6:

[0473] Users review the notified activity list and meal plan and proceed to the next step. User feedback is sent to the system and used as data to improve the accuracy of future suggestions.

[0474] 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.

[0475] 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.

[0476] 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.

[0477] [Third Embodiment]

[0478] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0479] 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.

[0480] 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).

[0481] 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.

[0482] 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.

[0483] 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).

[0484] 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.

[0485] 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.

[0486] 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.

[0487] 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.

[0488] 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.

[0489] 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".

[0490] This invention is an AI assistant system designed to make it easier for users to manage the growth of their children. This system functions through the exchange of information between a server, a terminal, and the user.

[0491] First, the user enters basic growth information about their child via their device. This information includes the child's age, gender, and any special notes regarding their growth (such as allergies or health conditions). The entered information is sent from the device to the server and stored in a database.

[0492] The server uses a generative model based on the received data to generate daily and weekly activity lists tailored to the child's developmental stage. These generated lists are used to streamline the user's childcare schedule and simplify management. Specific examples include appropriate play and educational activities, and health check-up dates.

[0493] Furthermore, the server analyzes the child's nutritional data and develops a meal plan that includes appropriate nutrients. This plan is notified to the user via their device and can be used to help with daily meal planning. It also provides advice on food selection for children with specific allergies.

[0494] To support education, the server sets specific educational themes and generates educational content using generative models. This content, delivered to users via their devices, helps parents provide their children with an appropriate learning environment.

[0495] In addition, the server searches a local childcare support system database and identifies and suggests suitable programs for the user. This is a particularly useful source of information for working parents and parents who are unfamiliar with childcare systems. The system also periodically prompts users to input health data, and the terminal manages the progress. By including the setting of medical reminders, it aims to ensure thorough health management.

[0496] In this way, this system provides multifaceted support for parents in childcare, realizing an efficient and effective child-rearing environment.

[0497] The following describes the processing flow.

[0498] Step 1:

[0499] Users input information about their child's development via their device. This information includes the child's age, gender, health status, and allergy information.

[0500] Step 2:

[0501] The terminal sends the entered information to the server. A secure protocol is used to ensure data security during this process.

[0502] Step 3:

[0503] The server saves the received data to the database. At the same time, it verifies the integrity and completeness of the information.

[0504] Step 4:

[0505] The server uses stored data to run a generative model that generates daily and weekly activity lists. These lists include activities and schedules that are optimal for the child.

[0506] Step 5:

[0507] The server sends the generated activity list to the terminal. The terminal notifies the user and displays it on the screen.

[0508] Step 6:

[0509] The server analyzes children's health data and generates meal plans that consider nutritional balance. It also incorporates allergy information to design safe menus.

[0510] Step 7:

[0511] The server generates a meal plan and sends it to the device, which then notifies the user. The user can then use this to plan their daily meals.

[0512] Step 8:

[0513] The server creates educational content based on educational themes using a generative model.

[0514] Step 9:

[0515] The server sends the created educational content to the terminal, and the terminal provides it to the user. The user then uses this content when their child is learning.

[0516] Step 10:

[0517] The server searches a database of local childcare support programs and collects information to identify the program best suited to the user.

[0518] Step 11:

[0519] The server sends system information to the terminal, and the terminal notifies the user. The user can then check the details of the system and how to use it.

[0520] Step 12:

[0521] The device prompts the user to periodically enter health data and manages their progress. This allows for the setting of necessary medical reminders and supports health management.

[0522] (Example 1)

[0523] 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."

[0524] Traditional childcare support systems often lack consistency and efficiency because information management, activities, nutrition, and educational content provision are all separate. Furthermore, customization to suit the specific characteristics of individual families and children is difficult, which can be a burden for caregivers. Therefore, there is a need for a system that reduces the user burden and provides a more efficient and effective childcare environment.

[0525] 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.

[0526] In this invention, the server includes data input means for receiving information related to the child's growth from the user, activity plan creation means for creating a time-series activity plan using a generative artificial intelligence model, and communication means for notifying the user of the created plan via communication means. This allows the user to easily receive individually optimized activity lists and nutrition plans, thereby improving the efficiency and effectiveness of childcare.

[0527] A "data input means" is a mechanism for collecting specific information from a user and handling it in a format usable within the system.

[0528] A "generative artificial intelligence model" is an algorithm that automatically generates complex patterns and predictions based on input data, and provides optimal results through a mechanical learning process.

[0529] "Activity planning tools" refer to processes or tools for automatically creating daily or weekly activity lists tailored to a child's developmental stage.

[0530] "Communication means" refers to the infrastructure and technologies used by a system to transmit information and notifications to a user.

[0531] "Nutritional planning methods" refer to the process of creating meal menus that include appropriate nutrients based on a child's age and health information.

[0532] "Educational material generation means" refers to a method or tool for creating new educational content based on a specific theme related to education.

[0533] "Program proposal methods" refer to the process of researching local childcare support programs, identifying programs that are beneficial to users, and guiding them to those programs.

[0534] The present invention is a smart system that supports parents in efficiently managing the growth of their children. This system is built around the exchange and processing of information between a server, a terminal, and a user. Specifically, it is implemented using the following hardware and software.

[0535] First, the user enters basic growth information about their child using their device. This device includes smartphones and tablets. A dedicated application installed on the device verifies the data entered by the user and then sends the data to the server via the internet.

[0536] The server analyzes the received data and stores it in a database. A cloud-based server solution is suitable for this purpose. Next, the server uses a generative AI model based on the stored data to create appropriate activity and nutrition plans tailored to the child's age and health condition.

[0537] For example, the server takes the prompt "3-year-old girl with no allergies" as input, and the generating AI model outputs a list of recommended activities such as "playing in the sandbox, reading picture books." Furthermore, the server automatically creates a nutritional plan, taking health information into consideration. The plan includes a list of recipes that consider nutritional balance, which are then notified to the user via the application.

[0538] Furthermore, the server provides educational support by generating educational content aligned with specific educational themes and delivering it to users via their devices. For example, it can create educational games on the theme of "learning numbers" for preschool children, allowing them to learn through these games. It can also research local childcare support systems and provide users with useful information.

[0539] In this way, servers, terminals, and users cooperate to provide a consistent and efficient childcare environment.

[0540] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0541] Step 1:

[0542] Users input information about their child's growth, such as age, gender, allergies, and health status, using a dedicated application on the device. This information is verified according to a pre-specified format by the device, and the integrity of the input data is checked. Basic growth parameters are input, and the output is data that has been verified for integrity.

[0543] Step 2:

[0544] The terminal sends verified user input data to the server. This data transmission takes place over the internet, and the server registers the received data in its database. The input consists of growth information submitted by the user, and the output is the information stored in the database. The server also checks for duplicate and missing data during registration.

[0545] Step 3:

[0546] The server uses a generative AI model to create an activity list based on growth information stored in the database. In this process, the data is processed based on age and special notes to select the most suitable activities, and prompts are input into the generative AI model. Based on this, the model outputs a daily and weekly activity list tailored to the child.

