System

Abstract

A system is provided.SOLUTION: A system comprising: means for receiving child-care related information input by a user through a terminal; means for a server to analyze the received information and generate optimal child-care advice; means for transmitting the generated advice to the terminal for display to the user; means for collecting facial expression and voice data of a child; means for the server to analyze the collected data and detect an emotional state of the child; and means for generating an alert based on the emotional state and transmitting the alert to the terminal.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

[0002] Patent document 1 discloses a persona chatbot control method 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 a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] In modern child-rearing, parents face diverse and complex challenges. New parents and working parents often find it difficult to respond quickly and appropriately to concerns and questions about child-rearing. It is also difficult to properly select and discard the information they need from the vast amount of information available. Furthermore, while it is important to detect a child's nonverbal needs and emotional changes early on, accurately grasping these is not easy. There is a need for a real-time child-rearing support system that can comprehensively resolve these issues. [Means for solving the problem]

[0005] The present invention provides a system including: means for receiving childcare information input by a user through a terminal; means for a server to analyze the received information and generate optimal childcare advice; means for transmitting the generated advice to the terminal and displaying it to the user; means for collecting data on a child's facial expression and voice; means for the server to analyze the collected data and detect the child's emotional state; and means for generating an alert based on the emotional state and transmitting it to the terminal. The system also includes means for a user to input growth record data into the terminal; means for the server to accumulate and analyze the input growth record data and generate notifications and information according to the child's developmental stage; and means for transmitting the notifications and information according to the developmental stage to the terminal and displaying them to the user. Furthermore, the system also includes means for the server to periodically update scientific data related to childcare, generate updated advice based on the analysis results, and transmit the updated advice to the terminal and display it to the user. In this way, a system that can comprehensively address the diverse challenges of modern childcare is realized.

[0006] "User" refers to a person who receives childcare support services using this system.

[0007] "Terminal" refers to the mobile device or computer that a User uses to access the System through an Interface.

[0008] "Server" refers to a central computing device that receives data sent by users, analyzes and processes it, and provides appropriate services.

[0009] "Childcare information" refers to various data and questions related to childcare, such as breastfeeding, discipline, and health care, that users input into the system.

[0010] "Childcare advice" refers to specific advice and guidance that the server generates based on childcare information and provides to the user.

[0011] "Facial expression and voice data" refers to data that indicates a child's emotions and state, collected from their facial expressions and tone of voice.

[0012] "Emotional state" refers to a child's psychological and emotional state, which can be obtained by analyzing facial and vocal data.

[0013] An "alert" refers to a message that the server generates and notifies the user when it detects a change in emotional state.

[0014] "Growth record data" refers to various data about a child's growth (height, weight, dietary content, etc.) entered by the user.

[0015] "Developmental stage-based notifications" refer to notifications generated by the server based on growth record data, which provide the user with appropriate information according to the child's developmental stage.

[0016] "Scientific data related to childcare" refers to data based on the latest scientific research and reports on childcare. [Brief explanation of the drawings]

[0017] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8]FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0018] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0019] First, the terms used in the following description will be explained.

[0020] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0021] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0022] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0023] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0024] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0025] [First embodiment]

[0026] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0027] 1, a 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.

[0028] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0029] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0030] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the 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.

[0031] 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 of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0032] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0033] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0034] 2, in the data processing device 12, a specific process 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" according to the technology of the present 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 process 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.

[0035] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0036] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0037] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0038] System Overview

[0039] This invention is a system in which a server uses childcare information entered by a user through a terminal to provide optimal childcare advice. It also has a function to collect and analyze data on a child's facial expressions and voice to detect their emotional state. It also includes a function to accumulate and analyze growth record data and provide notifications and information according to the child's developmental stage. This system also provides advice based on the latest scientific data related to childcare.

[0040] User registration and initial setup process

[0041] First, the user downloads and installs the AI ​​childcare assistant app from the app store. Next, they launch the app and enter basic information such as their child's name, age, and gender on the user registration screen. The device temporarily stores the entered information and prepares the data for login authentication. Once preparation is complete, the device encrypts the data and sends it to the server. The server receives it, stores it in a database, and sends a notification to the device that registration is complete.

[0042] Real-time childcare consultation process

[0043] When a user enters a question about childcare into the app and presses the send button, the question is sent from the device to the server. The server uses a natural language processing engine to analyze the received question. It then searches a database for the most appropriate advice according to categories such as breastfeeding, discipline, and health management, and generates customized advice based on the user's profile information. The generated advice is sent to the device and displayed to the user.

[0044] Sentiment Analysis Function Process

[0045] The device collects facial and voice data from the child through a camera and microphone. This data is periodically sent to the server. The server then applies an emotion recognition algorithm to the received data to identify the child's emotional state, such as smiling, anxious, or angry. If a change in the emotional state is detected, the server generates an appropriate alert message and sends it to the device. The user is then notified of this alert.

[0046] The process of tracking and storing growth records

[0047] The user enters their child's daily growth data (height, weight, dietary habits, etc.) into the app. The device sends the entered data to the server, which stores it in a database. Based on the stored data, the server generates a growth graph and sends it to the device. The generated graph is displayed visually to the user.

[0048] Developmentally appropriate notification and information processes

[0049] The server periodically analyzes the growth record data and selects appropriate information according to the child's developmental stage. This information is generated in the form of a notification and sent to the device. The device then displays this information to the user, making it useful for childcare.

[0050] A process for providing advice based on the latest scientific data related to childcare

[0051] The server periodically loads the latest scientific data related to childcare into its database and generates advice based on the latest scientific research. When a user asks a specific question about childcare, the server generates advice based on this information and sends it to the device. The device then displays the latest advice to the user.

[0052] Specific examples of programs

[0053] For example, suppose a user inputs the question, "My baby's crying at night is so bad I'm worried. Is there anything I can do about it?" The device sends this question to the server. The server analyzes the question and searches a database for the best solution for dealing with the crying. It generates specific advice, such as "Keep the room at the right temperature and humidity" or "Try playing calming music," and sends it to the device. The device then displays this to the user.

[0054] In this way, the system of the present invention provides comprehensive support for users to solve various child-rearing problems.

[0055] The processing flow will be explained below.

[0056] User registration and initial setup process

[0057] Step 1:

[0058] The user downloads and installs the AI ​​childcare assistant app from the app store.

[0059] Step 2:

[0060] The user launches the app and proceeds to the user registration screen.

[0061] Step 3:

[0062] The user enters basic information such as the child's name, age, and gender.

[0063] Step 4:

[0064] The device temporarily stores the entered information and prepares the data for login authentication.

[0065] Step 5:

[0066] Once the terminal is ready, it encrypts the entered information and sends it to the server.

[0067] Step 6:

[0068] The server stores the received data in a database.

[0069] Step 7:

[0070] The server sends a notification of registration completion to the terminal.

[0071] Step 8:

[0072] The device will inform the user that registration is complete.

[0073] Real-time childcare consultation process

[0074] Step 1:

[0075] Users enter parenting questions into the app.

[0076] Step 2:

[0077] The terminal sends a question to the server.

[0078] Step 3:

[0079] The server analyzes the question received using a natural language processing engine.

[0080] Step 4:

[0081] The server identifies categories such as breastfeeding, discipline, and health care based on the questions.

[0082] Step 5:

[0083] The server searches a database for appropriate advice based on the question and the user's profile information, and generates customized advice.

[0084] Step 6:

[0085] The server transmits the generated advice to the terminal.

[0086] Step 7:

[0087] The device displays the advice to the user.

[0088] Sentiment Analysis Function Process

[0089] Step 1:

[0090] The device activates the camera and microphone to collect the child's facial expressions and voice.

[0091] Step 2:

[0092] The terminal transmits the collected data to the server.

[0093] Step 3:

[0094] The server analyzes the received data and applies emotion recognition algorithms.

[0095] Step 4:

[0096] The server identifies the child's emotional state (e.g., smiling, anxious, angry).

[0097] Step 5:

[0098] The server generates an alert message based on the emotional state.

[0099] Step 6:

[0100] The server sends an alert message to the terminal.

[0101] Step 7:

[0102] The device will notify the user of the alert message.

[0103] The process of tracking and storing growth records

[0104] Step 1:

[0105] The user enters their child's daily growth data (height, weight, diet, etc.) into the app.

[0106] Step 2:

[0107] The terminal transmits the input growth data to the server.

[0108] Step 3:

[0109] The server stores the growth data in a database.

[0110] Step 4:

[0111] The server generates a growth graph based on the stored data.

[0112] Step 5:

[0113] The server transmits the generated growth graph to the terminal.

[0114] Step 6:

[0115] The device displays a growth graph to the user.

[0116] Developmentally appropriate notification and information processes

[0117] Step 1:

[0118] The server periodically analyzes the growth record data.

[0119] Step 2:

[0120] The server generates notification information according to the child's developmental stage.

[0121] Step 3:

[0122] The server sends the notification information to the terminal.

[0123] Step 4:

[0124] The device displays the notification to the user.

[0125] Providing the latest science-based parenting advice

[0126] Step 1:

[0127] The server periodically loads the latest childcare-related scientific data into the database.

[0128] Step 2:

[0129] The server generates advice using the latest data based on the questions about childcare received.

[0130] Step 3:

[0131] The server sends the advice to the terminal.

[0132] Step 4:

[0133] The device displays the advice to the user.

[0134] In this way, the system of the present invention realizes a process for supporting the user in raising their children.

[0135] Example 1

[0136] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0137] Conventional childcare support systems only allow users to ask questions about childcare and receive answers as they arise. They lack the ability to provide customized advice tailored to individual situations and the child's developmental stage. Furthermore, there are no systems that can analyze a child's emotional state in real time and provide appropriate responses based on those changes. Furthermore, functions for managing growth records and providing advice based on the latest scientific data related to childcare are limited. This creates challenges that make it difficult for parents to select appropriate childcare methods.

[0138] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0139] In this invention, the server includes means for receiving child-rearing information input by a user through a terminal, means for analyzing the received information to generate optimal child-rearing advice, means for transmitting the generated advice to the terminal and displaying it to the user, means for collecting data on the child's facial expressions and voice, means for analyzing the collected data to detect the child's emotional state, means for generating an alert based on the emotional state and transmitting it to the terminal, means for the user to input growth record data into the terminal, means for accumulating and analyzing the input growth record data and generating a growth graph, means for transmitting the growth graph to the terminal and displaying it to the user, means for analyzing the growth record data and generating notifications and information according to the child's developmental stage, and means for transmitting the notifications and information to the terminal and displaying them to the user. This enables users to receive comprehensive support in real time to solve various child-rearing issues.

[0140] "User" refers to a person such as a parent or guardian who uses the childcare support system.

[0141] "Terminal" refers to an electronic device used by a user, such as a smartphone, tablet, or computer.

[0142] "Server" refers to a central computer system that stores and processes data.

[0143] "Childcare information" refers to all information related to childcare, such as breastfeeding, discipline, health care, and growth records.

[0144] A "natural language processing engine" refers to an algorithm or software for analyzing text data entered by a user.

[0145] "Advice" refers to the best parenting advice and solutions.

[0146] "Child's facial expression and voice data" refers to the child's facial expression and voice information obtained through a camera and microphone.

[0147] "Emotional state" refers to the child's emotional changes and current emotional situation (e.g., smiling, anxious, angry).

[0148] An "alert message" refers to a message that notifies the user of important information or a change in status.

[0149] "Growth record data" refers to data relating to a child's daily growth (e.g., height, weight, dietary content).

[0150] A "growth graph" refers to a graph that visually represents a child's growth, generated based on growth record data.

[0151] "Notification" refers to a message or alert intended to inform the user of specific information or attention.

[0152] "Childcare-related scientific data" refers to information and data about childcare that is based on the latest scientific research.

[0153] "Analysis results" refers to the output results of data analyzed by the server.

[0154] A "generative AI model" refers to a computer model that uses artificial intelligence to analyze data and generate appropriate results or advice.

[0155] A "prompt sentence" refers to a specific question or instruction that a user enters into a system.

[0156] A specific embodiment of the childcare support system of the present invention will be described below. In this system, a server provides optimal childcare advice based on childcare information entered by a user through a terminal. Furthermore, the system is equipped with functions to collect and analyze data on a child's facial expressions and voice to detect their emotional state, and to accumulate and analyze growth record data to provide notifications and information according to the child's developmental stage.

[0157] User registration and initial setup process

[0158] First, the user downloads and installs the AI ​​childcare assistant app from the app store. Next, they launch the app and enter basic information such as their child's name, age, and gender on the user registration screen. The device temporarily stores this information and prepares the data for login authentication. Once preparation is complete, the device encrypts the data and sends it to the server. The server stores the received data in a database and sends a notification of registration completion to the device. The device receives the notification and displays a message informing the user that registration is complete.

[0159] Real-time childcare consultation process

[0160] When a user enters a question about childcare into the app and presses the send button, the device sends the question data to the server. The server analyzes the received question using a natural language processing engine (e.g., GPT-3). The server then searches a database for appropriate advice from categories such as breastfeeding, discipline, and health care based on the question, and generates customized advice using the user's profile information. The generated advice is sent to the device, which displays it to the user.

[0161] Sentiment Analysis Function Process

[0162] The device collects data on the child's facial expressions and voice through a camera and microphone. The collected data is periodically sent to a server. The server analyzes the received data using an emotion recognition algorithm (e.g., facial expression analysis software) to identify the child's emotional state (e.g., smiling, anxious, or angry). If there is a significant change in the emotional state, the server generates an appropriate alert message and sends it to the device. The device receives the alert message and notifies the user.

[0163] The process of tracking and storing growth records

[0164] The user enters their child's daily growth data (height, weight, dietary habits, etc.) into the app. The device sends the entered data to the server, which stores it in a database. Based on the stored data, the server generates a growth graph and sends it to the device. The device then visually displays the growth graph to the user, allowing them to easily understand their child's growth.

[0165] Developmentally appropriate notification and information processes

[0166] The server periodically analyzes the growth record data and selects appropriate information from the database according to the child's developmental stage. This information is generated in the form of a notification and sent to the device. The device displays this information to the user, providing support for the user to take appropriate parenting actions.

[0167] A process for providing advice based on the latest scientific data related to childcare

[0168] The server periodically loads the latest childcare-related scientific data into a database and generates advice based on the latest scientific research. When a user inputs and submits a specific childcare question, the device sends the question to the server. The server receives the question, generates advice based on the latest scientific research, and sends it to the device. The device displays the latest advice to the user.

[0169] Examples of specific examples and prompts

[0170] For example, if a user inputs a question such as "My baby's crying at night is so bad I'm worried. Is there anything I can do?", the device will send this question to the server. The server will analyze the question and generate specific advice, such as "Keep the room at an appropriate temperature and humidity" or "Try listening to calming music," and send it to the device. The device will then display this to the user.

[0171] In this way, the system of the present invention provides comprehensive support for users to solve various child-rearing problems.

[0172] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0173] Program processing steps

[0174] User registration and initial setup process

[0175] Step 1:

[0176] The user downloads and installs the AI ​​childcare assistant app from the app store.

[0177] Input: User downloads and installs the app

[0178] Output: Installed app

[0179] Step 2:

[0180] The user launches the app and enters basic information such as the child's name, age, and gender on the user registration screen.

[0181] Input: Basic information such as name, age, and gender

[0182] Output: Basic information entered

[0183] Step 3:

[0184] The device temporarily stores the entered information and prepares the data for login authentication.

[0185] Input: Basic information entered

[0186] Output: Temporarily saved authentication data

[0187] Step 4:

[0188] Once the device is ready, it encrypts the data and sends it to the server.

[0189] Input: Temporarily saved authentication data

[0190] Output: Encrypted data

[0191] Step 5:

[0192] The server stores the received data in a database and sends a notification of registration completion to the terminal.

[0193] Input: Encrypted data

[0194] Output: User information saved in the database, registration completion notification

[0195] Step 6:

[0196] The terminal receives the notification and displays a message to the user informing them of the completion of registration.

[0197] Input: Notification of registration completion

[0198] Output: Display of registration completion message

[0199] Real-time childcare consultation process

[0200] Step 1:

[0201] The user enters a question about childcare into the app and presses the send button.

[0202] Input: User question

[0203] Output: Generate question data

[0204] Step 2:

[0205] The terminal transmits the question data to the server.

[0206] Input: Question data

[0207] Output: Submitted question data

[0208] Step 3:

[0209] The server analyzes the received question using a natural language processing engine (e.g., GPT-3).

[0210] Input: Submitted question data

[0211] Output: Parsed question

[0212] Step 4:

[0213] Based on the question, the server searches a database for appropriate advice in categories such as breastfeeding, discipline, and health care.

[0214] Input: Parsed question content

[0215] Output: Advice data as search results

[0216] Step 5:

[0217] The server uses the user's profile information to generate customized advice.

[0218] Input: Advice data, user profile information

[0219] Output: Customized advice

[0220] Step 6:

[0221] The server transmits the generated advice to the terminal.

[0222] Input: Customized Advice

[0223] Output: Advice sent

[0224] Step 7:

[0225] The terminal receives the advice and displays it to the user.

[0226] Input: Submitted advice

[0227] Output: Advice displayed to the user

[0228] Sentiment Analysis Function Process

[0229] Step 1:

[0230] The device collects data on the child's facial expressions and voice through a camera and microphone.

[0231] Input: Child's facial expressions and voice

[0232] Output: Collected data

[0233] Step 2:

[0234] The terminal periodically transmits this data to the server.

[0235] Input: Collected data

[0236] Output: Data sent

[0237] Step 3:

[0238] The server analyzes the received data using emotion recognition algorithms.

[0239] Input: Data sent

[0240] Output: Parsed emotional state data

[0241] Step 4:

[0242] The server determines the emotional state of the child.

[0243] Input: Parsed emotional state data

[0244] Output: Identified emotional state (e.g., smiling, anxious, angry)

[0245] Step 5:

[0246] If the server detects a significant change in emotion, it generates an appropriate alert message and sends it to the device.

[0247] Input: Identified emotional state

[0248] Output: The generated alert message

[0249] Step 6:

[0250] The terminal receives the alert message and notifies the user.

[0251] Input: The generated alert message

[0252] Output: User notification

[0253] The process of tracking and storing growth records

[0254] Step 1:

[0255] The user enters their child's daily growth data (height, weight, diet, etc.) into the app.

[0256] Input: Child's daily growth data

[0257] Output: Input growth data

[0258] Step 2:

[0259] The terminal transmits the input data to the server.

[0260] Input: Input growth data

[0261] Output: Transmitted growth data

[0262] Step 3:

[0263] The server receives the data and stores it in a database.

[0264] Input: Submitted growth data

[0265] Output: Saved growth data

[0266] Step 4:

[0267] The server generates a growth graph based on the accumulated data.

[0268] Input: Saved growth data

[0269] Output: Generated growth graph

[0270] Step 5:

[0271] The server sends the growth graph to the terminal.

[0272] Input: Generated growth graph

[0273] Output: Growth graph sent

[0274] Step 6:

[0275] The terminal visually displays the growth graph to the user.

[0276] Input: Submitted growth graph

[0277] Output: Growth graph displayed to the user

[0278] Developmentally appropriate notification and information processes

[0279] Step 1:

[0280] The server periodically analyzes the growth record data.

[0281] Input: Saved growth record data

[0282] Output: Analysis results

[0283] Step 2:

[0284] Based on the analysis results, the server selects appropriate information from the database according to the child's developmental stage.

[0285] Input: Analysis results

[0286] Output: Selected information

[0287] Step 3:

[0288] The server generates the selected information in a notification format and transmits it to the terminal.

[0289] Input: Selected information

[0290] Output: Notification format generation

[0291] Step 4:

[0292] The device receives the notification and displays it to the user.

[0293] Input: Notification format information

[0294] Output: What is displayed to the user

[0295] A process for providing advice based on the latest scientific data related to childcare

[0296] Step 1:

[0297] The server periodically loads the latest childcare-related scientific data into the database.

[0298] Input: The latest childcare-related scientific data

[0299] Output: Updated database

[0300] Step 2:

[0301] The user inputs and submits a specific childcare question.

[0302] Input: User's specific question

[0303] Output: Generate question data

[0304] Step 3:

[0305] The terminal sends a question to the server.

[0306] Input: Question data

[0307] Output: Submitted question data

[0308] Step 4:

[0309] The server receives the question and generates advice based on the latest scientific research.

[0310] Input: Submitted query data, updated database

[0311] Output: Generated advice

[0312] Step 5:

[0313] The server sends the generated advice to the terminal.

[0314] Input: Generated advice

[0315] Output: Advice sent

[0316] Step 6:

[0317] The terminal displays the advice to the user.

[0318] Input: Submitted advice

[0319] Output: What is displayed to the user

[0320] (Application example 1)

[0321] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0322] While conventional childcare support systems can provide advice based on a child's growth record and emotional state, they are unable to provide specific dietary advice based on a child's nutritional status or food preferences. While meal suggestions to supplement a child's vitamin and mineral deficiencies are particularly important in childcare, no system existed that could provide such information in real time. Another challenge was linking this information with food delivery apps to make daily meal choices easier.

[0323] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0324] In this invention, the server includes means for receiving child-rearing information input by the user through the terminal, means for analyzing the received information and generating optimal child-rearing advice, means for transmitting the generated advice to the terminal and displaying it to the user, means for collecting data on the child's facial expressions and voice, means for analyzing the collected data and detecting the child's emotional state by the server, means for generating an alert based on the emotional state and transmitting it to the terminal, means for inputting and receiving dietary information through the terminal, means for analyzing the input diet-related information and growth record data by the server and generating optimal dietary advice based on the child's nutritional status, and means for transmitting the generated dietary advice to the terminal and displaying it to the user. This makes it possible to provide specific dietary suggestions based on the child's nutritional status and dietary preferences, making it easier for the child to make daily meal choices.

[0325] "Childcare information entered by the user through a device" refers to a function that allows the user to use a mobile device or computer to enter information such as questions related to childcare, growth records, and dietary details.

[0326] "Server" refers to a computer system on a network that has the function of receiving, analyzing, and storing childcare information and growth record data sent by users.

[0327] "Optimal child-rearing advice" refers to the most appropriate and useful guidance and suggestions regarding child-rearing that are provided based on the results of analyzing the child-rearing information entered.

[0328] "Means for collecting data on children's facial expressions and voices" refers to the function of using the device's built-in camera and microphone to record children's facial expressions and voices and send that information to a server.

[0329] "Means for detecting emotional states" refers to a function that analyzes collected data on a child's facial expressions and voice and identifies their emotional state using an algorithm that identifies emotions such as smiling, anxious, or angry.

[0330] "Means for generating and sending alerts to the device" refers to the function of generating appropriate warnings or notifications and sending them to the user's device when a change in emotional state is detected.

[0331] "Means for inputting and receiving information about meals" refers to a function whereby a user inputs information about the child's diet and nutritional status into a terminal, and the server receives that information.

[0332] "Means for generating dietary advice" refers to a function that generates the most appropriate dietary suggestions based on the nutritional status and dietary preferences based on the input diet-related information and growth record data.