[0547] Step 4:

[0548] The server further analyzes the child's health information and generates a nutrition plan. It pays attention to nutrient deficiencies and excesses, using an AI model to create appropriate meal menus. The input is health data, and the output is a nutrition plan tailored to the child. The server also considers combinations of ingredients.

[0549] Step 5:

[0550] The server inputs prompts into the AI ​​model to generate educational content tailored to the educational theme. This results in the output of educational content, including learning materials and games aligned with the specific theme. The input is the educational theme selected by the user, and the output is the educational content provided to the child.

[0551] Step 6:

[0552] The server investigates local childcare support programs and identifies support systems suitable for the user. This investigation uses database searches and takes into account information about the target area. Inputs are local information and user attributes, and output is available childcare support programs.

[0553] Step 7:

[0554] To notify the user, various lists, plans, and content generated by the server are sent to the terminal. The user reviews this content and uses it in actual childcare situations. Various generated items are inputs, and the output is displayed on the user's terminal.

[0555] (Application Example 1)

[0556] 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."

[0557] In recent years, the rise of nuclear families and dual-income households has increased the burden of childcare and the responsibility of managing children's development. Furthermore, the difficulty in obtaining specialized information and appropriate childcare support raises concerns about the impact on children's health and education. Therefore, there is a need for a system that allows parents to efficiently and effectively support their children's development with limited time.

[0558] 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.

[0559] In this invention, the server includes an information input means, a plan generation means, a notification means, a nutrition plan generation means, an educational information generation means, a suggestion means, and a home machine notification means. This makes it possible for parents to efficiently manage their children's growth, health, and education through a home machine, thereby reducing the burden of childcare.

[0560] "Information input means" refers to a device or software for users to input information about their child's growth and health.

[0561] A "plan generation means" is a system or function that automatically creates an activity plan using a generative model based on input growth information.

[0562] "Notification means" refers to technologies and methods for communicating generated activity plans and nutrition plans to users.

[0563] A "nutrition plan generation device" is a device or program that creates a meal plan including nutrients, taking into account the child's age and health information.

[0564] An "educational information generation means" is a system or process for generating educational information appropriate for a child's development based on an educational theme.

[0565] A "proposal tool" refers to a device or system that investigates local childcare support information and presents users with the most suitable support information and systems.

[0566] A "household mechanical notification means" is a function or mechanism that uses household mechanical devices to notify parents in real time about activity plans and nutrition plans.

[0567] This invention is a system designed to allow users to manage their children's development and receive efficient and effective support for childcare. The system utilizes home-use hardware, specifically household appliances, to perform various functions such as data entry, generation, and notification.

[0568] The server analyzes data using a generative AI model based on input information provided by the user. Specifically, it receives growth information and automatically generates daily and weekly activity plans using a plan generation system. The server provides information to the user through a notification system to notify them of the activity plan. The user receives the information via a home device and uses it in their daily childcare.

[0569] Furthermore, the server uses a nutrition plan generation system to create a nutrition plan based on the child's age and health information. This plan is notified to parents in real time via a home-use notification system to support appropriate dietary management. In addition, an educational information generation system generates and provides educational information based on specific educational themes to the user.

[0570] This system will utilize cloud services (e.g., AWS, Google Cloud) as servers, and the software will primarily use Python, with AI models implemented using TensorFlow. The API server will be built using Flask.

[0571] As a concrete example, when providing play plans tailored to a child's development, the system is operated with a prompt message such as, "Based on current childcare information, please suggest today's activity schedule and meal plan." For instance, on a day when exercise is needed, the home device might notify parents in the morning, "It would be good to play in the park today," providing childcare suggestions.

[0572] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0573] Step 1:

[0574] Users use a device to input information about their child's development. This information includes age, health status, and any special notes. This information is sent from the device to a server and stored in a database.

[0575] Step 2:

[0576] The server retrieves growth information from the database and automatically generates daily and weekly activity plans using a generative AI model. The AI ​​model analyzes the input information and lists activities appropriate for each stage of growth. The generated plans are then saved on the server.

[0577] Step 3:

[0578] The server generates an activity plan using a plan generation mechanism and notifies the user through a home-use machine notification mechanism. The terminal receives the notification and displays the activity plan to the parent in real time. Based on the displayed information, the parent plans their daily childcare.

[0579] Step 4:

[0580] The server uses a nutrition plan generation system to generate a nutrition plan based on acquired growth information and health status. The AI ​​model calculates the required amount of nutrients and creates a meal plan based on this. The generated plan is stored on the server and provided to the user via a home-use notification system.

[0581] Step 5:

[0582] The server uses an educational information generation system to generate educational information based on a specific educational theme. The theme is input into an AI model using prompt messages, generating educational content suitable for children. The educational information is then displayed to the user via a terminal.

[0583] Step 6:

[0584] The server collects local childcare support information through suggestion mechanisms and selects the most suitable childcare support system based on the user's local information. The selected information is notified to the user using home electronic notification devices and used to support childcare.

[0585] 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.

[0586] This invention provides a system that incorporates an emotion engine into an AI assistant system for childcare support, thereby offering support that takes into account the user's emotional state. This system functions effectively through data interaction between the server, terminal, and user.

[0587] Users input basic developmental information about their children using their devices and register various information necessary for childcare. This information is sent from the device to the server and stored in a database. The server uses a generative model based on the stored data to create daily and weekly activity lists. These lists reflect the child's developmental stage and home environment, and are designed to support the child's development.

[0588] In addition to generating this activity list, the emotion engine monitors the user's facial expressions and voice, analyzing their emotions in real time. Once the user's emotions are identified, this information is sent to the server, and the activity list and educational content are adjusted accordingly. For example, if the user is feeling stressed, the system will suggest activities that are more likely to have a relaxing effect.

[0589] Furthermore, the server uses nutrition generation tools to create a meal plan suitable for the child. This plan is created based on the child's age and health data, and allergy information is also taken into consideration. The server also uses educational generation tools to provide educational content based on the child's educational themes. This content is adjusted as needed based on the user's emotional state.

[0590] The system proposal mechanism collects information on local childcare support systems and proposes support suitable for the user. By also incorporating a health monitoring mechanism, the server periodically receives health data from the user and analyzes and monitors their health status.

[0591] As a concrete example, the system has a function that suggests effective childcare activities in a short amount of time when it recognizes that the user is feeling busy. It also estimates the user's stress level from their facial expressions and informs them of relaxation methods and support systems as needed. This system, through emotion recognition, can provide more personalized childcare support to the user.

[0592] The following describes the processing flow.

[0593] Step 1:

[0594] Users input information about their child's development via their device. This information includes the child's age, gender, health status, and allergy information.

[0595] Step 2:

[0596] The terminal sends the entered information to the server. A secure protocol is used to ensure data security during this process.

[0597] Step 3:

[0598] The server saves the received data to the database. At the same time, it verifies the integrity and completeness of the information.

[0599] Step 4:

[0600] The emotion engine analyzes the user's facial expressions and voice to identify their emotional state. This allows the system to understand in real time whether the user is stressed or experiencing other emotions.

[0601] Step 5:

[0602] The server uses stored data and emotional information from the emotion engine to run a generative model and generate daily and weekly activity lists. These lists include content tailored to the user's emotional state.

[0603] Step 6:

[0604] The server sends the generated activity list to the terminal. The terminal notifies the user and displays it on the screen.

[0605] Step 7:

[0606] The server analyzes the child's health data and generates a meal plan that takes nutritional balance into consideration. The plan may be adjusted based on emotional information.

[0607] Step 8:

[0608] The server generates a meal plan and sends it to the device, which then notifies the user. The user can then use this to plan their daily meals.

[0609] Step 9:

[0610] The server creates educational content based on educational themes, using a generative model, and incorporates emotional information.

[0611] Step 10:

[0612] The server sends the created educational content to the terminal, and the terminal provides it to the user. The user then uses this content when their child is learning.

[0613] Step 11:

[0614] The server searches a database of local childcare support programs and collects information to identify the program best suited to the user.

[0615] Step 12:

[0616] The server sends system information to the terminal, and the terminal notifies the user. The user can then check the details of the system and how to use it.

[0617] Step 13:

[0618] The device prompts the user to periodically enter health data and manages their progress. Health alerts and medical reminders can be set as needed, with the server providing support.

[0619] Step 14:

[0620] The emotion engine continuously monitors the user's emotional state and makes adjustments that affect the overall system operation.

[0621] (Example 2)

[0622] 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."

[0623] In childcare, there is a need to efficiently manage diverse information regarding the development of young people and provide support tailored to individual needs. In particular, it is important to reduce the emotional burden felt by parents while appropriately managing activities and nutrition according to the child's health status and educational needs. However, with conventional methods, information collection and analysis are often done manually, making it difficult to grasp emotions and health status in real time.

[0624] 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.

[0625] In this invention, the server includes an information input means, an activity generation means, and an emotion analysis means. This enables the collection of information from the user, the automatic generation of an activity table, and the real-time analysis of the user's emotional state.

[0626] "Information input means" refers to a device or method for receiving information from a user regarding the growth of young people.

[0627] "Activity generation means" refers to a device or method that automatically generates hourly and weekly activity schedules based on growth information of young people using a generation AI model.

[0628] "Information notification means" refers to a device or method for informing users of the generated activity schedule.

[0629] "Nutritional plan generation means" refers to an apparatus or method for creating a meal plan containing appropriate nutrients based on the age and health information of young people.

[0630] "Educational production means" refers to a device or method for creating educational content based on educational themes for young people.

[0631] "System proposal tools" refer to devices or methods for investigating local childcare support systems and proposing systems suitable for users.

[0632] An "emotional analysis tool" is a device or method that analyzes a user's emotional state in real time and reflects it in activity charts or educational content.

[0633] A "health monitoring device" is a device or method that periodically receives health information from users and analyzes it to understand their health status.

[0634] "Information display means" refers to a device or method for showing users the generated activity schedule, meal plan, educational content, and system proposals.

[0635] This invention is an AI assistant system designed to support childcare. The system is based on data interaction between a server, a terminal, and a user. The embodiment of the invention comprises the following specific processes.

[0636] Users input growth and health information of young people using devices such as smartphones and tablets. This information includes age, weight, height, dietary preferences, allergy information, and learning progress. Users fill in this information via a dedicated app and, by answering specific questions, can also provide information based on advanced prompts.

[0637] The terminal then securely transmits the collected information to the server. This process uses encrypted communication technologies such as SSL / TLS. Upon receiving the information, the server stores it in a database and performs the necessary data processing to organize the information.

[0638] The server utilizes a generative AI model based on the received data. The generative AI model creates hourly and weekly activity schedules based on user progress information. These activity schedules include activities tailored to the interests and learning stages of young people, designed to support further growth.

[0639] Furthermore, the server executes emotion analysis tools to perform sentiment analysis. This allows for real-time analysis of the user's emotions and adjustments to activity schedules and educational content as needed. For example, if a user is feeling stressed, activities that are expected to have a relaxation effect will be recommended.

[0640] Furthermore, the server uses a nutritional plan generation system to provide meal plans based on the health information of young people. These plans include a balanced mix of various nutrients and take allergy information into full consideration.

[0641] The server further prepares educational content using educational generation tools, collects information on local childcare support systems, and proposes new systems.

[0642] As a concrete example, users input information such as, "Please tell us more about the young person's physical condition and mood today," or "Please tell us what you've been feeling about their recent dietary imbalances," as prompt messages. This information is used to enhance the system's personalization capabilities and provide more appropriate support.

[0643] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0644] Step 1:

[0645] The user enters information into the device.

[0646] Users input basic growth information, health status, dietary preferences, and learning progress of their children through a dedicated app. This input includes detailed data based on prompts. This input data forms the basis for analyzing growth patterns.

[0647] Step 2:

[0648] The device sends information to the server.

[0649] The terminal encrypts the information collected from the user and sends it to the server using a secure communication protocol (SSL / TLS). The input data includes matters related to emotions, which are used for analysis on the server side.

[0650] Step 3:

[0651] The server saves the data to the database.

[0652] The server classifies the data it receives and stores it in a database. Data processing includes adding metadata and imputing missing values, which allows for smoother subsequent data processing.

[0653] Step 4:

[0654] The server generates an activity table using an AI model.

[0655] The server uses a generative AI model to generate activity schedules tailored to the developmental stages of young people, based on stored growth data. The model organizes activities on a daily and weekly basis, and creates personalized activities as needed. The output provides a detailed schedule including specific activities.

[0656] Step 5:

[0657] The server performs sentiment analysis.

[0658] The server analyzes the user's facial expressions and voice data, and reflects the processed emotional information in the activity log. It identifies the user's emotional state from the input data and visualizes emotions such as stress and anxiety. This analysis is performed by an AI-powered emotion recognition algorithm, and the generated activity log and educational content are adjusted according to the user's emotions.

[0659] Step 6:

[0660] The server generates a meal plan using its nutritional generation function.

[0661] Based on health information and dietary preferences, a nutritionally balanced meal plan is generated. Allergy information is also considered, and an appropriate ingredient list is created. The output provides daily meal recipes and ingredient lists.

[0662] Step 7:

[0663] The server prepares educational content using educational generation tools.

[0664] The server generates appropriate educational content based on the educational themes for young people. This content includes visual aids and audio guides, and is optimized to reflect the results of sentiment analysis. Content is output to support learning objectives.

[0665] Step 8:

[0666] The server submits the policy proposal.

[0667] This system investigates local childcare support programs and proposes programs that meet the user's needs. The collected program information is analyzed in a user-friendly format, and its benefits and usage procedures are summarized. A list of available programs is provided as output.

[0668] Step 9:

[0669] The server analyzes health data using health monitoring tools.

[0670] The server periodically analyzes received health data to detect anomalies and risk factors. Based on the analysis results, alerts and advice for health improvement are generated and notified to the user. The output provides an overview of the health status and recommended actions.

[0671] (Application Example 2)

[0672] 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."