[0333] "Means for transmitting the generated dietary advice to the terminal and displaying it to the user" refers to a function for transmitting the generated dietary advice to the user's terminal and displaying the information so that the user can visually confirm it.

[0334] The present invention is a system in which a server generates optimal advice and provides it to users using information entered by users in relation to a childcare support system. This system can provide comprehensive childcare support using information on childcare, the child's emotional state, growth records, and even information on diet.

[0335] System Overview

[0336] The present invention has a function that allows users to input information about childcare, their child's emotional state, growth records, and dietary information using a mobile device or computer. The input information is sent to a server, which analyzes the information to generate optimal childcare and dietary advice and sends it to the user's device.

[0337] User registration and initial setup process

[0338] The user downloads and installs the application. After installation, the user enters basic information such as the child's name, age, and gender on the initial setup screen. The entered information is temporarily saved, encrypted, and sent to the server. The server receives it and stores it in a database.

[0339] The process of providing parenting advice

[0340] When a user enters a question about childcare into the app and presses the send button, the question is sent from the device to the server. The server analyzes the received question and generates optimal childcare advice. The advice is then sent to the device and displayed to the user.

[0341] Sentiment Analysis Function Process

[0342] The device collects facial and vocal data from the child through a camera and microphone. This data is periodically sent to the server, which applies emotion recognition algorithms to identify the child's emotional state. If a change is detected, an alert message is generated and sent to the device. The user is notified of this alert.

[0343] The process of tracking and storing growth records

[0344] The user enters daily growth data (height, weight, dietary details, etc.) into the app. The device sends the entered data to the server, which stores it in a database. A growth graph is generated based on the stored data and sent to the device. The generated graph is displayed to the user.

[0345] The process for providing dietary advice

[0346] The user enters information about their child's diet into the app. The entered diet information is sent from the device to the server. The server receives this information and analyzes the diet-related information and growth record data. Optimal dietary advice is generated based on the child's nutritional status and sent to the device. The advice is then displayed to the user.

[0347] Program operation and concrete examples

[0348] The server uses a database system (e.g., MySQL) and a natural language processing engine (e.g., Spacy or NLTK). The device is a smartphone or tablet. By processing and calculating data, it is possible to provide individual advice to the user.

[0349] For example, if a user enters information such as "Taro, 4 years old, dislikes vegetables," the app will provide advice such as "If you are concerned about vitamin D deficiency, we recommend this menu."

[0350] Example prompts to input to the generative AI model

[0351] "What menu would you suggest for a 4-year-old who hates vegetables and is deficient in vitamin D?"

[0352] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0353] Step 1:

[0354] The user installs the application and performs initial setup. The user enters basic information about the child (such as name, age, and gender), which is temporarily stored on the device. The entered information is encrypted and sent to the server. The server receives this information and stores it in a database. As an output, a notification that registration is complete is sent to the device.

[0355] Step 2:

[0356] The user enters a question about childcare into the app and presses the send button. The device then sends the question to the server. The server receives the question and analyzes it using a natural language processing engine. Based on the analysis results, it searches a database for the most appropriate childcare advice and generates customized advice. The generated advice is then sent to the device and displayed to the user.

[0357] Step 3:

[0358] The device uses a camera and microphone to collect data on the child's facial expressions and voice. The collected data is periodically sent to the server. The server applies an emotion recognition algorithm to identify the child's emotional state (e.g., smiling, anxious, angry, etc.). If a change in the emotional state is detected, the server generates an alert message and sends it to the device. The user receives this alert.

[0359] Step 4:

[0360] The user enters daily growth data (height, weight, dietary details, etc.) into the app. The device sends the entered data to the server. The server receives it and stores it in a database. The server generates a growth graph and sends it to the device. The generated graph is displayed to the user.

[0361] Step 5:

[0362] The user enters information about their diet into the app. The device then sends the entered diet information to the server. The server receives and analyzes the diet-related information and growth record data, and generates optimal dietary advice based on the user's nutritional status. The generated dietary advice is then sent to the device and displayed to the user. For example, specific suggestions such as "If you are concerned about vitamin D deficiency, we recommend this menu" are provided.

[0363] Input and Output Complement

[0364] Step 1:

[0365] Input: Child's basic information (name, age, gender)

[0366] Output: Notification of successful registration

[0367] Step 2:

[0368] Input: Parenting Questions

[0369] Output: Best parenting advice

[0370] Step 3:

[0371] Input: Child's facial expression and voice data

[0372] Output: Emotional state alert message

[0373] Step 4:

[0374] Input: Growth data

[0375] Output: Growth graph

[0376] Step 5:

[0377] Input: Meal information

[0378] Output: Optimal dietary advice

[0379] Example prompts to input to the generative AI model

[0380] "What menu would you suggest for a 4-year-old who hates vegetables and is deficient in vitamin D?"

[0381] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0382] System Overview

[0383] This invention is a system in which a server uses childcare information entered by a user via a terminal to provide optimal childcare advice. It also has a function that collects and analyzes facial and vocal data from the child and the user to detect the emotional state of both parties. This improves the quality of childcare and facilitates smoother communication between parents and children. It also includes a function that accumulates and analyzes growth record data and provides notifications and information according to the developmental stage. This system also provides advice based on the latest scientific data related to childcare.

[0384] User registration and initial setup process

[0385] First, the user downloads and installs the AI ​​childcare assistant app from the app store. Next, they launch the app and enter their child's name, age, gender, and other basic user information on the user registration screen. The device temporarily stores the entered information and prepares the data for login authentication. Once preparation is complete, the device encrypts the data and sends it to the server. The server receives it, stores it in a database, and sends a notification to the device that registration is complete.

[0386] Real-time childcare consultation process

[0387] When a user enters a question about childcare into the app and presses the send button, the question is sent from the device to the server. The server uses a natural language processing engine to analyze the received question. It then searches a database for the most appropriate advice according to categories such as breastfeeding, discipline, and health management, and generates customized advice based on the user's profile information. The generated advice is sent to the device and displayed to the user.

[0388] Sentiment Analysis Function Process

[0389] The device collects facial and voice data of the child and user through a camera and microphone. This data is periodically sent to the server. The server applies an emotion recognition algorithm to the received data to identify the child's and user's emotional state, such as smile, anxiety, or anger. If a change in emotional state is detected, the server generates an appropriate alert message and sends it to the device. The user is notified of this alert.

[0390] User Emotion Engine Process

[0391] This adds a function to analyze the user's emotional state using an emotion engine that recognizes the user's emotions. The device's sensors are used to collect the user's facial expressions and voice in real time, and the data is sent to a server. The server then analyzes the user's emotional state based on the collected data and generates advice offering appropriate mindfulness exercises and relaxation techniques. The generated advice is sent to the device and displayed to the user.

[0392] The process of tracking and storing growth records

[0393] The user enters their child's daily growth data (height, weight, dietary habits, etc.) into the app. The device sends the entered data to the server, which stores it in a database. Based on the stored data, the server generates a growth graph and sends it to the device. The generated graph is displayed visually to the user.

[0394] Developmentally appropriate notification and information processes

[0395] The server periodically analyzes the growth record data and generates notification information according to the child's developmental stage. This information is generated in the form of a notification and sent to the device. The device displays this information to the user, making it useful for childcare.

[0396] Providing the latest science-based parenting advice

[0397] The server periodically loads the latest scientific data related to childcare into its database. When a user asks a specific question about childcare, the server generates advice based on this data and sends it to the device. The device then displays the latest advice to the user.

[0398] Specific examples of programs

[0399] For example, suppose a user inputs the question, "My baby's crying at night is so bad I'm worried. Is there anything I can do about it?" The device sends this question to the server. The server analyzes the question and searches a database for the best solution for dealing with the crying. It generates specific advice, such as "Keep the room at the right temperature and humidity" or "Try playing calming music," and sends it to the device. The device then displays this to the user.

[0400] Next, the device collects the child's facial expressions and voice, and the server analyzes the data to detect the child's state of anxiety. Based on this, the server generates an alert message such as, "Your child may be prone to anxiety recently. Let's spend some time relaxing together," and sends it to the device. The device then displays this alert to the user.

[0401] Furthermore, if the user's emotion engine detects that the user is feeling stressed, the server generates advice such as "Take a deep breath and take a few minutes to relax" and sends it to the device, which then displays it to the user. In this way, the system provides a wide range of support for the user's child-rearing needs.

[0402] The processing flow will be explained below.

[0403] User registration and initial setup process

[0404] Step 1:

[0405] The user downloads and installs the AI ​​childcare assistant app from the app store.

[0406] Step 2:

[0407] The user launches the app and proceeds to the user registration screen.

[0408] Step 3:

[0409] The user enters the child's name, age, gender, and basic user information.

[0410] Step 4:

[0411] The device temporarily stores the entered information and prepares the data for login authentication.

[0412] Step 5:

[0413] Once the device is ready, it encrypts the entered information and sends it to the server.

[0414] Step 6:

[0415] The server receives the data and stores it in a database.

[0416] Step 7:

[0417] The server sends a notification of registration completion to the terminal.

[0418] Step 8:

[0419] The device will inform the user that registration is complete.

[0420] Real-time childcare consultation process

[0421] Step 1:

[0422] Users enter parenting questions into the app.

[0423] Step 2:

[0424] The terminal sends a question to the server.

[0425] Step 3:

[0426] The server analyzes the question using a natural language processing engine.

[0427] Step 4:

[0428] The server identifies categories such as breastfeeding, discipline, and health care based on the questions.

[0429] Step 5:

[0430] The server searches a database for appropriate advice based on the question and the user's profile information, and generates customized advice.

[0431] Step 6:

[0432] The server transmits the generated advice to the terminal.

[0433] Step 7:

[0434] The device displays the advice to the user.

[0435] Sentiment Analysis Function Process

[0436] Step 1:

[0437] The device activates the camera and microphone to collect facial expressions and voices of the child and the user.

[0438] Step 2:

[0439] The terminal transmits the collected data to the server.

[0440] Step 3:

[0441] The server analyzes the received data and applies emotion recognition algorithms.

[0442] Step 4:

[0443] The server identifies the emotional state of the child and the user, for example, smiling, anxious, angry, etc.

[0444] Step 5:

[0445] The server generates an alert message based on the emotional state.

[0446] Step 6:

[0447] The server sends an alert message to the terminal.

[0448] Step 7:

[0449] The device will notify the user of the alert message.

[0450] User Emotion Engine Process

[0451] Step 1:

[0452] The device collects the user's voice and facial expression data.

[0453] Step 2:

[0454] The terminal transmits the collected data to the server.

[0455] Step 3:

[0456] The server analyzes the data and performs emotion recognition.

[0457] Step 4:

[0458] The server identifies the user's emotional state (e.g., stress, anxiety, happiness).

[0459] Step 5:

[0460] The server generates advice on mindfulness exercises and relaxation techniques based on the user's emotional state.

[0461] Step 6:

[0462] The server transmits the generated advice to the terminal.

[0463] Step 7:

[0464] The device displays the advice to the user.

[0465] The process of tracking and storing growth records

[0466] Step 1:

[0467] The user enters their child's daily growth data (height, weight, diet, etc.) into the app.

[0468] Step 2:

[0469] The terminal transmits the input growth data to the server.

[0470] Step 3:

[0471] The server stores the growth data in a database.

[0472] Step 4:

[0473] The server generates a growth graph based on the stored data.

[0474] Step 5:

[0475] The server transmits the generated growth graph to the terminal.

[0476] Step 6:

[0477] The device displays a growth graph to the user.

[0478] Developmentally appropriate notification and information processes

[0479] Step 1:

[0480] The server periodically analyzes the growth record data.

[0481] Step 2:

[0482] The server generates notification information according to the child's developmental stage.

[0483] Step 3:

[0484] The server sends the notification information to the terminal.

[0485] Step 4:

[0486] The device displays the notification to the user.

[0487] Providing the latest science-based parenting advice

[0488] Step 1:

[0489] The server periodically loads the latest childcare-related scientific data into the database.

[0490] Step 2:

[0491] The server generates advice using the latest data based on the questions about childcare received.

[0492] Step 3:

[0493] The server sends the advice to the terminal.

[0494] Step 4:

[0495] The device displays the advice to the user.

[0496] In this way, the system of the present invention realizes a process for supporting the user in raising their children.

[0497] Example 2

[0498] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0499] Conventional childcare support systems simply provide information about childcare, but lack real-time support for actual childcare environments. Furthermore, they lack a mechanism for accurately grasping the emotional state of parents and children and providing specific advice or warnings based on that information, making it difficult to improve the quality of childcare and facilitate smooth communication between parents and children. Furthermore, they lack the ability to provide childcare advice that reflects the latest scientific findings or notification functions that effectively utilize child growth records.

[0500] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for receiving child-rearing information input by a user through an information processing device; means for analyzing the received information by the information processing device to generate optimal child-rearing support information; means for transmitting the generated support information to the information processing device and displaying it to the user; means for collecting facial and voice data of the protected person; means for analyzing the collected data by the information processing device to detect the protected person's emotional state; means for generating warning information based on the emotional state and transmitting it to the information processing device; means for the user to input growth record data to the information processing device; means for the information processing device to accumulate and analyze the input growth record data and generate notifications and information according to the developmental stage; means for transmitting notifications and information according to the developmental stage to the information processing device and displaying them to the user; means for the information processing device to periodically update child-rearing-related scientific data and generate latest support information based on the analysis results; and means for transmitting the latest support information to the information processing device and displaying it to the user. This enables real-time child-rearing support and specific advice based on the protected person's emotional state, improving the quality of child-rearing and facilitating parent-child communication. In addition, it will provide reliable parenting advice based on the latest scientific knowledge, and will be able to provide notifications and information based on a child's growth based on growth records.

[0501] An "information processing device" is an electronic device that processes information entered by a user and communicates with a server.

[0502] "Childcare support information" refers to support information provided to users, such as advice and countermeasures regarding childcare, and information based on the latest scientific knowledge.

[0503] "Facial expression" refers to the movement and expression of the facial muscles of the protected person, and is visual data detected using a camera or other device.

[0504] "Audio" refers to the voice or sound emitted by the protected person or user, and is acoustic data detected using a microphone or the like.

[0505] "Emotional states" are psychological states that can be identified by analyzing facial expressions and voice, and include emotions such as joy, sadness, and anger.

[0506] "Warning information" is information that is generated based on the emotional state and that warns or advises the user.

[0507] "Growth record data" refers to information about a child's daily growth, including data such as height, weight, and dietary habits.

[0508] A "developmental stage" refers to a specific phase in a child's development and indicates the state of physical and psychological development.

[0509] "Notification" refers to a notice or message sent from the server to the information processing device, and provides the user with information useful for child-rearing.

[0510] "Scientific data related to childcare" refers to information collected based on scientific evidence, such as the latest research results and statistical data on childcare.

[0511] "Analysis results" refers to the conclusions or evaluations drawn by the server after analyzing the data received.

[0512] MODE FOR CARRYING OUT THE INVENTION

[0513] System Overview

[0514] The present invention is a system in which a server uses childcare information entered by a user through an information processing device to provide optimal childcare support information. Furthermore, the system has a function for collecting and analyzing facial and voice data of the user and the care recipient to detect the emotional state of both parties. This improves the quality of childcare and facilitates smoother communication between parents and children. It also includes a function for accumulating and analyzing growth record data and providing notifications and information according to the developmental stage. The system also provides support information based on the latest scientific data related to childcare.

[0515] Hardware and software configuration

[0516] Information processing devices: smartphones, tablets, PCs, etc.

[0517] Server: Cloud server for high-performance data processing

[0518] Camera: Built-in device camera or external camera

[0519] Microphone: Built-in microphone on device or external microphone

[0520] Natural language processing engine: AI model using Python and TensorFlow

[0521] Database: SQL or NoSQL database

[0522] Specific processing of the program

[0523] The user downloads the app using an information processing device and enters the child's name, age, gender, and basic information as the initial settings. The device temporarily stores this information, encrypts it, and sends it to the server. The server stores the received information in a database and notifies the device that registration is complete.

[0524] Real-time childcare consultation handling

[0525] The user enters a question about childcare into the app. For example, "My baby is crying a lot at night and it's bothering me. Is there anything I can do?" and presses the send button. The device sends this question to the server, which then analyzes the question using a natural language processing engine. The server then searches its database for the most appropriate childcare support information and generates a customized answer, taking into account the user's profile information. The generated support information is sent to the device and displayed to the user.

[0526] Sentiment analysis processing

[0527] The device uses a built-in camera and microphone to periodically collect facial expressions and voices of the protected person and the user. This data is periodically sent to the server, which then applies an emotion recognition algorithm to detect the child's emotional state. For example, if the server detects that the child is anxious, it generates a warning message such as "Your child may be prone to anxiety recently" and sends it to the device. The device then notifies the user of this message.

[0528] Track and save your growth record

[0529] Users enter their child's daily growth data (height, weight, dietary habits, etc.) into the app. The entered data is sent from the device to the server and stored in a database. The server then generates a growth graph based on this data and sends it to the device. The generated graph is then visually displayed to the user.

[0530] Notification and information provision according to developmental stage

[0531] The server periodically analyzes the growth record data and generates notifications based on the child's developmental stage, which are sent to the device and displayed to the user. For example, the notifications may include information on when to start solid food.

[0532] Providing advice based on the latest science

[0533] The server periodically loads the latest scientific data related to childcare into a database, and when a parent asks a specific question (e.g., "What is the latest vaccination schedule?"), it generates the latest support information based on that question. The generated information is sent to the device and displayed to the user.

[0534] As described above, this system supports improving the quality of child-rearing and smoother communication between parents and children by providing real-time child-rearing support, appropriate advice based on emotional states, and child-rearing information based on the latest scientific knowledge.

[0535] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0536] User Registration and Initial Setup Process

[0537] Step 1:

[0538] The user downloads the "AI Childcare Assistant App" from the app store and installs it on their information processing device.

[0539] Enter: Download and install the app

[0540] Output: App launch

[0541] Step 2:

[0542] The user launches the app and enters their child's name, age, gender, and basic information about themselves.

[0543] Input: Child's name, age, gender, basic user information

[0544] Output: Temporarily save input information

[0545] Step 3:

[0546] The device temporarily stores and encrypts the entered information.

[0547] Input: Basic information entered by the user

[0548] Output: Encrypted data

[0549] Step 4:

[0550] The device sends the encrypted data to the server.

[0551] Input: Encrypted data

[0552] Output: Data sent to server completed

[0553] Step 5:

[0554] The server stores the received data in a database and generates a registration completion notification.

[0555] Input: Received data

[0556] Output: Save to database, generate registration completion notification

[0557] Step 6:

[0558] The server sends a registration completion notice to the terminal, which displays it to the user.

[0559] Input: Registration completion notification

[0560] Output: Display a notification to the user

[0561] Real-time childcare consultation process

[0562] Step 1:

[0563] The user enters a question about childcare on the app and presses the send button.

[0564] Input: Question (e.g. "My baby is crying a lot at night. Is there anything I can do about it?")

[0565] Output: Transfer of question data

[0566] Step 2:

[0567] The terminal transmits the question data to the server.

[0568] Input: Question data

[0569] Output: Data sent to server completed

[0570] Step 3:

[0571] The server analyzes the received question data using a natural language processing engine.

[0572] Input: Question data

[0573] Output: Analysis results

[0574] Step 4:

[0575] The server searches the database for the most suitable childcare support information and generates a customized answer based on the user's profile information.

[0576] Input: Analysis results, user profile information

[0577] Output: Customized assistance information

[0578] Step 5:

[0579] The server transmits the generated support information to the terminal, which displays it to the user.

[0580] Input: Support information

[0581] Output: Display the answer to the user

[0582] The process of sentiment analysis

[0583] Step 1:

[0584] The device uses a built-in camera and microphone to periodically collect facial expressions and voices of the protected person and the user.

[0585] Input: facial expression data and voice data

[0586] Output: Collected data ready for transfer

[0587] Step 2:

[0588] The terminal transmits the collected data to the server.

[0589] Input: Collected data

[0590] Output: Data sent to server completed

[0591] Step 3:

[0592] The server analyzes the received data using emotion recognition algorithms to detect the emotional state.

[0593] Input: Collected data

[0594] Output: Emotional state detection result

[0595] Step 4:

[0596] The server generates alert information based on the emotional state.

[0597] Input: Emotional state detection result

[0598] Output: Warning information

[0599] Step 5:

[0600] The server transmits the warning information to the terminal, and the terminal notifies the user.

[0601] Input: Warning information

[0602] Output: Display a notification to the user

[0603] The process of tracking and storing growth records

[0604] Step 1:

[0605] The user enters their child's daily growth data (height, weight, diet, etc.) into the app.

[0606] Input: Growth data

[0607] Output: Temporarily saved on the device

[0608] Step 2:

[0609] The terminal transmits the input growth data to the server.

[0610] Input: Growth data

[0611] Output: Data sent to server completed

[0612] Step 3:

[0613] The server stores the growth data in a database.

[0614] Input: Received data

[0615] Output: Save to database

[0616] Step 4:

[0617] The server generates a growth graph based on the stored data.

[0618] Input: Growth data

[0619] Output: Growth graph

[0620] Step 5:

[0621] The server transmits the generated growth graph to the terminal, which displays it to the user.

[0622] Input: Growth graph

[0623] Output: Graphical display to the user

[0624] Developmentally appropriate notification and information processes

[0625] Step 1:

[0626] The server periodically analyzes the growth record data.

[0627] Input: Growth record data

[0628] Output: Analysis results

[0629] Step 2:

[0630] The server generates notification information according to the developmental stage.

[0631] Input: Analysis results

[0632] Output: Notification information

[0633] Step 3:

[0634] The server sends the notification information to the terminal, which displays it to the user.

[0635] Input: Notification information

[0636] Output: Display a notification to the user

[0637] A process for providing advice based on the latest science

[0638] Step 1:

[0639] The server periodically populates the database with childcare-related scientific data.

[0640] Input: Latest scientific data

[0641] Output: Database update

[0642] Step 2:

[0643] Users enter specific parenting questions into the app.

[0644] Input: Parenting question (e.g., "What is your current vaccination schedule?")

[0645] Output: Transfer of question data

[0646] Step 3:

[0647] The terminal transmits the question data to the server.

[0648] Input: Question data

[0649] Output: Data sent to server completed

[0650] Step 4:

[0651] The server analyzes the question and generates an answer from a database.

[0652] Input: Query data, latest scientific data

[0653] Output: Answer information

[0654] Step 5:

[0655] The server sends the generated answer to the terminal, which displays it to the user.

[0656] Input: Answer information

[0657] Output: Display the answer to the user

[0658] (Application example 2)

[0659] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0660] Modern childcare is extremely complex, and parents and guardians need a lot of information and advice. However, many childcare support systems do not adequately consider individual needs and emotional states. Furthermore, workers in factories and other settings need support in managing their emotional states and taking appropriate breaks, but current systems do not adequately address this issue.

[0661] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving childcare information entered by a user through a terminal, means for analyzing the received information and generating optimal childcare advice, means for sending the generated advice to the terminal and displaying it to the user, means for collecting data on the child's facial expression and voice, means for the server to analyze the collected data and detect the child's emotional state, means for generating an alert based on the emotional state and sending it to the terminal, means for collecting data on the worker's facial expression and voice, means for the server to analyze the collected data and detect the worker's emotional state, and means for generating advice on relaxation activities and breaks based on the emotional state and sending it to the terminal. This enables optimal advice and management based on individual conditions in both childcare support and worker support.

[0662] The "means for receiving information about childcare input by a user through a terminal" is a method by which a server receives data about childcare input by a user using a terminal such as a smartphone or tablet.

[0663] "Means for the server to analyze the information received and generate optimal child-rearing advice" refers to a method in which the server performs natural language processing and data analysis based on the received child-rearing information to generate optimal child-rearing advice for the user.

[0664] The "means for transmitting the generated advice to the terminal and displaying it to the user" is a method for transmitting the child-rearing advice generated by the server to the user's terminal and visually displaying it to the user.

[0665] "Means for collecting data on children's facial expressions and voices" refers to a method for collecting children's facial expressions and voices in real time using a camera or microphone.

[0666] The "means for the server to analyze the collected data and detect the emotional state of the child" refers to a method in which the server uses an emotion recognition algorithm to detect the emotional state of the child based on the collected data on facial expressions and voice.

[0667] The "means for generating and transmitting an alert to a terminal based on an emotional state" is a method for generating an appropriate alert message based on the detected emotional state and transmitting it to the user's terminal.

[0668] "Means for collecting data on workers' facial expressions and voices" refers to a method for collecting data on the facial expressions and voices of workers working in factories using cameras and microphones.

[0669] "Means for the server to analyze collected data and detect the emotional state of the worker" refers to a method in which the server performs emotional analysis based on collected data on the worker's facial expressions and voice to detect the worker's emotional state.

[0670] The "means for generating advice on relaxation activities and rest based on the emotional state and transmitting the advice to the terminal" is a method for generating advice to suggest appropriate relaxation and rest methods to the worker based on the detected emotional state and transmitting the advice to the worker's terminal.

[0671] This system utilizes childcare information entered by users via their devices, and the server provides optimal childcare advice. It also has the ability to collect and analyze facial and vocal data from children, users, and workers to detect their respective emotional states. This improves the quality of childcare and facilitates parent-child communication and worker wellness management.

[0672] Specifically, the server implements these functions using the following hardware and software:

[0673] Hardware

[0674] 1. Devices (smartphones, tablets): Used by users to input childcare information and worker emotional information.

[0675] 2. Camera: Used to collect facial expression data from children and workers.

[0676] 3. Microphone: Used to collect voice data from children and workers.

[0677] software

[0678] 1. TensorFlow: Runs emotion recognition algorithms to analyze the collected facial expression data.

[0679] 2. OpenCV: Processes camera images.

[0680] 3. pyaudio: Acquires audio data.

[0681] 4. Requests: A communication method for sending collected data to the server.

[0682] 5. Natural language processing engine: Analyzes questions about childcare entered by users and generates optimal advice.

[0683] To provide parenting advice, the server first receives questions and growth record data entered by the user from their device. The received information is stored in a database and analyzed using a natural language processing engine. Based on the analysis results, optimal parenting advice is then generated and sent to the user's device.

[0684] Additionally, facial and vocal data collected from the device's camera and microphone is used to analyze the child or worker's emotional state in real time, and alerts, relaxation activities, and break advice are generated and sent to the user's or worker's device based on the analysis results.

[0685] For example, if a worker looks exhausted while working in a factory, and the facial expression data captured by the camera indicates "fatigue," the system will generate a notification saying, "We recommend you take a 15-minute break," and send it to the device.

[0686] Examples of prompts include:

[0687] "Generate appropriate break notifications based on employee facial expression data and emotion analysis results. For example, suggest a short break if the employee feels fatigued."

[0688] This will provide a comprehensive support system that not only provides childcare support but also manages worker wellness.

[0689] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0690] Step 1:

[0691] The user inputs questions about childcare and growth record data through the terminal. The input data is temporarily saved and prepared for transmission to the server. The input includes questions about childcare and growth record data, and the output is encrypted transmission data.

[0692] Step 2:

[0693] The terminal sends encrypted data to the server. The server decrypts the received data and stores the contents in a database. The input is encrypted data, and the output is decrypted data stored in the database.

[0694] Step 3:

[0695] The server analyzes the user's question using a natural language processing engine. Based on the analysis results, it searches a database for the most appropriate childcare advice and generates customized advice. The user's question is the input, and customized advice is generated as the output.

[0696] Step 4:

[0697] The generated parenting advice is sent by the server to the terminal and displayed to the user. The customized advice is the input and is displayed on the user's terminal as the output.

[0698] Step 5:

[0699] Facial and voice data of children and workers is collected through the device's camera and microphone. The collected data is periodically sent to a server. Facial and voice data is input, and data sent to the server is generated as output.

[0700] Step 6:

[0701] The server applies an emotion recognition algorithm to the received facial and voice data to identify the emotional state of the child or worker. The input is facial and voice data, and the output is an analysis of the emotional state.

[0702] Step 7:

[0703] Based on the emotion analysis results, the server generates appropriate alert messages and advice on relaxation activities and breaks. The input is the analysis result of the emotional state, and the output is the generated alert message or advice.

[0704] Step 8:

[0705] The generated alert messages and advice are sent from the server to the terminal and displayed to the user or worker in the appropriate notification format. The input is an alert message or advice, and the output is a notification that is displayed on the terminal.

[0706] 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 a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the 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.

[0707] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0708] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0709] [Second embodiment]

[0710] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0711] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0712] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0713] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0714] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0715] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0716] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0717] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0718] The specific processing program 56 is an example of a "program" according to the technology of the present 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.

[0719] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0720] In the smart glasses 214, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0721] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. 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."

[0722] System Overview

[0723] This invention is a system in which a server uses childcare information entered by a user through a terminal to provide optimal childcare advice. It also has a function to collect and analyze data on a child's facial expressions and voice to detect their emotional state. It also includes a function to accumulate and analyze growth record data and provide notifications and information according to the child's developmental stage. This system also provides advice based on the latest scientific data related to childcare.

[0724] User registration and initial setup process

[0725] First, the user downloads and installs the AI ​​childcare assistant app from the app store. Next, they launch the app and enter basic information such as their child's name, age, and gender on the user registration screen. The device temporarily stores the entered information and prepares the data for login authentication. Once preparation is complete, the device encrypts the data and sends it to the server. The server receives it, stores it in a database, and sends a notification to the device that registration is complete.

[0726] Real-time childcare consultation process

[0727] When a user enters a question about childcare into the app and presses the send button, the question is sent from the device to the server. The server uses a natural language processing engine to analyze the received question. It then searches a database for the most appropriate advice according to categories such as breastfeeding, discipline, and health management, and generates customized advice based on the user's profile information. The generated advice is sent to the device and displayed to the user.

[0728] Sentiment Analysis Function Process

[0729] The device collects facial and voice data from the child through a camera and microphone. This data is periodically sent to the server. The server then applies an emotion recognition algorithm to the received data to identify the child's emotional state, such as smiling, anxious, or angry. If a change in the emotional state is detected, the server generates an appropriate alert message and sends it to the device. The user is then notified of this alert.

[0730] The process of tracking and storing growth records

[0731] The user enters their child's daily growth data (height, weight, dietary habits, etc.) into the app. The device sends the entered data to the server, which stores it in a database. Based on the stored data, the server generates a growth graph and sends it to the device. The generated graph is displayed visually to the user.

[0732] Developmentally appropriate notification and information processes

[0733] The server periodically analyzes the growth record data and selects appropriate information according to the child's developmental stage. This information is generated in the form of a notification and sent to the device. The device then displays this information to the user, making it useful for childcare.

[0734] A process for providing advice based on the latest scientific data related to childcare

[0735] The server periodically loads the latest scientific data related to childcare into its database and generates advice based on the latest scientific research. When a user asks a specific question about childcare, the server generates advice based on this information and sends it to the device. The device then displays the latest advice to the user.

[0736] Specific examples of programs

[0737] For example, suppose a user inputs the question, "My baby's crying at night is so bad I'm worried. Is there anything I can do about it?" The device sends this question to the server. The server analyzes the question and searches a database for the best solution for dealing with the crying. It generates specific advice, such as "Keep the room at the right temperature and humidity" or "Try playing calming music," and sends it to the device. The device then displays this to the user.

[0738] In this way, the system of the present invention provides comprehensive support for users to solve various child-rearing problems.

[0739] The processing flow will be explained below.

[0740] User registration and initial setup process

[0741] Step 1:

[0742] The user downloads and installs the AI ​​childcare assistant app from the app store.

[0743] Step 2:

[0744] The user launches the app and proceeds to the user registration screen.

[0745] Step 3:

[0746] The user enters basic information such as the child's name, age, and gender.

[0747] Step 4:

[0748] The device temporarily stores the entered information and prepares the data for login authentication.

[0749] Step 5:

[0750] Once the terminal is ready, it encrypts the entered information and sends it to the server.

[0751] Step 6:

[0752] The server stores the received data in a database.

[0753] Step 7:

[0754] The server sends a notification of registration completion to the terminal.

[0755] Step 8:

[0756] The device will inform the user that registration is complete.

[0757] Real-time childcare consultation process

[0758] Step 1:

[0759] Users enter parenting questions into the app.

[0760] Step 2:

[0761] The terminal sends a question to the server.

[0762] Step 3:

[0763] The server analyzes the question received using a natural language processing engine.

[0764] Step 4:

[0765] The server identifies categories such as breastfeeding, discipline, and health care based on the questions.

[0766] Step 5:

[0767] The server searches a database for appropriate advice based on the question and the user's profile information, and generates customized advice.

[0768] Step 6:

[0769] The server transmits the generated advice to the terminal.

[0770] Step 7:

[0771] The device displays the advice to the user.

[0772] Sentiment Analysis Function Process

[0773] Step 1:

[0774] The device activates the camera and microphone to collect the child's facial expressions and voice.

[0775] Step 2:

[0776] The terminal transmits the collected data to the server.

[0777] Step 3:

[0778] The server analyzes the received data and applies emotion recognition algorithms.

[0779] Step 4:

[0780] The server identifies the child's emotional state (e.g., smiling, anxious, angry).

[0781] Step 5:

[0782] The server generates an alert message based on the emotional state.

[0783] Step 6:

[0784] The server sends an alert message to the terminal.

[0785] Step 7:

[0786] The device will notify the user of the alert message.

[0787] The process of tracking and storing growth records

[0788] Step 1:

[0789] The user enters their child's daily growth data (height, weight, diet, etc.) into the app.

[0790] Step 2:

[0791] The terminal transmits the input growth data to the server.

[0792] Step 3:

[0793] The server stores the growth data in a database.

[0794] Step 4:

[0795] The server generates a growth graph based on the stored data.

[0796] Step 5:

[0797] The server transmits the generated growth graph to the terminal.

[0798] Step 6:

[0799] The device displays a growth graph to the user.

[0800] Developmentally appropriate notification and information processes

[0801] Step 1:

[0802] The server periodically analyzes the growth record data.

[0803] Step 2:

[0804] The server generates notification information according to the child's developmental stage.

[0805] Step 3:

[0806] The server sends the notification information to the terminal.

[0807] Step 4:

[0808] The device displays the notification to the user.

[0809] Providing the latest science-based parenting advice

[0810] Step 1:

[0811] The server periodically loads the latest childcare-related scientific data into the database.

[0812] Step 2:

[0813] The server generates advice using the latest data based on the questions about childcare received.

[0814] Step 3:

[0815] The server sends the advice to the terminal.

[0816] Step 4:

[0817] The device displays the advice to the user.

[0818] In this way, the system of the present invention realizes a process for supporting the user in raising their children.

[0819] Example 1

[0820] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0821] Conventional childcare support systems only allow users to ask questions about childcare and receive answers as they arise. They lack the ability to provide customized advice tailored to individual situations and the child's developmental stage. Furthermore, there are no systems that can analyze a child's emotional state in real time and provide appropriate responses based on those changes. Furthermore, functions for managing growth records and providing advice based on the latest scientific data related to childcare are limited. This creates challenges that make it difficult for parents to select appropriate childcare methods.

[0822] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0823] In this invention, the server includes means for receiving child-rearing information input by a user through a terminal, means for analyzing the received information to generate optimal child-rearing advice, means for transmitting the generated advice to the terminal and displaying it to the user, means for collecting data on the child's facial expressions and voice, means for analyzing the collected data to detect the child's emotional state, means for generating an alert based on the emotional state and transmitting it to the terminal, means for the user to input growth record data into the terminal, means for accumulating and analyzing the input growth record data and generating a growth graph, means for transmitting the growth graph to the terminal and displaying it to the user, means for analyzing the growth record data and generating notifications and information according to the child's developmental stage, and means for transmitting the notifications and information to the terminal and displaying them to the user. This enables users to receive comprehensive support in real time to solve various child-rearing issues.

[0824] "User" refers to a person such as a parent or guardian who uses the childcare support system.

[0825] "Terminal" refers to an electronic device used by a user, such as a smartphone, tablet, or computer.

[0826] "Server" refers to a central computer system that stores and processes data.

[0827] "Childcare information" refers to all information related to childcare, such as breastfeeding, discipline, health care, and growth records.

[0828] A "natural language processing engine" refers to an algorithm or software for analyzing text data entered by a user.

[0829] "Advice" refers to the best parenting advice and solutions.

[0830] "Child's facial expression and voice data" refers to the child's facial expression and voice information obtained through a camera and microphone.

[0831] "Emotional state" refers to the child's emotional changes and current emotional situation (e.g., smiling, anxious, angry).

[0832] An "alert message" refers to a message that notifies the user of important information or a change in status.

[0833] "Growth record data" refers to data relating to a child's daily growth (e.g., height, weight, dietary content).

[0834] A "growth graph" refers to a graph that visually represents a child's growth, generated based on growth record data.

[0835] "Notification" refers to a message or alert intended to inform the user of specific information or attention.

[0836] "Childcare-related scientific data" refers to information and data about childcare that is based on the latest scientific research.

[0837] "Analysis results" refers to the output results of data analyzed by the server.

[0838] A "generative AI model" refers to a computer model that uses artificial intelligence to analyze data and generate appropriate results or advice.

[0839] A "prompt sentence" refers to a specific question or instruction that a user enters into a system.

[0840] A specific embodiment of the childcare support system of the present invention will be described below. In this system, a server provides optimal childcare advice based on childcare information entered by a user through a terminal. Furthermore, the system is equipped with functions to collect and analyze data on a child's facial expressions and voice to detect their emotional state, and to accumulate and analyze growth record data to provide notifications and information according to the child's developmental stage.

[0841] User registration and initial setup process

[0842] First, the user downloads and installs the AI ​​childcare assistant app from the app store. Next, they launch the app and enter basic information such as their child's name, age, and gender on the user registration screen. The device temporarily stores this information and prepares the data for login authentication. Once preparation is complete, the device encrypts the data and sends it to the server. The server stores the received data in a database and sends a notification of registration completion to the device. The device receives the notification and displays a message informing the user that registration is complete.

[0843] Real-time childcare consultation process

[0844] When a user enters a question about childcare into the app and presses the send button, the device sends the question data to the server. The server analyzes the received question using a natural language processing engine (e.g., GPT-3). The server then searches a database for appropriate advice from categories such as breastfeeding, discipline, and health care based on the question, and generates customized advice using the user's profile information. The generated advice is sent to the device, which displays it to the user.

[0845] Sentiment Analysis Function Process

[0846] The device collects data on the child's facial expressions and voice through a camera and microphone. The collected data is periodically sent to a server. The server analyzes the received data using an emotion recognition algorithm (e.g., facial expression analysis software) to identify the child's emotional state (e.g., smiling, anxious, or angry). If there is a significant change in the emotional state, the server generates an appropriate alert message and sends it to the device. The device receives the alert message and notifies the user.

[0847] The process of tracking and storing growth records

[0848] The user enters their child's daily growth data (height, weight, dietary habits, etc.) into the app. The device sends the entered data to the server, which stores it in a database. Based on the stored data, the server generates a growth graph and sends it to the device. The device then visually displays the growth graph to the user, allowing them to easily understand their child's growth.

[0849] Developmentally appropriate notification and information processes

[0850] The server periodically analyzes the growth record data and selects appropriate information from the database according to the child's developmental stage. This information is generated in the form of a notification and sent to the device. The device displays this information to the user, providing support for the user to take appropriate parenting actions.

[0851] A process for providing advice based on the latest scientific data related to childcare

[0852] The server periodically loads the latest childcare-related scientific data into a database and generates advice based on the latest scientific research. When a user inputs and submits a specific childcare question, the device sends the question to the server. The server receives the question, generates advice based on the latest scientific research, and sends it to the device. The device displays the latest advice to the user.

[0853] Examples of specific examples and prompts

[0854] For example, if a user inputs a question such as "My baby's crying at night is so bad I'm worried. Is there anything I can do?", the device will send this question to the server. The server will analyze the question and generate specific advice, such as "Keep the room at an appropriate temperature and humidity" or "Try listening to calming music," and send it to the device. The device will then display this to the user.

[0855] In this way, the system of the present invention provides comprehensive support for users to solve various child-rearing problems.

[0856] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0857] Program processing steps

[0858] User registration and initial setup process

[0859] Step 1:

[0860] The user downloads and installs the AI ​​childcare assistant app from the app store.

[0861] Input: User downloads and installs the app

[0862] Output: Installed app

[0863] Step 2:

[0864] The user launches the app and enters basic information such as the child's name, age, and gender on the user registration screen.

[0865] Input: Basic information such as name, age, and gender

[0866] Output: Basic information entered

[0867] Step 3:

[0868] The device temporarily stores the entered information and prepares the data for login authentication.

[0869] Input: Basic information entered

[0870] Output: Temporarily saved authentication data

[0871] Step 4:

[0872] Once the device is ready, it encrypts the data and sends it to the server.

[0873] Input: Temporarily saved authentication data

[0874] Output: Encrypted data

[0875] Step 5:

[0876] The server stores the received data in a database and sends a notification of registration completion to the terminal.

[0877] Input: Encrypted data

[0878] Output: User information saved in the database, registration completion notification

[0879] Step 6:

[0880] The terminal receives the notification and displays a message to the user informing them of the completion of registration.

[0881] Input: Notification of registration completion

[0882] Output: Display of registration completion message

[0883] Real-time childcare consultation process

[0884] Step 1:

[0885] The user enters a question about childcare into the app and presses the send button.

[0886] Input: User question

[0887] Output: Generate question data

[0888] Step 2:

[0889] The terminal transmits the question data to the server.

[0890] Input: Question data

[0891] Output: Submitted question data

[0892] Step 3:

[0893] The server analyzes the received question using a natural language processing engine (e.g., GPT-3).

[0894] Input: Submitted question data

[0895] Output: Parsed question

[0896] Step 4:

[0897] Based on the question, the server searches a database for appropriate advice in categories such as breastfeeding, discipline, and health care.

[0898] Input: Parsed question content

[0899] Output: Advice data as search results

[0900] Step 5:

[0901] The server uses the user's profile information to generate customized advice.

[0902] Input: Advice data, user profile information

[0903] Output: Customized advice

[0904] Step 6:

[0905] The server transmits the generated advice to the terminal.

[0906] Input: Customized Advice

[0907] Output: Advice sent

[0908] Step 7:

[0909] The terminal receives the advice and displays it to the user.

[0910] Input: Submitted advice

[0911] Output: Advice displayed to the user

[0912] Sentiment Analysis Function Process

[0913] Step 1:

[0914] The device collects data on the child's facial expressions and voice through a camera and microphone.

[0915] Input: Child's facial expressions and voice

[0916] Output: Collected data

[0917] Step 2:

[0918] The terminal periodically transmits this data to the server.

[0919] Input: Collected data

[0920] Output: Data sent

[0921] Step 3:

[0922] The server analyzes the received data using emotion recognition algorithms.

[0923] Input: Data sent

[0924] Output: Parsed emotional state data

[0925] Step 4:

[0926] The server determines the emotional state of the child.

[0927] Input: Parsed emotional state data

[0928] Output: Identified emotional state (e.g., smiling, anxious, angry)

[0929] Step 5:

[0930] If the server detects a significant change in emotion, it generates an appropriate alert message and sends it to the device.

[0931] Input: Identified emotional state

[0932] Output: The generated alert message

[0933] Step 6:

[0934] The terminal receives the alert message and notifies the user.

[0935] Input: The generated alert message

[0936] Output: User notification

[0937] The process of tracking and storing growth records

[0938] Step 1:

[0939] The user enters their child's daily growth data (height, weight, diet, etc.) into the app.

[0940] Input: Child's daily growth data

[0941] Output: Input growth data

[0942] Step 2:

[0943] The terminal transmits the input data to the server.

[0944] Input: Input growth data

[0945] Output: Transmitted growth data

[0946] Step 3:

[0947] The server receives the data and stores it in a database.

[0948] Input: Submitted growth data

[0949] Output: Saved growth data

[0950] Step 4:

[0951] The server generates a growth graph based on the accumulated data.

[0952] Input: Saved growth data

[0953] Output: Generated growth graph

[0954] Step 5:

[0955] The server sends the growth graph to the terminal.

[0956] Input: Generated growth graph

[0957] Output: Growth graph sent

[0958] Step 6:

[0959] The terminal visually displays the growth graph to the user.

[0960] Input: Submitted growth graph

[0961] Output: Growth graph displayed to the user

[0962] Developmentally appropriate notification and information processes

[0963] Step 1:

[0964] The server periodically analyzes the growth record data.

[0965] Input: Saved growth record data

[0966] Output: Analysis results

[0967] Step 2:

[0968] Based on the analysis results, the server selects appropriate information from the database according to the child's developmental stage.

[0969] Input: Analysis results

[0970] Output: Selected information

[0971] Step 3:

[0972] The server generates the selected information in a notification format and transmits it to the terminal.

[0973] Input: Selected information

[0974] Output: Notification format generation

[0975] Step 4:

[0976] The device receives the notification and displays it to the user.

[0977] Input: Notification format information

[0978] Output: What is displayed to the user

[0979] A process for providing advice based on the latest scientific data related to childcare

[0980] Step 1:

[0981] The server periodically loads the latest childcare-related scientific data into the database.

[0982] Input: The latest childcare-related scientific data

[0983] Output: Updated database

[0984] Step 2:

[0985] The user inputs and submits a specific childcare question.

[0986] Input: User's specific question

[0987] Output: Generate question data

[0988] Step 3:

[0989] The terminal sends a question to the server.

[0990] Input: Question data

[0991] Output: Submitted question data

[0992] Step 4:

[0993] The server receives the question and generates advice based on the latest scientific research.

[0994] Input: Submitted query data, updated database

[0995] Output: Generated advice

[0996] Step 5:

[0997] The server sends the generated advice to the terminal.