[0673] In child-rearing, a parent's emotional state is a crucial factor influencing the quality of care. When parents are stressed, their interactions with their children and the educational content they provide may not be optimal. To improve this situation, a system is needed that accurately understands parents' emotional states and provides child-rearing support based on that understanding. While suggesting appropriate meals and educational content based on a child's age and health data is also important, the lack of individualized and emotionally responsive adjustments remains a challenge.

[0674] 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.

[0675] In this invention, the server includes emotion recognition means for analyzing the user's emotional state in real time, activity generation means for automatically generating an activity list using a generative model based on growth information and emotional state, and adjustment means for adjusting the activity list, educational materials, and meal plan according to the emotional state. This enables individualized and flexible childcare support that responds to the parent's emotional state.

[0676] An "emotion recognition method" is a means of monitoring a user's facial expressions and voice in real time and analyzing their emotional state.

[0677] A "data input method" is a means for users to input various information related to their child's growth.

[0678] The "activity generation method" is a method that uses a generative model based on input growth information and emotional states to automatically generate daily and weekly activity lists.

[0679] A "notification method" is a means of informing the user of the generated activity list.

[0680] A "nutrition generation method" is a method for generating a meal plan that includes appropriate nutrients, taking into account the child's age and health data.

[0681] "Educational production methods" refer to methods for generating educational materials based on children's educational themes.

[0682] "Methods for proposing systems" refer to methods for researching local childcare support systems and proposing systems that are suitable for users.

[0683] "Adjustment methods" refer to means for appropriately adjusting the activity list, educational materials, and meal plans according to the user's emotional state.

[0684] This invention is a system aimed at supporting child-rearing within the home. It uses an emotion engine to analyze the emotional state of parents in real time and, based on that analysis, proposes activity lists, educational materials, meal plans, and the like.

[0685] The server monitors the user's facial expressions and voice using emotion recognition tools to determine their emotional state. This emotional information is transmitted to the server and stored in a database. Based on the emotional state and the child's growth information entered by the user, the server uses a generative AI model to generate daily and weekly activity lists. The server also uses nutrition generation tools to create meal plans tailored to the child's age and health data. Furthermore, it provides educational materials suitable for the child's educational themes through educational generation tools.

[0686] The system adjusts based on the user's emotional state, appropriately tailoring activity lists, learning materials, and meal plans. This means that when the user is stressed, relaxing activities are recommended, and when they are in a positive emotional state, educational activities are suggested.

[0687] For example, when parents are busy and stressed, the server might suggest relaxation activities such as, "It would be good to set aside time to take a nap with your child." Also, if a smile is detected using emotion recognition technology, it can suggest activities that parents and children can enjoy together.

[0688] Examples of prompts for the generative AI model include, "Please suggest an effective relaxation activity for when the user is feeling stressed," and "Please suggest some fun, short activities that children can do at home."

[0689] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0690] Step 1:

[0691] The user enters their child's growth information into the terminal. This growth information includes age, height, weight, and medical history, and this information is transmitted to the server via the data entry system. This data is stored in a database and becomes the basic information used for subsequent data processing.

[0692] Step 2:

[0693] The server uses a generative model based on growth information obtained from the terminal to generate daily and weekly activity lists. It analyzes the input information and uses an algorithm to select the most suitable activities. The output is a customized activity list tailored to the child's developmental stage.

[0694] Step 3:

[0695] The emotion recognition system monitors the user's facial expressions and voice data transmitted from the terminal and analyzes their emotional state. Inputs include real-time video and audio information acquired by the camera and microphone. Based on this, the system interprets the user's emotional state (e.g., stress, joy, fatigue) and outputs an identification result of that emotional state.

[0696] Step 4:

[0697] The server uses an AI model to generate and refine activity lists, educational materials, and meal plans based on emotional state and growth information. Inputs include the activity list and emotional state identification results from step 2, which are combined to create more personalized suggestions. The output is an activity list, educational materials, and meal plan optimized for the emotional state.

[0698] Step 5:

[0699] The server notifies the terminal of the coordinated activity list, educational materials, and meal plans. Here, the suggestions are communicated directly to the user through the notification system, allowing the user to plan activities and meals with their child based on them. The output is a final suggestion message sent to the user.

[0700] Step 6:

[0701] Users review the notified activity list and meal plan and proceed to the next step. User feedback is sent to the system and used as data to improve the accuracy of future suggestions.

[0702] 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.

[0703] 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.

[0704] 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.

[0705] [Fourth Embodiment]

[0706] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0707] 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.

[0708] 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).

[0709] 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.

[0710] 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.

[0711] 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).

[0712] 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.

[0713] 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.

[0714] 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.

[0715] 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.

[0716] 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.

[0717] 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.

[0718] 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".

[0719] This invention is an AI assistant system designed to make it easier for users to manage the growth of their children. This system functions through the exchange of information between a server, a terminal, and the user.

[0720] First, the user enters basic growth information about their child via their device. This information includes the child's age, gender, and any special notes regarding their growth (such as allergies or health conditions). The entered information is sent from the device to the server and stored in a database.

[0721] The server uses a generative model based on the received data to generate daily and weekly activity lists tailored to the child's developmental stage. These generated lists are used to streamline the user's childcare schedule and simplify management. Specific examples include appropriate play and educational activities, and health check-up dates.

[0722] Furthermore, the server analyzes the child's nutritional data and develops a meal plan that includes appropriate nutrients. This plan is notified to the user via their device and can be used to help with daily meal planning. It also provides advice on food selection for children with specific allergies.

[0723] To support education, the server sets specific educational themes and generates educational content using generative models. This content, delivered to users via their devices, helps parents provide their children with an appropriate learning environment.

[0724] In addition, the server searches a local childcare support system database and identifies and suggests suitable programs for the user. This is a particularly useful source of information for working parents and parents who are unfamiliar with childcare systems. The system also periodically prompts users to input health data, and the terminal manages the progress. By including the setting of medical reminders, it aims to ensure thorough health management.

[0725] In this way, this system provides multifaceted support for parents in childcare, realizing an efficient and effective child-rearing environment.

[0726] The following describes the processing flow.

[0727] Step 1:

[0728] Users input information about their child's development via their device. This information includes the child's age, gender, health status, and allergy information.

[0729] Step 2:

[0730] The terminal sends the entered information to the server. A secure protocol is used to ensure data security during this process.

[0731] Step 3:

[0732] The server saves the received data to the database. At the same time, it verifies the integrity and completeness of the information.

[0733] Step 4:

[0734] The server uses stored data to run a generative model that generates daily and weekly activity lists. These lists include activities and schedules that are optimal for the child.

[0735] Step 5:

[0736] The server sends the generated activity list to the terminal. The terminal notifies the user and displays it on the screen.

[0737] Step 6:

[0738] The server analyzes children's health data and generates meal plans that consider nutritional balance. It also incorporates allergy information to design safe menus.

[0739] Step 7:

[0740] The server generates a meal plan and sends it to the device, which then notifies the user. The user can then use this to plan their daily meals.

[0741] Step 8:

[0742] The server creates educational content based on educational themes using a generative model.

[0743] Step 9:

[0744] The server sends the created educational content to the terminal, and the terminal provides it to the user. The user then uses this content when their child is learning.