[0998] Input: Generated advice

[0999] Output: Advice sent

[1000] Step 6:

[1001] The terminal displays the advice to the user.

[1002] Input: Submitted advice

[1003] Output: What is displayed to the user

[1004] (Application example 1)

[1005] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1006] While conventional childcare support systems can provide advice based on a child's growth record and emotional state, they are unable to provide specific dietary advice based on a child's nutritional status or food preferences. While meal suggestions to supplement a child's vitamin and mineral deficiencies are particularly important in childcare, no system existed that could provide such information in real time. Another challenge was linking this information with food delivery apps to make daily meal choices easier.

[1007] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1008] In this invention, the server includes means for receiving child-rearing information input by the user through the terminal, means for analyzing the received information and generating optimal child-rearing advice, means for transmitting the generated advice to the terminal and displaying it to the user, means for collecting data on the child's facial expressions and voice, means for analyzing the collected data and detecting the child's emotional state by the server, means for generating an alert based on the emotional state and transmitting it to the terminal, means for inputting and receiving dietary information through the terminal, means for analyzing the input diet-related information and growth record data by the server and generating optimal dietary advice based on the child's nutritional status, and means for transmitting the generated dietary advice to the terminal and displaying it to the user. This makes it possible to provide specific dietary suggestions based on the child's nutritional status and dietary preferences, making it easier for the child to make daily meal choices.

[1009] "Childcare information entered by the user through a device" refers to a function that allows the user to use a mobile device or computer to enter information such as questions related to childcare, growth records, and dietary details.

[1010] "Server" refers to a computer system on a network that has the function of receiving, analyzing, and storing childcare information and growth record data sent by users.

[1011] "Optimal child-rearing advice" refers to the most appropriate and useful guidance and suggestions regarding child-rearing that are provided based on the results of analyzing the child-rearing information entered.

[1012] "Means for collecting data on children's facial expressions and voices" refers to the function of using the device's built-in camera and microphone to record children's facial expressions and voices and send that information to a server.

[1013] "Means for detecting emotional states" refers to a function that analyzes collected data on a child's facial expressions and voice and identifies their emotional state using an algorithm that identifies emotions such as smiling, anxious, or angry.

[1014] "Means for generating and sending alerts to the device" refers to the function of generating appropriate warnings or notifications and sending them to the user's device when a change in emotional state is detected.

[1015] "Means for inputting and receiving information about meals" refers to a function whereby a user inputs information about the child's diet and nutritional status into a terminal, and the server receives that information.

[1016] "Means for generating dietary advice" refers to a function that generates the most appropriate dietary suggestions based on the nutritional status and dietary preferences based on the input diet-related information and growth record data.

[1017] "Means for transmitting the generated dietary advice to the terminal and displaying it to the user" refers to a function for transmitting the generated dietary advice to the user's terminal and displaying the information so that the user can visually confirm it.

[1018] The present invention is a system in which a server generates optimal advice and provides it to users using information entered by users in relation to a childcare support system. This system can provide comprehensive childcare support using information on childcare, the child's emotional state, growth records, and even information on diet.

[1019] System Overview

[1020] The present invention has a function that allows users to input information about childcare, their child's emotional state, growth records, and dietary information using a mobile device or computer. The input information is sent to a server, which analyzes the information to generate optimal childcare and dietary advice and sends it to the user's device.

[1021] User registration and initial setup process

[1022] The user downloads and installs the application. After installation, the user enters basic information such as the child's name, age, and gender on the initial setup screen. The entered information is temporarily saved, encrypted, and sent to the server. The server receives it and stores it in a database.

[1023] The process of providing parenting advice

[1024] When a user enters a question about childcare into the app and presses the send button, the question is sent from the device to the server. The server analyzes the received question and generates optimal childcare advice. The advice is then sent to the device and displayed to the user.

[1025] Sentiment Analysis Function Process

[1026] The device collects facial and vocal data from the child through a camera and microphone. This data is periodically sent to the server, which applies emotion recognition algorithms to identify the child's emotional state. If a change is detected, an alert message is generated and sent to the device. The user is notified of this alert.

[1027] The process of tracking and storing growth records

[1028] The user enters daily growth data (height, weight, dietary details, etc.) into the app. The device sends the entered data to the server, which stores it in a database. A growth graph is generated based on the stored data and sent to the device. The generated graph is displayed to the user.

[1029] The process for providing dietary advice

[1030] The user enters information about their child's diet into the app. The entered diet information is sent from the device to the server. The server receives this information and analyzes the diet-related information and growth record data. Optimal dietary advice is generated based on the child's nutritional status and sent to the device. The advice is then displayed to the user.

[1031] Program operation and concrete examples

[1032] The server uses a database system (e.g., MySQL) and a natural language processing engine (e.g., Spacy or NLTK). The device is a smartphone or tablet. By processing and calculating data, it is possible to provide individual advice to the user.

[1033] For example, if a user enters information such as "Taro, 4 years old, dislikes vegetables," the app will provide advice such as "If you are concerned about vitamin D deficiency, we recommend this menu."

[1034] Example prompts to input to the generative AI model

[1035] "What menu would you suggest for a 4-year-old who hates vegetables and is deficient in vitamin D?"

[1036] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1037] Step 1:

[1038] The user installs the application and performs initial setup. The user enters basic information about the child (such as name, age, and gender), which is temporarily stored on the device. The entered information is encrypted and sent to the server. The server receives this information and stores it in a database. As an output, a notification that registration is complete is sent to the device.

[1039] Step 2:

[1040] The user enters a question about childcare into the app and presses the send button. The device then sends the question to the server. The server receives the question and analyzes it using a natural language processing engine. Based on the analysis results, it searches a database for the most appropriate childcare advice and generates customized advice. The generated advice is then sent to the device and displayed to the user.

[1041] Step 3:

[1042] The device uses a camera and microphone to collect data on the child's facial expressions and voice. The collected data is periodically sent to the server. The server applies an emotion recognition algorithm to identify the child's emotional state (e.g., smiling, anxious, angry, etc.). If a change in the emotional state is detected, the server generates an alert message and sends it to the device. The user receives this alert.

[1043] Step 4:

[1044] The user enters daily growth data (height, weight, dietary details, etc.) into the app. The device sends the entered data to the server. The server receives it and stores it in a database. The server generates a growth graph and sends it to the device. The generated graph is displayed to the user.

[1045] Step 5:

[1046] The user enters information about their diet into the app. The device then sends the entered diet information to the server. The server receives and analyzes the diet-related information and growth record data, and generates optimal dietary advice based on the user's nutritional status. The generated dietary advice is then sent to the device and displayed to the user. For example, specific suggestions such as "If you are concerned about vitamin D deficiency, we recommend this menu" are provided.

[1047] Input and Output Complement

[1048] Step 1:

[1049] Input: Child's basic information (name, age, gender)

[1050] Output: Notification of successful registration

[1051] Step 2:

[1052] Input: Parenting Questions

[1053] Output: Best parenting advice

[1054] Step 3:

[1055] Input: Child's facial expression and voice data

[1056] Output: Emotional state alert message

[1057] Step 4:

[1058] Input: Growth data

[1059] Output: Growth graph

[1060] Step 5:

[1061] Input: Meal information

[1062] Output: Optimal dietary advice

[1063] Example prompts to input to the generative AI model

[1064] "What menu would you suggest for a 4-year-old who hates vegetables and is deficient in vitamin D?"

[1065] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1066] System Overview

[1067] This invention is a system in which a server uses childcare information entered by a user via a terminal to provide optimal childcare advice. It also has a function that collects and analyzes facial and vocal data from the child and the user to detect the emotional state of both parties. This improves the quality of childcare and facilitates smoother communication between parents and children. It also includes a function that accumulates and analyzes growth record data and provides notifications and information according to the developmental stage. This system also provides advice based on the latest scientific data related to childcare.

[1068] User registration and initial setup process

[1069] First, the user downloads and installs the AI ​​childcare assistant app from the app store. Next, they launch the app and enter their child's name, age, gender, and other basic user information on the user registration screen. The device temporarily stores the entered information and prepares the data for login authentication. Once preparation is complete, the device encrypts the data and sends it to the server. The server receives it, stores it in a database, and sends a notification to the device that registration is complete.

[1070] Real-time childcare consultation process

[1071] When a user enters a question about childcare into the app and presses the send button, the question is sent from the device to the server. The server uses a natural language processing engine to analyze the received question. It then searches a database for the most appropriate advice according to categories such as breastfeeding, discipline, and health management, and generates customized advice based on the user's profile information. The generated advice is sent to the device and displayed to the user.

[1072] Sentiment Analysis Function Process

[1073] The device collects facial and voice data of the child and user through a camera and microphone. This data is periodically sent to the server. The server applies an emotion recognition algorithm to the received data to identify the child's and user's emotional state, such as smile, anxiety, or anger. If a change in emotional state is detected, the server generates an appropriate alert message and sends it to the device. The user is notified of this alert.

[1074] User Emotion Engine Process

[1075] This adds a function to analyze the user's emotional state using an emotion engine that recognizes the user's emotions. The device's sensors are used to collect the user's facial expressions and voice in real time, and the data is sent to a server. The server then analyzes the user's emotional state based on the collected data and generates advice offering appropriate mindfulness exercises and relaxation techniques. The generated advice is sent to the device and displayed to the user.

[1076] The process of tracking and storing growth records

[1077] The user enters their child's daily growth data (height, weight, dietary habits, etc.) into the app. The device sends the entered data to the server, which stores it in a database. Based on the stored data, the server generates a growth graph and sends it to the device. The generated graph is displayed visually to the user.

[1078] Developmentally appropriate notification and information processes

[1079] The server periodically analyzes the growth record data and generates notification information according to the child's developmental stage. This information is generated in the form of a notification and sent to the device. The device displays this information to the user, making it useful for childcare.

[1080] Providing the latest science-based parenting advice

[1081] The server periodically loads the latest scientific data related to childcare into its database. When a user asks a specific question about childcare, the server generates advice based on this data and sends it to the device. The device then displays the latest advice to the user.

[1082] Specific examples of programs

[1083] For example, suppose a user inputs the question, "My baby's crying at night is so bad I'm worried. Is there anything I can do about it?" The device sends this question to the server. The server analyzes the question and searches a database for the best solution for dealing with the crying. It generates specific advice, such as "Keep the room at the right temperature and humidity" or "Try playing calming music," and sends it to the device. The device then displays this to the user.

[1084] Next, the device collects the child's facial expressions and voice, and the server analyzes the data to detect the child's state of anxiety. Based on this, the server generates an alert message such as, "Your child may be prone to anxiety recently. Let's spend some time relaxing together," and sends it to the device. The device then displays this alert to the user.

[1085] Furthermore, if the user's emotion engine detects that the user is feeling stressed, the server generates advice such as "Take a deep breath and take a few minutes to relax" and sends it to the device, which then displays it to the user. In this way, the system provides a wide range of support for the user's child-rearing needs.

[1086] The processing flow will be explained below.

[1087] User registration and initial setup process

[1088] Step 1:

[1089] The user downloads and installs the AI ​​childcare assistant app from the app store.

[1090] Step 2:

[1091] The user launches the app and proceeds to the user registration screen.

[1092] Step 3:

[1093] The user enters the child's name, age, gender, and basic user information.

[1094] Step 4:

[1095] The device temporarily stores the entered information and prepares the data for login authentication.

[1096] Step 5:

[1097] Once the device is ready, it encrypts the entered information and sends it to the server.

[1098] Step 6:

[1099] The server receives the data and stores it in a database.

[1100] Step 7:

[1101] The server sends a notification of registration completion to the terminal.

[1102] Step 8:

[1103] The device will inform the user that registration is complete.

[1104] Real-time childcare consultation process

[1105] Step 1:

[1106] Users enter parenting questions into the app.

[1107] Step 2:

[1108] The terminal sends a question to the server.

[1109] Step 3:

[1110] The server analyzes the question using a natural language processing engine.

[1111] Step 4:

[1112] The server identifies categories such as breastfeeding, discipline, and health care based on the questions.

[1113] Step 5:

[1114] The server searches a database for appropriate advice based on the question and the user's profile information, and generates customized advice.

[1115] Step 6:

[1116] The server transmits the generated advice to the terminal.

[1117] Step 7:

[1118] The device displays the advice to the user.

[1119] Sentiment Analysis Function Process

[1120] Step 1:

[1121] The device activates the camera and microphone to collect facial expressions and voices of the child and the user.

[1122] Step 2:

[1123] The terminal transmits the collected data to the server.

[1124] Step 3:

[1125] The server analyzes the received data and applies emotion recognition algorithms.

[1126] Step 4:

[1127] The server identifies the emotional state of the child and the user, for example, smiling, anxious, angry, etc.

[1128] Step 5:

[1129] The server generates an alert message based on the emotional state.

[1130] Step 6:

[1131] The server sends an alert message to the terminal.

[1132] Step 7:

[1133] The device will notify the user of the alert message.

[1134] User Emotion Engine Process

[1135] Step 1:

[1136] The device collects the user's voice and facial expression data.

[1137] Step 2:

[1138] The terminal transmits the collected data to the server.

[1139] Step 3:

[1140] The server analyzes the data and performs emotion recognition.

[1141] Step 4:

[1142] The server identifies the user's emotional state (e.g., stress, anxiety, happiness).

[1143] Step 5:

[1144] The server generates advice on mindfulness exercises and relaxation techniques based on the user's emotional state.

[1145] Step 6:

[1146] The server transmits the generated advice to the terminal.

[1147] Step 7:

[1148] The device displays the advice to the user.

[1149] The process of tracking and storing growth records

[1150] Step 1:

[1151] The user enters their child's daily growth data (height, weight, diet, etc.) into the app.

[1152] Step 2:

[1153] The terminal transmits the input growth data to the server.

[1154] Step 3:

[1155] The server stores the growth data in a database.

[1156] Step 4:

[1157] The server generates a growth graph based on the stored data.

[1158] Step 5:

[1159] The server transmits the generated growth graph to the terminal.

[1160] Step 6:

[1161] The device displays a growth graph to the user.

[1162] Developmentally appropriate notification and information processes

[1163] Step 1:

[1164] The server periodically analyzes the growth record data.

[1165] Step 2:

[1166] The server generates notification information according to the child's developmental stage.

[1167] Step 3:

[1168] The server sends the notification information to the terminal.

[1169] Step 4:

[1170] The device displays the notification to the user.

[1171] Providing the latest science-based parenting advice

[1172] Step 1:

[1173] The server periodically loads the latest childcare-related scientific data into the database.

[1174] Step 2:

[1175] The server generates advice using the latest data based on the questions about childcare received.

[1176] Step 3:

[1177] The server sends the advice to the terminal.

[1178] Step 4:

[1179] The device displays the advice to the user.

[1180] In this way, the system of the present invention realizes a process for supporting the user in raising their children.

[1181] Example 2

[1182] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1183] Conventional childcare support systems simply provide information about childcare, but lack real-time support for actual childcare environments. Furthermore, they lack a mechanism for accurately grasping the emotional state of parents and children and providing specific advice or warnings based on that information, making it difficult to improve the quality of childcare and facilitate smooth communication between parents and children. Furthermore, they lack the ability to provide childcare advice that reflects the latest scientific findings or notification functions that effectively utilize child growth records.

[1184] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for receiving child-rearing information input by a user through an information processing device; means for analyzing the received information by the information processing device to generate optimal child-rearing support information; means for transmitting the generated support information to the information processing device and displaying it to the user; means for collecting facial and voice data of the protected person; means for analyzing the collected data by the information processing device to detect the protected person's emotional state; means for generating warning information based on the emotional state and transmitting it to the information processing device; means for the user to input growth record data to the information processing device; means for the information processing device to accumulate and analyze the input growth record data and generate notifications and information according to the developmental stage; means for transmitting notifications and information according to the developmental stage to the information processing device and displaying them to the user; means for the information processing device to periodically update child-rearing-related scientific data and generate latest support information based on the analysis results; and means for transmitting the latest support information to the information processing device and displaying it to the user. This enables real-time child-rearing support and specific advice based on the protected person's emotional state, improving the quality of child-rearing and facilitating parent-child communication. In addition, it will provide reliable parenting advice based on the latest scientific knowledge, and will be able to provide notifications and information based on a child's growth based on growth records.

[1185] An "information processing device" is an electronic device that processes information entered by a user and communicates with a server.

[1186] "Childcare support information" refers to support information provided to users, such as advice and countermeasures regarding childcare, and information based on the latest scientific knowledge.

[1187] "Facial expression" refers to the movement and expression of the facial muscles of the protected person, and is visual data detected using a camera or other device.

[1188] "Audio" refers to the voice or sound emitted by the protected person or user, and is acoustic data detected using a microphone or the like.

[1189] "Emotional states" are psychological states that can be identified by analyzing facial expressions and voice, and include emotions such as joy, sadness, and anger.

[1190] "Warning information" is information that is generated based on the emotional state and that warns or advises the user.

[1191] "Growth record data" refers to information about a child's daily growth, including data such as height, weight, and dietary habits.

[1192] A "developmental stage" refers to a specific phase in a child's development and indicates the state of physical and psychological development.

[1193] "Notification" refers to a notice or message sent from the server to the information processing device, and provides the user with information useful for child-rearing.

[1194] "Scientific data related to childcare" refers to information collected based on scientific evidence, such as the latest research results and statistical data on childcare.

[1195] "Analysis results" refers to the conclusions or evaluations drawn by the server after analyzing the data received.

[1196] MODE FOR CARRYING OUT THE INVENTION

[1197] System Overview

[1198] The present invention is a system in which a server uses childcare information entered by a user through an information processing device to provide optimal childcare support information. Furthermore, the system has a function for collecting and analyzing facial and voice data of the user and the care recipient to detect the emotional state of both parties. This improves the quality of childcare and facilitates smoother communication between parents and children. It also includes a function for accumulating and analyzing growth record data and providing notifications and information according to the developmental stage. The system also provides support information based on the latest scientific data related to childcare.

[1199] Hardware and software configuration

[1200] Information processing devices: smartphones, tablets, PCs, etc.

[1201] Server: Cloud server for high-performance data processing

[1202] Camera: Built-in device camera or external camera

[1203] Microphone: Built-in microphone on device or external microphone

[1204] Natural language processing engine: AI model using Python and TensorFlow

[1205] Database: SQL or NoSQL database

[1206] Specific processing of the program

[1207] The user downloads the app using an information processing device and enters the child's name, age, gender, and basic information as the initial settings. The device temporarily stores this information, encrypts it, and sends it to the server. The server stores the received information in a database and notifies the device that registration is complete.

[1208] Real-time childcare consultation handling

[1209] The user enters a question about childcare into the app. For example, "My baby is crying a lot at night and it's bothering me. Is there anything I can do?" and presses the send button. The device sends this question to the server, which then analyzes the question using a natural language processing engine. The server then searches its database for the most appropriate childcare support information and generates a customized answer, taking into account the user's profile information. The generated support information is sent to the device and displayed to the user.

[1210] Sentiment analysis processing

[1211] The device uses a built-in camera and microphone to periodically collect facial expressions and voices of the protected person and the user. This data is periodically sent to the server, which then applies an emotion recognition algorithm to detect the child's emotional state. For example, if the server detects that the child is anxious, it generates a warning message such as "Your child may be prone to anxiety recently" and sends it to the device. The device then notifies the user of this message.

[1212] Track and save your growth record

[1213] Users enter their child's daily growth data (height, weight, dietary habits, etc.) into the app. The entered data is sent from the device to the server and stored in a database. The server then generates a growth graph based on this data and sends it to the device. The generated graph is then visually displayed to the user.

[1214] Notification and information provision according to developmental stage

[1215] The server periodically analyzes the growth record data and generates notifications based on the child's developmental stage, which are sent to the device and displayed to the user. For example, the notifications may include information on when to start solid food.

[1216] Providing advice based on the latest science

[1217] The server periodically loads the latest scientific data related to childcare into a database, and when a parent asks a specific question (e.g., "What is the latest vaccination schedule?"), it generates the latest support information based on that question. The generated information is sent to the device and displayed to the user.

[1218] As described above, this system supports improving the quality of child-rearing and smoother communication between parents and children by providing real-time child-rearing support, appropriate advice based on emotional states, and child-rearing information based on the latest scientific knowledge.

[1219] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1220] User Registration and Initial Setup Process

[1221] Step 1:

[1222] The user downloads the "AI Childcare Assistant App" from the app store and installs it on their information processing device.

[1223] Enter: Download and install the app

[1224] Output: App launch

[1225] Step 2:

[1226] The user launches the app and enters their child's name, age, gender, and basic information about themselves.

[1227] Input: Child's name, age, gender, basic user information

[1228] Output: Temporarily save input information

[1229] Step 3:

[1230] The device temporarily stores and encrypts the entered information.

[1231] Input: Basic information entered by the user

[1232] Output: Encrypted data

[1233] Step 4:

[1234] The device sends the encrypted data to the server.

[1235] Input: Encrypted data

[1236] Output: Data sent to server completed

[1237] Step 5:

[1238] The server stores the received data in a database and generates a registration completion notification.

[1239] Input: Received data

[1240] Output: Save to database, generate registration completion notification

[1241] Step 6:

[1242] The server sends a registration completion notice to the terminal, which displays it to the user.

[1243] Input: Registration completion notification

[1244] Output: Display a notification to the user

[1245] Real-time childcare consultation process

[1246] Step 1:

[1247] The user enters a question about childcare on the app and presses the send button.

[1248] Input: Question (e.g. "My baby is crying a lot at night. Is there anything I can do about it?")

[1249] Output: Transfer of question data

[1250] Step 2:

[1251] The terminal transmits the question data to the server.

[1252] Input: Question data

[1253] Output: Data sent to server completed

[1254] Step 3:

[1255] The server analyzes the received question data using a natural language processing engine.

[1256] Input: Question data

[1257] Output: Analysis results

[1258] Step 4:

[1259] The server searches the database for the most suitable childcare support information and generates a customized answer based on the user's profile information.

[1260] Input: Analysis results, user profile information

[1261] Output: Customized assistance information

[1262] Step 5:

[1263] The server transmits the generated support information to the terminal, which displays it to the user.

[1264] Input: Support information

[1265] Output: Display the answer to the user

[1266] The process of sentiment analysis

[1267] Step 1:

[1268] The device uses a built-in camera and microphone to periodically collect facial expressions and voices of the protected person and the user.

[1269] Input: facial expression data and voice data

[1270] Output: Collected data ready for transfer

[1271] Step 2:

[1272] The terminal transmits the collected data to the server.

[1273] Input: Collected data

[1274] Output: Data sent to server completed

[1275] Step 3:

[1276] The server analyzes the received data using emotion recognition algorithms to detect the emotional state.

[1277] Input: Collected data

[1278] Output: Emotional state detection result

[1279] Step 4:

[1280] The server generates alert information based on the emotional state.

[1281] Input: Emotional state detection result

[1282] Output: Warning information

[1283] Step 5:

[1284] The server transmits the warning information to the terminal, and the terminal notifies the user.

[1285] Input: Warning information

[1286] Output: Display a notification to the user

[1287] The process of tracking and storing growth records

[1288] Step 1:

[1289] The user enters their child's daily growth data (height, weight, diet, etc.) into the app.

[1290] Input: Growth data

[1291] Output: Temporarily saved on the device

[1292] Step 2:

[1293] The terminal transmits the input growth data to the server.

[1294] Input: Growth data

[1295] Output: Data sent to server completed

[1296] Step 3:

[1297] The server stores the growth data in a database.

[1298] Input: Received data

[1299] Output: Save to database

[1300] Step 4:

[1301] The server generates a growth graph based on the stored data.

[1302] Input: Growth data

[1303] Output: Growth graph

[1304] Step 5:

[1305] The server transmits the generated growth graph to the terminal, which displays it to the user.

[1306] Input: Growth graph

[1307] Output: Graphical display to the user

[1308] Developmentally appropriate notification and information processes

[1309] Step 1:

[1310] The server periodically analyzes the growth record data.

[1311] Input: Growth record data

[1312] Output: Analysis results

[1313] Step 2:

[1314] The server generates notification information according to the developmental stage.

[1315] Input: Analysis results

[1316] Output: Notification information

[1317] Step 3:

[1318] The server sends the notification information to the terminal, which displays it to the user.

[1319] Input: Notification information

[1320] Output: Display a notification to the user

[1321] A process for providing advice based on the latest science

[1322] Step 1:

[1323] The server periodically populates the database with childcare-related scientific data.

[1324] Input: Latest scientific data

[1325] Output: Database update

[1326] Step 2:

[1327] Users enter specific parenting questions into the app.

[1328] Input: Parenting question (e.g., "What is your current vaccination schedule?")

[1329] Output: Transfer of question data

[1330] Step 3:

[1331] The terminal transmits the question data to the server.

[1332] Input: Question data

[1333] Output: Data sent to server completed

[1334] Step 4:

[1335] The server analyzes the question and generates an answer from a database.

[1336] Input: Query data, latest scientific data

[1337] Output: Answer information

[1338] Step 5:

[1339] The server sends the generated answer to the terminal, which displays it to the user.

[1340] Input: Answer information

[1341] Output: Display the answer to the user

[1342] (Application example 2)

[1343] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1344] Modern childcare is extremely complex, and parents and guardians need a lot of information and advice. However, many childcare support systems do not adequately consider individual needs and emotional states. Furthermore, workers in factories and other settings need support in managing their emotional states and taking appropriate breaks, but current systems do not adequately address this issue.

[1345] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving childcare information entered by a user through a terminal, means for analyzing the received information and generating optimal childcare advice, means for sending the generated advice to the terminal and displaying it to the user, means for collecting data on the child's facial expression and voice, means for the server to analyze the collected data and detect the child's emotional state, means for generating an alert based on the emotional state and sending it to the terminal, means for collecting data on the worker's facial expression and voice, means for the server to analyze the collected data and detect the worker's emotional state, and means for generating advice on relaxation activities and breaks based on the emotional state and sending it to the terminal. This enables optimal advice and management based on individual conditions in both childcare support and worker support.

[1346] The "means for receiving information about childcare input by a user through a terminal" is a method by which a server receives data about childcare input by a user using a terminal such as a smartphone or tablet.

[1347] "Means for the server to analyze the information received and generate optimal child-rearing advice" refers to a method in which the server performs natural language processing and data analysis based on the received child-rearing information to generate optimal child-rearing advice for the user.

[1348] The "means for transmitting the generated advice to the terminal and displaying it to the user" is a method for transmitting the child-rearing advice generated by the server to the user's terminal and visually displaying it to the user.

[1349] "Means for collecting data on children's facial expressions and voices" refers to a method for collecting children's facial expressions and voices in real time using a camera or microphone.

[1350] The "means for the server to analyze the collected data and detect the emotional state of the child" refers to a method in which the server uses an emotion recognition algorithm to detect the emotional state of the child based on the collected data on facial expressions and voice.

[1351] The "means for generating and transmitting an alert to a terminal based on an emotional state" is a method for generating an appropriate alert message based on the detected emotional state and transmitting it to the user's terminal.

[1352] "Means for collecting data on workers' facial expressions and voices" refers to a method for collecting data on the facial expressions and voices of workers working in factories using cameras and microphones.

[1353] "Means for the server to analyze collected data and detect the emotional state of the worker" refers to a method in which the server performs emotional analysis based on collected data on the worker's facial expressions and voice to detect the worker's emotional state.

[1354] The "means for generating advice on relaxation activities and rest based on the emotional state and transmitting the advice to the terminal" is a method for generating advice to suggest appropriate relaxation and rest methods to the worker based on the detected emotional state and transmitting the advice to the worker's terminal.

[1355] This system utilizes childcare information entered by users via their devices, and the server provides optimal childcare advice. It also has the ability to collect and analyze facial and vocal data from children, users, and workers to detect their respective emotional states. This improves the quality of childcare and facilitates parent-child communication and worker wellness management.

[1356] Specifically, the server implements these functions using the following hardware and software:

[1357] Hardware

[1358] 1. Devices (smartphones, tablets): Used by users to input childcare information and worker emotional information.

[1359] 2. Camera: Used to collect facial expression data from children and workers.

[1360] 3. Microphone: Used to collect voice data from children and workers.

[1361] software

[1362] 1. TensorFlow: Runs emotion recognition algorithms to analyze the collected facial expression data.

[1363] 2. OpenCV: Processes camera images.

[1364] 3. pyaudio: Acquires audio data.

[1365] 4. Requests: A communication method for sending collected data to the server.

[1366] 5. Natural language processing engine: Analyzes questions about childcare entered by users and generates optimal advice.

[1367] To provide parenting advice, the server first receives questions and growth record data entered by the user from their device. The received information is stored in a database and analyzed using a natural language processing engine. Based on the analysis results, optimal parenting advice is then generated and sent to the user's device.

[1368] Additionally, facial and vocal data collected from the device's camera and microphone is used to analyze the child or worker's emotional state in real time, and alerts, relaxation activities, and break advice are generated and sent to the user's or worker's device based on the analysis results.

[1369] For example, if a worker looks exhausted while working in a factory, and the facial expression data captured by the camera indicates "fatigue," the system will generate a notification saying, "We recommend you take a 15-minute break," and send it to the device.

[1370] Examples of prompts include:

[1371] "Generate appropriate break notifications based on employee facial expression data and emotion analysis results. For example, suggest a short break if the employee feels fatigued."

[1372] This will provide a comprehensive support system that not only provides childcare support but also manages worker wellness.

[1373] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1374] Step 1:

[1375] The user inputs questions about childcare and growth record data through the terminal. The input data is temporarily saved and prepared for transmission to the server. The input includes questions about childcare and growth record data, and the output is encrypted transmission data.

[1376] Step 2:

[1377] The terminal sends encrypted data to the server. The server decrypts the received data and stores the contents in a database. The input is encrypted data, and the output is decrypted data stored in the database.

[1378] Step 3:

[1379] The server analyzes the user's question using a natural language processing engine. Based on the analysis results, it searches a database for the most appropriate childcare advice and generates customized advice. The user's question is the input, and customized advice is generated as the output.

[1380] Step 4:

[1381] The generated parenting advice is sent by the server to the terminal and displayed to the user. The customized advice is the input and is displayed on the user's terminal as the output.

[1382] Step 5:

[1383] Facial and voice data of children and workers is collected through the device's camera and microphone. The collected data is periodically sent to a server. Facial and voice data is input, and data sent to the server is generated as output.

[1384] Step 6:

[1385] The server applies an emotion recognition algorithm to the received facial and voice data to identify the emotional state of the child or worker. The input is facial and voice data, and the output is an analysis of the emotional state.

[1386] Step 7:

[1387] Based on the emotion analysis results, the server generates appropriate alert messages and advice on relaxation activities and breaks. The input is the analysis result of the emotional state, and the output is the generated alert message or advice.

[1388] Step 8:

[1389] The generated alert messages and advice are sent from the server to the terminal and displayed to the user or worker in the appropriate notification format. The input is an alert message or advice, and the output is a notification that is displayed on the terminal.

[1390] 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 a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1391] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1392] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1393] [Third embodiment]

[1394] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1395] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1396] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1397] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1398] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1399] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1400] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1401] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1402] The specific processing program 56 is an example of a "program" according to the technology of the present 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.

[1403] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1404] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1405] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. 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."

[1406] System Overview

[1407] This invention is a system in which a server uses childcare information entered by a user through a terminal to provide optimal childcare advice. It also has a function to collect and analyze data on a child's facial expressions and voice to detect their emotional state. It also includes a function to accumulate and analyze growth record data and provide notifications and information according to the child's developmental stage. This system also provides advice based on the latest scientific data related to childcare.

[1408] User registration and initial setup process

[1409] First, the user downloads and installs the AI ​​childcare assistant app from the app store. Next, they launch the app and enter basic information such as their child's name, age, and gender on the user registration screen. The device temporarily stores the entered information and prepares the data for login authentication. Once preparation is complete, the device encrypts the data and sends it to the server. The server receives it, stores it in a database, and sends a notification to the device that registration is complete.

[1410] Real-time childcare consultation process

[1411] When a user enters a question about childcare into the app and presses the send button, the question is sent from the device to the server. The server uses a natural language processing engine to analyze the received question. It then searches a database for the most appropriate advice according to categories such as breastfeeding, discipline, and health management, and generates customized advice based on the user's profile information. The generated advice is sent to the device and displayed to the user.

[1412] Sentiment Analysis Function Process

[1413] The device collects facial and voice data from the child through a camera and microphone. This data is periodically sent to the server. The server then applies an emotion recognition algorithm to the received data to identify the child's emotional state, such as smiling, anxious, or angry. If a change in the emotional state is detected, the server generates an appropriate alert message and sends it to the device. The user is then notified of this alert.

[1414] The process of tracking and storing growth records

[1415] The user enters their child's daily growth data (height, weight, dietary habits, etc.) into the app. The device sends the entered data to the server, which stores it in a database. Based on the stored data, the server generates a growth graph and sends it to the device. The generated graph is displayed visually to the user.

[1416] Developmentally appropriate notification and information processes

[1417] The server periodically analyzes the growth record data and selects appropriate information according to the child's developmental stage. This information is generated in the form of a notification and sent to the device. The device then displays this information to the user, making it useful for childcare.

[1418] A process for providing advice based on the latest scientific data related to childcare

[1419] The server periodically loads the latest scientific data related to childcare into its database and generates advice based on the latest scientific research. When a user asks a specific question about childcare, the server generates advice based on this information and sends it to the device. The device then displays the latest advice to the user.

[1420] Specific examples of programs

[1421] For example, suppose a user inputs the question, "My baby's crying at night is so bad I'm worried. Is there anything I can do about it?" The device sends this question to the server. The server analyzes the question and searches a database for the best solution for dealing with the crying. It generates specific advice, such as "Keep the room at the right temperature and humidity" or "Try playing calming music," and sends it to the device. The device then displays this to the user.

[1422] In this way, the system of the present invention provides comprehensive support for users to solve various child-rearing problems.

[1423] The processing flow will be explained below.

[1424] User registration and initial setup process

[1425] Step 1:

[1426] The user downloads and installs the AI ​​childcare assistant app from the app store.

[1427] Step 2:

[1428] The user launches the app and proceeds to the user registration screen.

[1429] Step 3:

[1430] The user enters basic information such as the child's name, age, and gender.

[1431] Step 4:

[1432] The device temporarily stores the entered information and prepares the data for login authentication.

[1433] Step 5:

[1434] Once the terminal is ready, it encrypts the entered information and sends it to the server.

[1435] Step 6:

[1436] The server stores the received data in a database.

[1437] Step 7:

[1438] The server sends a notification of registration completion to the terminal.

[1439] Step 8:

[1440] The device will inform the user that registration is complete.

[1441] Real-time childcare consultation process

[1442] Step 1:

[1443] Users enter parenting questions into the app.

[1444] Step 2:

[1445] The terminal sends a question to the server.

[1446] Step 3:

[1447] The server analyzes the question received using a natural language processing engine.

[1448] Step 4:

[1449] The server identifies categories such as breastfeeding, discipline, and health care based on the questions.

[1450] Step 5:

[1451] The server searches a database for appropriate advice based on the question and the user's profile information, and generates customized advice.

[1452] Step 6:

[1453] The server transmits the generated advice to the terminal.

[1454] Step 7:

[1455] The device displays the advice to the user.

[1456] Sentiment Analysis Function Process

[1457] Step 1:

[1458] The device activates the camera and microphone to collect the child's facial expressions and voice.

[1459] Step 2:

[1460] The terminal transmits the collected data to the server.

[1461] Step 3:

[1462] The server analyzes the received data and applies emotion recognition algorithms.

[1463] Step 4:

[1464] The server identifies the child's emotional state (e.g., smiling, anxious, angry).

[1465] Step 5:

[1466] The server generates an alert message based on the emotional state.

[1467] Step 6:

[1468] The server sends an alert message to the terminal.

[1469] Step 7:

[1470] The device will notify the user of the alert message.

[1471] The process of tracking and storing growth records

[1472] Step 1:

[1473] The user enters their child's daily growth data (height, weight, diet, etc.) into the app.

[1474] Step 2:

[1475] The terminal transmits the input growth data to the server.

[1476] Step 3:

[1477] The server stores the growth data in a database.

[1478] Step 4:

[1479] The server generates a growth graph based on the stored data.

[1480] Step 5:

[1481] The server transmits the generated growth graph to the terminal.

[1482] Step 6:

[1483] The device displays a growth graph to the user.

[1484] Developmentally appropriate notification and information processes

[1485] Step 1:

[1486] The server periodically analyzes the growth record data.

[1487] Step 2:

[1488] The server generates notification information according to the child's developmental stage.

[1489] Step 3:

[1490] The server sends the notification information to the terminal.

[1491] Step 4:

[1492] The device displays the notification to the user.

[1493] Providing the latest science-based parenting advice

[1494] Step 1:

[1495] The server periodically loads the latest childcare-related scientific data into the database.

[1496] Step 2:

[1497] The server generates advice using the latest data based on the questions about childcare received.

[1498] Step 3:

[1499] The server sends the advice to the terminal.

[1500] Step 4:

[1501] The device displays the advice to the user.

[1502] In this way, the system of the present invention realizes a process for supporting the user in raising their children.

[1503] Example 1

[1504] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1505] Conventional childcare support systems only allow users to ask questions about childcare and receive answers as they arise. They lack the ability to provide customized advice tailored to individual situations and the child's developmental stage. Furthermore, there are no systems that can analyze a child's emotional state in real time and provide appropriate responses based on those changes. Furthermore, functions for managing growth records and providing advice based on the latest scientific data related to childcare are limited. This creates challenges that make it difficult for parents to select appropriate childcare methods.

[1506] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1507] In this invention, the server includes means for receiving child-rearing information input by a user through a terminal, means for analyzing the received information to generate optimal child-rearing advice, means for transmitting the generated advice to the terminal and displaying it to the user, means for collecting data on the child's facial expressions and voice, means for analyzing the collected data to detect the child's emotional state, means for generating an alert based on the emotional state and transmitting it to the terminal, means for the user to input growth record data into the terminal, means for accumulating and analyzing the input growth record data and generating a growth graph, means for transmitting the growth graph to the terminal and displaying it to the user, means for analyzing the growth record data and generating notifications and information according to the child's developmental stage, and means for transmitting the notifications and information to the terminal and displaying them to the user. This enables users to receive comprehensive support in real time to solve various child-rearing issues.

[1508] "User" refers to a person such as a parent or guardian who uses the childcare support system.

[1509] "Terminal" refers to an electronic device used by a user, such as a smartphone, tablet, or computer.

[1510] "Server" refers to a central computer system that stores and processes data.

[1511] "Childcare information" refers to all information related to childcare, such as breastfeeding, discipline, health care, and growth records.

[1512] A "natural language processing engine" refers to an algorithm or software for analyzing text data entered by a user.

[1513] "Advice" refers to the best parenting advice and solutions.

[1514] "Child's facial expression and voice data" refers to the child's facial expression and voice information obtained through a camera and microphone.

[1515] "Emotional state" refers to the child's emotional changes and current emotional situation (e.g., smiling, anxious, angry).

[1516] An "alert message" refers to a message that notifies the user of important information or a change in status.

[1517] "Growth record data" refers to data relating to a child's daily growth (e.g., height, weight, dietary content).

[1518] A "growth graph" refers to a graph that visually represents a child's growth, generated based on growth record data.

[1519] "Notification" refers to a message or alert intended to inform the user of specific information or attention.

[1520] "Childcare-related scientific data" refers to information and data about childcare that is based on the latest scientific research.

[1521] "Analysis results" refers to the output results of data analyzed by the server.

[1522] A "generative AI model" refers to a computer model that uses artificial intelligence to analyze data and generate appropriate results or advice.

[1523] A "prompt sentence" refers to a specific question or instruction that a user enters into a system.

[1524] A specific embodiment of the childcare support system of the present invention will be described below. In this system, a server provides optimal childcare advice based on childcare information entered by a user through a terminal. Furthermore, the system is equipped with functions to collect and analyze data on a child's facial expressions and voice to detect their emotional state, and to accumulate and analyze growth record data to provide notifications and information according to the child's developmental stage.

[1525] User registration and initial setup process

[1526] First, the user downloads and installs the AI ​​childcare assistant app from the app store. Next, they launch the app and enter basic information such as their child's name, age, and gender on the user registration screen. The device temporarily stores this information and prepares the data for login authentication. Once preparation is complete, the device encrypts the data and sends it to the server. The server stores the received data in a database and sends a notification of registration completion to the device. The device receives the notification and displays a message informing the user that registration is complete.

[1527] Real-time childcare consultation process

[1528] When a user enters a question about childcare into the app and presses the send button, the device sends the question data to the server. The server analyzes the received question using a natural language processing engine (e.g., GPT-3). The server then searches a database for appropriate advice from categories such as breastfeeding, discipline, and health care based on the question, and generates customized advice using the user's profile information. The generated advice is sent to the device, which displays it to the user.

[1529] Sentiment Analysis Function Process

[1530] The device collects data on the child's facial expressions and voice through a camera and microphone. The collected data is periodically sent to a server. The server analyzes the received data using an emotion recognition algorithm (e.g., facial expression analysis software) to identify the child's emotional state (e.g., smiling, anxious, or angry). If there is a significant change in the emotional state, the server generates an appropriate alert message and sends it to the device. The device receives the alert message and notifies the user.

[1531] The process of tracking and storing growth records

[1532] The user enters their child's daily growth data (height, weight, dietary habits, etc.) into the app. The device sends the entered data to the server, which stores it in a database. Based on the stored data, the server generates a growth graph and sends it to the device. The device then visually displays the growth graph to the user, allowing them to easily understand their child's growth.

[1533] Developmentally appropriate notification and information processes

[1534] The server periodically analyzes the growth record data and selects appropriate information from the database according to the child's developmental stage. This information is generated in the form of a notification and sent to the device. The device displays this information to the user, providing support for the user to take appropriate parenting actions.

[1535] A process for providing advice based on the latest scientific data related to childcare

[1536] The server periodically loads the latest childcare-related scientific data into a database and generates advice based on the latest scientific research. When a user inputs and submits a specific childcare question, the device sends the question to the server. The server receives the question, generates advice based on the latest scientific research, and sends it to the device. The device displays the latest advice to the user.

[1537] Examples of specific examples and prompts

[1538] For example, if a user inputs a question such as "My baby's crying at night is so bad I'm worried. Is there anything I can do?", the device will send this question to the server. The server will analyze the question and generate specific advice, such as "Keep the room at an appropriate temperature and humidity" or "Try listening to calming music," and send it to the device. The device will then display this to the user.

[1539] In this way, the system of the present invention provides comprehensive support for users to solve various child-rearing problems.

[1540] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1541] Program processing steps

[1542] User registration and initial setup process

[1543] Step 1:

[1544] The user downloads and installs the AI ​​childcare assistant app from the app store.

[1545] Input: User downloads and installs the app

[1546] Output: Installed app

[1547] Step 2:

[1548] The user launches the app and enters basic information such as the child's name, age, and gender on the user registration screen.

[1549] Input: Basic information such as name, age, and gender

[1550] Output: Basic information entered

[1551] Step 3:

[1552] The device temporarily stores the entered information and prepares the data for login authentication.

[1553] Input: Basic information entered

[1554] Output: Temporarily saved authentication data

[1555] Step 4:

[1556] Once the device is ready, it encrypts the data and sends it to the server.

[1557] Input: Temporarily saved authentication data

[1558] Output: Encrypted data

[1559] Step 5:

[1560] The server stores the received data in a database and sends a notification of registration completion to the terminal.

[1561] Input: Encrypted data

[1562] Output: User information saved in the database, registration completion notification

[1563] Step 6:

[1564] The terminal receives the notification and displays a message to the user informing them of the completion of registration.

[1565] Input: Notification of registration completion

[1566] Output: Display of registration completion message

[1567] Real-time childcare consultation process

[1568] Step 1:

[1569] The user enters a question about childcare into the app and presses the send button.

[1570] Input: User question

[1571] Output: Generate question data

[1572] Step 2:

[1573] The terminal transmits the question data to the server.

[1574] Input: Question data

[1575] Output: Submitted question data

[1576] Step 3:

[1577] The server analyzes the received question using a natural language processing engine (e.g., GPT-3).

[1578] Input: Submitted question data

[1579] Output: Parsed question

[1580] Step 4:

[1581] Based on the question, the server searches a database for appropriate advice in categories such as breastfeeding, discipline, and health care.

[1582] Input: Parsed question content

[1583] Output: Advice data as search results

[1584] Step 5:

[1585] The server uses the user's profile information to generate customized advice.

[1586] Input: Advice data, user profile information

[1587] Output: Customized advice

[1588] Step 6:

[1589] The server transmits the generated advice to the terminal.

[1590] Input: Customized Advice

[1591] Output: Advice sent

[1592] Step 7:

[1593] The terminal receives the advice and displays it to the user.

[1594] Input: Submitted advice

[1595] Output: Advice displayed to the user

[1596] Sentiment Analysis Function Process

[1597] Step 1:

[1598] The device collects data on the child's facial expressions and voice through a camera and microphone.

[1599] Input: Child's facial expressions and voice

[1600] Output: Collected data

[1601] Step 2:

[1602] The terminal periodically transmits this data to the server.

[1603] Input: Collected data

[1604] Output: Data sent

[1605] Step 3:

[1606] The server analyzes the received data using emotion recognition algorithms.

[1607] Input: Data sent

[1608] Output: Parsed emotional state data

[1609] Step 4:

[1610] The server determines the emotional state of the child.

[1611] Input: Parsed emotional state data

[1612] Output: Identified emotional state (e.g., smiling, anxious, angry)

[1613] Step 5:

[1614] If the server detects a significant change in emotion, it generates an appropriate alert message and sends it to the device.