[0745] Step 10:

[0746] The server searches a database of local childcare support programs and collects information to identify the program best suited to the user.

[0747] Step 11:

[0748] The server sends system information to the terminal, and the terminal notifies the user. The user can then check the details of the system and how to use it.

[0749] Step 12:

[0750] The device prompts the user to periodically enter health data and manages their progress. This allows for the setting of necessary medical reminders and supports health management.

[0751] (Example 1)

[0752] 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".

[0753] Traditional childcare support systems often lack consistency and efficiency because information management, activities, nutrition, and educational content provision are all separate. Furthermore, customization to suit the specific characteristics of individual families and children is difficult, which can be a burden for caregivers. Therefore, there is a need for a system that reduces the user burden and provides a more efficient and effective childcare environment.

[0754] 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.

[0755] In this invention, the server includes data input means for receiving information related to the child's growth from the user, activity plan creation means for creating a time-series activity plan using a generative artificial intelligence model, and communication means for notifying the user of the created plan via communication means. This allows the user to easily receive individually optimized activity lists and nutrition plans, thereby improving the efficiency and effectiveness of childcare.

[0756] A "data input means" is a mechanism for collecting specific information from a user and handling it in a format usable within the system.

[0757] A "generative artificial intelligence model" is an algorithm that automatically generates complex patterns and predictions based on input data, and provides optimal results through a mechanical learning process.

[0758] "Activity planning tools" refer to processes or tools for automatically creating daily or weekly activity lists tailored to a child's developmental stage.

[0759] "Communication means" refers to the infrastructure and technologies used by a system to transmit information and notifications to a user.

[0760] "Nutritional planning methods" refer to the process of creating meal menus that include appropriate nutrients based on a child's age and health information.

[0761] "Educational material generation means" refers to a method or tool for creating new educational content based on a specific theme related to education.

[0762] "Program proposal methods" refer to the process of researching local childcare support programs, identifying programs that are beneficial to users, and guiding them to those programs.

[0763] The present invention is a smart system that supports parents in efficiently managing the growth of their children. This system is built around the exchange and processing of information between a server, a terminal, and a user. Specifically, it is implemented using the following hardware and software.

[0764] First, the user enters basic growth information about their child using their device. This device includes smartphones and tablets. A dedicated application installed on the device verifies the data entered by the user and then sends the data to the server via the internet.

[0765] The server analyzes the received data and stores it in a database. A cloud-based server solution is suitable for this purpose. Next, the server uses a generative AI model based on the stored data to create appropriate activity and nutrition plans tailored to the child's age and health condition.

[0766] For example, the server takes the prompt "3-year-old girl with no allergies" as input, and the generating AI model outputs a list of recommended activities such as "playing in the sandbox, reading picture books." Furthermore, the server automatically creates a nutritional plan, taking health information into consideration. The plan includes a list of recipes that consider nutritional balance, which are then notified to the user via the application.

[0767] Furthermore, the server provides educational support by generating educational content aligned with specific educational themes and delivering it to users via their devices. For example, it can create educational games on the theme of "learning numbers" for preschool children, allowing them to learn through these games. It can also research local childcare support systems and provide users with useful information.

[0768] In this way, servers, terminals, and users cooperate to provide a consistent and efficient childcare environment.

[0769] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0770] Step 1:

[0771] Users input information about their child's growth, such as age, gender, allergies, and health status, using a dedicated application on the device. This information is verified according to a pre-specified format by the device, and the integrity of the input data is checked. Basic growth parameters are input, and the output is data that has been verified for integrity.

[0772] Step 2:

[0773] The terminal sends verified user input data to the server. This data transmission takes place over the internet, and the server registers the received data in its database. The input consists of growth information submitted by the user, and the output is the information stored in the database. The server also checks for duplicate and missing data during registration.

[0774] Step 3:

[0775] The server uses a generative AI model to create an activity list based on growth information stored in the database. In this process, the data is processed based on age and special notes to select the most suitable activities, and prompts are input into the generative AI model. Based on this, the model outputs a daily and weekly activity list tailored to the child.

[0776] Step 4:

[0777] The server further analyzes the child's health information and generates a nutrition plan. It pays attention to nutrient deficiencies and excesses, using an AI model to create appropriate meal menus. The input is health data, and the output is a nutrition plan tailored to the child. The server also considers combinations of ingredients.

[0778] Step 5:

[0779] The server inputs prompts into the AI ​​model to generate educational content tailored to the educational theme. This results in the output of educational content, including learning materials and games aligned with the specific theme. The input is the educational theme selected by the user, and the output is the educational content provided to the child.

[0780] Step 6:

[0781] The server investigates local childcare support programs and identifies support systems suitable for the user. This investigation uses database searches and takes into account information about the target area. Inputs are local information and user attributes, and output is available childcare support programs.

[0782] Step 7:

[0783] To notify the user, various lists, plans, and content generated by the server are sent to the terminal. The user reviews this content and uses it in actual childcare situations. Various generated items are inputs, and the output is displayed on the user's terminal.

[0784] (Application Example 1)

[0785] 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".

[0786] In recent years, the rise of nuclear families and dual-income households has increased the burden of childcare and the responsibility of managing children's development. Furthermore, the difficulty in obtaining specialized information and appropriate childcare support raises concerns about the impact on children's health and education. Therefore, there is a need for a system that allows parents to efficiently and effectively support their children's development with limited time.

[0787] 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.

[0788] In this invention, the server includes an information input means, a plan generation means, a notification means, a nutrition plan generation means, an educational information generation means, a suggestion means, and a home machine notification means. This makes it possible for parents to efficiently manage their children's growth, health, and education through a home machine, thereby reducing the burden of childcare.

[0789] "Information input means" refers to a device or software for users to input information about their child's growth and health.

[0790] A "plan generation means" is a system or function that automatically creates an activity plan using a generative model based on input growth information.

[0791] "Notification means" refers to technologies and methods for communicating generated activity plans and nutrition plans to users.

[0792] A "nutrition plan generation device" is a device or program that creates a meal plan including nutrients, taking into account the child's age and health information.

[0793] An "educational information generation means" is a system or process for generating educational information appropriate for a child's development based on an educational theme.

[0794] A "proposal tool" refers to a device or system that investigates local childcare support information and presents users with the most suitable support information and systems.

[0795] A "household mechanical notification means" is a function or mechanism that uses household mechanical devices to notify parents in real time about activity plans and nutrition plans.

[0796] This invention is a system designed to allow users to manage their children's development and receive efficient and effective support for childcare. The system utilizes home-use hardware, specifically household appliances, to perform various functions such as data entry, generation, and notification.

[0797] The server analyzes data using a generative AI model based on input information provided by the user. Specifically, it receives growth information and automatically generates daily and weekly activity plans using a plan generation system. The server provides information to the user through a notification system to notify them of the activity plan. The user receives the information via a home device and uses it in their daily childcare.

[0798] Furthermore, the server uses a nutrition plan generation system to create a nutrition plan based on the child's age and health information. This plan is notified to parents in real time via a home-use notification system to support appropriate dietary management. In addition, an educational information generation system generates and provides educational information based on specific educational themes to the user.