[1615] Input: Identified emotional state

[1616] Output: The generated alert message

[1617] Step 6:

[1618] The terminal receives the alert message and notifies the user.

[1619] Input: The generated alert message

[1620] Output: User notification

[1621] The process of tracking and storing growth records

[1622] Step 1:

[1623] The user enters their child's daily growth data (height, weight, diet, etc.) into the app.

[1624] Input: Child's daily growth data

[1625] Output: Input growth data

[1626] Step 2:

[1627] The terminal transmits the input data to the server.

[1628] Input: Input growth data

[1629] Output: Transmitted growth data

[1630] Step 3:

[1631] The server receives the data and stores it in a database.

[1632] Input: Submitted growth data

[1633] Output: Saved growth data

[1634] Step 4:

[1635] The server generates a growth graph based on the accumulated data.

[1636] Input: Saved growth data

[1637] Output: Generated growth graph

[1638] Step 5:

[1639] The server sends the growth graph to the terminal.

[1640] Input: Generated growth graph

[1641] Output: Growth graph sent

[1642] Step 6:

[1643] The terminal visually displays the growth graph to the user.

[1644] Input: Submitted growth graph

[1645] Output: Growth graph displayed to the user

[1646] Developmentally appropriate notification and information processes

[1647] Step 1:

[1648] The server periodically analyzes the growth record data.

[1649] Input: Saved growth record data

[1650] Output: Analysis results

[1651] Step 2:

[1652] Based on the analysis results, the server selects appropriate information from the database according to the child's developmental stage.

[1653] Input: Analysis results

[1654] Output: Selected information

[1655] Step 3:

[1656] The server generates the selected information in a notification format and transmits it to the terminal.

[1657] Input: Selected information

[1658] Output: Notification format generation

[1659] Step 4:

[1660] The device receives the notification and displays it to the user.

[1661] Input: Notification format information

[1662] Output: What is displayed to the user

[1663] A process for providing advice based on the latest scientific data related to childcare

[1664] Step 1:

[1665] The server periodically loads the latest childcare-related scientific data into the database.

[1666] Input: The latest childcare-related scientific data

[1667] Output: Updated database

[1668] Step 2:

[1669] The user inputs and submits a specific childcare question.

[1670] Input: User's specific question

[1671] Output: Generate question data

[1672] Step 3:

[1673] The terminal sends a question to the server.

[1674] Input: Question data

[1675] Output: Submitted question data

[1676] Step 4:

[1677] The server receives the question and generates advice based on the latest scientific research.

[1678] Input: Submitted query data, updated database

[1679] Output: Generated advice

[1680] Step 5:

[1681] The server sends the generated advice to the terminal.

[1682] Input: Generated advice

[1683] Output: Advice sent

[1684] Step 6:

[1685] The terminal displays the advice to the user.

[1686] Input: Submitted advice

[1687] Output: What is displayed to the user

[1688] (Application example 1)

[1689] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1690] While conventional childcare support systems can provide advice based on a child's growth record and emotional state, they are unable to provide specific dietary advice based on a child's nutritional status or food preferences. While meal suggestions to supplement a child's vitamin and mineral deficiencies are particularly important in childcare, no system existed that could provide such information in real time. Another challenge was linking this information with food delivery apps to make daily meal choices easier.

[1691] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1692] In this invention, the server includes means for receiving child-rearing information input by the user through the terminal, means for analyzing the received information and generating optimal child-rearing advice, means for transmitting the generated advice to the terminal and displaying it to the user, means for collecting data on the child's facial expressions and voice, means for analyzing the collected data and detecting the child's emotional state by the server, means for generating an alert based on the emotional state and transmitting it to the terminal, means for inputting and receiving dietary information through the terminal, means for analyzing the input diet-related information and growth record data by the server and generating optimal dietary advice based on the child's nutritional status, and means for transmitting the generated dietary advice to the terminal and displaying it to the user. This makes it possible to provide specific dietary suggestions based on the child's nutritional status and dietary preferences, making it easier for the child to make daily meal choices.

[1693] "Childcare information entered by the user through a device" refers to a function that allows the user to use a mobile device or computer to enter information such as questions related to childcare, growth records, and dietary details.

[1694] "Server" refers to a computer system on a network that has the function of receiving, analyzing, and storing childcare information and growth record data sent by users.

[1695] "Optimal child-rearing advice" refers to the most appropriate and useful guidance and suggestions regarding child-rearing that are provided based on the results of analyzing the child-rearing information entered.

[1696] "Means for collecting data on children's facial expressions and voices" refers to the function of using the device's built-in camera and microphone to record children's facial expressions and voices and send that information to a server.

[1697] "Means for detecting emotional states" refers to a function that analyzes collected data on a child's facial expressions and voice and identifies their emotional state using an algorithm that identifies emotions such as smiling, anxious, or angry.

[1698] "Means for generating and sending alerts to the device" refers to the function of generating appropriate warnings or notifications and sending them to the user's device when a change in emotional state is detected.

[1699] "Means for inputting and receiving information about meals" refers to a function whereby a user inputs information about the child's diet and nutritional status into a terminal, and the server receives that information.

[1700] "Means for generating dietary advice" refers to a function that generates the most appropriate dietary suggestions based on the nutritional status and dietary preferences based on the input diet-related information and growth record data.

[1701] "Means for transmitting the generated dietary advice to the terminal and displaying it to the user" refers to a function for transmitting the generated dietary advice to the user's terminal and displaying the information so that the user can visually confirm it.

[1702] The present invention is a system in which a server generates optimal advice and provides it to users using information entered by users in relation to a childcare support system. This system can provide comprehensive childcare support using information on childcare, the child's emotional state, growth records, and even information on diet.

[1703] System Overview

[1704] The present invention has a function that allows users to input information about childcare, their child's emotional state, growth records, and dietary information using a mobile device or computer. The input information is sent to a server, which analyzes the information to generate optimal childcare and dietary advice and sends it to the user's device.

[1705] User registration and initial setup process

[1706] The user downloads and installs the application. After installation, the user enters basic information such as the child's name, age, and gender on the initial setup screen. The entered information is temporarily saved, encrypted, and sent to the server. The server receives it and stores it in a database.

[1707] The process of providing parenting advice

[1708] When a user enters a question about childcare into the app and presses the send button, the question is sent from the device to the server. The server analyzes the received question and generates optimal childcare advice. The advice is then sent to the device and displayed to the user.

[1709] Sentiment Analysis Function Process

[1710] The device collects facial and vocal data from the child through a camera and microphone. This data is periodically sent to the server, which applies emotion recognition algorithms to identify the child's emotional state. If a change is detected, an alert message is generated and sent to the device. The user is notified of this alert.

[1711] The process of tracking and storing growth records

[1712] The user enters daily growth data (height, weight, dietary details, etc.) into the app. The device sends the entered data to the server, which stores it in a database. A growth graph is generated based on the stored data and sent to the device. The generated graph is displayed to the user.

[1713] The process for providing dietary advice

[1714] The user enters information about their child's diet into the app. The entered diet information is sent from the device to the server. The server receives this information and analyzes the diet-related information and growth record data. Optimal dietary advice is generated based on the child's nutritional status and sent to the device. The advice is then displayed to the user.

[1715] Program operation and concrete examples

[1716] The server uses a database system (e.g., MySQL) and a natural language processing engine (e.g., Spacy or NLTK). The device is a smartphone or tablet. By processing and calculating data, it is possible to provide individual advice to the user.

[1717] For example, if a user enters information such as "Taro, 4 years old, dislikes vegetables," the app will provide advice such as "If you are concerned about vitamin D deficiency, we recommend this menu."

[1718] Example prompts to input to the generative AI model

[1719] "What menu would you suggest for a 4-year-old who hates vegetables and is deficient in vitamin D?"

[1720] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1721] Step 1:

[1722] The user installs the application and performs initial setup. The user enters basic information about the child (such as name, age, and gender), which is temporarily stored on the device. The entered information is encrypted and sent to the server. The server receives this information and stores it in a database. As an output, a notification that registration is complete is sent to the device.

[1723] Step 2:

[1724] The user enters a question about childcare into the app and presses the send button. The device then sends the question to the server. The server receives the question and analyzes it using a natural language processing engine. Based on the analysis results, it searches a database for the most appropriate childcare advice and generates customized advice. The generated advice is then sent to the device and displayed to the user.

[1725] Step 3:

[1726] The device uses a camera and microphone to collect data on the child's facial expressions and voice. The collected data is periodically sent to the server. The server applies an emotion recognition algorithm to identify the child's emotional state (e.g., smiling, anxious, angry, etc.). If a change in the emotional state is detected, the server generates an alert message and sends it to the device. The user receives this alert.

[1727] Step 4:

[1728] The user enters daily growth data (height, weight, dietary details, etc.) into the app. The device sends the entered data to the server. The server receives it and stores it in a database. The server generates a growth graph and sends it to the device. The generated graph is displayed to the user.

[1729] Step 5:

[1730] The user enters information about their diet into the app. The device then sends the entered diet information to the server. The server receives and analyzes the diet-related information and growth record data, and generates optimal dietary advice based on the user's nutritional status. The generated dietary advice is then sent to the device and displayed to the user. For example, specific suggestions such as "If you are concerned about vitamin D deficiency, we recommend this menu" are provided.

[1731] Input and Output Complement

[1732] Step 1:

[1733] Input: Child's basic information (name, age, gender)

[1734] Output: Notification of successful registration

[1735] Step 2:

[1736] Input: Parenting Questions

[1737] Output: Best parenting advice

[1738] Step 3:

[1739] Input: Child's facial expression and voice data

[1740] Output: Emotional state alert message

[1741] Step 4:

[1742] Input: Growth data

[1743] Output: Growth graph

[1744] Step 5:

[1745] Input: Meal information

[1746] Output: Optimal dietary advice

[1747] Example prompts to input to the generative AI model

[1748] "What menu would you suggest for a 4-year-old who hates vegetables and is deficient in vitamin D?"

[1749] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1750] System Overview

[1751] This invention is a system in which a server uses childcare information entered by a user via a terminal to provide optimal childcare advice. It also has a function that collects and analyzes facial and vocal data from the child and the user to detect the emotional state of both parties. This improves the quality of childcare and facilitates smoother communication between parents and children. It also includes a function that accumulates and analyzes growth record data and provides notifications and information according to the developmental stage. This system also provides advice based on the latest scientific data related to childcare.

[1752] User registration and initial setup process

[1753] First, the user downloads and installs the AI ​​childcare assistant app from the app store. Next, they launch the app and enter their child's name, age, gender, and other basic user information on the user registration screen. The device temporarily stores the entered information and prepares the data for login authentication. Once preparation is complete, the device encrypts the data and sends it to the server. The server receives it, stores it in a database, and sends a notification to the device that registration is complete.

[1754] Real-time childcare consultation process

[1755] When a user enters a question about childcare into the app and presses the send button, the question is sent from the device to the server. The server uses a natural language processing engine to analyze the received question. It then searches a database for the most appropriate advice according to categories such as breastfeeding, discipline, and health management, and generates customized advice based on the user's profile information. The generated advice is sent to the device and displayed to the user.

[1756] Sentiment Analysis Function Process

[1757] The device collects facial and voice data of the child and user through a camera and microphone. This data is periodically sent to the server. The server applies an emotion recognition algorithm to the received data to identify the child's and user's emotional state, such as smile, anxiety, or anger. If a change in emotional state is detected, the server generates an appropriate alert message and sends it to the device. The user is notified of this alert.

[1758] User Emotion Engine Process

[1759] This adds a function to analyze the user's emotional state using an emotion engine that recognizes the user's emotions. The device's sensors are used to collect the user's facial expressions and voice in real time, and the data is sent to a server. The server then analyzes the user's emotional state based on the collected data and generates advice offering appropriate mindfulness exercises and relaxation techniques. The generated advice is sent to the device and displayed to the user.

[1760] The process of tracking and storing growth records

[1761] The user enters their child's daily growth data (height, weight, dietary habits, etc.) into the app. The device sends the entered data to the server, which stores it in a database. Based on the stored data, the server generates a growth graph and sends it to the device. The generated graph is displayed visually to the user.

[1762] Developmentally appropriate notification and information processes

[1763] The server periodically analyzes the growth record data and generates notification information according to the child's developmental stage. This information is generated in the form of a notification and sent to the device. The device displays this information to the user, making it useful for childcare.

[1764] Providing the latest science-based parenting advice

[1765] The server periodically loads the latest scientific data related to childcare into its database. When a user asks a specific question about childcare, the server generates advice based on this data and sends it to the device. The device then displays the latest advice to the user.

[1766] Specific examples of programs

[1767] For example, suppose a user inputs the question, "My baby's crying at night is so bad I'm worried. Is there anything I can do about it?" The device sends this question to the server. The server analyzes the question and searches a database for the best solution for dealing with the crying. It generates specific advice, such as "Keep the room at the right temperature and humidity" or "Try playing calming music," and sends it to the device. The device then displays this to the user.

[1768] Next, the device collects the child's facial expressions and voice, and the server analyzes the data to detect the child's state of anxiety. Based on this, the server generates an alert message such as, "Your child may be prone to anxiety recently. Let's spend some time relaxing together," and sends it to the device. The device then displays this alert to the user.

[1769] Furthermore, if the user's emotion engine detects that the user is feeling stressed, the server generates advice such as "Take a deep breath and take a few minutes to relax" and sends it to the device, which then displays it to the user. In this way, the system provides a wide range of support for the user's child-rearing needs.

[1770] The processing flow will be explained below.

[1771] User registration and initial setup process

[1772] Step 1:

[1773] The user downloads and installs the AI ​​childcare assistant app from the app store.

[1774] Step 2:

[1775] The user launches the app and proceeds to the user registration screen.

[1776] Step 3:

[1777] The user enters the child's name, age, gender, and basic user information.

[1778] Step 4:

[1779] The device temporarily stores the entered information and prepares the data for login authentication.

[1780] Step 5:

[1781] Once the device is ready, it encrypts the entered information and sends it to the server.

[1782] Step 6:

[1783] The server receives the data and stores it in a database.

[1784] Step 7:

[1785] The server sends a notification of registration completion to the terminal.

[1786] Step 8:

[1787] The device will inform the user that registration is complete.

[1788] Real-time childcare consultation process

[1789] Step 1:

[1790] Users enter parenting questions into the app.

[1791] Step 2:

[1792] The terminal sends a question to the server.

[1793] Step 3:

[1794] The server analyzes the question using a natural language processing engine.

[1795] Step 4:

[1796] The server identifies categories such as breastfeeding, discipline, and health care based on the questions.

[1797] Step 5:

[1798] The server searches a database for appropriate advice based on the question and the user's profile information, and generates customized advice.

[1799] Step 6:

[1800] The server transmits the generated advice to the terminal.

[1801] Step 7:

[1802] The device displays the advice to the user.

[1803] Sentiment Analysis Function Process

[1804] Step 1:

[1805] The device activates the camera and microphone to collect facial expressions and voices of the child and the user.

[1806] Step 2:

[1807] The terminal transmits the collected data to the server.

[1808] Step 3:

[1809] The server analyzes the received data and applies emotion recognition algorithms.

[1810] Step 4:

[1811] The server identifies the emotional state of the child and the user, for example, smiling, anxious, angry, etc.

[1812] Step 5:

[1813] The server generates an alert message based on the emotional state.

[1814] Step 6:

[1815] The server sends an alert message to the terminal.

[1816] Step 7:

[1817] The device will notify the user of the alert message.

[1818] User Emotion Engine Process

[1819] Step 1:

[1820] The device collects the user's voice and facial expression data.

[1821] Step 2:

[1822] The terminal transmits the collected data to the server.

[1823] Step 3:

[1824] The server analyzes the data and performs emotion recognition.

[1825] Step 4:

[1826] The server identifies the user's emotional state (e.g., stress, anxiety, happiness).

[1827] Step 5:

[1828] The server generates advice on mindfulness exercises and relaxation techniques based on the user's emotional state.

[1829] Step 6:

[1830] The server transmits the generated advice to the terminal.

[1831] Step 7:

[1832] The device displays the advice to the user.

[1833] The process of tracking and storing growth records

[1834] Step 1:

[1835] The user enters their child's daily growth data (height, weight, diet, etc.) into the app.

[1836] Step 2:

[1837] The terminal transmits the input growth data to the server.

[1838] Step 3:

[1839] The server stores the growth data in a database.

[1840] Step 4:

[1841] The server generates a growth graph based on the stored data.

[1842] Step 5:

[1843] The server transmits the generated growth graph to the terminal.

[1844] Step 6:

[1845] The device displays a growth graph to the user.

[1846] Developmentally appropriate notification and information processes

[1847] Step 1:

[1848] The server periodically analyzes the growth record data.

[1849] Step 2:

[1850] The server generates notification information according to the child's developmental stage.

[1851] Step 3:

[1852] The server sends the notification information to the terminal.

[1853] Step 4:

[1854] The device displays the notification to the user.

[1855] Providing the latest science-based parenting advice

[1856] Step 1:

[1857] The server periodically loads the latest childcare-related scientific data into the database.

[1858] Step 2:

[1859] The server generates advice using the latest data based on the questions about childcare received.

[1860] Step 3:

[1861] The server sends the advice to the terminal.

[1862] Step 4:

[1863] The device displays the advice to the user.

[1864] In this way, the system of the present invention realizes a process for supporting the user in raising their children.

[1865] Example 2

[1866] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1867] Conventional childcare support systems simply provide information about childcare, but lack real-time support for actual childcare environments. Furthermore, they lack a mechanism for accurately grasping the emotional state of parents and children and providing specific advice or warnings based on that information, making it difficult to improve the quality of childcare and facilitate smooth communication between parents and children. Furthermore, they lack the ability to provide childcare advice that reflects the latest scientific findings or notification functions that effectively utilize child growth records.

[1868] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for receiving child-rearing information input by a user through an information processing device; means for analyzing the received information by the information processing device to generate optimal child-rearing support information; means for transmitting the generated support information to the information processing device and displaying it to the user; means for collecting facial and voice data of the protected person; means for analyzing the collected data by the information processing device to detect the protected person's emotional state; means for generating warning information based on the emotional state and transmitting it to the information processing device; means for the user to input growth record data to the information processing device; means for the information processing device to accumulate and analyze the input growth record data and generate notifications and information according to the developmental stage; means for transmitting notifications and information according to the developmental stage to the information processing device and displaying them to the user; means for the information processing device to periodically update child-rearing-related scientific data and generate latest support information based on the analysis results; and means for transmitting the latest support information to the information processing device and displaying it to the user. This enables real-time child-rearing support and specific advice based on the protected person's emotional state, improving the quality of child-rearing and facilitating parent-child communication. In addition, it will provide reliable parenting advice based on the latest scientific knowledge, and will be able to provide notifications and information based on a child's growth based on growth records.

[1869] An "information processing device" is an electronic device that processes information entered by a user and communicates with a server.

[1870] "Childcare support information" refers to support information provided to users, such as advice and countermeasures regarding childcare, and information based on the latest scientific knowledge.

[1871] "Facial expression" refers to the movement and expression of the facial muscles of the protected person, and is visual data detected using a camera or other device.

[1872] "Audio" refers to the voice or sound emitted by the protected person or user, and is acoustic data detected using a microphone or the like.

[1873] "Emotional states" are psychological states that can be identified by analyzing facial expressions and voice, and include emotions such as joy, sadness, and anger.

[1874] "Warning information" is information that is generated based on the emotional state and that warns or advises the user.

[1875] "Growth record data" refers to information about a child's daily growth, including data such as height, weight, and dietary habits.

[1876] A "developmental stage" refers to a specific phase in a child's development and indicates the state of physical and psychological development.

[1877] "Notification" refers to a notice or message sent from the server to the information processing device, and provides the user with information useful for child-rearing.

[1878] "Scientific data related to childcare" refers to information collected based on scientific evidence, such as the latest research results and statistical data on childcare.

[1879] "Analysis results" refers to the conclusions or evaluations drawn by the server after analyzing the data received.

[1880] MODE FOR CARRYING OUT THE INVENTION

[1881] System Overview

[1882] The present invention is a system in which a server uses childcare information entered by a user through an information processing device to provide optimal childcare support information. Furthermore, the system has a function for collecting and analyzing facial and voice data of the user and the care recipient to detect the emotional state of both parties. This improves the quality of childcare and facilitates smoother communication between parents and children. It also includes a function for accumulating and analyzing growth record data and providing notifications and information according to the developmental stage. The system also provides support information based on the latest scientific data related to childcare.

[1883] Hardware and software configuration

[1884] Information processing devices: smartphones, tablets, PCs, etc.

[1885] Server: Cloud server for high-performance data processing

[1886] Camera: Built-in device camera or external camera

[1887] Microphone: Built-in microphone on device or external microphone

[1888] Natural language processing engine: AI model using Python and TensorFlow

[1889] Database: SQL or NoSQL database

[1890] Specific processing of the program

[1891] The user downloads the app using an information processing device and enters the child's name, age, gender, and basic information as the initial settings. The device temporarily stores this information, encrypts it, and sends it to the server. The server stores the received information in a database and notifies the device that registration is complete.

[1892] Real-time childcare consultation handling

[1893] The user enters a question about childcare into the app. For example, "My baby is crying a lot at night and it's bothering me. Is there anything I can do?" and presses the send button. The device sends this question to the server, which then analyzes the question using a natural language processing engine. The server then searches its database for the most appropriate childcare support information and generates a customized answer, taking into account the user's profile information. The generated support information is sent to the device and displayed to the user.

[1894] Sentiment analysis processing

[1895] The device uses a built-in camera and microphone to periodically collect facial expressions and voices of the protected person and the user. This data is periodically sent to the server, which then applies an emotion recognition algorithm to detect the child's emotional state. For example, if the server detects that the child is anxious, it generates a warning message such as "Your child may be prone to anxiety recently" and sends it to the device. The device then notifies the user of this message.

[1896] Track and save your growth record

[1897] Users enter their child's daily growth data (height, weight, dietary habits, etc.) into the app. The entered data is sent from the device to the server and stored in a database. The server then generates a growth graph based on this data and sends it to the device. The generated graph is then visually displayed to the user.

[1898] Notification and information provision according to developmental stage

[1899] The server periodically analyzes the growth record data and generates notifications based on the child's developmental stage, which are sent to the device and displayed to the user. For example, the notifications may include information on when to start solid food.

[1900] Providing advice based on the latest science

[1901] The server periodically loads the latest scientific data related to childcare into a database, and when a parent asks a specific question (e.g., "What is the latest vaccination schedule?"), it generates the latest support information based on that question. The generated information is sent to the device and displayed to the user.

[1902] As described above, this system supports improving the quality of child-rearing and smoother communication between parents and children by providing real-time child-rearing support, appropriate advice based on emotional states, and child-rearing information based on the latest scientific knowledge.

[1903] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1904] User Registration and Initial Setup Process

[1905] Step 1:

[1906] The user downloads the "AI Childcare Assistant App" from the app store and installs it on their information processing device.