[0799] This system will utilize cloud services (e.g., AWS, Google Cloud) as servers, and the software will primarily use Python, with AI models implemented using TensorFlow. The API server will be built using Flask.

[0800] As a concrete example, when providing play plans tailored to a child's development, the system is operated with a prompt message such as, "Based on current childcare information, please suggest today's activity schedule and meal plan." For instance, on a day when exercise is needed, the home device might notify parents in the morning, "It would be good to play in the park today," providing childcare suggestions.

[0801] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0802] Step 1:

[0803] Users use a device to input information about their child's development. This information includes age, health status, and any special notes. This information is sent from the device to a server and stored in a database.

[0804] Step 2:

[0805] The server retrieves growth information from the database and automatically generates daily and weekly activity plans using a generative AI model. The AI ​​model analyzes the input information and lists activities appropriate for each stage of growth. The generated plans are then saved on the server.

[0806] Step 3:

[0807] The server generates an activity plan using a plan generation mechanism and notifies the user through a home-use machine notification mechanism. The terminal receives the notification and displays the activity plan to the parent in real time. Based on the displayed information, the parent plans their daily childcare.

[0808] Step 4:

[0809] The server uses a nutrition plan generation system to generate a nutrition plan based on acquired growth information and health status. The AI ​​model calculates the required amount of nutrients and creates a meal plan based on this. The generated plan is stored on the server and provided to the user via a home-use notification system.

[0810] Step 5:

[0811] The server uses an educational information generation system to generate educational information based on a specific educational theme. The theme is input into an AI model using prompt messages, generating educational content suitable for children. The educational information is then displayed to the user via a terminal.

[0812] Step 6:

[0813] The server collects local childcare support information through suggestion mechanisms and selects the most suitable childcare support system based on the user's local information. The selected information is notified to the user using home electronic notification devices and used to support childcare.

[0814] 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.

[0815] This invention provides a system that incorporates an emotion engine into an AI assistant system for childcare support, thereby offering support that takes into account the user's emotional state. This system functions effectively through data interaction between the server, terminal, and user.

[0816] Users input basic developmental information about their children using their devices and register various information necessary for childcare. This information is sent from the device to the server and stored in a database. The server uses a generative model based on the stored data to create daily and weekly activity lists. These lists reflect the child's developmental stage and home environment, and are designed to support the child's development.

[0817] In addition to generating this activity list, the emotion engine monitors the user's facial expressions and voice, analyzing their emotions in real time. Once the user's emotions are identified, this information is sent to the server, and the activity list and educational content are adjusted accordingly. For example, if the user is feeling stressed, the system will suggest activities that are more likely to have a relaxing effect.

[0818] Furthermore, the server uses nutrition generation tools to create a meal plan suitable for the child. This plan is created based on the child's age and health data, and allergy information is also taken into consideration. The server also uses educational generation tools to provide educational content based on the child's educational themes. This content is adjusted as needed based on the user's emotional state.

[0819] The system proposal mechanism collects information on local childcare support systems and proposes support suitable for the user. By also incorporating a health monitoring mechanism, the server periodically receives health data from the user and analyzes and monitors their health status.

[0820] As a concrete example, the system has a function that suggests effective childcare activities in a short amount of time when it recognizes that the user is feeling busy. It also estimates the user's stress level from their facial expressions and informs them of relaxation methods and support systems as needed. This system, through emotion recognition, can provide more personalized childcare support to the user.

[0821] The following describes the processing flow.

[0822] Step 1:

[0823] Users input information about their child's development via their device. This information includes the child's age, gender, health status, and allergy information.

[0824] Step 2:

[0825] The terminal sends the entered information to the server. A secure protocol is used to ensure data security during this process.

[0826] Step 3:

[0827] The server saves the received data to the database. At the same time, it verifies the integrity and completeness of the information.

[0828] Step 4:

[0829] The emotion engine analyzes the user's facial expressions and voice to identify their emotional state. This allows the system to understand in real time whether the user is stressed or experiencing other emotions.

[0830] Step 5:

[0831] The server uses stored data and emotional information from the emotion engine to run a generative model and generate daily and weekly activity lists. These lists include content tailored to the user's emotional state.

[0832] Step 6:

[0833] The server sends the generated activity list to the terminal. The terminal notifies the user and displays it on the screen.

[0834] Step 7:

[0835] The server analyzes the child's health data and generates a meal plan that takes nutritional balance into consideration. The plan may be adjusted based on emotional information.

[0836] Step 8:

[0837] The server generates a meal plan and sends it to the device, which then notifies the user. The user can then use this to plan their daily meals.

[0838] Step 9:

[0839] The server creates educational content based on educational themes, using a generative model, and incorporates emotional information.

[0840] Step 10:

[0841] The server sends the created educational content to the terminal, and the terminal provides it to the user. The user then uses this content when their child is learning.

[0842] Step 11:

[0843] The server searches a database of local childcare support programs and collects information to identify the program best suited to the user.

[0844] Step 12:

[0845] The server sends system information to the terminal, and the terminal notifies the user. The user can then check the details of the system and how to use it.

[0846] Step 13:

[0847] The device prompts the user to periodically enter health data and manages their progress. Health alerts and medical reminders can be set as needed, with the server providing support.

[0848] Step 14:

[0849] The emotion engine continuously monitors the user's emotional state and makes adjustments that affect the overall system operation.

[0850] (Example 2)

[0851] 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".

[0852] In childcare, there is a need to efficiently manage diverse information regarding the development of young people and provide support tailored to individual needs. In particular, it is important to reduce the emotional burden felt by parents while appropriately managing activities and nutrition according to the child's health status and educational needs. However, with conventional methods, information collection and analysis are often done manually, making it difficult to grasp emotions and health status in real time.

[0853] 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.

[0854] In this invention, the server includes an information input means, an activity generation means, and an emotion analysis means. This enables the collection of information from the user, the automatic generation of an activity table, and the real-time analysis of the user's emotional state.

[0855] "Information input means" refers to a device or method for receiving information from a user regarding the growth of young people.

[0856] "Activity generation means" refers to a device or method that automatically generates hourly and weekly activity schedules based on growth information of young people using a generation AI model.

[0857] "Information notification means" refers to a device or method for informing users of the generated activity schedule.

[0858] "Nutritional plan generation means" refers to an apparatus or method for creating a meal plan containing appropriate nutrients based on the age and health information of young people.

[0859] "Educational production means" refers to a device or method for creating educational content based on educational themes for young people.

[0860] "System proposal tools" refer to devices or methods for investigating local childcare support systems and proposing systems suitable for users.

[0861] An "emotional analysis tool" is a device or method that analyzes a user's emotional state in real time and reflects it in activity charts or educational content.

[0862] A "health monitoring device" is a device or method that periodically receives health information from users and analyzes it to understand their health status.

[0863] "Information display means" refers to a device or method for showing users the generated activity schedule, meal plan, educational content, and system proposals.

[0864] This invention is an AI assistant system designed to support childcare. The system is based on data interaction between a server, a terminal, and a user. The embodiment of the invention comprises the following specific processes.

[0865] Users input growth and health information of young people using devices such as smartphones and tablets. This information includes age, weight, height, dietary preferences, allergy information, and learning progress. Users fill in this information via a dedicated app and, by answering specific questions, can also provide information based on advanced prompts.

[0866] The terminal then securely transmits the collected information to the server. This process uses encrypted communication technologies such as SSL / TLS. Upon receiving the information, the server stores it in a database and performs the necessary data processing to organize the information.

[0867] The server utilizes a generative AI model based on the received data. The generative AI model creates hourly and weekly activity schedules based on user progress information. These activity schedules include activities tailored to the interests and learning stages of young people, designed to support further growth.

[0868] Furthermore, the server executes emotion analysis tools to perform sentiment analysis. This allows for real-time analysis of the user's emotions and adjustments to activity schedules and educational content as needed. For example, if a user is feeling stressed, activities that are expected to have a relaxation effect will be recommended.

[0869] Furthermore, the server uses a nutritional plan generation system to provide meal plans based on the health information of young people. These plans include a balanced mix of various nutrients and take allergy information into full consideration.

[0870] The server further prepares educational content using educational generation tools, collects information on local childcare support systems, and proposes new systems.

[0871] As a concrete example, users input information such as, "Please tell us more about the young person's physical condition and mood today," or "Please tell us what you've been feeling about their recent dietary imbalances," as prompt messages. This information is used to enhance the system's personalization capabilities and provide more appropriate support.

[0872] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0873] Step 1:

[0874] The user enters information into the device.

[0875] Users input basic growth information, health status, dietary preferences, and learning progress of their children through a dedicated app. This input includes detailed data based on prompts. This input data forms the basis for analyzing growth patterns.

[0876] Step 2:

[0877] The device sends information to the server.

[0878] The terminal encrypts the information collected from the user and sends it to the server using a secure communication protocol (SSL / TLS). The input data includes matters related to emotions, which are used for analysis on the server side.

[0879] Step 3:

[0880] The server saves the data to the database.

[0881] The server classifies the data it receives and stores it in a database. Data processing includes adding metadata and imputing missing values, which allows for smoother subsequent data processing.

[0882] Step 4:

[0883] The server generates an activity table using an AI model.

[0884] The server uses a generative AI model to generate activity schedules tailored to the developmental stages of young people, based on stored growth data. The model organizes activities on a daily and weekly basis, and creates personalized activities as needed. The output provides a detailed schedule including specific activities.

[0885] Step 5:

[0886] The server performs sentiment analysis.

[0887] The server analyzes the user's facial expressions and voice data, and reflects the processed emotional information in the activity log. It identifies the user's emotional state from the input data and visualizes emotions such as stress and anxiety. This analysis is performed by an AI-powered emotion recognition algorithm, and the generated activity log and educational content are adjusted according to the user's emotions.

[0888] Step 6:

[0889] The server generates a meal plan using its nutritional generation function.

[0890] Based on health information and dietary preferences, a nutritionally balanced meal plan is generated. Allergy information is also considered, and an appropriate ingredient list is created. The output provides daily meal recipes and ingredient lists.

[0891] Step 7:

[0892] The server prepares educational content using educational generation tools.

[0893] The server generates appropriate educational content based on the educational themes for young people. This content includes visual aids and audio guides, and is optimized to reflect the results of sentiment analysis. Content is output to support learning objectives.

[0894] Step 8:

[0895] The server submits the policy proposal.

[0896] This system investigates local childcare support programs and proposes programs that meet the user's needs. The collected program information is analyzed in a user-friendly format, and its benefits and usage procedures are summarized. A list of available programs is provided as output.

[0897] Step 9:

[0898] The server analyzes health data using health monitoring tools.

[0899] The server periodically analyzes received health data to detect anomalies and risk factors. Based on the analysis results, alerts and advice for health improvement are generated and notified to the user. The output provides an overview of the health status and recommended actions.

[0900] (Application Example 2)

[0901] 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".

[0902] In child-rearing, a parent's emotional state is a crucial factor influencing the quality of care. When parents are stressed, their interactions with their children and the educational content they provide may not be optimal. To improve this situation, a system is needed that accurately understands parents' emotional states and provides child-rearing support based on that understanding. While suggesting appropriate meals and educational content based on a child's age and health data is also important, the lack of individualized and emotionally responsive adjustments remains a challenge.

[0903] 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.

[0904] In this invention, the server includes emotion recognition means for analyzing the user's emotional state in real time, activity generation means for automatically generating an activity list using a generative model based on growth information and emotional state, and adjustment means for adjusting the activity list, educational materials, and meal plan according to the emotional state. This enables individualized and flexible childcare support that responds to the parent's emotional state.

[0905] An "emotion recognition method" is a means of monitoring a user's facial expressions and voice in real time and analyzing their emotional state.

[0906] A "data input method" is a means for users to input various information related to their child's growth.

[0907] The "activity generation method" is a method that uses a generative model based on input growth information and emotional states to automatically generate daily and weekly activity lists.

[0908] A "notification method" is a means of informing the user of the generated activity list.

[0909] A "nutrition generation method" is a method for generating a meal plan that includes appropriate nutrients, taking into account the child's age and health data.

[0910] "Educational production methods" refer to methods for generating educational materials based on children's educational themes.

[0911] "Methods for proposing systems" refer to methods for researching local childcare support systems and proposing systems that are suitable for users.

[0912] "Adjustment methods" refer to means for appropriately adjusting the activity list, educational materials, and meal plans according to the user's emotional state.

[0913] This invention is a system aimed at supporting child-rearing within the home. It uses an emotion engine to analyze the emotional state of parents in real time and, based on that analysis, proposes activity lists, educational materials, meal plans, and the like.

[0914] The server monitors the user's facial expressions and voice using emotion recognition tools to determine their emotional state. This emotional information is transmitted to the server and stored in a database. Based on the emotional state and the child's growth information entered by the user, the server uses a generative AI model to generate daily and weekly activity lists. The server also uses nutrition generation tools to create meal plans tailored to the child's age and health data. Furthermore, it provides educational materials suitable for the child's educational themes through educational generation tools.

[0915] The system adjusts based on the user's emotional state, appropriately tailoring activity lists, learning materials, and meal plans. This means that when the user is stressed, relaxing activities are recommended, and when they are in a positive emotional state, educational activities are suggested.

[0916] For example, when parents are busy and stressed, the server might suggest relaxation activities such as, "It would be good to set aside time to take a nap with your child." Also, if a smile is detected using emotion recognition technology, it can suggest activities that parents and children can enjoy together.

[0917] Examples of prompts for the generative AI model include, "Please suggest an effective relaxation activity for when the user is feeling stressed," and "Please suggest some fun, short activities that children can do at home."

[0918] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0919] Step 1:

[0920] The user enters their child's growth information into the terminal. This growth information includes age, height, weight, and medical history, and this information is transmitted to the server via the data entry system. This data is stored in a database and becomes the basic information used for subsequent data processing.

[0921] Step 2:

[0922] The server uses a generative model based on growth information obtained from the terminal to generate daily and weekly activity lists. It analyzes the input information and uses an algorithm to select the most suitable activities. The output is a customized activity list tailored to the child's developmental stage.