[1907] Enter: Download and install the app

[1908] Output: App launch

[1909] Step 2:

[1910] The user launches the app and enters their child's name, age, gender, and basic information about themselves.

[1911] Input: Child's name, age, gender, basic user information

[1912] Output: Temporarily save input information

[1913] Step 3:

[1914] The device temporarily stores and encrypts the entered information.

[1915] Input: Basic information entered by the user

[1916] Output: Encrypted data

[1917] Step 4:

[1918] The device sends the encrypted data to the server.

[1919] Input: Encrypted data

[1920] Output: Data sent to server completed

[1921] Step 5:

[1922] The server stores the received data in a database and generates a registration completion notification.

[1923] Input: Received data

[1924] Output: Save to database, generate registration completion notification

[1925] Step 6:

[1926] The server sends a registration completion notice to the terminal, which displays it to the user.

[1927] Input: Registration completion notification

[1928] Output: Display a notification to the user

[1929] Real-time childcare consultation process

[1930] Step 1:

[1931] The user enters a question about childcare on the app and presses the send button.

[1932] Input: Question (e.g. "My baby is crying a lot at night. Is there anything I can do about it?")

[1933] Output: Transfer of question data

[1934] Step 2:

[1935] The terminal transmits the question data to the server.

[1936] Input: Question data

[1937] Output: Data sent to server completed

[1938] Step 3:

[1939] The server analyzes the received question data using a natural language processing engine.

[1940] Input: Question data

[1941] Output: Analysis results

[1942] Step 4:

[1943] The server searches the database for the most suitable childcare support information and generates a customized answer based on the user's profile information.

[1944] Input: Analysis results, user profile information

[1945] Output: Customized assistance information

[1946] Step 5:

[1947] The server transmits the generated support information to the terminal, which displays it to the user.

[1948] Input: Support information

[1949] Output: Display the answer to the user

[1950] The process of sentiment analysis

[1951] Step 1:

[1952] The device uses a built-in camera and microphone to periodically collect facial expressions and voices of the protected person and the user.

[1953] Input: facial expression data and voice data

[1954] Output: Collected data ready for transfer

[1955] Step 2:

[1956] The terminal transmits the collected data to the server.

[1957] Input: Collected data

[1958] Output: Data sent to server completed

[1959] Step 3:

[1960] The server analyzes the received data using emotion recognition algorithms to detect the emotional state.

[1961] Input: Collected data

[1962] Output: Emotional state detection result

[1963] Step 4:

[1964] The server generates alert information based on the emotional state.

[1965] Input: Emotional state detection result

[1966] Output: Warning information

[1967] Step 5:

[1968] The server transmits the warning information to the terminal, and the terminal notifies the user.

[1969] Input: Warning information

[1970] Output: Display a notification to the user

[1971] The process of tracking and storing growth records

[1972] Step 1:

[1973] The user enters their child's daily growth data (height, weight, diet, etc.) into the app.

[1974] Input: Growth data

[1975] Output: Temporarily saved on the device

[1976] Step 2:

[1977] The terminal transmits the input growth data to the server.

[1978] Input: Growth data

[1979] Output: Data sent to server completed

[1980] Step 3:

[1981] The server stores the growth data in a database.

[1982] Input: Received data

[1983] Output: Save to database

[1984] Step 4:

[1985] The server generates a growth graph based on the stored data.

[1986] Input: Growth data

[1987] Output: Growth graph

[1988] Step 5:

[1989] The server transmits the generated growth graph to the terminal, which displays it to the user.

[1990] Input: Growth graph

[1991] Output: Graphical display to the user

[1992] Developmentally appropriate notification and information processes

[1993] Step 1:

[1994] The server periodically analyzes the growth record data.

[1995] Input: Growth record data

[1996] Output: Analysis results

[1997] Step 2:

[1998] The server generates notification information according to the developmental stage.

[1999] Input: Analysis results

[2000] Output: Notification information

[2001] Step 3:

[2002] The server sends the notification information to the terminal, which displays it to the user.

[2003] Input: Notification information

[2004] Output: Display a notification to the user

[2005] A process for providing advice based on the latest science

[2006] Step 1:

[2007] The server periodically populates the database with childcare-related scientific data.

[2008] Input: Latest scientific data

[2009] Output: Database update

[2010] Step 2:

[2011] Users enter specific parenting questions into the app.

[2012] Input: Parenting question (e.g., "What is your current vaccination schedule?")

[2013] Output: Transfer of question data

[2014] Step 3:

[2015] The terminal transmits the question data to the server.

[2016] Input: Question data

[2017] Output: Data sent to server completed

[2018] Step 4:

[2019] The server analyzes the question and generates an answer from a database.

[2020] Input: Query data, latest scientific data

[2021] Output: Answer information

[2022] Step 5:

[2023] The server sends the generated answer to the terminal, which displays it to the user.

[2024] Input: Answer information

[2025] Output: Display the answer to the user

[2026] (Application example 2)

[2027] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[2028] Modern childcare is extremely complex, and parents and guardians need a lot of information and advice. However, many childcare support systems do not adequately consider individual needs and emotional states. Furthermore, workers in factories and other settings need support in managing their emotional states and taking appropriate breaks, but current systems do not adequately address this issue.

[2029] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving childcare information entered by a user through a terminal, means for analyzing the received information and generating optimal childcare advice, means for sending the generated advice to the terminal and displaying it to the user, means for collecting data on the child's facial expression and voice, means for the server to analyze the collected data and detect the child's emotional state, means for generating an alert based on the emotional state and sending it to the terminal, means for collecting data on the worker's facial expression and voice, means for the server to analyze the collected data and detect the worker's emotional state, and means for generating advice on relaxation activities and breaks based on the emotional state and sending it to the terminal. This enables optimal advice and management based on individual conditions in both childcare support and worker support.

[2030] The "means for receiving information about childcare input by a user through a terminal" is a method by which a server receives data about childcare input by a user using a terminal such as a smartphone or tablet.

[2031] "Means for the server to analyze the information received and generate optimal child-rearing advice" refers to a method in which the server performs natural language processing and data analysis based on the received child-rearing information to generate optimal child-rearing advice for the user.

[2032] The "means for transmitting the generated advice to the terminal and displaying it to the user" is a method for transmitting the child-rearing advice generated by the server to the user's terminal and visually displaying it to the user.

[2033] "Means for collecting data on children's facial expressions and voices" refers to a method for collecting children's facial expressions and voices in real time using a camera or microphone.

[2034] The "means for the server to analyze the collected data and detect the emotional state of the child" refers to a method in which the server uses an emotion recognition algorithm to detect the emotional state of the child based on the collected data on facial expressions and voice.

[2035] The "means for generating and transmitting an alert to a terminal based on an emotional state" is a method for generating an appropriate alert message based on the detected emotional state and transmitting it to the user's terminal.

[2036] "Means for collecting data on workers' facial expressions and voices" refers to a method for collecting data on the facial expressions and voices of workers working in factories using cameras and microphones.

[2037] "Means for the server to analyze collected data and detect the emotional state of the worker" refers to a method in which the server performs emotional analysis based on collected data on the worker's facial expressions and voice to detect the worker's emotional state.

[2038] The "means for generating advice on relaxation activities and rest based on the emotional state and transmitting the advice to the terminal" is a method for generating advice to suggest appropriate relaxation and rest methods to the worker based on the detected emotional state and transmitting the advice to the worker's terminal.

[2039] This system utilizes childcare information entered by users via their devices, and the server provides optimal childcare advice. It also has the ability to collect and analyze facial and vocal data from children, users, and workers to detect their respective emotional states. This improves the quality of childcare and facilitates parent-child communication and worker wellness management.

[2040] Specifically, the server implements these functions using the following hardware and software:

[2041] Hardware

[2042] 1. Devices (smartphones, tablets): Used by users to input childcare information and worker emotional information.

[2043] 2. Camera: Used to collect facial expression data from children and workers.

[2044] 3. Microphone: Used to collect voice data from children and workers.

[2045] software

[2046] 1. TensorFlow: Runs emotion recognition algorithms to analyze the collected facial expression data.

[2047] 2. OpenCV: Processes camera images.

[2048] 3. pyaudio: Acquires audio data.

[2049] 4. Requests: A communication method for sending collected data to the server.

[2050] 5. Natural language processing engine: Analyzes questions about childcare entered by users and generates optimal advice.

[2051] To provide parenting advice, the server first receives questions and growth record data entered by the user from their device. The received information is stored in a database and analyzed using a natural language processing engine. Based on the analysis results, optimal parenting advice is then generated and sent to the user's device.

[2052] Additionally, facial and vocal data collected from the device's camera and microphone is used to analyze the child or worker's emotional state in real time, and alerts, relaxation activities, and break advice are generated and sent to the user's or worker's device based on the analysis results.

[2053] For example, if a worker looks exhausted while working in a factory, and the facial expression data captured by the camera indicates "fatigue," the system will generate a notification saying, "We recommend you take a 15-minute break," and send it to the device.

[2054] Examples of prompts include:

[2055] "Generate appropriate break notifications based on employee facial expression data and emotion analysis results. For example, suggest a short break if the employee feels fatigued."

[2056] This will provide a comprehensive support system that not only provides childcare support but also manages worker wellness.

[2057] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2058] Step 1:

[2059] The user inputs questions about childcare and growth record data through the terminal. The input data is temporarily saved and prepared for transmission to the server. The input includes questions about childcare and growth record data, and the output is encrypted transmission data.

[2060] Step 2:

[2061] The terminal sends encrypted data to the server. The server decrypts the received data and stores the contents in a database. The input is encrypted data, and the output is decrypted data stored in the database.

[2062] Step 3:

[2063] The server analyzes the user's question using a natural language processing engine. Based on the analysis results, it searches a database for the most appropriate childcare advice and generates customized advice. The user's question is the input, and customized advice is generated as the output.

[2064] Step 4:

[2065] The generated parenting advice is sent by the server to the terminal and displayed to the user. The customized advice is the input and is displayed on the user's terminal as the output.

[2066] Step 5:

[2067] Facial and voice data of children and workers is collected through the device's camera and microphone. The collected data is periodically sent to a server. Facial and voice data is input, and data sent to the server is generated as output.

[2068] Step 6:

[2069] The server applies an emotion recognition algorithm to the received facial and voice data to identify the emotional state of the child or worker. The input is facial and voice data, and the output is an analysis of the emotional state.

[2070] Step 7:

[2071] Based on the emotion analysis results, the server generates appropriate alert messages and advice on relaxation activities and breaks. The input is the analysis result of the emotional state, and the output is the generated alert message or advice.

[2072] Step 8:

[2073] The generated alert messages and advice are sent from the server to the terminal and displayed to the user or worker in the appropriate notification format. The input is an alert message or advice, and the output is a notification that is displayed on the terminal.

[2074] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[2075] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[2076] 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 the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[2077] [Fourth embodiment]

[2078] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[2079] 7, a 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.

[2080] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[2081] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[2082] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[2083] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[2084] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[2085] The control object 443 includes a display device, LEDs in the eyes, and motors for driving 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 emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[2086] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[2087] The specific processing program 56 is an example of a "program" according to the technology of the present 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.

[2088] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[2089] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[2090] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2091] System Overview

[2092] This invention is a system in which a server uses childcare information entered by a user through a terminal to provide optimal childcare advice. It also has a function to collect and analyze data on a child's facial expressions and voice to detect their emotional state. It also includes a function to accumulate and analyze growth record data and provide notifications and information according to the child's developmental stage. This system also provides advice based on the latest scientific data related to childcare.

[2093] User registration and initial setup process

[2094] First, the user downloads and installs the AI ​​childcare assistant app from the app store. Next, they launch the app and enter basic information such as their child's name, age, and gender on the user registration screen. The device temporarily stores the entered information and prepares the data for login authentication. Once preparation is complete, the device encrypts the data and sends it to the server. The server receives it, stores it in a database, and sends a notification to the device that registration is complete.

[2095] Real-time childcare consultation process

[2096] When a user enters a question about childcare into the app and presses the send button, the question is sent from the device to the server. The server uses a natural language processing engine to analyze the received question. It then searches a database for the most appropriate advice according to categories such as breastfeeding, discipline, and health management, and generates customized advice based on the user's profile information. The generated advice is sent to the device and displayed to the user.

[2097] Sentiment Analysis Function Process

[2098] The device collects facial and voice data from the child through a camera and microphone. This data is periodically sent to the server. The server then applies an emotion recognition algorithm to the received data to identify the child's emotional state, such as smiling, anxious, or angry. If a change in the emotional state is detected, the server generates an appropriate alert message and sends it to the device. The user is then notified of this alert.

[2099] The process of tracking and storing growth records

[2100] The user enters their child's daily growth data (height, weight, dietary habits, etc.) into the app. The device sends the entered data to the server, which stores it in a database. Based on the stored data, the server generates a growth graph and sends it to the device. The generated graph is displayed visually to the user.

[2101] Developmentally appropriate notification and information processes

[2102] The server periodically analyzes the growth record data and selects appropriate information according to the child's developmental stage. This information is generated in the form of a notification and sent to the device. The device then displays this information to the user, making it useful for childcare.

[2103] A process for providing advice based on the latest scientific data related to childcare

[2104] The server periodically loads the latest scientific data related to childcare into its database and generates advice based on the latest scientific research. When a user asks a specific question about childcare, the server generates advice based on this information and sends it to the device. The device then displays the latest advice to the user.

[2105] Specific examples of programs

[2106] For example, suppose a user inputs the question, "My baby's crying at night is so bad I'm worried. Is there anything I can do about it?" The device sends this question to the server. The server analyzes the question and searches a database for the best solution for dealing with the crying. It generates specific advice, such as "Keep the room at the right temperature and humidity" or "Try playing calming music," and sends it to the device. The device then displays this to the user.

[2107] In this way, the system of the present invention provides comprehensive support for users to solve various child-rearing problems.

[2108] The processing flow will be explained below.

[2109] User registration and initial setup process

[2110] Step 1:

[2111] The user downloads and installs the AI ​​childcare assistant app from the app store.

[2112] Step 2:

[2113] The user launches the app and proceeds to the user registration screen.

[2114] Step 3:

[2115] The user enters basic information such as the child's name, age, and gender.

[2116] Step 4:

[2117] The device temporarily stores the entered information and prepares the data for login authentication.

[2118] Step 5:

[2119] Once the terminal is ready, it encrypts the entered information and sends it to the server.

[2120] Step 6:

[2121] The server stores the received data in a database.

[2122] Step 7:

[2123] The server sends a notification of registration completion to the terminal.

[2124] Step 8:

[2125] The device will inform the user that registration is complete.

[2126] Real-time childcare consultation process

[2127] Step 1:

[2128] Users enter parenting questions into the app.

[2129] Step 2:

[2130] The terminal sends a question to the server.

[2131] Step 3:

[2132] The server analyzes the question received using a natural language processing engine.

[2133] Step 4:

[2134] The server identifies categories such as breastfeeding, discipline, and health care based on the questions.

[2135] Step 5:

[2136] The server searches a database for appropriate advice based on the question and the user's profile information, and generates customized advice.

[2137] Step 6:

[2138] The server transmits the generated advice to the terminal.

[2139] Step 7:

[2140] The device displays the advice to the user.

[2141] Sentiment Analysis Function Process

[2142] Step 1:

[2143] The device activates the camera and microphone to collect the child's facial expressions and voice.

[2144] Step 2:

[2145] The terminal transmits the collected data to the server.

[2146] Step 3:

[2147] The server analyzes the received data and applies emotion recognition algorithms.

[2148] Step 4:

[2149] The server identifies the child's emotional state (e.g., smiling, anxious, angry).

[2150] Step 5:

[2151] The server generates an alert message based on the emotional state.

[2152] Step 6:

[2153] The server sends an alert message to the terminal.

[2154] Step 7:

[2155] The device will notify the user of the alert message.

[2156] The process of tracking and storing growth records

[2157] Step 1:

[2158] The user enters their child's daily growth data (height, weight, diet, etc.) into the app.

[2159] Step 2:

[2160] The terminal transmits the input growth data to the server.

[2161] Step 3:

[2162] The server stores the growth data in a database.

[2163] Step 4:

[2164] The server generates a growth graph based on the stored data.

[2165] Step 5:

[2166] The server transmits the generated growth graph to the terminal.

[2167] Step 6:

[2168] The device displays a growth graph to the user.

[2169] Developmentally appropriate notification and information processes

[2170] Step 1:

[2171] The server periodically analyzes the growth record data.

[2172] Step 2:

[2173] The server generates notification information according to the child's developmental stage.

[2174] Step 3:

[2175] The server sends the notification information to the terminal.

[2176] Step 4:

[2177] The device displays the notification to the user.

[2178] Providing the latest science-based parenting advice

[2179] Step 1:

[2180] The server periodically loads the latest childcare-related scientific data into the database.

[2181] Step 2:

[2182] The server generates advice using the latest data based on the questions about childcare received.

[2183] Step 3:

[2184] The server sends the advice to the terminal.

[2185] Step 4:

[2186] The device displays the advice to the user.

[2187] In this way, the system of the present invention realizes a process for supporting the user in raising their children.

[2188] Example 1

[2189] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2190] Conventional childcare support systems only allow users to ask questions about childcare and receive answers as they arise. They lack the ability to provide customized advice tailored to individual situations and the child's developmental stage. Furthermore, there are no systems that can analyze a child's emotional state in real time and provide appropriate responses based on those changes. Furthermore, functions for managing growth records and providing advice based on the latest scientific data related to childcare are limited. This creates challenges that make it difficult for parents to select appropriate childcare methods.

[2191] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[2192] In this invention, the server includes means for receiving child-rearing information input by a user through a terminal, means for analyzing the received information to generate optimal child-rearing advice, means for transmitting the generated advice to the terminal and displaying it to the user, means for collecting data on the child's facial expressions and voice, means for analyzing the collected data to detect the child's emotional state, means for generating an alert based on the emotional state and transmitting it to the terminal, means for the user to input growth record data into the terminal, means for accumulating and analyzing the input growth record data and generating a growth graph, means for transmitting the growth graph to the terminal and displaying it to the user, means for analyzing the growth record data and generating notifications and information according to the child's developmental stage, and means for transmitting the notifications and information to the terminal and displaying them to the user. This enables users to receive comprehensive support in real time to solve various child-rearing issues.

[2193] "User" refers to a person such as a parent or guardian who uses the childcare support system.

[2194] "Terminal" refers to an electronic device used by a user, such as a smartphone, tablet, or computer.

[2195] "Server" refers to a central computer system that stores and processes data.

[2196] "Childcare information" refers to all information related to childcare, such as breastfeeding, discipline, health care, and growth records.

[2197] A "natural language processing engine" refers to an algorithm or software for analyzing text data entered by a user.

[2198] "Advice" refers to the best parenting advice and solutions.

[2199] "Child's facial expression and voice data" refers to the child's facial expression and voice information obtained through a camera and microphone.

[2200] "Emotional state" refers to the child's emotional changes and current emotional situation (e.g., smiling, anxious, angry).

[2201] An "alert message" refers to a message that notifies the user of important information or a change in status.

[2202] "Growth record data" refers to data relating to a child's daily growth (e.g., height, weight, dietary content).

[2203] A "growth graph" refers to a graph that visually represents a child's growth, generated based on growth record data.

[2204] "Notification" refers to a message or alert intended to inform the user of specific information or attention.

[2205] "Childcare-related scientific data" refers to information and data about childcare that is based on the latest scientific research.

[2206] "Analysis results" refers to the output results of data analyzed by the server.

[2207] A "generative AI model" refers to a computer model that uses artificial intelligence to analyze data and generate appropriate results or advice.

[2208] A "prompt sentence" refers to a specific question or instruction that a user enters into a system.

[2209] A specific embodiment of the childcare support system of the present invention will be described below. In this system, a server provides optimal childcare advice based on childcare information entered by a user through a terminal. Furthermore, the system is equipped with functions to collect and analyze data on a child's facial expressions and voice to detect their emotional state, and to accumulate and analyze growth record data to provide notifications and information according to the child's developmental stage.

[2210] User registration and initial setup process

[2211] First, the user downloads and installs the AI ​​childcare assistant app from the app store. Next, they launch the app and enter basic information such as their child's name, age, and gender on the user registration screen. The device temporarily stores this information and prepares the data for login authentication. Once preparation is complete, the device encrypts the data and sends it to the server. The server stores the received data in a database and sends a notification of registration completion to the device. The device receives the notification and displays a message informing the user that registration is complete.

[2212] Real-time childcare consultation process

[2213] When a user enters a question about childcare into the app and presses the send button, the device sends the question data to the server. The server analyzes the received question using a natural language processing engine (e.g., GPT-3). The server then searches a database for appropriate advice from categories such as breastfeeding, discipline, and health care based on the question, and generates customized advice using the user's profile information. The generated advice is sent to the device, which displays it to the user.

[2214] Sentiment Analysis Function Process

[2215] The device collects data on the child's facial expressions and voice through a camera and microphone. The collected data is periodically sent to a server. The server analyzes the received data using an emotion recognition algorithm (e.g., facial expression analysis software) to identify the child's emotional state (e.g., smiling, anxious, or angry). If there is a significant change in the emotional state, the server generates an appropriate alert message and sends it to the device. The device receives the alert message and notifies the user.

[2216] The process of tracking and storing growth records

[2217] The user enters their child's daily growth data (height, weight, dietary habits, etc.) into the app. The device sends the entered data to the server, which stores it in a database. Based on the stored data, the server generates a growth graph and sends it to the device. The device then visually displays the growth graph to the user, allowing them to easily understand their child's growth.

[2218] Developmentally appropriate notification and information processes

[2219] The server periodically analyzes the growth record data and selects appropriate information from the database according to the child's developmental stage. This information is generated in the form of a notification and sent to the device. The device displays this information to the user, providing support for the user to take appropriate parenting actions.

[2220] A process for providing advice based on the latest scientific data related to childcare

[2221] The server periodically loads the latest childcare-related scientific data into a database and generates advice based on the latest scientific research. When a user inputs and submits a specific childcare question, the device sends the question to the server. The server receives the question, generates advice based on the latest scientific research, and sends it to the device. The device displays the latest advice to the user.

[2222] Examples of specific examples and prompts

[2223] For example, if a user inputs a question such as "My baby's crying at night is so bad I'm worried. Is there anything I can do?", the device will send this question to the server. The server will analyze the question and generate specific advice, such as "Keep the room at an appropriate temperature and humidity" or "Try listening to calming music," and send it to the device. The device will then display this to the user.

[2224] In this way, the system of the present invention provides comprehensive support for users to solve various child-rearing problems.

[2225] The flow of the identification process in the first embodiment will be described with reference to FIG.

[2226] Program processing steps

[2227] User registration and initial setup process

[2228] Step 1:

[2229] The user downloads and installs the AI ​​childcare assistant app from the app store.

[2230] Input: User downloads and installs the app

[2231] Output: Installed app

[2232] Step 2:

[2233] The user launches the app and enters basic information such as the child's name, age, and gender on the user registration screen.