[0923] Step 3:

[0924] The emotion recognition system monitors the user's facial expressions and voice data transmitted from the terminal and analyzes their emotional state. Inputs include real-time video and audio information acquired by the camera and microphone. Based on this, the system interprets the user's emotional state (e.g., stress, joy, fatigue) and outputs an identification result of that emotional state.

[0925] Step 4:

[0926] The server uses an AI model to generate and refine activity lists, educational materials, and meal plans based on emotional state and growth information. Inputs include the activity list and emotional state identification results from step 2, which are combined to create more personalized suggestions. The output is an activity list, educational materials, and meal plan optimized for the emotional state.

[0927] Step 5:

[0928] The server notifies the terminal of the coordinated activity list, educational materials, and meal plans. Here, the suggestions are communicated directly to the user through the notification system, allowing the user to plan activities and meals with their child based on them. The output is a final suggestion message sent to the user.

[0929] Step 6:

[0930] Users review the notified activity list and meal plan and proceed to the next step. User feedback is sent to the system and used as data to improve the accuracy of future suggestions.

[0931] 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.

[0932] 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.

[0933] 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.

[0934] 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.

[0935] 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.

[0936] 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.

[0937] 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.

[0938] 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.

[0939] 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."

[0940] 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.

[0941] 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.

[0942] 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.

[0943] 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.

[0944] 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.

[0945] 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.

[0946] 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.

[0947] 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.

[0948] 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.

[0949] 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.

[0950] 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.

[0951] 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.

[0952] The following is further disclosed regarding the embodiments described above.

[0953] (Claim 1)

[0954] A data input method for users to input information about their child's growth,

[0955] Based on the growth information described above, an activity generation means automatically generates daily and weekly activity lists using a generative model,

[0956] A notification method for informing the user of the generated activity list,

[0957] A nutrition generation method that generates a meal plan containing appropriate nutrients based on a child's age and health data,

[0958] An educational generation method that generates educational content based on children's educational themes,

[0959] A system that includes a system proposal tool that investigates local childcare support systems and suggests suitable systems to users.

[0960] (Claim 2)

[0961] The system according to claim 1, further comprising a health monitoring means for periodically receiving and analyzing health data from a user to monitor their health status.

[0962] (Claim 3)

[0963] The system according to claim 1, further comprising a display means for integrally displaying the generated activity list, meal plan, educational content, and institutional proposals.

[0964] "Example 1"

[0965] (Claim 1)

[0966] A data input method for receiving information related to a child's growth from a user,

[0967] An activity planning means that uses a generative artificial intelligence model based on the above information to create a time-series activity plan,

[0968] A communication means for notifying the user of the created activity plan via a communication means,

[0969] A nutritional planning method that creates a nutritionally balanced meal plan considering the child's age function and health data,

[0970] An educational material generation method for generating educational materials based on educational themes,

[0971] A system that includes a program suggestion mechanism that surveys local childcare support programs and proposes identified programs to users.

[0972] (Claim 2)

[0973] The system according to claim 1, further comprising a health status monitoring means for monitoring the user's health status by periodically receiving and analyzing health-related information from the user.

[0974] (Claim 3)

[0975] The system according to claim 1, further comprising display means for integrating and displaying the generated activity plans, meal plans, educational materials, and program suggestions.

[0976] "Application Example 1"

[0977] (Claim 1)

[0978] An information input method for users to input growth information,

[0979] A plan generation means that automatically generates an activity plan using a generative model based on growth information,

[0980] A notification method for providing the generated activity plan to the user,

[0981] A nutrition plan generation means that generates a meal plan including nutrients based on age and health information,

[0982] An educational information generation means for generating educational information based on educational themes,

[0983] A means of suggesting suitable information to users by researching local childcare support information,

[0984] A system that uses a home appliance to implement the above-mentioned measures and includes a home appliance notification means that notifies parents in real time of activity plans and nutrition plans.

[0985] (Claim 2)

[0986] The system according to claim 1, further comprising a health information monitoring means for periodically receiving and analyzing health information from a user to monitor their health status.

[0987] (Claim 3)

[0988] The system according to claim 1, further comprising an information display means for integrating and displaying the generated activity plan, meal plan, educational information, and suggestions.

[0989] "Example 2 of combining an emotion engine"

[0990] (Claim 1)

[0991] An information input method for users to input growth information of young people,

[0992] Based on the growth information described above, an activity generation means automatically generates hourly and weekly activity schedules using a generative AI model,

[0993] An information notification means for notifying users of the generated activity schedule,

[0994] A nutrition plan generation means that generates a meal plan containing appropriate nutrients based on the age and health information of young people,

[0995] An educational generation method that generates educational content based on educational themes for young people,

[0996] A system proposal tool that investigates local childcare support systems and suggests suitable systems to users,

[0997] An emotion analysis tool that analyzes the emotional state of users and adjusts activity charts and educational content according to their emotions,

[0998] A system that includes this.

[0999] (Claim 2)

[1000] The system according to claim 1, further comprising a health monitoring means for periodically receiving and analyzing health information from a user to monitor their health status.

[1001] (Claim 3)

[1002] The system according to claim 1, further comprising an information display means for integrating and displaying the generated activity chart, meal plan, educational content, and system proposal.

[1003] "Application example 2 when combining with an emotional engine"

[1004] (Claim 1)

[1005] A means of recognizing emotions that analyzes the user's emotional state in real time,

[1006] A data input means for inputting growth information based on the user's emotional state,

[1007] Based on the above growth information and emotional state, an activity generation means automatically generates daily and weekly activity lists using a generative model,

[1008] A notification method for informing the user of the generated activity list,

[1009] A nutrition generation method that generates a meal plan containing appropriate nutrients based on a child's age and health data,

[1010] An educational generation method for generating educational materials based on children's educational themes,

[1011] A system proposal tool that investigates local childcare support systems and suggests suitable systems to users,

[1012] A system that includes adjustment mechanisms to modify activity lists, educational materials, and meal plans according to emotional states.

[1013] (Claim 2)

[1014] The system according to claim 1, further comprising a health monitoring means for periodically receiving and analyzing health data from a user to monitor their health status.

[1015] (Claim 3)

[1016] The system according to claim 1, further comprising a display means for integrating and displaying the generated activity list, meal plan, educational materials, and institutional proposals. [Explanation of Symbols]

[1017] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. An information input method for users to input growth information, A plan generation means that automatically generates an activity plan using a generative model based on growth information, A notification method for providing the generated activity plan to the user, A nutrition plan generation means that generates a meal plan including nutrients based on age and health information, An educational information generation means for generating educational information based on educational themes, A means of suggesting suitable information to users by researching local childcare support information, A system that uses a home appliance to implement the above-mentioned measures and includes a home appliance notification means that notifies parents in real time of activity plans and nutrition plans.

2. The system according to claim 1, further comprising a health information monitoring means for periodically receiving and analyzing health information from a user to monitor their health status.

3. The system according to claim 1, further comprising information display means for integrating and displaying the generated activity plan, meal plan, educational information, and suggestions.

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