[2234] Input: Basic information such as name, age, and gender

[2235] Output: Basic information entered

[2236] Step 3:

[2237] The device temporarily stores the entered information and prepares the data for login authentication.

[2238] Input: Basic information entered

[2239] Output: Temporarily saved authentication data

[2240] Step 4:

[2241] Once the device is ready, it encrypts the data and sends it to the server.

[2242] Input: Temporarily saved authentication data

[2243] Output: Encrypted data

[2244] Step 5:

[2245] The server stores the received data in a database and sends a notification of registration completion to the terminal.

[2246] Input: Encrypted data

[2247] Output: User information saved in the database, registration completion notification

[2248] Step 6:

[2249] The terminal receives the notification and displays a message to the user informing them of the completion of registration.

[2250] Input: Notification of registration completion

[2251] Output: Display of registration completion message

[2252] Real-time childcare consultation process

[2253] Step 1:

[2254] The user enters a question about childcare into the app and presses the send button.

[2255] Input: User question

[2256] Output: Generate question data

[2257] Step 2:

[2258] The terminal transmits the question data to the server.

[2259] Input: Question data

[2260] Output: Submitted question data

[2261] Step 3:

[2262] The server analyzes the received question using a natural language processing engine (e.g., GPT-3).

[2263] Input: Submitted question data

[2264] Output: Parsed question

[2265] Step 4:

[2266] Based on the question, the server searches a database for appropriate advice in categories such as breastfeeding, discipline, and health care.

[2267] Input: Parsed question content

[2268] Output: Advice data as search results

[2269] Step 5:

[2270] The server uses the user's profile information to generate customized advice.

[2271] Input: Advice data, user profile information

[2272] Output: Customized advice

[2273] Step 6:

[2274] The server transmits the generated advice to the terminal.

[2275] Input: Customized Advice

[2276] Output: Advice sent

[2277] Step 7:

[2278] The terminal receives the advice and displays it to the user.

[2279] Input: Submitted advice

[2280] Output: Advice displayed to the user

[2281] Sentiment Analysis Function Process

[2282] Step 1:

[2283] The device collects data on the child's facial expressions and voice through a camera and microphone.

[2284] Input: Child's facial expressions and voice

[2285] Output: Collected data

[2286] Step 2:

[2287] The terminal periodically transmits this data to the server.

[2288] Input: Collected data

[2289] Output: Data sent

[2290] Step 3:

[2291] The server analyzes the received data using emotion recognition algorithms.

[2292] Input: Data sent

[2293] Output: Parsed emotional state data

[2294] Step 4:

[2295] The server determines the emotional state of the child.

[2296] Input: Parsed emotional state data

[2297] Output: Identified emotional state (e.g., smiling, anxious, angry)

[2298] Step 5:

[2299] If the server detects a significant change in emotion, it generates an appropriate alert message and sends it to the device.

[2300] Input: Identified emotional state

[2301] Output: The generated alert message

[2302] Step 6:

[2303] The terminal receives the alert message and notifies the user.

[2304] Input: The generated alert message

[2305] Output: User notification

[2306] The process of tracking and storing growth records

[2307] Step 1:

[2308] The user enters their child's daily growth data (height, weight, diet, etc.) into the app.

[2309] Input: Child's daily growth data

[2310] Output: Input growth data

[2311] Step 2:

[2312] The terminal transmits the input data to the server.

[2313] Input: Input growth data

[2314] Output: Transmitted growth data

[2315] Step 3:

[2316] The server receives the data and stores it in a database.

[2317] Input: Submitted growth data

[2318] Output: Saved growth data

[2319] Step 4:

[2320] The server generates a growth graph based on the accumulated data.

[2321] Input: Saved growth data

[2322] Output: Generated growth graph

[2323] Step 5:

[2324] The server sends the growth graph to the terminal.

[2325] Input: Generated growth graph

[2326] Output: Growth graph sent

[2327] Step 6:

[2328] The terminal visually displays the growth graph to the user.

[2329] Input: Submitted growth graph

[2330] Output: Growth graph displayed to the user

[2331] Developmentally appropriate notification and information processes

[2332] Step 1:

[2333] The server periodically analyzes the growth record data.

[2334] Input: Saved growth record data

[2335] Output: Analysis results

[2336] Step 2:

[2337] Based on the analysis results, the server selects appropriate information from the database according to the child's developmental stage.

[2338] Input: Analysis results

[2339] Output: Selected information

[2340] Step 3:

[2341] The server generates the selected information in a notification format and transmits it to the terminal.

[2342] Input: Selected information

[2343] Output: Notification format generation

[2344] Step 4:

[2345] The device receives the notification and displays it to the user.

[2346] Input: Notification format information

[2347] Output: What is displayed to the user

[2348] A process for providing advice based on the latest scientific data related to childcare

[2349] Step 1:

[2350] The server periodically loads the latest childcare-related scientific data into the database.

[2351] Input: The latest childcare-related scientific data

[2352] Output: Updated database

[2353] Step 2:

[2354] The user inputs and submits a specific childcare question.

[2355] Input: User's specific question

[2356] Output: Generate question data

[2357] Step 3:

[2358] The terminal sends a question to the server.

[2359] Input: Question data

[2360] Output: Submitted question data

[2361] Step 4:

[2362] The server receives the question and generates advice based on the latest scientific research.

[2363] Input: Submitted query data, updated database

[2364] Output: Generated advice

[2365] Step 5:

[2366] The server sends the generated advice to the terminal.

[2367] Input: Generated advice

[2368] Output: Advice sent

[2369] Step 6:

[2370] The terminal displays the advice to the user.

[2371] Input: Submitted advice

[2372] Output: What is displayed to the user

[2373] (Application example 1)

[2374] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2375] While conventional childcare support systems can provide advice based on a child's growth record and emotional state, they are unable to provide specific dietary advice based on a child's nutritional status or food preferences. While meal suggestions to supplement a child's vitamin and mineral deficiencies are particularly important in childcare, no system existed that could provide such information in real time. Another challenge was linking this information with food delivery apps to make daily meal choices easier.

[2376] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[2377] In this invention, the server includes means for receiving child-rearing information input by the user through the terminal, means for analyzing the received information and generating optimal child-rearing advice, means for transmitting the generated advice to the terminal and displaying it to the user, means for collecting data on the child's facial expressions and voice, means for analyzing the collected data and detecting the child's emotional state by the server, means for generating an alert based on the emotional state and transmitting it to the terminal, means for inputting and receiving dietary information through the terminal, means for analyzing the input diet-related information and growth record data by the server and generating optimal dietary advice based on the child's nutritional status, and means for transmitting the generated dietary advice to the terminal and displaying it to the user. This makes it possible to provide specific dietary suggestions based on the child's nutritional status and dietary preferences, making it easier for the child to make daily meal choices.

[2378] "Childcare information entered by the user through a device" refers to a function that allows the user to use a mobile device or computer to enter information such as questions related to childcare, growth records, and dietary details.

[2379] "Server" refers to a computer system on a network that has the function of receiving, analyzing, and storing childcare information and growth record data sent by users.

[2380] "Optimal child-rearing advice" refers to the most appropriate and useful guidance and suggestions regarding child-rearing that are provided based on the results of analyzing the child-rearing information entered.

[2381] "Means for collecting data on children's facial expressions and voices" refers to the function of using the device's built-in camera and microphone to record children's facial expressions and voices and send that information to a server.

[2382] "Means for detecting emotional states" refers to a function that analyzes collected data on a child's facial expressions and voice and identifies their emotional state using an algorithm that identifies emotions such as smiling, anxious, or angry.

[2383] "Means for generating and sending alerts to the device" refers to the function of generating appropriate warnings or notifications and sending them to the user's device when a change in emotional state is detected.

[2384] "Means for inputting and receiving information about meals" refers to a function whereby a user inputs information about the child's diet and nutritional status into a terminal, and the server receives that information.

[2385] "Means for generating dietary advice" refers to a function that generates the most appropriate dietary suggestions based on the nutritional status and dietary preferences based on the input diet-related information and growth record data.

[2386] "Means for transmitting the generated dietary advice to the terminal and displaying it to the user" refers to a function for transmitting the generated dietary advice to the user's terminal and displaying the information so that the user can visually confirm it.

[2387] The present invention is a system in which a server generates optimal advice and provides it to users using information entered by users in relation to a childcare support system. This system can provide comprehensive childcare support using information on childcare, the child's emotional state, growth records, and even information on diet.

[2388] System Overview

[2389] The present invention has a function that allows users to input information about childcare, their child's emotional state, growth records, and dietary information using a mobile device or computer. The input information is sent to a server, which analyzes the information to generate optimal childcare and dietary advice and sends it to the user's device.

[2390] User registration and initial setup process

[2391] The user downloads and installs the application. After installation, the user enters basic information such as the child's name, age, and gender on the initial setup screen. The entered information is temporarily saved, encrypted, and sent to the server. The server receives it and stores it in a database.

[2392] The process of providing parenting advice

[2393] When a user enters a question about childcare into the app and presses the send button, the question is sent from the device to the server. The server analyzes the received question and generates optimal childcare advice. The advice is then sent to the device and displayed to the user.

[2394] Sentiment Analysis Function Process

[2395] The device collects facial and vocal data from the child through a camera and microphone. This data is periodically sent to the server, which applies emotion recognition algorithms to identify the child's emotional state. If a change is detected, an alert message is generated and sent to the device. The user is notified of this alert.

[2396] The process of tracking and storing growth records

[2397] The user enters daily growth data (height, weight, dietary details, etc.) into the app. The device sends the entered data to the server, which stores it in a database. A growth graph is generated based on the stored data and sent to the device. The generated graph is displayed to the user.

[2398] The process for providing dietary advice

[2399] The user enters information about their child's diet into the app. The entered diet information is sent from the device to the server. The server receives this information and analyzes the diet-related information and growth record data. Optimal dietary advice is generated based on the child's nutritional status and sent to the device. The advice is then displayed to the user.

[2400] Program operation and concrete examples

[2401] The server uses a database system (e.g., MySQL) and a natural language processing engine (e.g., Spacy or NLTK). The device is a smartphone or tablet. By processing and calculating data, it is possible to provide individual advice to the user.

[2402] For example, if a user enters information such as "Taro, 4 years old, dislikes vegetables," the app will provide advice such as "If you are concerned about vitamin D deficiency, we recommend this menu."

[2403] Example prompts to input to the generative AI model

[2404] "What menu would you suggest for a 4-year-old who hates vegetables and is deficient in vitamin D?"

[2405] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2406] Step 1:

[2407] The user installs the application and performs initial setup. The user enters basic information about the child (such as name, age, and gender), which is temporarily stored on the device. The entered information is encrypted and sent to the server. The server receives this information and stores it in a database. As an output, a notification that registration is complete is sent to the device.

[2408] Step 2:

[2409] The user enters a question about childcare into the app and presses the send button. The device then sends the question to the server. The server receives the question and analyzes it using a natural language processing engine. Based on the analysis results, it searches a database for the most appropriate childcare advice and generates customized advice. The generated advice is then sent to the device and displayed to the user.

[2410] Step 3:

[2411] The device uses a camera and microphone to collect data on the child's facial expressions and voice. The collected data is periodically sent to the server. The server applies an emotion recognition algorithm to identify the child's emotional state (e.g., smiling, anxious, angry, etc.). If a change in the emotional state is detected, the server generates an alert message and sends it to the device. The user receives this alert.

[2412] Step 4:

[2413] The user enters daily growth data (height, weight, dietary details, etc.) into the app. The device sends the entered data to the server. The server receives it and stores it in a database. The server generates a growth graph and sends it to the device. The generated graph is displayed to the user.

[2414] Step 5:

[2415] The user enters information about their diet into the app. The device then sends the entered diet information to the server. The server receives and analyzes the diet-related information and growth record data, and generates optimal dietary advice based on the user's nutritional status. The generated dietary advice is then sent to the device and displayed to the user. For example, specific suggestions such as "If you are concerned about vitamin D deficiency, we recommend this menu" are provided.

[2416] Input and Output Complement

[2417] Step 1:

[2418] Input: Child's basic information (name, age, gender)

[2419] Output: Notification of successful registration

[2420] Step 2:

[2421] Input: Parenting Questions

[2422] Output: Best parenting advice

[2423] Step 3:

[2424] Input: Child's facial expression and voice data

[2425] Output: Emotional state alert message

[2426] Step 4:

[2427] Input: Growth data

[2428] Output: Growth graph

[2429] Step 5:

[2430] Input: Meal information

[2431] Output: Optimal dietary advice

[2432] Example prompts to input to the generative AI model

[2433] "What menu would you suggest for a 4-year-old who hates vegetables and is deficient in vitamin D?"

[2434] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[2435] System Overview

[2436] This invention is a system in which a server uses childcare information entered by a user via a terminal to provide optimal childcare advice. It also has a function that collects and analyzes facial and vocal data from the child and the user to detect the emotional state of both parties. This improves the quality of childcare and facilitates smoother communication between parents and children. It also includes a function that accumulates and analyzes growth record data and provides notifications and information according to the developmental stage. This system also provides advice based on the latest scientific data related to childcare.

[2437] User registration and initial setup process

[2438] First, the user downloads and installs the AI ​​childcare assistant app from the app store. Next, they launch the app and enter their child's name, age, gender, and other basic user information on the user registration screen. The device temporarily stores the entered information and prepares the data for login authentication. Once preparation is complete, the device encrypts the data and sends it to the server. The server receives it, stores it in a database, and sends a notification to the device that registration is complete.

[2439] Real-time childcare consultation process

[2440] When a user enters a question about childcare into the app and presses the send button, the question is sent from the device to the server. The server uses a natural language processing engine to analyze the received question. It then searches a database for the most appropriate advice according to categories such as breastfeeding, discipline, and health management, and generates customized advice based on the user's profile information. The generated advice is sent to the device and displayed to the user.

[2441] Sentiment Analysis Function Process

[2442] The device collects facial and voice data of the child and user through a camera and microphone. This data is periodically sent to the server. The server applies an emotion recognition algorithm to the received data to identify the child's and user's emotional state, such as smile, anxiety, or anger. If a change in emotional state is detected, the server generates an appropriate alert message and sends it to the device. The user is notified of this alert.

[2443] User Emotion Engine Process

[2444] This adds a function to analyze the user's emotional state using an emotion engine that recognizes the user's emotions. The device's sensors are used to collect the user's facial expressions and voice in real time, and the data is sent to a server. The server then analyzes the user's emotional state based on the collected data and generates advice offering appropriate mindfulness exercises and relaxation techniques. The generated advice is sent to the device and displayed to the user.

[2445] The process of tracking and storing growth records

[2446] The user enters their child's daily growth data (height, weight, dietary habits, etc.) into the app. The device sends the entered data to the server, which stores it in a database. Based on the stored data, the server generates a growth graph and sends it to the device. The generated graph is displayed visually to the user.

[2447] Developmentally appropriate notification and information processes

[2448] The server periodically analyzes the growth record data and generates notification information according to the child's developmental stage. This information is generated in the form of a notification and sent to the device. The device displays this information to the user, making it useful for childcare.

[2449] Providing the latest science-based parenting advice

[2450] The server periodically loads the latest scientific data related to childcare into its database. When a user asks a specific question about childcare, the server generates advice based on this data and sends it to the device. The device then displays the latest advice to the user.

[2451] Specific examples of programs

[2452] For example, suppose a user inputs the question, "My baby's crying at night is so bad I'm worried. Is there anything I can do about it?" The device sends this question to the server. The server analyzes the question and searches a database for the best solution for dealing with the crying. It generates specific advice, such as "Keep the room at the right temperature and humidity" or "Try playing calming music," and sends it to the device. The device then displays this to the user.

[2453] Next, the device collects the child's facial expressions and voice, and the server analyzes the data to detect the child's state of anxiety. Based on this, the server generates an alert message such as, "Your child may be prone to anxiety recently. Let's spend some time relaxing together," and sends it to the device. The device then displays this alert to the user.

[2454] Furthermore, if the user's emotion engine detects that the user is feeling stressed, the server generates advice such as "Take a deep breath and take a few minutes to relax" and sends it to the device, which then displays it to the user. In this way, the system provides a wide range of support for the user's child-rearing needs.

[2455] The processing flow will be explained below.

[2456] User registration and initial setup process

[2457] Step 1:

[2458] The user downloads and installs the AI ​​childcare assistant app from the app store.

[2459] Step 2:

[2460] The user launches the app and proceeds to the user registration screen.

[2461] Step 3:

[2462] The user enters the child's name, age, gender, and basic user information.

[2463] Step 4:

[2464] The device temporarily stores the entered information and prepares the data for login authentication.

[2465] Step 5:

[2466] Once the device is ready, it encrypts the entered information and sends it to the server.

[2467] Step 6:

[2468] The server receives the data and stores it in a database.

[2469] Step 7:

[2470] The server sends a notification of registration completion to the terminal.

[2471] Step 8:

[2472] The device will inform the user that registration is complete.

[2473] Real-time childcare consultation process

[2474] Step 1:

[2475] Users enter parenting questions into the app.

[2476] Step 2:

[2477] The terminal sends a question to the server.

[2478] Step 3:

[2479] The server analyzes the question using a natural language processing engine.

[2480] Step 4:

[2481] The server identifies categories such as breastfeeding, discipline, and health care based on the questions.

[2482] Step 5:

[2483] The server searches a database for appropriate advice based on the question and the user's profile information, and generates customized advice.

[2484] Step 6:

[2485] The server transmits the generated advice to the terminal.

[2486] Step 7:

[2487] The device displays the advice to the user.

[2488] Sentiment Analysis Function Process

[2489] Step 1:

[2490] The device activates the camera and microphone to collect facial expressions and voices of the child and the user.

[2491] Step 2:

[2492] The terminal transmits the collected data to the server.

[2493] Step 3:

[2494] The server analyzes the received data and applies emotion recognition algorithms.

[2495] Step 4:

[2496] The server identifies the emotional state of the child and the user, for example, smiling, anxious, angry, etc.

[2497] Step 5:

[2498] The server generates an alert message based on the emotional state.

[2499] Step 6:

[2500] The server sends an alert message to the terminal.

[2501] Step 7:

[2502] The device will notify the user of the alert message.

[2503] User Emotion Engine Process

[2504] Step 1:

[2505] The device collects the user's voice and facial expression data.

[2506] Step 2:

[2507] The terminal transmits the collected data to the server.

[2508] Step 3:

[2509] The server analyzes the data and performs emotion recognition.

[2510] Step 4:

[2511] The server identifies the user's emotional state (e.g., stress, anxiety, happiness).

[2512] Step 5:

[2513] The server generates advice on mindfulness exercises and relaxation techniques based on the user's emotional state.

[2514] Step 6:

[2515] The server transmits the generated advice to the terminal.

[2516] Step 7:

[2517] The device displays the advice to the user.

[2518] The process of tracking and storing growth records

[2519] Step 1:

[2520] The user enters their child's daily growth data (height, weight, diet, etc.) into the app.

[2521] Step 2:

[2522] The terminal transmits the input growth data to the server.

[2523] Step 3:

[2524] The server stores the growth data in a database.

[2525] Step 4:

[2526] The server generates a growth graph based on the stored data.

[2527] Step 5:

[2528] The server transmits the generated growth graph to the terminal.

[2529] Step 6:

[2530] The device displays a growth graph to the user.

[2531] Developmentally appropriate notification and information processes

[2532] Step 1:

[2533] The server periodically analyzes the growth record data.

[2534] Step 2:

[2535] The server generates notification information according to the child's developmental stage.

[2536] Step 3:

[2537] The server sends the notification information to the terminal.

[2538] Step 4:

[2539] The device displays the notification to the user.

[2540] Providing the latest science-based parenting advice

[2541] Step 1:

[2542] The server periodically loads the latest childcare-related scientific data into the database.

[2543] Step 2:

[2544] The server generates advice using the latest data based on the questions about childcare received.

[2545] Step 3:

[2546] The server sends the advice to the terminal.

[2547] Step 4:

[2548] The device displays the advice to the user.

[2549] In this way, the system of the present invention realizes a process for supporting the user in raising their children.

[2550] Example 2

[2551] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2552] Conventional childcare support systems simply provide information about childcare, but lack real-time support for actual childcare environments. Furthermore, they lack a mechanism for accurately grasping the emotional state of parents and children and providing specific advice or warnings based on that information, making it difficult to improve the quality of childcare and facilitate smooth communication between parents and children. Furthermore, they lack the ability to provide childcare advice that reflects the latest scientific findings or notification functions that effectively utilize child growth records.

[2553] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for receiving child-rearing information input by a user through an information processing device; means for analyzing the received information by the information processing device to generate optimal child-rearing support information; means for transmitting the generated support information to the information processing device and displaying it to the user; means for collecting facial and voice data of the protected person; means for analyzing the collected data by the information processing device to detect the protected person's emotional state; means for generating warning information based on the emotional state and transmitting it to the information processing device; means for the user to input growth record data to the information processing device; means for the information processing device to accumulate and analyze the input growth record data and generate notifications and information according to the developmental stage; means for transmitting notifications and information according to the developmental stage to the information processing device and displaying them to the user; means for the information processing device to periodically update child-rearing-related scientific data and generate latest support information based on the analysis results; and means for transmitting the latest support information to the information processing device and displaying it to the user. This enables real-time child-rearing support and specific advice based on the protected person's emotional state, improving the quality of child-rearing and facilitating parent-child communication. In addition, it will provide reliable parenting advice based on the latest scientific knowledge, and will be able to provide notifications and information based on a child's growth based on growth records.

[2554] An "information processing device" is an electronic device that processes information entered by a user and communicates with a server.

[2555] "Childcare support information" refers to support information provided to users, such as advice and countermeasures regarding childcare, and information based on the latest scientific knowledge.

[2556] "Facial expression" refers to the movement and expression of the facial muscles of the protected person, and is visual data detected using a camera or other device.

[2557] "Audio" refers to the voice or sound emitted by the protected person or user, and is acoustic data detected using a microphone or the like.

[2558] "Emotional states" are psychological states that can be identified by analyzing facial expressions and voice, and include emotions such as joy, sadness, and anger.

[2559] "Warning information" is information that is generated based on the emotional state and that warns or advises the user.

[2560] "Growth record data" refers to information about a child's daily growth, including data such a...

Claims

1. means for receiving information about childcare input by a user through a terminal; A means for analyzing the information received by the server and generating optimal childcare advice; means for transmitting the generated advice to a terminal and displaying the advice to a user; A means of collecting data on the child's facial expressions and voice; means by the server to analyze the collected data to detect the emotional state of the child; The system includes means for generating and transmitting an alert to a device based on the emotional state.

2. A means for a user to input growth record data into a terminal; A server stores and analyzes the input growth record data, and generates notifications and information according to the developmental stage.

2. The system of claim 1, further comprising means for transmitting notifications and information according to the developmental stage to the terminal and displaying them to the user.

3. A server periodically updates scientific data related to childcare and generates the latest advice based on the analysis results; 2. The system of claim 1, further comprising means for transmitting the latest advice to the terminal and displaying it to the user.

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